anton-l/python_sample_10k · Datasets at Hugging Face

txazo/txazodevelop

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/python/test/4.py

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https://github.com/txazo/txazodevelop

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refs/heads/master

2020-03-25T22:44:25.477523

2018-08-10T05:16:06

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# -*- coding: utf-8 -*- # tuple：不可变更 s1 = (12, 12.5, True, "hello") print s1, type(s1) print s1[0] print s1[-1] # 最后一个 print s1[-2] # 倒数第二个 print s1[:3] #(0, 1, 2) print s1[1:] #1到最后 print s1[1:3] #(1, 2) print s1[0:4:2] #(0, 2) print s1[3:1:-1] #(3, 2) # list：可以变更 s2 = [12, 12.5, True, "hello"] print s2, type(s2) print s2[0] s2[1] = False print s2[1] # 字符串(tuple) str = "abcdefg" print str[2]

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gaoyan10/server-sdk-python

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692b8244918908c1763c21c0764c7a73b862b24c

/rongcloud/api.py

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https://github.com/gaoyan10/server-sdk-python

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#! /usr/bin/env python # coding=utf-8 import os import json import logging import random import datetime import hashlib import platform import requests import util import exceptions from version import __version__ class ApiClient(object): api_host = "https://api.cn.rong.io" response_type = "json" library_details = "python %s" % platform.python_version() user_agent = "RongCloudSdk/RongCloud-Python-Sdk %s (%s)" % \ (library_details, __version__) ACTION_USER_TOKEN = "/user/getToken" ACTION_MESSAGE_PUBLISH = "/message/publish" ACTION_MESSAGE_SYSTEM_PUBLISH = "/message/system/publish" ACTION_MESSAGE_GROUP_PUBLISH = "/message/group/publish" ACTION_MESSAGE_CHATROOM_PUBLISH = "/message/chatroom/publish" ACTION_GROUP_SYNC = "/group/sync" ACTION_GROUP_CREATE = "/group/create" ACTION_GROUP_JOIN = "/group/join" ACTION_GROUP_QUIT = "/group/quit" ACTION_GROUP_DISMISS = "/group/dismiss" ACTION_CHATROOM_CREATE = "/chatroom/create" ACTION_CHATROOM_DESTROY = "/chatroom/destroy" ACTION_CHATROOM_QUERY = "/chatroom/query" def __init__(self, app_key=None, app_secret=None, verify=True): """ API 客户端 Usage:: >>> from rongcloud.api import ApiClient >>> client = ApiClient('xxxxx', 'xxxx') 建议您将APPKEY, APPSECRET 保存在系统的环境变量中环境变量的键值分别为：rongcloud-app-key， rongcloud-app-secret >>> from rongcloud.api import ApiClient >>> client = ApiClient() :param app_key: 开发者平台分配的 App Key :param app_secret: 开发者平台分配的 App Secret。 :param verify: 发送请求时是否验证SSL证书的有效性 """ self.app_key = app_key or os.environ.get('rongcloud-app-key') self.app_secret = app_secret or os.environ.get('rongcloud-app-secret') self.verify = verify def make_common_signature(self): """生成通用签名一般情况下，您不需要调用该方法文档详见 http://docs.rongcloud.cn/server.html#_API_调用签名规则 :return: {'app-key':'xxx','nonce':'xxx','timestamp':'xxx','signature':'xxx'} """ nonce = str(random.random()) timestamp = str( int(datetime.datetime.now().strftime("%s")) * 1000 ) signature = hashlib.sha1( self.app_secret + nonce + timestamp ).hexdigest() return { "rc-app-key": self.app_key, "rc-nonce": nonce, "rc-timestamp": timestamp, "rc-signature": signature } def headers(self): """Default HTTP headers """ return util.merge_dict( self.make_common_signature(), { "content-type": "application/x-www-form-urlencoded", "user-agent": self.user_agent } ) def http_call(self, url, method, **kwargs): """Makes a http call. Logs response information. """ logging.info("Request[%s]: %s" % (method, url)) start_time = datetime.datetime.now() response = requests.request(method, url, verify=self.verify, **kwargs) duration = datetime.datetime.now() - start_time logging.info("Response[%d]: %s, Duration: %s.%ss." % (response.status_code, response.reason, duration.seconds, duration.microseconds)) return self.handle_response(response, response.content.decode("utf-8")) def handle_response(self, response, content): """Validate HTTP response """ status = response.status_code if status in (301, 302, 303, 307): raise exceptions.Redirection(response, content) elif 200 <= status <= 299: return json.loads(content) if content else {} elif status == 400: raise exceptions.BadRequest(response, content) elif status == 401: raise exceptions.UnauthorizedAccess(response, content) elif status == 403: raise exceptions.ForbiddenAccess(response, content) elif status == 404: raise exceptions.ResourceNotFound(response, content) elif status == 405: raise exceptions.MethodNotAllowed(response, content) elif status == 409: raise exceptions.ResourceConflict(response, content) elif status == 410: raise exceptions.ResourceGone(response, content) elif status == 422: raise exceptions.ResourceInvalid(response, content) elif 401 <= status <= 499: raise exceptions.ClientError(response, content) elif 500 <= status <= 599: raise exceptions.ServerError(response, content) else: raise exceptions.ConnectionError(response, content, "Unknown response code: #{response.code}") def post(self, action, params=None): """POST 应用参数到接口地址所有http请求由此处理，方法内部封装统一的签名规则及 API URL 当有新的接口推出，而SDK未更新时，您可用该方法 Usage:: >>> from rongcloud.api import ApiClient >>> client = ApiClient() >>> client.post('/user/getToken', {}) :param action: 接口地址，例如：/message/chatroom/publish :param params: 应用级别参数，{"fromUserId":"xxxx", "content":"xxxxx"} :return: {"code":200, "userId":"jlk456j5", "token":"sfd9823ihufi"} """ return self.http_call( url=util.join_url(self.api_host, "%s.%s" % (action, self.response_type)), method="POST", data=params, headers=self.headers() ) def user_get_token(self, user_id, name, portrait_uri): """ 获取token http://docs.rongcloud.cn/server.html#_获取_Token_方法 :param user_id: :param name: :param portrait_uri: :return: {"code":200, "userId":"jlk456j5", "token":"sfd9823ihufi"} """ return self.post( action=self.ACTION_USER_TOKEN, params={ "userId": user_id, "name": name, "portraitUri": portrait_uri } ) def message_publish(self, from_user_id, to_user_id, object_name, content, push_content=None, push_data=None): """ 发送会话消息 http://docs.rongcloud.cn/server.html#_融云内置消息类型表 http://docs.rongcloud.cn/server.html#_发送会话消息_方法 :param from_user_id:发送人用户 Id :param to_user_id:接收用户 Id，提供多个本参数可以实现向多人发送消息。 :param object_name:消息类型,目前包括如下类型 ["RC:TxtMsg","RC:ImgMsg","RC:VcMsg","RC:LocMsg"] :param content:发送消息内容，参考融云消息类型表.示例说明；如果 objectName 为自定义消息类型，该参数可自定义格式。（必传） :param push_content:如果为自定义消息，定义显示的 Push 内容(可选) :param push_data:针对 iOS 平台，Push 通知附加的 payload 字段，字段名为 appData。(可选) :return:{"code":200} """ return self.post( action=self.ACTION_MESSAGE_PUBLISH, params={ "fromUserId": from_user_id, "toUserId": to_user_id, "objectName": object_name, "content": content, "pushContent": push_content if push_content is not None else "", "pushData": push_data if push_data is not None else "" } ) def message_system_publish(self, from_user_id, to_user_id, object_name, content, push_content=None, push_data=None): """发送系统消息 http://docs.rongcloud.cn/server.html#_发送系统消息_方法 :param from_user_id:发送人用户 Id :param to_user_id:接收用户 Id，提供多个本参数可以实现向多人发送消息。 :param object_name:消息类型,目前包括如下类型 ["RC:TxtMsg","RC:ImgMsg","RC:VcMsg","RC:LocMsg"] :param content:发送消息内容，参考融云消息类型表.示例说明；如果 objectName 为自定义消息类型，该参数可自定义格式。（必传） :param push_content:如果为自定义消息，定义显示的 Push 内容(可选) :param push_data:针对 iOS 平台，Push 通知附加的 payload 字段，字段名为 appData。(可选) :return:{"code":200} """ return self.post( action=self.ACTION_MESSAGE_SYSTEM_PUBLISH, params={ "fromUserId": from_user_id, "toUserId": to_user_id, "objectName": object_name, "content": content, "pushContent": push_content if push_content is not None else '', "pushData": push_data if push_data is not None else '' } ) def message_group_publish(self, from_user_id, to_group_id, object_name, content, push_content=None, push_data=None): """以一个用户身份向群组发送消息 http://docs.rongcloud.cn/server.html#_发送群组消息_方法 :param from_user_id:发送人用户 Id :param to_group_id:接收群Id，提供多个本参数可以实现向多群发送消息。（必传） :param object_name:消息类型,目前包括如下类型 ["RC:TxtMsg","RC:ImgMsg","RC:VcMsg","RC:LocMsg"] :param content:发送消息内容，参考融云消息类型表.示例说明；如果 objectName 为自定义消息类型，该参数可自定义格式。（必传） :param push_content:如果为自定义消息，定义显示的 Push 内容(可选) :param push_data:针对 iOS 平台，Push 通知附加的 payload 字段，字段名为 appData。(可选) :return:{"code":200} """ return self.post( action=self.ACTION_MESSAGE_GROUP_PUBLISH, params={ "fromUserId": from_user_id, "toGroupId": to_group_id, "objectName": object_name, "content": content, "pushContent": push_content if push_content is not None else '', "pushData": push_data if push_data is not None else '' } ) def message_chatroom_publish(self, from_user_id, to_chatroom_id, object_name, content): """一个用户向聊天室发送消息 http://docs.rongcloud.cn/server.html#_发送聊天室消息_方法 :param from_user_id:发送人用户 Id。（必传） :param to_chatroom_id:接收聊天室Id，提供多个本参数可以实现向多个聊天室发送消息。（必传） :param object_name:消息类型，参考融云消息类型表.消息标志；可自定义消息类型。（必传） :param content:发送消息内容，参考融云消息类型表.示例说明；如果 objectName 为自定义消息类型，该参数可自定义格式。（必传） :return:{"code":200} """ return self.post( action=self.ACTION_MESSAGE_GROUP_PUBLISH, params={ "fromUserId": from_user_id, "toGroupId": to_chatroom_id, "objectName": object_name, "content": content } ) def group_sync(self, user_id, groups): """同步用户所属群组融云当前群组的架构设计决定，您不需要调用融云服务器去“创建”群组也就是告诉融云服务器哪些群组有哪些用户。您只需要同步当前用户所属的群组信息给融云服务器即相当于“订阅”或者“取消订阅”了所属群组的消息。融云会根据用户同步的群组数据，计算群组的成员信息并群发消息。 :param user_id:用户Id :param groups: groupId 和 groupName 的对应关系.例如：{10001:'group1',10002:'group2'} :return:{"code":200} """ group_mapping = {"group[%s]" % k:v for k, v in groups.items()} group_mapping.setdefault("userId", user_id) return self.post(action=self.ACTION_GROUP_SYNC, params=group_mapping) def group_create(self, user_id_list, group_id, group_name): """创建群组，并将用户加入该群组，用户将可以收到该群的消息。注：其实本方法是加入群组方法 /group/join 的别名。 http://docs.rongcloud.cn/server.html#_创建群组_方法 :param user_id_list:要加入群的用户 Id ，可以传递多个值:[userid1,userid2] :param group_id:要加入的群 Id。 :param group_name:要加入的群 Id 对应的名称。 :return:{"code":200} """ return self.post(action=self.ACTION_GROUP_CREATE, params={ "userId":user_id_list, "groupId":group_id, "groupName":group_name }) def group_join(self, user_id_list, group_id, group_name): """将用户加入指定群组，用户将可以收到该群的消息 http://docs.rongcloud.cn/server.html#_加入群组_方法 :param user_id_list:要加入群的用户 [userid1,userid2 ...] :param group_id:要加入的群 Id。 :param group_name:要加入的群 Id 对应的名称。 :return:{"code":200} """ return self.post(action=self.ACTION_GROUP_JOIN, params={ "userId":user_id_list, "groupId":group_id, "groupName":group_name }) def group_dismiss(self, user_id, group_id): """将该群解散，所有用户都无法再接收该群的消息。 http://docs.rongcloud.cn/server.html#_解散群组_方法 :param user_id: 操作解散群的用户 Id。 :param group_id:要解散的群 Id。 :return:{"code":200} """ return self.post(action=self.ACTION_GROUP_DISMISS, params={ "userId":user_id, "groupId":group_id, }) def chatroom_create(self, chatrooms): """创建聊天室方法 http://docs.rongcloud.cn/server.html#_创建聊天室_方法 :param chatrooms: {'r001':'room1'} id:要创建的聊天室的id；name:要创建的聊天室的name :return:{"code":200} """ chatroom_mapping = {'chatroom[%s]' % k:v for k, v in chatrooms.items()} return self.post(action=self.ACTION_CHATROOM_CREATE, params=chatroom_mapping) def chatroom_destroy(self, chatroom_id_list=None): """销毁聊天室方法当提交参数chatroomId多个时表示销毁多个聊天室 http://docs.rongcloud.cn/server.html#_销毁聊天室_方法 :param chatroom_id_list:要销毁的聊天室 Id。 :return:{"code":200} """ params={ "chatroomId":chatroom_id_list } if chatroom_id_list is not None else {} return self.post(action=self.ACTION_CHATROOM_DESTROY, params=params) def chatroom_query(self, chatroom_id_list=None): """查询聊天室信息方法 http://docs.rongcloud.cn/server.html#_查询聊天室信息_方法 :param chatroom_id_list:当提交多个时表示查询多个聊天室，如果为None ，则查询所有聊天室 :return:{"code":200,"chatRooms":[{"chatroomId":"id1001","name":"name1","time":"2014-01-01 1:1:1"},{"chatroomId":"id1002","name":"name2","time":"2014-01-01 1:1:2"}]} """ params={ "chatroomId":chatroom_id_list } if chatroom_id_list is not None else {} return self.post(action=self.ACTION_CHATROOM_QUERY, params=params)

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xuanxin-L/Dissertation_Work

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/Chapter8/walking_data/gait_separation.py

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[]

no_license

https://github.com/xuanxin-L/Dissertation_Work

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2022-06-14T14:34:44.522936

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# -*- coding: utf-8 -*- """ Created on Thu Jul 26 18:39:41 2018 @author: Huawei """ import numpy as np from scipy import signal import matplotlib.pyplot as plt from hip_ankle_points_calculation import get_hip_point, get_ankle_point def sep_gait_by_force(motion, grf, st_walking, ed_walking, num_nodes, ext_nodes, ext_gait, delta, const_dicts, plot_sign=False, write_sign=False, store_path=''): every_node = int(delta/0.01) b, a = signal.butter(2, 2.0*8/(50), 'low', analog=False) LFy = signal.filtfilt(b, a, grf[:, 1]) RFy = signal.filtfilt(b, a, grf[:, 7]) Lthigh = const_dicts['ThighLen'] Lshank = const_dicts['ShankLen'] signL = np.zeros(num_nodes) signR = np.zeros(num_nodes) for indL in range(len(LFy)): if LFy[indL] > 100: signL[indL] = 1 for indR in range(len(RFy)): if RFy[indR] > 100: signR[indR] = 1 DsignL = np.diff(signL) DsignR = np.diff(signR) Lhs = (np.where(DsignL==1)[0]).astype(int) Lto = (np.where(DsignL==-1)[0]).astype(int) Rhs = (np.where(DsignR==1)[0]).astype(int) Rto = (np.where(DsignR==-1)[0]).astype(int) Lgait = np.min([len(Lhs), len(Lto)]) Rgait = np.min([len(Rhs), len(Rto)]) Lswingx = np.zeros((Lgait, 100)) Lswingy = np.zeros((Lgait, 100)) Lswingt = np.zeros((Lgait, 100)) Lstancex = np.zeros((Lgait, 100)) Lstancey = np.zeros((Lgait, 100)) Lstancet = np.zeros((Lgait, 100)) Rswingx = np.zeros((Rgait, 100)) Rswingy = np.zeros((Rgait, 100)) Rswingt = np.zeros((Rgait, 100)) Rstancex = np.zeros((Rgait, 100)) Rstancey = np.zeros((Rgait, 100)) Rstancet = np.zeros((Rgait, 100)) InitialDataL = np.zeros((num_nodes, 9)) InitialDataR = np.zeros((num_nodes, 9)) if Lto[0] < Lhs[0]: for k in range(Lgait-1): for j in range(Lto[k], Lhs[k]): InitialDataL[j, 0] = 0 InitialDataL[j, 1] = (j-Lto[k])*delta InitialDataL[j, 2] = (Lhs[k]-Lto[k])*delta InitialDataL[j, 3:5] = get_ankle_point(motion[Lto[k], 2], motion[Lto[k], 3], motion[Lto[k], 4], Lthigh, Lshank) InitialDataL[j, 5:7] = get_ankle_point(motion[j, 2], motion[j, 3], motion[j, 4], Lthigh, Lshank) InitialDataL[j, 7:9] = get_ankle_point(motion[Lhs[k], 2], motion[Lhs[k], 3], motion[Lhs[k], 4], Lthigh, Lshank) for i in range(Lhs[k], Lto[k+1]): InitialDataL[i, 0] = 1 InitialDataL[i, 1] = (i-Lhs[k])*delta InitialDataL[i, 2] = (Lto[k+1]-Lhs[k])*delta InitialDataL[i, 3:5] = get_hip_point(motion[Lhs[k], 2], motion[Lhs[k], 3], motion[Lhs[k], 4], Lthigh, Lshank) InitialDataL[i, 5:7] = get_hip_point(motion[i, 2], motion[i, 3], motion[i, 4], Lthigh, Lshank) InitialDataL[i, 7:9] = get_hip_point(motion[Lto[k+1], 2], motion[Lto[k+1], 3], motion[Lto[k+1], 4], Lthigh, Lshank) time_sw = np.linspace(0, (Lhs[k]-Lto[k])*delta, Lhs[k]-Lto[k]) time_st = np.linspace(0, (Lto[k+1]-Lhs[k])*delta, Lto[k+1]-Lhs[k]) time_swn = np.linspace(0, (Lhs[k]-Lto[k])*delta, 100) time_stn = np.linspace(0, (Lto[k+1]-Lhs[k])*delta, 100) Lswingx[k, :] = np.interp(time_swn, time_sw, InitialDataL[Lto[k]:Lhs[k], 5]) Lswingy[k, :] = np.interp(time_swn, time_sw, InitialDataL[Lto[k]:Lhs[k], 6]) Lswingt[k, :] = time_swn Lstancex[k, :] = np.interp(time_stn, time_st, InitialDataL[Lhs[k]:Lto[k+1], 5]) Lstancey[k, :] = np.interp(time_stn, time_st, InitialDataL[Lhs[k]:Lto[k+1], 6]) Lstancet[k, :] = time_stn else: for k in range(Lgait-1): for i in range(Lhs[k], Lto[k]): InitialDataL[i, 0] = 1 InitialDataL[i, 1] = (i-Lhs[k])*delta InitialDataL[i, 2] = (Lto[k]-Lhs[k])*delta InitialDataL[i, 3:5] = get_hip_point(motion[Lhs[k], 2], motion[Lhs[k], 3], motion[Lhs[k], 4], Lthigh, Lshank) InitialDataL[i, 5:7] = get_hip_point(motion[i, 2], motion[i, 3], motion[i, 4], Lthigh, Lshank) InitialDataL[i, 7:9] = get_hip_point(motion[Lto[k], 2], motion[Lto[k], 3], motion[Lto[k], 4], Lthigh, Lshank) for j in range(Lto[k], Lhs[k+1]): InitialDataL[j, 0] = 0 InitialDataL[j, 1] = (j-Lto[k])*delta InitialDataL[j, 2] = (Lhs[k+1]-Lto[k])*delta InitialDataL[j, 3:5] = get_ankle_point(motion[Lto[k], 2], motion[Lto[k], 3], motion[Lto[k], 4], Lthigh, Lshank) InitialDataL[j, 5:7] = get_ankle_point(motion[j, 2], motion[j, 3], motion[j, 4], Lthigh, Lshank) InitialDataL[j, 7:9] = get_ankle_point(motion[Lhs[k+1], 2], motion[Lhs[k+1], 3], motion[Lhs[k+1], 4], Lthigh, Lshank) time_sw = np.linspace(0, (Lhs[k+1]-Lto[k])*delta, Lhs[k+1]-Lto[k]) time_st = np.linspace(0, (Lto[k]-Lhs[k])*delta, Lto[k]-Lhs[k]) time_swn = np.linspace(0, (Lhs[k+1]-Lto[k])*delta, 100) time_stn = np.linspace(0, (Lto[k]-Lhs[k])*delta, 100) Lswingx[k, :] = np.interp(time_swn, time_sw, InitialDataL[Lto[k]:Lhs[k+1], 5]) Lswingy[k, :] = np.interp(time_swn, time_sw, InitialDataL[Lto[k]:Lhs[k+1], 6]) Lswingt[k, :] = time_swn Lstancex[k, :] = np.interp(time_stn, time_st, InitialDataL[Lhs[k]:Lto[k], 5]) Lstancey[k, :] = np.interp(time_stn, time_st, InitialDataL[Lhs[k]:Lto[k], 6]) Lstancet[k, :] = time_stn if Rto[0] < Rhs[0]: for p in range(Rgait-1): for j in range(Rto[p], Rhs[p]): InitialDataR[j, 0] = 0 InitialDataR[j, 1] = (j-Rto[p])*delta InitialDataR[j, 2] = (Rhs[p]-Rto[p])*delta InitialDataR[j, 3:5] = get_ankle_point(motion[Rto[p], 2], motion[Rto[p], 6], motion[Rto[p], 7], Lthigh, Lshank) InitialDataR[j, 5:7] = get_ankle_point(motion[j, 2], motion[j, 6], motion[j, 7], Lthigh, Lshank) InitialDataR[j, 7:9] = get_ankle_point(motion[Rhs[p], 2], motion[Rhs[p], 6], motion[Rhs[p], 7], Lthigh, Lshank) for i in range(Rhs[p], Rto[p+1]): InitialDataR[i, 0] = 1 InitialDataR[i, 1] = (i-Rhs[p])*delta InitialDataR[i, 2] = (Rto[p+1]-Rhs[p])*delta InitialDataR[i, 3:5] = get_hip_point(motion[Rhs[p], 2], motion[Rhs[p], 6], motion[Rhs[p], 7], Lthigh, Lshank) InitialDataR[i, 5:7] = get_hip_point(motion[i, 2], motion[i, 6], motion[i, 7], Lthigh, Lshank) InitialDataR[i, 7:9] = get_hip_point(motion[Rto[p+1], 2], motion[Rto[p+1], 6], motion[Rto[p+1], 7], Lthigh, Lshank) time_sw = np.linspace(0, (Rhs[p]-Rto[p])*delta, Rhs[p]-Rto[p]) time_st = np.linspace(0, (Rto[p+1]-Rhs[p])*delta, Rto[p+1]-Rhs[p]) time_swn = np.linspace(0, (Rhs[p]-Rto[p])*delta, 100) time_stn = np.linspace(0, (Rto[p+1]-Rhs[p])*delta, 100) Rswingx[p, :] = np.interp(time_swn, time_sw, InitialDataR[Rto[p]:Rhs[p], 5]) Rswingy[p, :] = np.interp(time_swn, time_sw, InitialDataR[Rto[p]:Rhs[p], 6]) Rswingt[p, :] = time_swn Rstancex[p, :] = np.interp(time_stn, time_st, InitialDataR[Rhs[p]:Rto[p+1], 5]) Rstancey[p, :] = np.interp(time_stn, time_st, InitialDataR[Rhs[p]:Rto[p+1], 6]) Rstancet[p, :] = time_stn else: for p in range(Rgait-1): for i in range(Rhs[p], Rto[p]): InitialDataR[i, 0] = 1 InitialDataR[i, 1] = (i-Rhs[p])*delta InitialDataR[i, 2] = (Rto[p]-Rhs[p])*delta InitialDataR[i, 3:5] = get_hip_point(motion[Rhs[p], 2], motion[Rhs[p], 6], motion[Rhs[p], 7], Lthigh, Lshank) InitialDataR[i, 5:7] = get_hip_point(motion[i, 2], motion[i, 6], motion[i, 7], Lthigh, Lshank) InitialDataR[i, 7:9] = get_hip_point(motion[Rto[p], 2], motion[Rto[p], 6], motion[Rto[p], 7], Lthigh, Lshank) for j in range(Rto[p], Rhs[p+1]): InitialDataR[j, 0] = 0 InitialDataR[j, 1] = (j-Rto[p])*delta InitialDataR[j, 2] = (Rhs[p+1]-Rto[p])*delta InitialDataR[j, 3:5] = get_ankle_point(motion[Rto[p], 2], motion[Rto[p], 6], motion[Rto[p], 7], Lthigh, Lshank) InitialDataR[j, 5:7] = get_ankle_point(motion[j, 2], motion[j, 6], motion[j, 7], Lthigh, Lshank) InitialDataR[j, 7:9] = get_ankle_point(motion[Rhs[p+1], 2], motion[Rhs[p+1], 6], motion[Rhs[p+1], 7], Lthigh, Lshank) time_sw = np.linspace(0, (Rhs[p+1]-Rto[p])*delta, Rhs[p+1]-Rto[p]) time_st = np.linspace(0, (Rto[p]-Rhs[p])*delta, Rto[p]-Rhs[p]) time_swn = np.linspace(0, (Rhs[p+1]-Rto[p])*delta, 100) time_stn = np.linspace(0, (Rto[p]-Rhs[p])*delta, 100) Rswingx[p, :] = np.interp(time_swn, time_sw, InitialDataR[Rto[p]:Rhs[p+1], 5]) Rswingy[p, :] = np.interp(time_swn, time_sw, InitialDataR[Rto[p]:Rhs[p+1], 6]) Rswingt[p, :] = time_swn Rstancex[p, :] = np.interp(time_stn, time_st, InitialDataR[Rhs[p]:Rto[p], 5]) Rstancey[p, :] = np.interp(time_stn, time_st, InitialDataR[Rhs[p]:Rto[p], 6]) Rstancet[p, :] = time_stn if write_sign == True: with open(store_path+'InitialDataL_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(0, num_nodes-2*ext_nodes): for g in range(9): StringP += str(InitialDataL[r + ext_nodes, g]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'InitialDataR_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(0, num_nodes-2*ext_nodes): for g in range(9): StringP += str(InitialDataR[r + ext_nodes, g]) StringP += ' ' StringP += '\n' outfile.write(StringP) Lhs_s = Lhs[(Lhs >= ext_nodes) & (Lhs <= num_nodes-ext_nodes)] Lto_s = Lto[(Lto >= ext_nodes) & (Lto <= num_nodes-ext_nodes)] if Lhs_s[0] < Lto_s[0]: with open(store_path+'Lhs_Lto_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(np.min([len(Lhs_s), len(Lto_s)])): StringP += str(Lhs_s[r]-ext_nodes) StringP += ' ' StringP += str(Lto_s[r]-ext_nodes) StringP += ' ' StringP += '\n' outfile.write(StringP) else: with open(store_path+'Lto_Lhs_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(np.min([len(Lhs_s), len(Lto_s)])): StringP += str(Lto_s[r]-ext_nodes) StringP += ' ' StringP += str(Lhs_s[r]-ext_nodes) StringP += ' ' StringP += '\n' outfile.write(StringP) Rhs_s = Rhs[(Rhs >= ext_nodes) & (Rhs <= num_nodes-ext_nodes)] Rto_s = Rto[(Rto >= ext_nodes) & (Rto <= num_nodes-ext_nodes)] if Rhs_s[0] < Rto_s[0]: with open(store_path+'Rhs_Rto_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(np.min([len(Rhs_s), len(Rto_s)])): StringP += str(Rhs_s[r]-ext_nodes) StringP += ' ' StringP += str(Rto_s[r]-ext_nodes) StringP += ' ' StringP += '\n' outfile.write(StringP) else: with open(store_path+'Rto_Rhs_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(np.min([len(Rhs_s), len(Rto_s)])): StringP += str(Rto_s[r]-ext_nodes) StringP += ' ' StringP += str(Rhs_s[r]-ext_nodes) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Lswingx_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Lgait-2*ext_gait): for q in range(100): StringP += str(Lswingx[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Lswingy_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Lgait-2*ext_gait): for q in range(100): StringP += str(Lswingy[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Lswingt_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Lgait-2*ext_gait): for q in range(100): StringP += str(Lswingt[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Lstancex_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Lgait-2*ext_gait): for q in range(100): StringP += str(Lstancex[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Lstancey_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Lgait-2*ext_gait): for q in range(100): StringP += str(Lstancey[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Lstancet_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Lgait-2*ext_gait): for q in range(100): StringP += str(Lstancet[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Rswingx_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Rgait-2*ext_gait): for q in range(100): StringP += str(Rswingx[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Rswingy_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Rgait-2*ext_gait): for q in range(100): StringP += str(Rswingy[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Rswingt_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Rgait-2*ext_gait): for q in range(100): StringP += str(Rswingt[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Rstancex_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Rgait-2*ext_gait): for q in range(100): StringP += str(Rstancex[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Rstancey_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Rgait-2*ext_gait): for q in range(100): StringP += str(Rstancey[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) with open(store_path+'Rstancet_'+str(st_walking) +'_'+str(ed_walking)+'_'+str(int(100/every_node))+'HZ.txt', 'w') as outfile: StringP = '' for r in range(Rgait-2*ext_gait): for q in range(100): StringP += str(Rstancet[r+ext_gait, q]) StringP += ' ' StringP += '\n' outfile.write(StringP) if plot_sign ==True: Gait_info = np.zeros(6) Gait_info_std = np.zeros(6) Gait_info[0] = np.mean(np.diff(Lhs))*delta Gait_info_std[0] = np.std(np.diff(Lhs))*delta Gait_info[1] = np.mean(Lto[2:-2] - Lhs[1:-3])*delta Gait_info_std[1] = np.std(Lto[2:-2] - Lhs[1:-3])*delta Gait_info[2] = np.mean(Lhs[2:-2] - Lto[2:-2])*delta Gait_info_std[2] = np.std(Lhs[2:-2] - Lto[2:-2])*delta Gait_info[3] = np.mean(np.diff(Rhs))*delta Gait_info_std[3] = np.std(np.diff(Rhs))*delta Gait_info[4] = np.mean(Rto[1:] - Rhs[:-1])*delta Gait_info_std[4] = np.std(Rto[1:] - Rhs[:-1])*delta Gait_info[5] = np.mean(Rhs - Rto)*delta Gait_info_std[5] = np.std(Rhs - Rto)*delta num_par = 3 index = np.arange(num_par) fig2 = plt.figure(figsize=(8, 6)) ax = fig2.add_subplot(1, 1, 1) width = 0.3 p1 = ax.bar(index, Gait_info[:3], width, color='r', bottom=0, yerr=Gait_info_std[:3]) p2 = ax.bar(index+width, Gait_info[3:6], width, color='y', bottom=0, yerr=Gait_info_std[3:6]) ax.set_title('Gait Period Info (s)', fontsize=14) ax.set_xticks(index + width / 2) ax.set_xticklabels(('Full Gait', 'Stance', 'Swing'), fontsize=14) ax.legend((p1[0], p2[0]), ('Left', 'Right'), fontsize=14) plt.show() Lstance_ind = np.where(InitialDataL[:, 0] == 1)[0] Lswing_ind = np.where(InitialDataL[:, 0] == 0)[0] Rstance_ind = np.where(InitialDataR[:, 0] == 1)[0] Rswing_ind = np.where(InitialDataR[:, 0] == 0)[0] fig4 = plt.figure(figsize=(14, 8)) ax1 = fig4.add_subplot(2, 2, 1) plt.ylabel('Pelvis x (m)', fontsize = 14) ax2 = fig4.add_subplot(2, 2, 2) plt.ylabel('Pelvis y (m)', fontsize = 14) ax3 = fig4.add_subplot(2, 2, 3) plt.ylabel('Ankle x (m)', fontsize = 14) plt.xlabel('Gait period (s)', fontsize = 14) ax4 = fig4.add_subplot(2, 2, 4) plt.ylabel('Ankle y (m)', fontsize = 14) plt.xlabel('Gait period (s)', fontsize = 14) ax1.plot(InitialDataL[Lstance_ind, 1], InitialDataL[Lstance_ind, 5], '.', label='Left Leg') ax1.plot(InitialDataR[Rstance_ind, 1], InitialDataR[Rstance_ind, 5], '.', label='Right Leg') ax2.plot(InitialDataL[Lstance_ind, 1], InitialDataL[Lstance_ind, 6], '.', label='Left Leg') ax2.plot(InitialDataR[Rstance_ind, 1], InitialDataR[Rstance_ind, 6], '.', label='Right Leg') ax3.plot(InitialDataL[Lswing_ind, 1], InitialDataL[Lswing_ind, 5], '.', label='Left Leg') ax3.plot(InitialDataR[Rswing_ind, 1], InitialDataR[Rswing_ind, 5], '.', label='Right Leg') ax4.plot(InitialDataL[Lswing_ind, 1], InitialDataL[Lswing_ind, 6], '.', label='Left Leg') ax4.plot(InitialDataR[Rswing_ind, 1], InitialDataR[Rswing_ind, 6], '.', label='Right Leg') plt.legend(fontsize=14) plt.show()

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smunix/brickv

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/src/brickv/build_pkg.py

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https://github.com/smunix/brickv

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# -*- coding: utf-8 -*- """ brickv (Brick Viewer) Copyright (C) 2011 Olaf Lüke <olaf@tinkerforge.com> 2011 Bastian Nordmeyer <bastian@tinkerforge.com> build_pkg.py: Package builder for Brick Viewer This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. """ # Windows: # dependencies: # pythonxy (2.6) # py2exe # nsis # win redistributables vcredist under winxp # # run build scripts in all folders # run python build_pkg.py win to build the windows exe # final data is stored in folder "dist" # # script copies OpenGL, special libs and plugin_system # in dist folder import config import sys from distutils.core import setup import os import glob import shutil import matplotlib DESCRIPTION = 'Brick Viewer' NAME = 'Brickv' def build_windows_pkg(): import py2exe # os.system("python build_all_ui.py") # data_files = matplotlib.get_py2exe_datafiles() data_files = [] def visitor(arg, dirname, names): for n in names: if os.path.isfile(os.path.join(dirname, n)): if arg[0] == 'y': #replace first folder name data_files.append((os.path.join(dirname.replace(arg[1],"")) , [os.path.join(dirname, n)])) else: # keep full path data_files.append((os.path.join(dirname) , [os.path.join(dirname, n)])) os.path.walk(os.path.normcase("../build_data/Windows/"), visitor, ('y',os.path.normcase("../build_data/Windows/"))) os.path.walk("plugin_system", visitor, ('n',"plugin_system")) data_files.append( ( os.path.join('.') , [os.path.join('.', 'brickv-icon.png')] ) ) setup( name = NAME, description = DESCRIPTION, version = config.BRICKV_VERSION, data_files = data_files, options = { "py2exe":{ "dll_excludes":["MSVCP90.dll"], "includes":["PyQt4.QtSvg", "sip","PyQt4.Qwt5", "PyQt4.QtCore", "PyQt4.QtGui","numpy.core.multiarray", "PyQt4.QtOpenGL","OpenGL.GL", "ctypes.util", "plot_widget", "pylab", "matplotlib.backends.backend_qt4agg", "scipy.interpolate"], "excludes":["_gtkagg", "_tkagg"] } }, zipfile=None, windows = [{'script':'main.py', 'icon_resources':[(0,os.path.normcase("../build_data/Windows/brickv-icon.ico"))]}] ) # build nsis run = "\"" + os.path.join("C:\Program Files\NSIS\makensis.exe") + "\"" data = " dist\\nsis\\brickv_installer_windows.nsi" print "run:", run print "data:", data os.system(run + data) def build_linux_pkg(): import shutil src_path = os.getcwd() build_dir = 'build_data/linux/brickv/usr/share/brickv' dest_path = os.path.join(os.path.split(src_path)[0], build_dir) if os.path.isdir(dest_path): shutil.rmtree(dest_path) shutil.copytree(src_path, dest_path) build_data_path = os.path.join(os.path.split(src_path)[0], 'build_data/linux') os.chdir(build_data_path) os.system('dpkg -b brickv/ brickv-' + config.BRICKV_VERSION + '_all.deb') if __name__ == "__main__": if sys.argv[1] == "win": sys.argv[1] = "py2exe" # rewrite sys.argv[1] for setup(), want to call py2exe build_windows_pkg() if sys.argv[1] == "linux": build_linux_pkg()

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nkapetanas/Deep-Learning-Image-Classifier

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/cnnSVHN.py

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[]

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https://github.com/nkapetanas/Deep-Learning-Image-Classifier

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refs/heads/master

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import os import numpy as np from scipy.io import loadmat from sklearn import metrics from sklearn.model_selection import StratifiedKFold np.random.seed(1400) import itertools from keras.models import Sequential from keras.layers import Dense, Flatten, Conv2D, MaxPool2D from keras.callbacks import EarlyStopping, ModelCheckpoint from six.moves import urllib import matplotlib.pyplot as plt URL_TRAIN_PATH = 'http://ufldl.stanford.edu/housenumbers/train_32x32.mat' URL_TEST_PATH = 'http://ufldl.stanford.edu/housenumbers/test_32x32.mat' DOWNLOADED_FILENAME_TRAIN = 'housenumbers_training.mat' DOWNLOADED_FILENAME_TEST = 'housenumbers_test.mat' HEIGHT = 32 WIDTH = 32 CHANNELS = 3 # since there are rgb images N_INPUTS = HEIGHT * WIDTH N_OUTPUTS = 11 def download_data(): if not os.path.exists(DOWNLOADED_FILENAME_TRAIN): filename, _ = urllib.request.urlretrieve(URL_TRAIN_PATH, DOWNLOADED_FILENAME_TRAIN) print('Found and verified file from this path: ', URL_TRAIN_PATH) print('Download file: ', DOWNLOADED_FILENAME_TRAIN) if not os.path.exists(DOWNLOADED_FILENAME_TEST): filename, _ = urllib.request.urlretrieve(URL_TEST_PATH, DOWNLOADED_FILENAME_TEST) print('Found and verified file from this path: ', URL_TEST_PATH) print('Download file: ', DOWNLOADED_FILENAME_TEST) def get_kfold(x_train, y_train, k): folds = list(StratifiedKFold(n_splits=k, shuffle=True, random_state=1).split(x_train, y_train)) return folds, x_train, y_train def get_model(x_train): model = Sequential() model.add(Conv2D(9, (3, 3), padding='same', activation='relu', input_shape=x_train.shape[1:])) model.add(MaxPool2D(pool_size=(3, 3))) model.add(Conv2D(36, (3, 3), padding='same', activation='relu')) model.add(MaxPool2D(pool_size=(3, 3))) model.add(Conv2D(49, (3, 3), padding='same', activation='relu')) model.add(MaxPool2D(pool_size=(3, 3))) model.add(Flatten()) model.add(Dense(128, activation='relu')) model.add(Dense(64, activation='relu')) model.add(Dense(32, activation='relu')) model.add(Dense(11, activation="softmax")) return model def plot_confusion_matrix(confusion_matrix, target_names, normalize=False, title='Confusion matrix'): plt.figure(figsize=(8, 6)) plt.imshow(confusion_matrix, interpolation='nearest', cmap=plt.get_cmap('Blues')) plt.title(title) if target_names is not None: tick_marks = np.arange(len(target_names)) plt.xticks(tick_marks, target_names, rotation=45) plt.yticks(tick_marks, target_names) thresh = confusion_matrix.max() / 1.5 if normalize else confusion_matrix.max() / 2 for i, j in itertools.product(range(confusion_matrix.shape[0]), range(confusion_matrix.shape[1])): if normalize: plt.text(j, i, "{:0.4f}".format(confusion_matrix[i, j]), horizontalalignment="center", color="white" if confusion_matrix[i, j] > thresh else "black") else: plt.text(j, i, "{:,}".format(confusion_matrix[i, j]), horizontalalignment="center", color="white" if confusion_matrix[i, j] > thresh else "black") plt.tight_layout() plt.ylabel('True label') plt.xlabel('Predicted label') plt.show() def get_random_index_of_images(): indexes_for_ran_chosen_image_each_class = dict() indexes_for_ran_chosen_image_each_class[1] = 9 indexes_for_ran_chosen_image_each_class[2] = 2 indexes_for_ran_chosen_image_each_class[3] = 3 indexes_for_ran_chosen_image_each_class[4] = 15 indexes_for_ran_chosen_image_each_class[5] = 5 indexes_for_ran_chosen_image_each_class[6] = 21 indexes_for_ran_chosen_image_each_class[7] = 14 indexes_for_ran_chosen_image_each_class[8] = 13 indexes_for_ran_chosen_image_each_class[9] = 1 return indexes_for_ran_chosen_image_each_class download_data() # squeeze_me= True -> Unit 1x1 matrix dimensions are squeezed to be scalars train_data_mat = loadmat(DOWNLOADED_FILENAME_TRAIN, squeeze_me=True) test_data_mat = loadmat(DOWNLOADED_FILENAME_TEST, squeeze_me=True) x_train = train_data_mat['X'] y_train = train_data_mat['y'] x_test = test_data_mat['X'] y_test = test_data_mat['y'] # num_images, height, width, num_channels x_train = np.transpose(x_train, (3, 0, 1, 2)) x_test = np.transpose(x_test, (3, 0, 1, 2)) x_train_validation_data = x_train[:7326] y_train_validation_data = y_train[:7326] x_train = x_train[7326:] y_train = y_train[7326:] es = EarlyStopping(monitor='val_loss', mode='auto', verbose=1, patience=2) checkpoint = ModelCheckpoint('/logs/logs.h5', monitor='val_loss', mode='min', save_best_only=True, verbose=1) model = get_model(x_train) model.compile(loss='sparse_categorical_crossentropy', optimizer='Adam', metrics=['accuracy']) model.fit(x_train, y_train, epochs=10, validation_data=(x_train_validation_data, y_train_validation_data), callbacks=[es]) predicted_values = model.predict_classes(x_test) matrix = metrics.confusion_matrix(y_test, predicted_values) print(metrics.accuracy_score(y_test, predicted_values)) print(metrics.f1_score(y_test, predicted_values, average='micro')) print(metrics.recall_score(y_test, predicted_values, average='micro')) print(metrics.precision_score(y_test, predicted_values, average='micro')) target_names = ['1', '2', '3', '4', '5', '6', '7', '8', '9'] plot_confusion_matrix(matrix, target_names)

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cnnSVHN.py

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anstepp/junkyardTemplesSolanum

2,113,123,911,496

19f5f755f8baea09d876af9390f6c2c88cdf168e

8c3bf4b4800ab72666f9add6b66ca628eb319e5d

/testGenePlay.py

07411673f9d35fcef4f06b8a0db2b43f1f6289eb

[]

no_license

https://github.com/anstepp/junkyardTemplesSolanum

0b0dee326d33ce70dc2e0961dda56485f383f032

af4bd0543a633680ae42e10d2eaa6e74fba02cd2

refs/heads/master

2020-05-17T11:17:43.642121

2017-05-08T14:58:35

38,716,606

0

null

from rtcmix import * import utils, words import random, sys rtsetparams(44100, 2) load("SPECTACLE2") start = 0 #chosen = random.choice(words.words) #file = chosen[1] for thing in words.words: rtinput(thing[1]) amp = 10 env = maketable("curve", 1000, 0,0,-2, 10,1,2, 1000,0) dur = DUR() fftsize = 16384 windowsize = fftsize * 2 winTab = 0 overlap = 2 eqTab = maketable("curve", "nonorm", fftsize, 0,-90,0, 151,-90,2, 152,0,0, 153,0,2, 154,-90,0, 160,-90,2, 161,0,1, 162,0,2, 163,-90,0, 179,-90,2, 180,0,1, 181,0,2, 182,-90,0, 243,-90,2, 244,0,2, 245,-90,0, fftsize,-90) delayTab = maketable("random", fftsize, 0, 0, 10) fbTab = .99 pan = random.random() ringdown = 50 SPECTACLE2(0, 0, dur, amp * env, 1, dur * ringdown, fftsize, windowsize, winTab, overlap, eqTab, delayTab, fbTab, 0, 22050, 0, 22050, 0, 1, 0, pan) start += ring print thing

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889

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testGenePlay.py

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skdonepudi/100DaysOfCode

5,299,989,666,111

cdc3b695a5a8f843965a83562593f438aa6e63b0

9818262abff066b528a4c24333f40bdbe0ae9e21

/Day 16/SetNumbers.py

b0da7bb7d42efc289f22494e47d87c54e7658ceb

[ "MIT" ]

permissive

https://github.com/skdonepudi/100DaysOfCode

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af4594fb6933e4281d298fa921311ccc07295a7c

refs/heads/master

2023-02-01T08:51:33.074538

2020-12-20T14:02:36

null

0

null

''' Set numbers You are given the binary representation of a number. You must consider the highest number of set bits in the binary representation to complete your task. For example, is represented as in binary and it contains four set bits (1-bits). You are also given a number and your task is to determine the number that is less than or equal to and contains the maximum number of set bits in its binary representation. In other words, print a number that is less than or equal to such that the number of set bits in the binary representation of must be maximum Input format First line: An integer denoting the number of test cases For each test case: First line: An integer Output format For each test case, print the answer on a new line denoting a number that is less than or equal to such that the number of set bits in the binary representation of must be maximum. SAMPLE INPUT 1 345 SAMPLE OUTPUT 255 Explanation The number 255 (< 345) has most number of set bits. ''' for _ in range(int(input())): x = bin(int(input())) if all(i == '1' for i in x[2:]): print (int(x, 2)) else: print(int('1' * len(x[3:]), 2))

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py

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SetNumbers.py

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atom015/py_boj

6,133,213,336,532

578b957f56cbd4d38e0ac365cc318b313500eac9

592498a0e22897dcc460c165b4c330b94808b714

/2000번/2309_일곱 난쟁이.py

0b837fff035012f572d6763c934cbd76d02b85fa

[]

no_license

https://github.com/atom015/py_boj

abb3850469b39d0004f996e04aa7aa449b71b1d6

42b737c7c9d7ec59d8abedf2918e4ab4c86cb01d

refs/heads/master

2022-12-18T08:14:51.277802

2020-09-24T15:44:52

179,933,927

0

null

def main(li,s): for i in range(9): for j in range(9): if i != j: if 100 == s-(li[i]+li[j]): for k in sorted(li): if k != li[i] and k != li[j]: print(k) return num_li = [] for i in range(9): num_li.append(int(input())) main(num_li,sum(num_li)) #이문제는 백설공주와 일곱난쟁이랑 비슷한 브루트 포스문제이다.

UTF-8

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2309_일곱 난쟁이.py

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bigheadG/gardCharge_rpi

4,183,298,163,513

3aa7423ccef1ffd8ffffbf60b11d24f9b4e4eb8e

73d3ccab5158d4f33d81818eef0b7cd0a5bf3275

/code/packBTSend.py

b492b5da981c5347a93bb0ccd2b8743f6051bd24

[ "MIT" ]

permissive

https://github.com/bigheadG/gardCharge_rpi

15d23af9cd52b45ffedd24cc89ba8843ba7e99fb

45135cf83ac0daa0114d0409bbcfcbd982071ef1

refs/heads/master

2020-04-29T02:15:33.846878

2019-04-02T09:46:07

175,760,187

8

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null

# #Code is under develop for control GC101 # class Gdefine: CMD_DRIVE = 1, CMD_CUTOFF_TIME = 2 CMD_TIMER_EN = 3 CMD_READ_MEM = 4 CMD_READ_MEM_A = 4 CMD_FACT_INIT = 5 CMD_SAMPLE_TIME = 6 CMD_READ_CONFIG = 7 CMD_ERASE_QUE = 8 CMD_RUN_TEST = 9 CMD_SET_TRIP_AMP = 11 CMD_SET_OFFTIME = 12 CMD_READ_CONFIG_2 = 14 CMD_OFFLINE_ENABLE = 17 class packBTSend: flow = 0 def packTXdata(self,mode,data): outBuf = [0xaa for i in range(20)] inBuf = [0xaa for i in range(20)] inBuf[2] = mode #outBuf no decrypt outBuf[0] = 40 outBuf[1] = self.flow outBuf[19] = 41 if mode == 1 or mode == 3 or mode == 4 or mode == 6 or mode == 11 or mode == 17: inBuf[3] = (data & 0x000000FF) elif mode == 2: #CMD_CUTOFF_TIME inBuf[4] = data & 0x000000FF inBuf[5] = (data & 0x0000FF00) >> 8 inBuf[6] = (data & 0x00FF0000) >> 16 inBuf[7] = (data & 0xFF000000) >> 24 elif mode == 12: #CMD_SETOFF_TIME inBuf[3] = data & 0x000000FF inBuf[4] = (data & 0x0000FF00) >> 8 inBuf[5] = (data & 0x00FF0000) >> 16 #print("inBuf:{}".format(inBuf)) # encrypt i = 2 for x in inBuf[2:17]: d = x ^ ((i ^ inBuf[18]) ^ 0x38) outBuf[i] = d i += 1 self.flow += 1 self.flow = self.flow % 10 #print("flow = {:d}".format(self.flow)) return outBuf

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thelebster/zapret-info-parser

6,682,969,114,065

d83e6851ef14c5b867c50e860c0a98f518721b0e

8cb749f1c834495e0b98da16d45a028dd30c5259

/updater/update.py

c573edcc4f255a0c79071a998fb9d24ca2be30ef

[]

no_license

https://github.com/thelebster/zapret-info-parser

187fea5215b2e0a3490318720615bab88c8b01b2

1c053b1f38594a05225f130d234551a282c24d23

refs/heads/master

2021-01-05T14:11:03.547108

2020-03-01T19:23:07

241,046,135

0

null

import os import glob from pymongo import MongoClient import ipaddress from bson.int64 import Int64 MONGODB_URI = os.getenv('MONGODB_URI', 'mongodb://root:root@localhost:27017/blocked?authMechanism=DEFAULT&authSource=admin') MONGODB_IMPORT_COLLECTION = os.getenv('MONGODB_IMPORT_COLLECTION', 'blocked_new') MONGODB_PROD_COLLECTION = os.getenv('MONGODB_PROD_COLLECTION', 'blocked') IMPORT_DIR = os.getenv('IMPORT_DIR', '../data/archive/utf8') def import_file(filename): mongodb_client = MongoClient(MONGODB_URI) db = mongodb_client.get_database() blocked = db.get_collection(MONGODB_IMPORT_COLLECTION) with open(filename, 'r') as csv_file: lines = csv_file.readlines() inserts = [] inserted = 0 for line in lines: components = line.strip().split(';') if len(components) < 6: continue ips = components[0].split(' | ') domain = components[1] url = components[2].strip('"') decision_org = components[3] decision_num = components[4] decision_date = components[5] if domain.strip() == '': domain = None if url.strip() == '' or url == 'http://' or url == 'https://': url = None for ip in ips: if ip.strip() == '': if domain is not None and len(domain.split('.')) == 4: ip = domain else: ip = None ip_first = None ip_last = None length = None if ip is not None: pair = ip.split('/') ip_first = ipaddress.ip_address(pair[0]) # Skip ipv6. if ip_first.version == 6: continue ip_first = Int64(ip_first) if len(pair) > 1: length = int(pair[1]) ip_last = ip_first | (1 << (32 - length)) - 1 else: length = 32 ip_last = ip_first inserts.append({ 'ip': ip, 'ip_first': ip_first, 'ip_last': ip_last, 'length': length, 'decision_date': decision_date, 'decision_org': decision_org, 'decision_num': decision_num, 'domain': domain, 'url': url, }) if len(inserts) == 10000: result = blocked.insert_many(inserts) result.inserted_ids inserted += len(inserts) inserts = [] pass if len(inserts) > 0: result = blocked.insert_many(inserts) result.inserted_ids inserted += len(inserts) pass if __name__ == '__main__': files = [f for f in glob.glob(IMPORT_DIR + "/*.csv")] for f in files: basename = os.path.basename(f) print(f'Importing {basename} file...') import_file(f) # @todo Run health check somewhere...? mongodb_client = MongoClient(MONGODB_URI) db = mongodb_client.get_database() try: # Try to drop temporary collection. blocked_tmp = db.get_collection(f'~{MONGODB_PROD_COLLECTION}') blocked_tmp.drop() except Exception as err: print(err) try: # Try to rename current collection. blocked = db.get_collection(MONGODB_PROD_COLLECTION) blocked.rename(f'~{MONGODB_PROD_COLLECTION}') except Exception as err: print(err) blocked_new = db.get_collection(MONGODB_IMPORT_COLLECTION) blocked_new.create_index('domain') blocked_new.create_index('ip') blocked_new.create_index('url') blocked_new.rename(MONGODB_PROD_COLLECTION)

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py

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update.py

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amyc28/Premiere-Pro-Silence-Cutter

13,786,845,029,431

9fe608314030874affd5d54da4c8916be138f402

073412f89865e4f726bf14a115630c52a17658e6

/MouseTracker.py

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[]

no_license

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bbe7347b0dc7e74f0bd5a5b56f2d0edd8b2885df

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refs/heads/master

2021-02-19T07:38:55.288611

2020-02-28T03:20:47

null

0

null

import numpy as np from PIL import ImageGrab import cv2 from directKeys import click, queryMousePosition, PressKey, ReleaseKey, SPACE import time import math from pynput.keyboard import Key, Controller as KeyboardController from pynput.mouse import Controller, Button as MouseController import pyautogui while True: mouse_pos = queryMousePosition() #sets mouse_pos to the current position of the mouse print(mouse_pos.x, mouse_pos.y) time.sleep(.01)

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MouseTracker.py

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S-boker/Personal-Projects-

10,015,863,780,553

7c7874bfd98986a3de47f095df60da0399e5b71a

281e4720eab3c1ae339bd0f6c5554e9c35a1fd79

/Sudoku_Solver.py

f7959557e3ec71e2d2e5e3d7ec18691434e15818

[]

no_license

https://github.com/S-boker/Personal-Projects-

869a19282ae357bc884b188cfa1e8ba819596b6c

b03772707981e006b95e90be6b851d6ccf12373d

refs/heads/master

2021-01-08T03:48:21.486816

2020-02-20T14:45:26

241,903,557

0

null

# Shohum Boker # 2/19/20 # initializing lists box0 = [0] * 9 box1 = [0] * 9 box2 = [0] * 9 box3 = [0] * 9 box4 = [0] * 9 box5 = [0] * 9 box6 = [0] * 9 box7 = [0] * 9 box8 = [0] * 9 boxes = [box0, box1, box2, box3, box4, box5, box6, box7, box8] # Okay function def okay(b, sq): # box test bs = [int(s) for s in b] for s in b: if bs.count(s) > 1 and s != 0: return False # Initializing helper lists lists rt = [] ct = [] for box in boxes: tbi = boxes.index(box) bi = boxes.index(b) if b is box: continue if tbi % 3 == bi % 3: ct.append(box) # Column adjacent Boxes if tbi // 3 == bi // 3: rt.append(box) # Row adjacent Boxes sqi = b.index(sq) ri = [i for i in range(9) if i // 3 == sqi // 3] # Row helper list ci = [i for i in range(9) if i % 3 == sqi % 3] # Column helper list # Using helper lists for column and row test for x in range(6): y = x // 3 cb = ct[y] rb = rt[y] c = ci[x % 3] r = ri[x % 3] if int(rb[r]) == sq or int(cb[c]) == sq: return False return True # Finding the last integer if the entry goes out of bounds def lastInt(b, ind): ind -= 1 while isinstance(b[ind], str) or ind < 0: if ind < 0: b = boxes[boxes.index(b) - 1] ind = 8 if isinstance(b[ind], str): ind -= 1 return [b, ind] def printr(): # Checking if the board was Solvable for box in boxes: for s in box: if s ==0: print("----------------------------------") print("Unsolvable") quit() # Helper list row = [[0, 1, 2], [3, 4, 5], [6, 7, 8]] s = "----------------------" for x in range(81): # Every row has nine entries if x % 9 == 0: s += "\n" # Complex formula taking advantage of the helper list to convert boxes into rows s += str(boxes[row[x // 27][(x // 3) % 3]][row[(x // 9) % 3][x % 3]]) print(s) # Instructions for the user to operate the UI system (hopefully in the future the UI will be better) print("Welcome to Sudoku Solver:") print("Enter the rows in your Sudoku Board from the top to the bottom and all blank entries should be'0'") print("For example: 104005007 is a valid row") row = [[0, 1, 2], [3, 4, 5], [6, 7, 8]] x = 0 boo = False while x < 9: n = input("row" + str(x + 1) + ": ") # Check for proper length while len(n) != 9: print("Error: Row is not of size 9") n = input("row" + str(x + 1) + ": ") for y in range(9): if boo: boo = False break try: # Check for proper data type and have all values as ints bs = [int(s) for s in n] except ValueError: print("Error: Invalid input, characters are not acceptable. ") # Allows the user to redo the row x -= 1 break else: # Checks that the row is valid for s in bs: if bs.count(s) > 1 and s != 0: print("Error: Repeating value found: " + str(s)) x -= 1 boo = True break # Converts all 0's to ints if n[y] == "0": r = int(n[y]) else: r = n[y] # Complex formula to put to rows in the forms of boxes boxes[row[x // 3][y // 3]][row[x % 3][y % 3]] = r x += 1 # Initializing index of "boxes" q = -1 while True: # Moving to the next box q += 1 # If all boxes are filled print if q == 9: printr() break else: box = boxes[q] # Initializing index of "boxes" p = -1 while True: # Moving to the next square in the box p += 1 # If all squares are filled up then move on to the next box if p == 9: break else: while True: # Checking if the value was entered by the user if isinstance(box[p], str): break else: # Add one to the current value in the square box[p] += 1 # If the value is to big: backtrack if box[p] == 10: box[p] = 0 cord = lastInt(box, p) box = cord[0] p = cord[1] q = boxes.index(box) # Check if the value in the square is valid in rules of Sudoku at its current index elif okay(box, box[p]): break

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LMZimmer/Auto-PyTorch_refactor

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/autoPyTorch/search_space/search_space.py

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refs/heads/master

2023-02-19T02:02:57.256438

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import typing from typing import Optional import ConfigSpace as cs class SearchSpace: hyperparameter_types = { 'categorical': cs.CategoricalHyperparameter, 'integer': cs.UniformIntegerHyperparameter, 'float': cs.UniformFloatHyperparameter, 'constant': cs.Constant, } @typing.no_type_check def __init__( self, cs_name: str = 'Default Hyperparameter Config', seed: int = 11, ): """Fit the selected algorithm to the training data. Args: cs_name (str): The name of the configuration space. seed (int): Seed value used for the configuration space. Returns: """ self._hp_search_space = cs.ConfigurationSpace( name=cs_name, seed=seed, ) @typing.no_type_check def add_hyperparameter( self, name: str, hyperparameter_type: str, **kwargs, ): """Add a new hyperparameter to the configuration space. Args: name (str): The name of the hyperparameter to be added. hyperparameter_type (str): The type of the hyperparameter to be added. Returns: hyperparameter (cs.Hyperparameter): The hyperparameter that was added to the hyperparameter search space. """ missing_arg = SearchSpace._assert_necessary_arguments_given( hyperparameter_type, **kwargs, ) if missing_arg is not None: raise TypeError(f'A {hyperparameter_type} must have a value for {missing_arg}') else: hyperparameter = SearchSpace.hyperparameter_types[hyperparameter_type]( name=name, **kwargs, ) self._hp_search_space.add_hyperparameter( hyperparameter ) return hyperparameter @staticmethod @typing.no_type_check def _assert_necessary_arguments_given( hyperparameter_type: str, **kwargs, ) -> Optional[str]: """Assert that given a particular hyperparameter type, all the necessary arguments are given to create the hyperparameter. Args: hyperparameter_type (str): The type of the hyperparameter to be added. Returns: missing_argument (str|None): The argument that is missing to create the given hyperparameter. """ necessary_args = { 'categorical': {'choices', 'default_value'}, 'integer': {'lower', 'upper', 'default', 'log'}, 'float': {'lower', 'upper', 'default', 'log'}, 'constant': {'value'}, } hp_necessary_args = necessary_args[hyperparameter_type] for hp_necessary_arg in hp_necessary_args: if hp_necessary_arg not in kwargs: return hp_necessary_arg return None @typing.no_type_check def set_parent_hyperperparameter( self, child_hp, parent_hp, parent_value, ): """Activate the child hyperparameter on the search space only if the parent hyperparameter takes a particular value. Args: child_hp (cs.Hyperparameter): The child hyperparameter to be added. parent_hp (cs.Hyperparameter): The parent hyperparameter to be considered. parent_value (str|float|int): The value of the parent hyperparameter for when the child hyperparameter will be added to the search space. Returns: """ self._hp_search_space.add_condition( cs.EqualsCondition( child_hp, parent_hp, parent_value, ) ) @typing.no_type_check def add_configspace_condition( self, child_hp, parent_hp, configspace_condition, value, ): """Add a condition on the chi Args: child_hp (cs.Hyperparameter): The child hyperparameter to be added. parent_hp (cs.Hyperparameter): The parent hyperparameter to be considered. configspace_condition (cs.AbstractCondition): The condition to be fullfilled by the parent hyperparameter. A list of all the possible conditions can be found at ConfigSpace/conditions.py. value (str|float|int|list): The value of the parent hyperparameter to be matched in the condition. value needs to be a list only for the InCondition. Returns: """ self._hp_search_space.add_condition( configspace_condition( child_hp, parent_hp, value, ) )

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Heisenberg2017/LogColorizer

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refs/heads/master

2020-07-23T04:46:00.549544

2019-12-09T08:56:27

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from monitor.watcher import Watcher import time try: import configparser except ImportError: import ConfigParser as configparser def multi_watch(args): gens = [] config = configparser.ConfigParser() config.read('conf/monitor.conf') for name in config.sections(): print('-----[%s]-----' % name) watch_dict = {} for key, value in config[name].items(): print("%s: %s" % (key, value)) watch_dict[key] = value excludes = watch_dict['excludes'].split('|') if watch_dict.get('excludes') else None gen = Watcher(watch_dict['path'], excludes=excludes, project=name).auto_reload(watch_dict['action']) gens.append(gen) while True: for g in gens: next(g) time.sleep(1)

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AlexLSmith/mqtt-app

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/mqtt_app/config.py

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[]

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refs/heads/master

2020-06-21T13:52:30.987317

2019-07-18T07:20:17

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HOST = "localhost" PORT = 1883 SENSOR_TOPIC = "sensor/upload" AGGREGATE_TOPIC = "sensor/aggregate" AVG_TIME_PERIODS = (1, 5, 30)

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yuanhaoz/Python-Scrapy

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/test/test2.py

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[]

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refs/heads/master

2020-12-01T05:41:58.159997

2016-08-27T07:53:45

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# -*- coding: utf-8 -*- ######################################################################## # # Copyright (c) 2016 Baidu.com, Inc. All Rights Reserved # ######################################################################## import md5 import time import urllib import re import scrapy from scrapy.http import Request from bs4 import BeautifulSoup from scrapy import signals html_doc = """ <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"> <html xmlns="http://www.w3.org/1999/xhtml" xml:lang="zh-HK" lang="zh-hk"> <head> <meta name="Keywords" content="保安局禁毒處, 禁毒影音短片"> <meta name="description" content="保安局禁毒處 - 禁毒影音短片"> <meta name="description-2" content="Security Bureau, Narcotics Division Website"> <meta name="author" content="Security Bureau, Narcotics Division"> <script language="JavaScript" src="/js/jquery-1.11.0.min.js" type="text/javascript"></script> <link href="/css/print.css" rel="stylesheet" type="text/css" media="print"> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <script language="JavaScript" src="../js/genLayer.js" type="text/javascript"></script> <script language="JavaScript" src="../js/common.js" type="text/javascript"></script> <script language="JavaScript" src="../js/data.js" type="text/javascript"></script> <script language="JavaScript" src="../js/swf.js" type="text/javascript"></script> <script language="JavaScript" src="../js/jquery-1.11.0.min.js" type="text/javascript"></script> <script language="JavaScript" src="../js/reCon.js" type="text/javascript"></script> <link href="/css/format.css" rel="stylesheet" type="text/css" > <title>保安局禁毒處 - 禁毒影音短片</title> <script language="JavaScript" type="text/javascript">  </script> <style type="text/css">  .reCon3 .batch { clear: both; padding-top: 5px !important; } </style> </head> <body><h1 style="display:none">Title</h1> <table border="0" cellpadding="0" cellspacing="0" width="760"> <tr valign="top"> <td> <script language="JavaScript" type="text/javascript">targetSwitchPage = ""</script> <script language="JavaScript" src="/js/header.js" type="text/javascript"></script> </td> </tr> </table> <table id="content" width="760" border="0" align="left" cellpadding="0" cellspacing="0"> <tr> <td align="left" valign="top" width="153" height="22" > <script language="JavaScript" type="text/javascript">getLeftMenu();</script> </td> <td align="left" valign="top" bgcolor="#FFFFFF"> <table width="597" border="0" cellpadding="5" cellspacing="5" >  <tr> <td> <table border="1"> <Tr valign="middle"> <td width="25%"><a href="druginfo.htm" title="This link will open in new window">毒品資料</a></td> <td width="25%"><a href="publications.htm" title="This link will open in new window">禁毒刊物</a></td> <td width="25%"><a href="videos_radio_clips.htm" title="This link will open in new window">禁毒影音短片</a></td> <td width="25%"><a href="resources_parents.htm" title="This link will open in new window">給家長的禁毒資源</a></td> </tr> <Tr valign="middle"> <td width="25%"><a href="resources_teachers.htm" title="This link will open in new window">給教師和社工的禁毒資源</a></td> <td width="25%"><a href="resources_professionals.htm" title="This link will open in new window">給醫護人員的禁毒資源</a></td> <td width="25%"><a href="resources_youths.htm" title="This link will open in new window">給青年人的禁毒資源</a></td> <td width="25%"><a href="druginfocentre.htm" title="This link will open in new window">香港賽馬會藥物資訊天地</a></td> </tr> </table> </td> </tr> <tr> <td valign="top" align="left"><img src="images/top_buttons/top_buttons_dot_line.gif" alt=""> </td> </tr> <tr> <td valign="top" align="left"><a name="top"></a></td> </tr> <tr> <a name="main-content" id="main-content" tabindex="0"></a> <td valign="top"><span ><strong>禁毒影音短片</strong></span></td> </tr> <tr> <td valign="top"> <table border="0" cellspacing="2" cellpadding="8" > <Tr valign="top"> <td><strong>禁毒影像短片：</strong></td> </tr> <tr> <td> <div style="width:100%;" class="reCon3"> <div class="iso"> <a href="http://www.hkayd.org.hk/YourChoice/finalentries.pdf" target="_blank"><img src="/tc/images/finalentries.jpg" alt="" border="0" > <br>禁毒基金贊助「 Your Choice 」納米電影創作比賽</a> </div> <div class="iso"> <a href="tv_announcements.htm"><img src="/tc/images/banner_03.gif" alt="" border="0" > <br>電視宣傳短片</a> </div> <div class="iso"> <a href="sunproject.htm"><img src="/tc/images/sunlife_icon.gif" alt="" border="0" > <br>禁毒基金贊助「路訊通」節目《Sun 生命》</a> </div>      <div class="iso"> <a href="antidrug_themesong_2.htm"><img src="/tc/images/icon_antidrug_song_2.gif" border="0" width="137" height="103" alt="" b> <br>「不可一．不可再」<br>全港青少年禁毒運動2009 <br>主題曲「天造之材」MTV</a> </div> <div class="iso"> <a href="antidrug_themesong.htm"><img src="/tc/images/icon_antidrug_song.gif" border="0" width="137" height="103" alt="" b> <br>「不可一．不可再」禁毒運動主題曲「不不不」MTV</a> </div> </div> </td> </tr> <tr> <td> </td> </tr> </table> </td> </tr> <tr> <td valign="top"> <table border="0" cellspacing="2" cellpadding="8" > <Tr valign="top"> <td colspan="3"><strong>禁毒聲音短片：</strong></td> </tr> <tr> <td> <div style="width:100%;" class="reCon3"> <div class="iso"> <a href="radio_announcements.htm"><img src="/tc/images/icon_antidrug_radio.gif" border="0" width="137" height="103" alt="" > <br>電台宣傳聲帶</a> </div> <div class="iso"> <a href="rs_handstogether_2015.htm"><img src="/tc/images/sqsqkd2015.jpg" border="0" alt="" > <br>禁毒電台環節「手牽手　齊抗毒」</a> </div> <div class="iso"> <a href="adEduSeg.htm"><img src="/tc/images/jjdp_qxkd_s.jpg" border="0" alt="" > <br>禁毒電台環節「堅拒毒品　齊心抗毒」</a> </div> <div class="iso"> <a href="http://www.metroradio.com.hk/Campaign/2013/997/Narcotics/" target="_blank" title="此連結會於新視窗開啟"><img src="/tc/images/jbtc.gif" alt="" b width="137" height="103" border="0"> <br>禁毒廣播劇「戒不太遲」</a> </div> <div class="iso"> <a href="antidrug_themesong_2.htm"><img src="/tc/images/icon_antidrug_song_2.gif" border="0" width="137" height="103" alt="" b> <br>「不可一．不可再」全港青少年禁毒運動2009 主題曲「天造之材」</a> </div> <div class="iso"> <a href="antidrug_themesong.htm"><img src="/tc/images/icon_antidrug_song.gif" border="0" width="137" height="103" alt="" b> <br>「不可一．不可再」禁毒運動主題曲「不不不」</a> </div> </div> </td> </tr> <tr> <td> </td> <td> </td> </tr> </table> </td> </tr> <tr> <td> <div align="center"><img src="images/chi/botdot.jpg" alt="" width="602" height="3" style="width:603px;" ></div> <table align="center" border="0" cellpadding="0" cellspacing="0" width="98%"> <tbody><tr> <td><script language="JavaScript" src="../js/footer.js" type="text/javascript"></script><script language="JavaScript" type="text/javascript"> footer(); </script></td> <td> <div align="right"><span class="footer"><script type="text/javascript">var manual_date ="";lastrevision();</script></span></div> </td> </tr>  </tbody></table> </td> </tr> </table> </td> </tr> </table> <p> </p>   <script type="text/javascript">  </script> </body> </html> """ soup = BeautifulSoup(html_doc, "lxml-xml") # print '---------------------------------' # all_p = soup.find_all('table')[1].find_all('td')[1].find_all('tr')[1].get_text().strip() # all_p = all_p.replace('0 cellpadding=0 cellspacing=0>', '') # all_p = all_p.replace('footer();', '') # all_p = all_p.replace('''left valign=top width="50">''', '') # all_p = all_p.replace('left valign=top>', '') # all_p = all_p.replace('''border="0">''', '') # all_p = all_p.replace('250>', '') # all_p = all_p.replace('\n', '') # all_p = all_p.replace('\t', '') # print all_p # print '---------------------------------' # all_p = soup.find_all('table')[1].find_all('td')[1].find_all('p') # titles = soup.find_all('h1') # title = '' # content = '' # for i in range(1, len(titles)): # title += titles[i].get_text().strip() # for i in range(0, len(all_p)-1): # content += all_p[i].get_text().strip() # content = content.replace('\n', '') # content = content.replace('\t', '') # content = title + '\n' + content # print content print '---------------------------------' # all_p = soup.find_all('table')[1].find_all('td')[1].find_all('p') all_p = soup.find_all('table')[1].find_all('td')[1] titles = soup.find_all('h1') title = '' content = '' for i in range(1, len(titles)): title += titles[i].get_text().strip() if all_p: ex1 = all_p.find_all(['p','h2','h3','h4','strong','a']) for i in range(0, len(ex1)-1): content += ex1[i].get_text().strip() content = re.sub(r'\w+=\"(\w+)?\"', "", content) content = re.sub(r'\w+=\w+', "", content) content = re.sub(r'\w+=\"\w+\:#\d+\;\w+\-\w+:\w+;\w+\-\w+:\w+\">', "", content) content = re.sub(r':#\d+;\w+-\w+:\w+;\w+-\w+:\w+', "", content) content = re.sub(r'>\"', "", content) content = re.sub(r'>', "", content) content = re.sub(r'\"', "", content) content = re.sub(r'top', "", content) content = content.replace('\n', '') content = content.replace('\t', '') content = title + '\n' + content print content print '---------------------------------'

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dangpzanco/disciplina-fala

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/experiment/experiment.py

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[]

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3649a103777370fb7a8b15fce37e97446074c9f4

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refs/heads/master

2020-07-30T21:35:56.252159

2019-12-04T14:19:40

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import pathlib import soundfile as sf import librosa import librosa.display import numpy as np import numpy.random as rnd import pandas as pd import matplotlib.pyplot as plt import seaborn as sns from tqdm import trange import shutil rnd.seed(0) metadata = pd.read_csv('../analysis/speechmetrics_results.csv') metadata = metadata.drop(['pesq', 'stoi', 'srmr'], axis=1) print(metadata.columns) print(metadata) technique_list = ['noisy', 'wiener', 'bayes', 'binary'] num_techniques = len(technique_list) # exit() snr_values = np.array([-20,-10,0,10,20]) num_snr = snr_values.size # 5 files_per_snr = 4 num_rep = 1 exp_folder = pathlib.Path('exp_data') exp_folder.mkdir(parents=True, exist_ok=True) speech_folder = pathlib.Path('../data/speech/') noisy_folder = pathlib.Path('../data/speech+noise/') # id_list = [] # filename = [] # speech_name = [] # noise_name = [] # realization = [] # SNR = [] # technique = [] # rep_list = [] # Metadata definitions num_files = num_snr * (files_per_snr + num_rep) * num_techniques exp_metadata = pd.DataFrame(index=np.arange(num_files), columns=['id', 'filename', 'speech_name', 'noise_name', 'realization', 'SNR', 'technique', 'rep']) file_list = [] exp_index = 0 for k, tech in enumerate(technique_list): for i in range(num_snr): ind = metadata['SNR'] == snr_values[i] rnd_ind = rnd.permutation(ind.sum())[:files_per_snr] filenames = metadata['filename'].values[ind][rnd_ind] for j, item in enumerate(filenames): exp_metadata['filename'][exp_index] = item exp_metadata['speech_name'][exp_index] = item.split('_')[0] exp_metadata['noise_name'][exp_index] = item.split('_')[1][:-1] exp_metadata['realization'][exp_index] = item.split('_')[1][-1] exp_metadata['SNR'][exp_index] = float(item.split('_')[-1]) exp_metadata['technique'][exp_index] = tech exp_metadata['rep'][exp_index] = False exp_index +=1 file_list.append(item) exp_metadata['rep'][exp_index-1] = True # Repeated audios for j in range(num_rep): exp_metadata['filename'][exp_index] = item exp_metadata['speech_name'][exp_index] = item.split('_')[0] exp_metadata['noise_name'][exp_index] = item.split('_')[1][:-1] exp_metadata['realization'][exp_index] = item.split('_')[1][-1] exp_metadata['SNR'][exp_index] = float(item.split('_')[-1]) exp_metadata['technique'][exp_index] = tech exp_metadata['rep'][exp_index] = True exp_index +=1 file_list.append(item) num_files = len(file_list) print(num_files, file_list) exp_metadata = exp_metadata.sample(frac=1).reset_index(drop=True) exp_metadata['id'] = np.arange(num_files) print(exp_metadata) exp_metadata.to_csv('exp_metadata.csv', index=False) subject_metadata = exp_metadata.drop([ 'filename', 'speech_name', 'noise_name', 'realization', 'SNR', 'technique', 'rep'], axis=1) subject_metadata['quality'] = -1 print(subject_metadata) # exit() for i in range(num_files): tech = exp_metadata['technique'][i] if tech is 'noisy': processed_folder = pathlib.Path('../data/speech+noise/') else: processed_folder = pathlib.Path('../data/processed/') / tech in_filename = exp_metadata['filename'][i] out_filename = exp_metadata['id'][i] # print(in_filename, out_filename) src = processed_folder / f'{in_filename}.wav' dst = exp_folder / f'{out_filename:03}.wav' shutil.copy2(str(src), str(dst)) print(src, dst) # exp_metadata = pd.DataFrame(index=[],columns=['filename', 'quality']) # exp_metadata['filename'] = sorted(file_list) # exp_metadata['quality'] = 0 # print(exp_metadata) subject_metadata.to_csv(exp_folder / 'subject_metadata.csv', index=False)

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felipediel/django-commerce

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/commerce/views/cart.py

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2023-06-16T14:51:49.301650

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from django.contrib import messages from django.contrib.auth.mixins import LoginRequiredMixin from django.contrib.contenttypes.models import ContentType from django.shortcuts import get_object_or_404, redirect from django.utils.translation import ugettext_lazy as _ from django.views import View from django.views.generic import DetailView, UpdateView from commerce import settings as commerce_settings from commerce.forms import AddressesForm, ShippingAndPaymentForm, DiscountCodeForm from commerce.models import Cart, Order, PaymentMethod, Item, Option, ShippingOption from commerce.templatetags.commerce import discount_for_product class AddToCartView(LoginRequiredMixin, View): def get(self, request, *args, **kwargs): content_type = get_object_or_404(ContentType, id=kwargs['content_type_id']) product = get_object_or_404(content_type.model_class(), id=kwargs['object_id']) option = get_object_or_404(Option, slug_i18n=request.GET['option']) if 'option' in request.GET else None cart = Cart.get_for_user(request.user) # TODO: settings: # TODO: check if product can be added multiple times into cart # TODO: max items in cart ALLOW_MULTIPLE_SAME_ITEMS = False MAX_ITEMS = 3 if cart.items_quantity >= MAX_ITEMS: messages.warning(request, _(f'You can order at most %d items at once') % MAX_ITEMS) else: if ALLOW_MULTIPLE_SAME_ITEMS or not cart.has_item(product, option): # add item into cart cart.add_item(product, option) # discount if cart.discount: # remove discount if it is not valid anymore if not cart.discount.is_valid: cart.discount = None cart.save(update_fields=['discount']) if not cart.discount: # if no discount is applied yet, check if there is a valid discount available for product self.apply_discount_by_product(cart, product) messages.info(request, _('%s was added into cart') % product) else: messages.warning(request, _('%s is already in cart') % product) back_url = request.GET.get('back_url', cart.get_absolute_url()) return redirect(back_url) def apply_discount_by_product(self, cart, product): discount = discount_for_product({'request': self.request}, product) if discount and discount.add_to_cart: cart.discount = discount cart.save(update_fields=['discount']) class UnapplyDiscountCartView(LoginRequiredMixin, View): def get(self, request, *args, **kwargs): cart = Cart.get_for_user(request.user) cart.discount = None cart.save(update_fields=['discount']) back_url = request.GET.get('back_url', cart.get_absolute_url()) return redirect(back_url) class RemoveFromCartView(LoginRequiredMixin, View): def get(self, request, *args, **kwargs): item = get_object_or_404(Item, id=kwargs['item_id']) cart = Cart.get_for_user(request.user) if item in cart.item_set.all(): item.quantity -= 1 item.save(update_fields=['quantity']) if item.quantity <= 0: item.delete() messages.info(request, _('%s removed from cart') % item) # discount if cart.discount: # remove discount if it is not valid anymore if not cart.discount.is_valid: cart.discount = None cart.save(update_fields=['discount']) # unset loyalty points if cart.subtotal < 0 < cart.loyalty_points: cart.update_loyalty_points() # delete empty cart if not cart.item_set.exists(): cart.delete() back_url = request.GET.get('back_url', cart.get_absolute_url()) return redirect(back_url) class CartMixin(LoginRequiredMixin): model = Cart def get_object(self, queryset=None): return self.model.get_for_user(self.request.user) class CartDetailView(CartMixin, UpdateView): form_class = DiscountCodeForm template_name = 'commerce/cart_detail.html' def get_context_data(self, **kwargs): context_data = super().get_context_data(**kwargs) context_data.update({ 'loyalty_program_enabled': commerce_settings.LOYALTY_PROGRAM_ENABLED, }) return context_data def get_form_kwargs(self): form_kwargs = super().get_form_kwargs() form_kwargs.update({ 'user': self.request.user }) return form_kwargs class EmptyCartRedirectMixin(object): def dispatch(self, request, *args, **kwargs): cart = self.get_object() if cart.is_empty(): return redirect(cart.get_absolute_url()) return super().dispatch(request, *args, **kwargs) class CheckoutAddressesView(CartMixin, EmptyCartRedirectMixin, UpdateView): template_name = 'commerce/checkout_form.html' form_class = AddressesForm def get_initial(self): initial = super().get_initial() user = self.object.user last_user_order = user.order_set.last() # TODO: refactor if last_user_order: initial.update({ 'delivery_name': self.object.delivery_name or last_user_order.delivery_name, 'delivery_street': self.object.delivery_street or last_user_order.delivery_street, 'delivery_postcode': self.object.delivery_postcode or last_user_order.delivery_postcode, 'delivery_city': self.object.delivery_city or last_user_order.delivery_city, 'delivery_country': self.object.delivery_country or last_user_order.delivery_country, 'billing_name': self.object.billing_name or last_user_order.billing_name, 'billing_street': self.object.billing_street or last_user_order.billing_street, 'billing_postcode': self.object.billing_postcode or last_user_order.billing_postcode, 'billing_city': self.object.billing_city or last_user_order.billing_city, 'billing_country': self.object.billing_country or last_user_order.billing_country, 'reg_id': self.object.reg_id or last_user_order.reg_id, 'tax_id': self.object.tax_id or last_user_order.tax_id, 'vat_id': self.object.vat_id or last_user_order.vat_id, 'email': self.object.email or last_user_order.email, 'phone': self.object.phone or last_user_order.phone, }) else: initial.update({ 'delivery_name': self.object.delivery_name or user.get_full_name(), 'delivery_street': self.object.delivery_street or user.street, 'delivery_postcode': self.object.delivery_postcode or user.postcode, 'delivery_city': self.object.delivery_city or user.city, 'delivery_country': self.object.delivery_country or user.country, 'billing_name': self.object.billing_name or user.get_full_name(), 'billing_street': self.object.billing_street or user.street, 'billing_postcode': self.object.billing_postcode or user.postcode, 'billing_city': self.object.billing_city or user.city, 'billing_country': self.object.billing_country or user.country, 'email': self.object.email or user.email, 'phone': self.object.phone or user.phone, }) return initial def form_valid(self, form): form.save() return redirect('commerce:checkout_shipping_and_payment') class CheckoutShippingAndPaymentView(CartMixin, EmptyCartRedirectMixin, UpdateView): template_name = 'commerce/checkout_form.html' form_class = ShippingAndPaymentForm def form_valid(self, form): form.save() return redirect('commerce:checkout_summary') def get_initial(self): initial = super().get_initial() shipping_options = ShippingOption.objects.for_country(self.object.delivery_country) if shipping_options.count() == 1: initial.update({ 'shipping_option': shipping_options.first() }) payment_methods = PaymentMethod.objects.all() if payment_methods.count() == 1: initial.update({ 'payment_method': payment_methods.first() }) return initial class CheckoutSummaryView(CartMixin, EmptyCartRedirectMixin, DetailView): template_name = 'commerce/checkout_summary.html' def get_context_data(self, **kwargs): context_data = super().get_context_data(**kwargs) context_data.update({ 'loyalty_program_enabled': commerce_settings.LOYALTY_PROGRAM_ENABLED, }) return context_data class CheckoutFinishView(CartMixin, DetailView): def get(self, request, *args, **kwargs): cart = self.get_object() if cart.can_be_finished(): order_status = Order.STATUS_AWAITING_PAYMENT if cart.total > 0 else Order.STATUS_PENDING order = cart.to_order(status=order_status) if order.status != Order.STATUS_AWAITING_PAYMENT: return redirect(order.get_absolute_url()) if not order.payment_method: messages.error(request, _('Missing payment method')) return redirect(order.get_absolute_url()) if order.payment_method.method == PaymentMethod.METHOD_ONLINE_PAYMENT: return redirect(order.get_payment_url()) return redirect(order.get_absolute_url()) else: messages.warning(request, _('Checkout process can not be finished yet')) return redirect(cart.get_absolute_url())

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cart.py

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abu-sayem/Data-Structures-Algorithms-And-Databases

5,085,241,310,017

b39f55f73025ed2ef605a8f93881610365a9b4d6

d78a742d4b4109c3af39216edfc3f8fb5706cc36

/leetcode/653. Two Sum IV - Input is a BST.py

91ea31c213d9121589b19fca7e7807b8ddbc6318

[]

no_license

https://github.com/abu-sayem/Data-Structures-Algorithms-And-Databases

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refs/heads/master

2023-04-20T03:42:27.292639

2021-04-27T03:30:24

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1

0

null

# Definition for a binary tree node. # class TreeNode: # def __init__(self, x): # self.val = x # self.left = None # self.right = None class Solution: def findTarget(self, root: TreeNode, k: int) -> bool: store = set() list = [root] while list: temp = list.pop() if temp.val in store: return True store.add(k-temp.val) if temp.left: list.append(temp.left) if temp.right: list.append(temp.right) return False

UTF-8

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py

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653. Two Sum IV - Input is a BST.py

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0.487091

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roger3/pom

15,092,515,123,551

d2f2fe7ad2efab7b7a647e20570772237b148b22

28359230e823d6dc6fbe53f607a12f1b30a74d9e

/pom/game/migrations/0028_auto_20160222_2227.py

01216c647f4a825a39d0ade3e7c2c8c82bd35b08

[]

no_license

https://github.com/roger3/pom

5bd9720adabe7f3338ce0a24756846eac0991bb9

f3e2227064fade140c24046b054a7f006adc90b3

refs/heads/master

2019-07-22T18:33:59.211289

2016-05-20T13:37:48

55,376,032

0

null

# -*- coding: utf-8 -*- # Generated by Django 1.9.2 on 2016-02-22 22:27 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('game', '0027_auto_20160222_2215'), ] operations = [ migrations.AlterField( model_name='inhabitant', name='workplace', field=models.OneToOneField(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='workplace', to='game.Workplace'), ), ]

UTF-8

Python

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591

py

25

0028_auto_20160222_2227.py

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0.64467

0.590525

0

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27.142857

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choandrew/Project-Euler-with-Python

4,183,298,162,528

ab4bc22415e3110fa4954f239c8863fe2917a7a9

233f22c397e78024cdff3d8c8006a829fba34659

/Project Euler 7.py

38148192e61c0505cfd46b35fc7173899d642f5b

[]

no_license

https://github.com/choandrew/Project-Euler-with-Python

96aff8daa57cf84aa8b9a904c0fbaa21ae63b91b

20f270869dff99d5b3ed651833240d38277b4ea2

refs/heads/master

2021-01-01T06:04:57.693954

2015-04-23T07:51:18

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0

null

""" By listing the first six prime numbers: 2, 3, 5, 7, 11, and 13, we can see that the 6th prime is 13. What is the 10 001st prime number? """ import math from datetime import datetime startTime = datetime.now() #to measure speed n = 10001 # int(input("What number prime do you want? ")) primes = [2] m = 3 while len(primes) < n: a = [] for divisors in range(2,math.floor(math.sqrt(m))+1): a.append(m % divisors != 0) if all(a) == True: primes.append(m) m += 2 print(primes[-1]) print(datetime.now()-startTime)

UTF-8

Python

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555

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Project Euler 7.py

14

0.625225

0.574775

0

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bschnitz/recipes

11,828,339,942,629

5f074f5d619648f5e382267a19cc6b7972c37625

efcecf1f695e371dfbbc5c58ac7ef7ad33366e90

/recipes/gui/form/recipe/instructions/instruction_section.py

c1b2d0b6e558a881a9410d7089317c64401d29b2

[ "MIT" ]

permissive

https://github.com/bschnitz/recipes

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8af348774a1edc11ccab3da9753bc456c19f2000

refs/heads/master

2022-05-22T21:39:35.309599

2022-03-22T08:22:01

155,336,136

0

null

import wx from recipes.gui.fonts import Head2 from recipes.gui.form.framework import TitleBox from recipes.gui.form.framework import PaddedBox from recipes.gui.form.framework import AutoResizeMultilineText from wx.lib.expando import ExpandoTextCtrl, EVT_ETC_LAYOUT_NEEDED class InstructionSection: def __init__(self, parent): self.parent = parent title = 'Instructions for first meal' titled_box = TitleBox(self.form(parent), parent, title, Head2()) parent.SetSizer(PaddedBox(titled_box)) def form(self, parent): sizer = wx.GridBagSizer(10, 10) label = wx.StaticText(parent, label='Section Title') input = wx.TextCtrl(parent) sizer.Add(label, pos=(0,0), flag=wx.ALIGN_LEFT|wx.ALIGN_CENTER_VERTICAL) sizer.Add(input, pos=(0,1), flag=wx.EXPAND) instructions_input = AutoResizeMultilineText(parent) sizer.Add(instructions_input, pos=(1,0), span=(1, 2), flag=wx.EXPAND) sizer.AddGrowableCol(1) return sizer

UTF-8

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py

46

instruction_section.py

42

0.690802

0.676125

0

29

34.241379

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mhuijsmans/sandbox

11,201,274,708,525

83ef2f9b51371ca26614c716a95fd3df45fe7f9a

1e5e98034373ac7b58fe11f9b4a3bbb5e2d8acf2

/c++/scons_hierarchical2/components/comp4/test/SConscript

4d65b141c7127f3b8a456173aef0d108dc28e859

[]

no_license

https://github.com/mhuijsmans/sandbox

9718cb4414975502033abe791d2c2de747c5a04c

eb036140d91ea74af1b0215f5d5899ca070bd26c

refs/heads/master

2022-12-10T14:33:45.213736

2022-12-08T21:57:30

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null

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2022-12-10T06:22:02

2015-10-22T21:26:43

2022-01-09T00:56:18

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Java

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Import("env") opt = env.CreateClone('comp4.test') # COMP4 depends on COMP2 opt.BuildTests('comp4_tests', [ opt.Glob('*.cpp') ] )

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swopnilnep/kattis

15,161,234,600,391

c01f59f5c233efbfb5bdbc73c779779a64814641

d5919f63f2a0f0f5758be0c9bdcc12b61a1bcd7d

/python3/countingstars/countingstars.py

123cffc730ece9c5b5465704355d2a9c47ff4c01

[ "MIT" ]

permissive

https://github.com/swopnilnep/kattis

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8e41c83985137fad20e59416a3a0f9c3ed0ae847

refs/heads/master

2021-06-20T06:04:33.645790

2021-01-28T09:15:37

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0

2

null

from sys import setrecursionlimit, stdin setrecursionlimit(10 ** 4) def remove(items, x, y): if items[x][y]: items[x][y] = False for i, j in ((0, 1),(0,-1),(1, 0),(-1, 0)): x_mod, y_mod = x + i, y + j if not any((x_mod < 0,\ y_mod < 0,\ x_mod >= len(items),\ y_mod >= len(items[0]))): items = remove(items, x_mod, y_mod) return items for row_num, meta in enumerate(stdin): x_axis, y_axis = map(int, meta.split()) is_star = [[False for x in range(y_axis)] for x in range(x_axis)] for l in range(x_axis): line = stdin.readline() for star in range(y_axis): if line[star] == "-": is_star[l][star] = True count = 0 not_visited = list(range(len(is_star))) while len(not_visited) > 0: for x in not_visited: line = is_star[x] if True in line: y = line.index(True) is_star = remove(is_star, x, y) count += 1 else: not_visited.remove(x) continue print(f"Case {row_num + 1}: {count}")

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countingstars.py

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ZakHussain/Python_OOP

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d517bd40bfe43938dea47b0a815d8d3660e4609e

/Building_Objects_OOP.py

63d3e8de1f9ebc5eb0507391f8f06c67426df9b4

[]

no_license

https://github.com/ZakHussain/Python_OOP

6e943a9d31ad333accaeb353e06bd0d0090bbeb7

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refs/heads/master

2021-01-22T07:27:18.653986

2017-02-13T11:15:28

81,816,207

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null

# The Goal of this program is to get practice with Object Oriented Programming (OOP). # Here we create the 'blueprints' for 4 kind of objects - Cat, Human, Bike, and Car. # The Cat object requires a color, type, and age parameter to create an instance of a 'Cat'. class Cat(object): def __init__(self, color, type, age): self.color = color self.type = type self.age = age # The Human object requires no user input, and will print "New Human" once initialized. class Human(object): def __init__(self, clan=None): print "New Human!!!" # The Bike object has an initialization that takes form, prim, max_speed, and miles as input. # It has a displayinfo(), ride(), and reverse() method to allow for interaction with the object. class Bike(object): def __init__(self, form, price, max_speed, miles): self.form = form self.price = price self.max_speed = max_speed self.miles = 0 def displayinfo(self): print self.form print "Price for this is $" + str(self.price) print "Top speeds for this is "+ str(self.max_speed)+ 'mph' print "Total miles " + str(self.miles) + " miles " def ride(self): print 'driving' self.miles += 10 def reverse(self): print 'Reversing' if self.miles >= 5: self.miles -= 5 # The car object is initialized with four attributes, price, speed, fuel, and mileage. # It also contains a display_all method that will show the information about the state of the #car class Car(object): def __init__(self, price, speed, fuel, mileage): self.price = price self.speed = speed self.fuel = fuel self.mileage = mileage self.tax = .15 if self.price <= 10000: self.tax = 0.12 def display_all(self): print 'the price is ', str(self.price) print 'the speed of this car is ', str(self.speed) print 'the current tank is ', str(self.fuel) print 'the present mileage is ', str(self.mileage) print self.tax # here, we create an instance of a Cat, that we named 'garfield.' This # instance now has all the attributes that make a 'Cat,' (color, type, age, etc) garfield = Cat('orange', 'fat', 5) print garfield.color print garfield.type print garfield.age # these following calls create instances of the 'Bike' object locomotion = Bike('\n locomotion', 100, 200 , 0) tricycle = Bike('\n trycyle', 2,20, 0) motorcycle = Bike('\n motorcycle', 1000, 200, 0) # the following object.method() calls, calls of the methods of the specific object locomotion.ride() locomotion.ride() locomotion.ride() locomotion.reverse() locomotion.displayinfo() tricycle.ride() tricycle.ride() tricycle.reverse() tricycle.reverse() tricycle.displayinfo motorcycle.reverse() motorcycle.reverse() motorcycle.reverse() motorcycle.displayinfo() # the following object 'Kirby' is an instance of a 'Car' object Kirby1 = Car(10000, 35, 'Full', 15) # the following print methods call on the 'fields' of the Kirby, Car Object print Kirby1.speed print Kirby1.fuel print Kirby1.mileage print Kirby1.price print Kirby1.tax

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Building_Objects_OOP.py

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andreas-ibm/mqtt-bridge-websockets-python

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e9197f9b46df068933ff379fea588179b843f103

fa4fe37bd76285ed0cbc1216908c22f43b1af427

/app.py

1ca3b2dea51da2e6e8552b381087e4410541095e

[]

no_license

https://github.com/andreas-ibm/mqtt-bridge-websockets-python

80c62d7805c81733135ba76a7ad3a71f61b84c59

362ab7654e9222c8ef54991c9a96b0433690305c

refs/heads/master

2023-05-15T05:58:22.138023

2023-05-02T09:40:58

236,773,791

0

1

null

false

2023-05-02T09:41:00

2020-01-28T15:53:18

2020-01-28T15:53:49

2023-05-02T09:40:59

2

0

Python

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# MQTT Standalone bridge for sending data using WebSockets import argparse import paho.mqtt.client as paho import time import threading import uuid from flask import Flask parser = argparse.ArgumentParser() parser.add_argument("-s","--sourcebroker", help="The hostname of the broker to subscribe to") parser.add_argument("-p","--sourceport", type=int, help="The port of the broker to subscribe to", default=1883) parser.add_argument("-d","--targetbroker", help="The hostname of the broker to publish to") parser.add_argument("-o","--targetport", type=int, help="The port of the broker to publish to", default=9001) parser.add_argument("-e","--endpoint",help="The endpoint to register the edge broker as, defaults to ws://<sourcebroker>:9001") parser.add_argument("-t","--topic", help="The topic to bridge", default='#') parser.add_argument("-v","--verbose", help="Be verbose about relaying messages", action="store_true") args = parser.parse_args() app = Flask(__name__) app.debug = False @app.route('/') def hello(): return "Bridge config: Bridging {} from {}({}) to {}({})".format(arguments.topic, arguments.sourcebroker, arguments.sourceport, arguments.targetbroker, arguments.targetport) def on_subscribe(client, userdata, mid, granted_qos): #create function for callback print("subscribed with qos",granted_qos, "\n") pass def on_target_message(client, userdata, message): ## we didn't really expect to receive anything here... print("message received from target " ,str(message.payload.decode("utf-8"))) def on_publish(client,userdata,mid): #create function for callback if args.verbose: print("data published mid=",mid, "\n") pass def on_disconnect(client, userdata, rc): print("client disconnected ok") def on_source_connect(client, userdata, flags, rc): print("Connected to source broker with rc={}".format(rc)) print(" subscribing to ",args.topic) client.subscribe(args.topic) def main(arguments): threading.Thread(target=app.run).start() print("Bridge config: Bridging {} from {}({}) to {}({})".format(arguments.topic, arguments.sourcebroker, arguments.sourceport, arguments.targetbroker, arguments.targetport)) # the function that will do the actual bridging def on_source_message(client, userdata, message): ## this needs to pass on to the target if arguments.verbose: print("message received from source:\n\t{}\n\t{}".format(message.topic,str(message.payload.decode("utf-8")))) publisher.publish(message.topic, message.payload) # connect to the target broker id = str(uuid.uuid4().fields[-1])[:5] subscriber = paho.Client("mqtt-bridge-source-"+id) # we want to pass a lot of messages around subscriber.max_inflight_messages_set(300) # Use callback functions, pass them in subscriber.on_subscribe = on_subscribe subscriber.on_publish = on_publish subscriber.on_message = on_source_message subscriber.on_disconnect = on_disconnect subscriber.on_connect = on_source_connect print("connecting to broker ",arguments.sourcebroker,"on port ",arguments.sourceport) subscriber.connect(arguments.sourcebroker,arguments.sourceport) # connect to the target broker will = "" topic_will = "mqtt/edge" publisher = paho.Client("mqtt-bridge-target-"+id,transport='websockets') publisher.will_set(topic_will, payload=will, qos=0, retain=False) publisher.max_inflight_messages_set(300) # use callback functions, some are the same as the source broker. publisher.on_subscribe = on_subscribe publisher.on_publish = on_publish publisher.on_message = on_target_message publisher.on_disconnect = on_disconnect print("connecting to broker ",arguments.targetbroker,"on port ",arguments.targetport) publisher.connect(arguments.targetbroker,arguments.targetport) # Tell the broker that there is now an edge broker it's getting data from endpoint = "ws://"+arguments.sourcebroker+":9001" if arguments.endpoint is not None: endpoint = arguments.endpoint print("publishing edge endpoint "+endpoint+" to broker") publisher.publish(topic_will, endpoint, retain=True) publisher.loop_start() # keep going foverever! subscriber.loop_forever() if __name__ == "__main__": main(args)

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GraphicalDot/Assignments

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/assignment_1_nov_2014.py

c3d4c047cc4f455c5cab4071eb97c7324ad9dcb8

[]

no_license

https://github.com/GraphicalDot/Assignments

c273f3cf66f2012583e0fc4552f85d914fefaec9

9632f9fa1284a00001fad672a2456e3f67379012

refs/heads/master

2021-05-28T07:12:04.582583

2015-01-13T08:26:03

null

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#!/usr/bin/env python def Upto_you(): """ Write the most fancier 10 if, else statements, Its upto you """ pass def sort_list(): """ 1.Prepare a list of all alphabets 2.Prepare a list by shuffling them and joining them without spaces 3.From this list which will have 20 elements, prepare a list of dictionaries with key as 1 to 20 and values as the above mentioned randomly joined alphabets. 4.sort this list in descending order according to the value Hint: Output is like [{1: 'afmeniyhqvkdxrlocswgjpbtu'}, {2: jdtprombhueifnygskvclwxqa'}, ....so on] """ pass def another_sort_list(): """ From the update of sort_list() Step2: Update every dictionary present in the list by removing last three elements from each value Hint [{1: 'afmeniyhqvkdxrlocswgjp'}, {2: jdtprombhueifnygskvclw'}, ....so on] {'a': 1, 'c': 3, 'b': 2, 'e': 5, 'd': 4, 'g': 7, 'f': 6, 'i': 9, 'h': 8, 'k': 11, 'j': 10, 'm': 13, 'l': 12, 'o': 15, 'n': 14, 'q': 17, 'p': 16, 's': 19, 'r': 18, 'u': 21, 't': 20, 'w': 23, 'v': 22, 'y': 25, 'x': 24, 'z': 26} Then sum the values according to the above mentioned dictionary The above mentioned dictionary is just for your reference, dont copy that and make your own code Hint: Output is like [{1: 'afmeniyhqvkdxrlocswgjpbtu', "sum": "282"}, {2: jdtprombhueifnygskvclw', "sum": "283"}, ....so on] """ new_dict = dict() #Preparing the list like this {'a': 1, 'c': 3, 'b': 2, 'e': 5, 'd': 4, 'g': 7 and so on [new_dict.update({element[1]:element[0]})for element in zip(range(1,27), map(chr,range(ord("a"),ord("z")+1)))] h = lambda x : sum([new_dict[element] for element in x ]) [element.update({"sum": h(element.values()[0])}) for element in shivam_dict] return shivam_dict def lambda__(): """ should returns a output of a list which will not have prime numbers upto 1000 """ pass def and_or(): """ returns a list which will not have any number divisible by [18, 19, 21, 99, 45] Original list will have 1, 10000 """ pass def exception_handling(): """ Handle exception After handling this exception raise your own excpetion which should only print the error messege as the output """ pass def open_file(file_path): """ Print the contents of the file ying on file_path Now opena new file in your home directory, Write something in that file and then mv that file into this current directory Hint: os or subprocess module """ def convert_string_to_list(string): """ Convert this string into a list string = "HEY_MAN_WHAT_the_fuck_is_going_on" output = ["Hey", "man", "what", "the", "fuck", "is"m "going", "on"] The convert this list into string = "hey man what the fuck is going on"" Sonvert this string into string = "hey man, everything is great" Everything what you have done shall be done in one line with the help of list comprehensions """ pass if __name__ == "__main__":

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tedhtchang/kfserving

16,389,595,216,730

3e53452c7d94319102fe8b3d9bf10cca9ee1cce9

7d476ec8de08ccdc4e986faefe0512b205c0d219

/python/kserve/kserve/storage/test/test_s3_storage.py

c52d52f97a4bfd501d7d97569dfb62c08ea85b73

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permissive

https://github.com/tedhtchang/kfserving

67912db2e7e39805e2048e277b3771b156bfd679

f2f0717a9d6341b6ec9b939bdd324b2c8c507551

refs/heads/master

2023-08-17T22:25:43.120863

2023-08-06T21:36:10

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null

# Copyright 2021 The KServe Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import unittest.mock as mock from botocore.client import Config from botocore import UNSIGNED from kserve.storage import Storage STORAGE_MODULE = 'kserve.storage.storage' def create_mock_obj(path): mock_obj = mock.MagicMock() mock_obj.key = path mock_obj.is_dir = False return mock_obj def create_mock_boto3_bucket(mock_storage, paths): mock_s3_resource = mock.MagicMock() mock_s3_bucket = mock.MagicMock() mock_s3_bucket.objects.filter.return_value = [create_mock_obj(p) for p in paths] mock_s3_resource.Bucket.return_value = mock_s3_bucket mock_storage.resource.return_value = mock_s3_resource return mock_s3_bucket def get_call_args(call_args_list): arg_list = [] for call in call_args_list: args, _ = call arg_list.append(args) return arg_list def expected_call_args_list_single_obj(dest, path): return [( f'{path}'.strip('/'), f'{dest}/{path.rsplit("/", 1)[-1]}'.strip('/'))] def expected_call_args_list(parent_key, dest, paths): return [(f'{parent_key}/{p}'.strip('/'), f'{dest}/{p}'.strip('/')) for p in paths] # pylint: disable=protected-access @mock.patch(STORAGE_MODULE + '.boto3') def test_parent_key(mock_storage): # given bucket_name = 'foo' paths = ['models/weights.pt', '0002.h5', 'a/very/long/path/config.json'] object_paths = ['bar/' + p for p in paths] # when mock_boto3_bucket = create_mock_boto3_bucket(mock_storage, object_paths) Storage._download_s3(f's3://{bucket_name}/bar', 'dest_path') # then arg_list = get_call_args(mock_boto3_bucket.download_file.call_args_list) assert arg_list == expected_call_args_list('bar', 'dest_path', paths) mock_boto3_bucket.objects.filter.assert_called_with(Prefix='bar') @mock.patch(STORAGE_MODULE + '.boto3') def test_no_key(mock_storage): # given bucket_name = 'foo' object_paths = ['models/weights.pt', '0002.h5', 'a/very/long/path/config.json'] # when mock_boto3_bucket = create_mock_boto3_bucket(mock_storage, object_paths) Storage._download_s3(f's3://{bucket_name}/', 'dest_path') # then arg_list = get_call_args(mock_boto3_bucket.download_file.call_args_list) assert arg_list == expected_call_args_list('', 'dest_path', object_paths) mock_boto3_bucket.objects.filter.assert_called_with(Prefix='') @mock.patch(STORAGE_MODULE + '.boto3') def test_full_name_key(mock_storage): # given bucket_name = 'foo' object_key = 'path/to/model/name.pt' # when mock_boto3_bucket = create_mock_boto3_bucket(mock_storage, [object_key]) Storage._download_s3(f's3://{bucket_name}/{object_key}', 'dest_path') # then arg_list = get_call_args(mock_boto3_bucket.download_file.call_args_list) assert arg_list == expected_call_args_list_single_obj('dest_path', object_key) mock_boto3_bucket.objects.filter.assert_called_with(Prefix=object_key) @mock.patch(STORAGE_MODULE + '.boto3') def test_full_name_key_root_bucket_dir(mock_storage): # given bucket_name = 'foo' object_key = 'name.pt' # when mock_boto3_bucket = create_mock_boto3_bucket(mock_storage, [object_key]) Storage._download_s3(f's3://{bucket_name}/{object_key}', 'dest_path') # then arg_list = get_call_args(mock_boto3_bucket.download_file.call_args_list) assert arg_list == expected_call_args_list_single_obj('dest_path', object_key) mock_boto3_bucket.objects.filter.assert_called_with(Prefix=object_key) AWS_TEST_CREDENTIALS = {"AWS_ACCESS_KEY_ID": "testing", "AWS_SECRET_ACCESS_KEY": "testing", "AWS_SECURITY_TOKEN": "testing", "AWS_SESSION_TOKEN": "testing"} def test_get_S3_config(): DEFAULT_CONFIG = Config() ANON_CONFIG = Config(signature_version=UNSIGNED) VIRTUAL_CONFIG = Config(s3={"addressing_style": "virtual"}) with mock.patch.dict(os.environ, {}): config1 = Storage.get_S3_config() assert vars(config1) == vars(DEFAULT_CONFIG) with mock.patch.dict(os.environ, {"awsAnonymousCredential": "False"}): config2 = Storage.get_S3_config() assert vars(config2) == vars(DEFAULT_CONFIG) with mock.patch.dict(os.environ, AWS_TEST_CREDENTIALS): config3 = Storage.get_S3_config() assert vars(config3) == vars(DEFAULT_CONFIG) with mock.patch.dict(os.environ, {"awsAnonymousCredential": "True"}): config4 = Storage.get_S3_config() assert config4.signature_version == ANON_CONFIG.signature_version # assuming Python 3.5 or greater for joining dictionaries credentials_and_anon = {**AWS_TEST_CREDENTIALS, "awsAnonymousCredential": "True"} with mock.patch.dict(os.environ, credentials_and_anon): config5 = Storage.get_S3_config() assert config5.signature_version == ANON_CONFIG.signature_version with mock.patch.dict(os.environ, {"S3_USER_VIRTUAL_BUCKET": "False"}): config6 = Storage.get_S3_config() assert vars(config6) == vars(DEFAULT_CONFIG) with mock.patch.dict(os.environ, {"S3_USER_VIRTUAL_BUCKET": "True"}): config7 = Storage.get_S3_config() assert config7.s3["addressing_style"] == VIRTUAL_CONFIG.s3["addressing_style"]

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test_s3_storage.py

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samd-a/ebshare2.0

7,078,106,141,143

abb6d33646fd1d11d1ae35b73c0824866dd1945b

9d41222e8e2359d53b3f776a941675f9056cea90

/books/models.py

3ee18ec00be525814ef033c40655a31dac5de396

[]

no_license

https://github.com/samd-a/ebshare2.0

40b0a3ecc6e70a1a8f1fbe0653fd7305dabf11bd

ffa4ed4f107281095c796756711b6f57285da8b2

refs/heads/master

2021-01-10T04:00:26.210803

2015-12-11T11:09:55

47,309,176

0

null

from django.db import models from django.contrib.auth.models import User # Create your models here. class book(models.Model): user = models.ForeignKey(User) book_title = models.CharField(max_length=100) book_author = models.CharField(max_length=60) cover = models.ImageField(upload_to='book_cover') alt_text = models.CharField(max_length=20) description = models.TextField(max_length=750) details = models.CharField(max_length=200) genre = models.CharField(max_length=20) #ideally, these would 1 non-array field with the paragraph text #current error: "need more than 1 value to unpack" #description = ArrayField(models.CharField(max_length=500)) #details = ArrayField(models.CharField(max_length=200)) def __unicode__(self): return self.book_title #class txtbook(book): # fixtures = ['books.json'] class review(models.Model): user = models.ForeignKey(User) book_review = models.ForeignKey(book) content = models.CharField(max_length=750) def __unicode__(self): return str(self.id)

UTF-8

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py

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zrq495/OnlineJudge

11,235,634,463,095

dca16921fdcbeac0b8272a7ccc61e6ebc515ce80

9bd23c46e3f594d9557e3c049f753b05adff2b94

/oj/core/jinja.py

fee18fd552567518e3859284c884da84db8c0123

[]

no_license

https://github.com/zrq495/OnlineJudge

26a5f865734c306f521b922ecf2c46e74d6fe905

44be892ed657f462fb441d785c8550fc144f8896

refs/heads/master

2021-01-19T22:05:27.492272

2015-11-20T09:00:40

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null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from datetime import datetime, timedelta from jinja2 import Markup import pygments from pygments.formatters.html import HtmlFormatter from pygments.lexers import guess_lexer from oj import app def highlight(code): try: lexer = guess_lexer(code) formatter = HtmlFormatter(linenos='table', linenostart=0) code = pygments.highlight(code, lexer, formatter) except: pass return Markup(code) def digital_to_letter(value, base='A'): try: return chr(value % 26 + ord(base)) except: return '' def time_since(dt, default='刚刚', time_format='%Y-%m-%d %H:%M'): """将 datetime 替换成字符串 ('3小时前', '2天前' 等等) 的 Jinja filter copy from https://github.com/tonyblundell/socialdump/blob/master/socialdump.py sqlite 的 CURRENT_TIMESTAMP 只能使用 UTC 时间, 所以单元测试看到时间是8小时前的 don't panic, PostgreSQL 是有时区设定的. """ # added by jade if not dt: return '' now = datetime.now() diff = now - dt total_seconds = diff.total_seconds() if total_seconds > 0: if total_seconds < 10800: # 3 小时内 periods = ( (diff.seconds / 3600, '小时'), (diff.seconds / 60, '分钟'), (diff.seconds, '秒'), ) for period, unit in periods: if period > 0: return '%d%s前' % (period, unit) elif total_seconds < 86400 and dt.day == now.day: # 严格的今天内 return '今天' + dt.strftime('%H:%M') elif (total_seconds < 2 * 86400 and dt.day == (now - timedelta(days=1)).day): # 严格的昨天 return '昨天' + dt.strftime('%H:%M') else: return unicode(dt.strftime(time_format)) return default def convert_timedelta_to_hms(duration): seconds = int(duration.total_seconds()) sign = '-' if seconds < 0 else '' seconds = abs(seconds) hours = seconds // 3600 minutes = (seconds % 3600) // 60 seconds = (seconds % 60) return sign + str(hours), str(minutes), str(seconds) JINJA_FILTERS = { 'digital_to_letter': digital_to_letter, 'time_since': time_since, 'highlight': highlight, 'convert_timedelta_to_hms': convert_timedelta_to_hms, } @app.template_global() def get_headlines(): from oj.models import HeadlineModel return HeadlineModel.query.filter( HeadlineModel.is_display.is_(True)).all()

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hellomeeddie/flask_saverly_api

15,814,069,603,872

8c3aa6f042990f70ef3a58c4f82812c26fdcc304

07c51b31eb3a70189ac1be3f9f0b2cef140068cc

/dan/insert.py

3678d1eb2ec2b2061d89e213ff7aff2daa1fd2d0

[]

no_license

https://github.com/hellomeeddie/flask_saverly_api

4433682788c71a10e70147a22ac719cb282962f7

0a3a11c76d517a9ccb9dd7e2f237cfebb161330c

refs/heads/master

2020-12-28T22:02:02.369035

2016-07-19T02:45:41

null

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null

#Daniel Engelberth from py2neo import authenticate, Graph, Node, Relationship #Params: t - String, type of node being inserted (User, Goal, Budget, etc.), info - Array, array of all other info to be used to set up node properties #Returns: None #Description: Inserts a new node into the Neo4j database that corresponds with the requested data type as well as any required relationships def insert(graph, t, info): if t == "User": graph.run("CREATE (n:User {userName: {userName},firstName: {firstName},lastName: {lastName},email: {email},password: {password}})",userName=info[0],firstName=info[1],lastName=info[2],email=info[3],password=info[4]) elif t == "Goal": graph.run("CREATE (n:Goal {name: {name},amount: {amount},downpay: {downpay},term: {term},description: {description}})",name=info[0],amount=info[1],downpay=info[2],term=info[3],description=info[4]) for category in info[5]: insert(graph, "Category", category) graph.run("MATCH (a:Goal),(b:Category) WHERE a.name = {name} AND b.name = {category} CREATE (a)-[r:HAS]->(b)",name=info[0],category=category) graph.run("MATCH (a:User),(b:Goal) WHERE a.userName = {userName} AND b.name = {name} CREATE (a)-[r:HAS]->(b)",userName=info[5],name=info[0]) elif t == "Budget": graph.run("CREATE (n:Budget {name: {name},amount: {amount},startDate: {startDate},endDate: {endDate},description: {description}})",name=info[0],amount=info[1],startDate=info[2],endDate=info[3],description=info[4]) for category in info[5]: insert(graph, "Category", category) graph.run("MATCH (a:Budget),(b:Category) WHERE a.name = {name} AND b.name = {category} CREATE (a)-[r:HAS]->(b)",name=info[0],category=category) graph.run("MATCH (a:User),(b:Budget) WHERE a.userName = {userName} AND b.name = {name} CREATE (a)-[r:HAS]->(b)",userName=info[6],name=info[0]) elif t == "Wish": graph.run("CREATE (n:Wish {name: {name},purchaseLink: {purchaseLink},date: {date},description: {description}})",name=info[0],purchaseLink=info[1],date=info[2],description=info[3]) for category in info[4]: insert(graph, "Category", category) graph.run("MATCH (a:Wish),(b:Category) WHERE a.name = {name} AND b.name = {category} CREATE (a)-[r:HAS]->(b)",name=info[0],category=category) graph.run("MATCH (a:User),(b:Wish) WHERE a.userName = {userName} AND b.name = {name} CREATE (a)-[r:HAS]->(b)",userName=info[5],name=info[0]) elif t == "Transaction": graph.run("CREATE (n:Transaction{name: {name},amount: {amount},date: {date},location: {location}})",name=info[0],amount=info[1],date=info[2],location=info[3]) for category in info[4]: insert(graph, "Category", category) graph.run("MATCH (a:Transaction),(b:Category) WHERE a.name = {name} AND b.name = {category} CREATE (a)-[r:HAS]->(b)",name=info[0],category=category) insert(graph, "Merchant",info[5]) graph.run("MATCH (a:Transaction),(b:Merchant) WHERE a.name = {name} AND b.name = {merchantName} CREATE (a)-[r:HAS]->(b)",name=info[0],merchantName=info[5]) graph.run("MATCH (a:User),(b:Transaction) WHERE a.userName = {userName} AND b.name = {name} CREATE (a)-[r:HAS]->(b)",userName=info[7],name=info[0]) elif t == "Bill": graph.run("CREATE (n:Bill {name: {name},amount: {amount},startDate: {startDate},endDate: {endDate},description: {description},freq: {freq}})",name=info[0],amount=info[1],startDate=info[2],endDate=info[3],description=info[4],freq=info[5]) for category in info[6]: insert(graph, "Category", category) graph.run("MATCH (a:Bill),(b:Category) WHERE a.name = {name} AND b.name = {category} CREATE (a)-[r:HAS]->(b)",name=info[0],category=category) graph.run("MATCH (a:User),(b:Bill) WHERE a.userName = {userName} AND b.name = {name} CREATE (a)-[r:HAS]->(b)",userName=info[7],name=info[0]) """elif t == "Tag": graph.run("MERGE (t:Tag { name: {name} })",name=info)""" elif t == "Merchant": graph.run("MERGE (t:Merchant { name: {name} })",name=info) elif t == "Category": graph.run("MERGE (c:Category {name: {name})",name=info) else: raise ValueError("t must be a type of node {'User','Goal','Transaction', etc.")

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Nikkuniku/AtcoderProgramming

9,826,885,179,047

550e6f1f75bc4e863673a2cdfa8a915679b2bfd2

63b0fed007d152fe5e96640b844081c07ca20a11

/くじかつ/よるかつ50/C.py

999de7c70eed8d6057ad3477f79c698c5172ce11

[]

no_license

https://github.com/Nikkuniku/AtcoderProgramming

8ff54541c8e65d0c93ce42f3a98aec061adf2f05

fbaf7b40084c52e35c803b6b03346f2a06fb5367

refs/heads/master

2023-08-21T10:20:43.520468

2023-08-12T09:53:07

254,373,698

0

null

n=int(input()) h=list(map(int,input().split())) h_min=min(h) for i in range(n): h[i]-=h_min for j in range(n): if h[j]==0: print(h)

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false

155

py

2,078

C.py

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0.503226

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49ers-DB/Atlanta-Movie

19,542,101,197,174

d299880c948280a90a990cc98d0319ca15f61979

33ef7d427278c371b101b047459d7c669d5d8eff

/app/http/api/endpoints.py

0ae14ab032fd9d54570f94d7c158e7234d37e321

[ "MIT" ]

permissive

https://github.com/49ers-DB/Atlanta-Movie

ac808f7c8f07ca2cc3f28b7f2af877bf7647af74

1cff0760ba8b57831dd87f9d216b7b3ae4cac6e2

refs/heads/master

2021-07-08T05:09:01.582449

2019-11-30T04:06:46

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0

MIT

false

2021-01-05T17:19:22

2019-11-12T18:37:12

2020-01-10T01:05:52

2021-01-05T17:19:20

799

1

0

22

JavaScript

false

from middleware import login_required, admin_only from flask import Flask, json, g, request, render_template from flask_cors import CORS import pymysql.cursors from app.util.custom_jwt import create_access_token from app.services.LoginService import LoginService from app.services.ManagerService import ManagerService from app.services.RegisterService import RegisterService from app.services.DropDownService import DropDownService from app.services.UserService import UserService from app.services.CustomerService import CustomerService from app.services.AdminService import AdminService from app.services.DBService import db_reset from logging.config import dictConfig import logging import sys dictConfig({ 'version': 1, 'formatters': {'default': { 'format': '[%(asctime)s] %(levelname)s in %(module)s: %(message)s', }}, 'handlers': {'wsgi': { 'class': 'logging.StreamHandler', 'stream': 'ext://flask.logging.wsgi_errors_stream', 'formatter': 'default' }}, 'root': { 'level': 'DEBUG', 'handlers': ['wsgi'] } }) logging.basicConfig(level=logging.DEBUG) handler = logging.StreamHandler(sys.stdout) root = logging.getLogger() root.addHandler(handler) app = Flask(__name__, static_folder="build/static", template_folder="build") CORS(app) app.config['EXPLAIN_TEMPLATE_LOADING'] = True db_reset() # create services login_service = LoginService() register_service = RegisterService() manager_service = ManagerService() drop_down_service = DropDownService() user_service = UserService() customer_service = CustomerService() admin_service = AdminService() #-----------Main------------ @app.route('/', defaults={'path': ''}) @app.route('/<path:path>') def index(path): return render_template('index.html') #------------LOGIN------------ @app.route('/userLogin', methods=['POST']) def userLogin(): data = request.get_json() user = data['user'] try: success = login_service.login(user) if success: del user['password'] access_token = create_access_token(identity=data) user['jwt'] = access_token return json_response({'ok': True, 'data': user}) except Exception as e: print("Exception", e) return json_response({'message': 'Bad request parameters'}, 400) #-------REGISTRATIONS-------- #user @app.route('/userRegister', methods=['POST']) def userRegister(): data = request.get_json() user = data['user'] response = json_response({'message': 'Bad request parameters'}, 400) try: success = register_service.registerUser(user) print(success) if success: response = json_response({'ok': True, 'data': user}) else: response = json_response({'message': 'username taken'}, 401) except: response = json_response({'message': 'Bad request parameters'}, 400) print("Failed to insert record") return response #customer @app.route('/customerRegister', methods=['POST']) def customerRegister(): data = request.get_json() user = data try: response = register_service.registerCustomer(user) return json_response(response) except pymysql.InternalError as e: print(e) print("Failed to insert record") return json_response({'message': 'Bad request parameters'}, 400) #manager @app.route('/managerRegister', methods=['POST']) def managerRegister(): data = request.get_json() user = data try: response = register_service.registerManager(user) return json_response(response) except pymysql.InternalError as e: print(e) print("Failed to insert record") return json_response({'message': 'Bad request parameters'}, 400) #managerCustomer @app.route('/managerCustomerRegister', methods=['POST']) def managerCustomerRegister(): data = request.get_json() user = data try: response = register_service.registerManagerCustomer(user) return json_response(response) except pymysql.InternalError as e: print(e) print("Failed to insert record") return json_response({'message': 'Bad request parameters'}, 400) #-------DropDownService--------- @app.route('/getCompanies', methods=['GET']) def getCompanies(): response = drop_down_service.CompanyDropDown() return json_response(response) @app.route('/movies', methods=['GET']) def getMovies(): response = drop_down_service.MovieDropDown() return json_response(response) @app.route('/theaters/<string:comName>', methods=['GET']) @login_required def getTheaters(comName): theaters = drop_down_service.TheaterDropDown() return json_response({'ok': True, 'theaters': theaters}) @app.route('/creditcard', methods=['GET']) @login_required def getCreditCardNumbers(): username = g.user['username'] response = drop_down_service.getCreditCardNumbers(username) return json_response(response) @app.route('/managers', methods=['GET']) @admin_only def get_managers(): response = drop_down_service.ManagerDropDown() return json_response(response) #----------UserService-------------------- @app.route('/exploreTheater', methods=['POST']) @login_required def explore_theater(): data = request.get_json() print(data) query_data = user_service.ExploreTheater(data) return json_response({'ok': True, 'theaters': query_data}) @app.route('/logVisit', methods=['POST']) @login_required def log_visit(): data = request.get_json() user = g.user['username'] user_service.LogVisit(user, data) return json_response({'ok': True}) #--------CustomerService------------------- @app.route('/exploreMovie', methods=['POST']) @login_required def explore_movie(): data = request.get_json() query_data = customer_service.ExploreMovie(data) return json_response({'ok': True, 'moviePlays': query_data}) @app.route('/viewMovie', methods=['POST']) @login_required def view_movie(): data = request.get_json() username = g.user['username'] resp = customer_service.ViewMovie(username, data) if resp is not None: return json_response({'ok': True, 'data':resp}) return json_response({'ok': True}) #----------ManagerService----------------- @app.route('/theaterOverview', methods=['POST']) @login_required def get_theater_overview(): data = request.get_json() user = g.user['username'] response = manager_service.TheaterOverview(user, data) return json_response({'ok': True, "data": response}) @app.route('/GetVisitHistory', methods=['POST']) @login_required def get_visit_history(): data = request.get_json() user = g.user['username'] data = user_service.VisitHistory(user, data) return json_response({'data': data}) @app.route('/moviePlay', methods=['POST']) @login_required def ScheduleMovie(): data=request.get_json() user=g.user['username'] manager_service.ScheduleMovie(user, data) return json_response({'ok': True}) #------------Admin Service------------- @app.route('/manageCompany', methods=['POST']) @login_required @admin_only def manage_company(): data = request.get_json() response = admin_service.ManageCompany(data) return json_response(response) @app.route('/filterUser', methods=['POST']) @login_required @admin_only def filter_user(): data = request.get_json() response = admin_service.FilterUser(data) return json_response({"data":response}) @app.route('/approveUser', methods=['POST']) @login_required @admin_only def approve_user(): data = request.get_json() admin_service.ApproveUser(data) return json_response({"ok":True}) @app.route('/declineUser', methods=['POST']) @login_required @admin_only def decline_user(): data = request.get_json() admin_service.DeclineUser(data) return json_response({"ok":True}) @app.route('/theater', methods=['POST']) @login_required @admin_only def create_theater(): data = request.get_json() admin_service.CreateTheater(data) return json_response({"ok":True}) @app.route('/companyDetail/<string:name>', methods=['GET']) @login_required @admin_only def company_detail(name): response = admin_service.CompanyDetail(name) return json_response(response) @app.route("/example/<int:param_1>", methods=['GET']) @login_required def example_endpoint(param_1): print(param_1) user = g.user # response = json_response({'userType': 'user'}, 200) # userType = login_service.findUserType(user['username']) # response = json_response({'userType': userType}, 200) return json_response({'ok':True}) @app.route("/user", methods=['GET']) @login_required def get_user_type(): user = g.user response = json_response({'userType': 'user'}, 200) userType = login_service.findUserType(user['username']) response = json_response({'userType': userType}, 200) return response @app.route('/createMovie', methods=['POST']) @login_required @admin_only def create_movie(): data = request.get_json() resp = admin_service.CreateMovie(data) return json_response({"data": resp}) #----------CustomerService-------------------- @app.route('/viewHistory', methods=['POST']) @login_required def viewHistory(): user = g.user['username'] print(user) data = customer_service.ViewHistory(user) return json_response({'data': data}) def json_response(payload, status_code=200): return json.dumps(payload), status_code, {'Content-type': 'application/json'}

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ogrisel/probability

2,164,663,550,020

6ab68426a4274241e0bbe0ea6f151d41279ea6cd

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/tensorflow_probability/python/internal/dtype_util.py

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permissive

https://github.com/ogrisel/probability

846f5c13cddee5cf167b215e651b7479003f15d2

8f67456798615f9bf60ced2ce6db5d3dba3515fe

refs/heads/master

2022-11-09T10:53:23.000918

2020-07-01T23:16:03

2020-07-01T23:17:25

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2020-07-02T07:37:58

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2020-07-01T23:17:33

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# Copyright 2018 The TensorFlow Probability Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """Utility functions for dtypes.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function # Dependency imports import numpy as np import tensorflow.compat.v2 as tf __all__ = [ 'as_numpy_dtype', 'assert_same_float_dtype', 'base_dtype', 'base_equal', 'common_dtype', 'is_bool', 'is_complex', 'is_floating', 'is_integer', 'max', 'min', 'name', 'real_dtype', 'size', ] SKIP_DTYPE_CHECKS = False def as_numpy_dtype(dtype): """Returns a `np.dtype` based on this `dtype`.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'as_numpy_dtype'): return dtype.as_numpy_dtype return dtype def base_dtype(dtype): """Returns a non-reference `dtype` based on this `dtype`.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'base_dtype'): return dtype.base_dtype return dtype def base_equal(a, b): """Returns `True` if base dtypes are identical.""" return base_dtype(a) == base_dtype(b) def common_dtype(args_list, dtype_hint=None): """Returns explict dtype from `args_list` if there is one.""" dtype = None seen = [] for a in tf.nest.flatten(args_list): if hasattr(a, 'dtype') and a.dtype: dt = as_numpy_dtype(a.dtype) seen.append(dt) else: seen.append(None) continue if dtype is None: dtype = dt elif dtype != dt: if SKIP_DTYPE_CHECKS: dtype = (np.ones([2], dtype) + np.ones([2], dt)).dtype else: raise TypeError( 'Found incompatible dtypes, {} and {}. Seen so far: {}'.format( dtype, dt, seen)) return dtype_hint if dtype is None else base_dtype(dtype) def convert_to_dtype(tensor_or_dtype, dtype=None, dtype_hint=None): """Get a dtype from a list/tensor/dtype using convert_to_tensor semantics.""" if tensor_or_dtype is None: return dtype or dtype_hint # Tensorflow dtypes need to be typechecked if tf.is_tensor(tensor_or_dtype): dt = base_dtype(tensor_or_dtype.dtype) elif isinstance(tensor_or_dtype, tf.DType): dt = base_dtype(tensor_or_dtype) # Numpy dtypes defer to dtype/dtype_hint elif isinstance(tensor_or_dtype, np.ndarray): dt = base_dtype(dtype or dtype_hint or tensor_or_dtype.dtype) elif np.issctype(tensor_or_dtype): dt = base_dtype(dtype or dtype_hint or tensor_or_dtype) else: # If this is a Python object, call `convert_to_tensor` and grab the dtype. # Note that this will add ops in graph-mode; we may want to consider # other ways to handle this case. dt = tf.convert_to_tensor(tensor_or_dtype, dtype, dtype_hint).dtype if not SKIP_DTYPE_CHECKS and dtype and not base_equal(dtype, dt): raise TypeError('Found incompatible dtypes, {} and {}.'.format(dtype, dt)) return dt def is_bool(dtype): """Returns whether this is a boolean data type.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'is_bool'): return dtype.is_bool # We use `kind` because: # np.issubdtype(np.uint8, np.bool) == True. return np.dtype(dtype).kind == 'b' def is_complex(dtype): """Returns whether this is a complex floating point type.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'is_complex'): return dtype.is_complex return np.issubdtype(np.dtype(dtype), np.complexfloating) def is_floating(dtype): """Returns whether this is a (non-quantized, real) floating point type.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'is_floating'): return dtype.is_floating return np.issubdtype(np.dtype(dtype), np.floating) def is_integer(dtype): """Returns whether this is a (non-quantized) integer type.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'is_integer') and not callable(dtype.is_integer): return dtype.is_integer return np.issubdtype(np.dtype(dtype), np.integer) def max(dtype): # pylint: disable=redefined-builtin """Returns the maximum representable value in this data type.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'max') and not callable(dtype.max): return dtype.max use_finfo = is_floating(dtype) or is_complex(dtype) return np.finfo(dtype).max if use_finfo else np.iinfo(dtype).max def min(dtype): # pylint: disable=redefined-builtin """Returns the minimum representable value in this data type.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'min') and not callable(dtype.min): return dtype.min use_finfo = is_floating(dtype) or is_complex(dtype) return np.finfo(dtype).min if use_finfo else np.iinfo(dtype).min def name(dtype): """Returns the string name for this `dtype`.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'name'): return dtype.name if hasattr(dtype, '__name__'): return dtype.__name__ return str(dtype) def size(dtype): """Returns the number of bytes to represent this `dtype`.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'size') and hasattr(dtype, 'as_numpy_dtype'): return dtype.size return np.dtype(dtype).itemsize def real_dtype(dtype): """Returns the dtype of the real part.""" dtype = tf.as_dtype(dtype) if hasattr(dtype, 'real_dtype'): return dtype.real_dtype # TODO(jvdillon): Find a better way. return np.array(0, as_numpy_dtype(dtype)).real.dtype def _assert_same_base_type(items, expected_type=None): r"""Asserts all items are of the same base type. Args: items: List of graph items (e.g., `Variable`, `Tensor`, `SparseTensor`, `Operation`, or `IndexedSlices`). Can include `None` elements, which will be ignored. expected_type: Expected type. If not specified, assert all items are of the same base type. Returns: Validated type, or none if neither expected_type nor items provided. Raises: ValueError: If any types do not match. """ original_expected_type = expected_type mismatch = False for item in items: if item is not None: item_type = base_dtype(item.dtype) if expected_type is None: expected_type = item_type elif expected_type != item_type: mismatch = True break if mismatch: # Loop back through and build up an informative error message (this is very # slow, so we don't do it unless we found an error above). expected_type = original_expected_type original_item_str = None get_name = lambda x: x.name if hasattr(x, 'name') else str(x) for item in items: if item is not None: item_type = base_dtype(item.dtype) if not expected_type: expected_type = item_type original_item_str = get_name(item) elif expected_type != item_type: raise ValueError( '{}, type={}, must be of the same type ({}){}.'.format( get_name(item), item_type, expected_type, ((' as {}'.format(original_item_str)) if original_item_str else ''))) return expected_type # Should be unreachable else: return expected_type def assert_same_float_dtype(tensors=None, dtype=None): """Validate and return float type based on `tensors` and `dtype`. For ops such as matrix multiplication, inputs and weights must be of the same float type. This function validates that all `tensors` are the same type, validates that type is `dtype` (if supplied), and returns the type. Type must be a floating point type. If neither `tensors` nor `dtype` is supplied, the function will return `dtypes.float32`. Args: tensors: Tensors of input values. Can include `None` elements, which will be ignored. dtype: Expected type. Returns: Validated type. Raises: ValueError: if neither `tensors` nor `dtype` is supplied, or result is not float, or the common type of the inputs is not a floating point type. """ if tensors: dtype = _assert_same_base_type(tensors, dtype) if not dtype: dtype = tf.float32 elif not is_floating(dtype): raise ValueError('Expected floating point type, got {}.'.format(dtype)) return dtype

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dtype_util.py

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Raul-Pinheiro/projetoPessoal-controleDeEstoqueLojaVirtual

7,327,214,229,338

24b2a8cd753446b0ace893d4d053057301eaf720

5b5450b16fbde30b6677386cc5b6b54d24cb7bd2

/apps/controlEstoque/migrations/0009_auto_20200908_1824.py

5cd4b14b95b6a1f6794d68ad3cc6a646646d42ea

[]

no_license

https://github.com/Raul-Pinheiro/projetoPessoal-controleDeEstoqueLojaVirtual

c82e74fc6f1cbf08a26560171cfc31cd9f8f80cf

54afb55114e482aaa4e1b4ccbc0c1baddcd448a2

refs/heads/master

2023-01-22T16:39:53.818655

2020-12-08T16:20:58

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null

# Generated by Django 3.1.1 on 2020-09-08 21:24 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('controlEstoque', '0008_auto_20200908_1823'), ] operations = [ migrations.AlterField( model_name='produtos', name='data_ultima_compra', field=models.DateTimeField(default=datetime.datetime(2020, 9, 8, 18, 24, 8, 670532)), ), migrations.AlterField( model_name='produtos_loja', name='foto_produto', field=models.ImageField(blank=True, upload_to='fotos/%d/%m/%Y/loja/'), ), ]

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Python

false

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py

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0009_auto_20200908_1824.py

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0.595808

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GianfrancoJara/Exp3Backend_JaraGonzalez_004D

19,138,374,288,920

c5cd41ec07ab78ccf8ecdd78ae47ec85f0d9bda8

033b5305f992c7e06df8563e1e69c600c94e90bd

/SoporteIT/SoporteIT/core/migrations/0002_solicitud_comentario.py

95e1f3026e569c2a28f1ed3cd95d8895680d48ae

[]

no_license

https://github.com/GianfrancoJara/Exp3Backend_JaraGonzalez_004D

ac95fa2ec4cfa108a8da647042a93573c38a9795

b0950e70487269a587c3a53f24aa3cbc2d766a72

refs/heads/main

2023-06-07T11:50:07.967530

2021-06-22T02:04:14

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0

null

# Generated by Django 3.2.3 on 2021-06-20 00:29 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('core', '0001_initial'), ] operations = [ migrations.AddField( model_name='solicitud', name='comentario', field=models.CharField(max_length=512, null=True, verbose_name='Comentario'), ), ]

UTF-8

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416

py

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0002_solicitud_comentario.py

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christofsteel/mtgman

3,298,534,912,378

09a81e6923094022cd5fad1e4ac1afbeef4c1003

07ea87b4d3ec31f39452cc95c166b48c2c3abc1a

/mtgman/imports/faces.py

f80c78dfc7a1162f35ee80f400aece2187dc9ab3

[]

no_license

https://github.com/christofsteel/mtgman

ba5793cebc93cc0eba8d391b57f3b31c98067e6e

acaa2a83f5964845c0273778824c223486f233f0

refs/heads/master

2020-09-13T03:31:01.581869

2019-12-16T05:40:55

222,644,442

0

null

from . import create_dict from .card import get_card_from_sf from ..model import CardFacePrinting, CardFaceBase, CardFace def get_db_card_face(name, session): return session.query(CardFace).filter(CardFace.name == name).first() def get_db_card_face_from_sf(face, session): return get_db_card_face(face["name"], session) #faces = [] #if "card_faces" in e: # for face in e["card_faces"]: # faces.append(get_db_card_face(face["name"], session)) #return faces def get_card_face_from_sf(face, e, session): card_face = get_db_card_face_from_sf(face, session) if card_face is not None: return card_face card_face = add_card_face(face, e, session) session.commit() return card_face def add_card_face(face, e, session): card = get_card_from_sf(e, session) card_face = create_card_face(face, card) session.add(card_face) return card_face def create_card_face(face, card): fields = ["name", "mana_cost", "type_line", "oracle_text"] fields_int = ["power", "toughness"] lists=["colors", "color_indicator"] fields_uuid = [] renames = {"power": "power_str", "toughness": "toughness_str"} if type(card) is int: custom = {"card_id": card} else: custom = {"card": card} dict_all = create_dict(face, fields=fields, lists=lists, fields_int=fields_int, fields_uuid=fields_uuid, renames=renames, custom=custom) return CardFace(**dict_all) def create_card_face_printing(face, card_face_base, printing): fields = ["printed_name", "printed_text", "printed_type_line"] objects = { "image_uris": { "png": ("image_uri_png", lambda x: x) , "border_crop": ("image_uri_border_crop", lambda x: x) , "art_crop": ("image_uri_art_crop", lambda x: x) , "large": ("image_uri_large", lambda x: x) , "normal": ("image_uri_normal", lambda x: x) , "small": ("image_uri_small", lambda x: x) } } custom = {} if type(card_face_base) is int: custom["card_face_base_id"] = card_face_base else: custom["card_face_base"] = card_face_base if type(printing) is int: custom["card_printing_id"] = printing else: custom["card_printing"] = printing dict_all = create_dict(face, fields=fields, objects=objects, custom=custom) return CardFacePrinting(**dict_all) def makeCardFacePrinting(e, card_base_face, printing, session): card_face_printing = session.query(CardFacePrinting)\ .filter(CardFacePrinting.card_face_base == card_base_face)\ .filter(CardFacePrinting.card_printing == printing).first() if card_face_printing is None: card_face_printing = create_card_face_printing(e, card_base_face, printing) session.add(card_face_printing) return card_face_printing def create_card_face_base(face, card_face, basecard): fields = ["artist", "flavor_text", "watermark"] fields_uuid = ["artist_id", "illustration_id"] custom = {} if type(card_face) is int: custom["card_face_id"] = card_face else: custom["card_face"] = card_face if type(basecard) is int: custom["basecard_id"] = basecard else: custom["basecard"] = basecard dict_all = create_dict(face, fields=fields, fields_uuid=fields_uuid, custom = custom) return CardFaceBase(**dict_all) def makeCardBaseFace(face, card_face, basecard, session): card_base_face = session.query(CardFaceBase)\ .filter(CardFaceBase.card_face == card_face)\ .filter(CardFaceBase.basecard == basecard).first() if card_base_face is None: card_base_face = create_card_face_base(face, card_face, basecard) session.add(card_base_face) return card_base_face

UTF-8

Python

false

3,794

py

19

faces.py

17

0.633105

0

107

34.383178

140

Aswin-Sureshumar/Python-Programs

14,001,593,400,178

0103eaec5aed67e745956b0de8df3f3f3b654ff6

b42c827e57b6c24251dedf0894ba3a97eb876b7c

/list gen.py

f7e04b92baf5fb49a18e00903c340c02df6f359e

[]

no_license

https://github.com/Aswin-Sureshumar/Python-Programs

77f20bacefc32307b60a00e9345cae95dc14185f

0387eb732e1b43995d161b5088b49b1155405411

refs/heads/master

2022-12-22T11:53:04.864017

2020-09-22T10:23:57

283,938,006

0

null

n=int(input(" enter the elements req ")) list=[] for i in range(0,n): a=int(input()) list.append(a) print(list)

UTF-8

Python

false

124

py

76

list gen.py

76

0.596774

0.58871

0

6

19

40

jjsjann123/cs526_proj2_enhance

13,554,916,820,038

31854d3d854c4e2e93d021763022963544d50b4a

5b4a2fb592f39e07bf5de619071d3e75b7aa3cb0

/multiples.py

61a7bc8d9ab8412158f6ee979b768c6d649466b4

[]

no_license

https://github.com/jjsjann123/cs526_proj2_enhance

70dcb6c03410b50bfc059f2ec5dbacd81fd535d7

7c661664937d4c056b14bbd62bafe3a0a484f684

refs/heads/master

2020-03-28T18:57:39.803999

2013-12-09T02:00:25

null

0

null

from omega import * from cyclops import * from math import * from euclid import * from fun import * class multiples(object): global stellarColorMap orbitScale = Uniform.create('orbitScale', UniformType.Float, 1) radiusScale = Uniform.create('radiusScale', UniformType.Float, 1) orbitRatio = Uniform.create('orbit_ratio', UniformType.Float, 1) radiusRatio = Uniform.create('radius_ratio', UniformType.Float, 1) #glowPower = Uniform.create('unif_Glow', UniformType.Float, 1) #starColor = Uniform.create('star_color', UniformType.Color, 1) cutOffX = Uniform.create('cutoff_x', UniformType.Float, 1) cutOffY = Uniform.create('cutoff_y', UniformType.Float, 1) offPanelSize = Uniform.create('off_size', UniformType.Float, 1) multipleScale = 0.05 height = 5.0 width = 40.0 offsize = 0.2 orbitRatioFloat = 10.0 radiusRatioFloat = 4.0 ratioRadius = 20.0 fontSize = 0.7 @staticmethod def getData(str, type, default): if str == None: return default else: return type(str) @classmethod def initialize(cls): multipleScale = cls.multipleScale width = cls.width * multipleScale height = cls.height * multipleScale cls.orbitScale.setFloat(1.0) cls.orbitRatio.setFloat(cls.orbitRatioFloat) cls.radiusRatio.setFloat(cls.radiusRatioFloat) cls.radiusScale.setFloat(1.0) #cls.glowPower.setFloat(20) #cls.starColor.setColor(Color(1, 0, 0, 1)) cls.cutOffX.setFloat(width - cls.offsize*multipleScale) cls.cutOffY.setFloat(height - cls.offsize*multipleScale) cls.offPanelSize.setFloat(cls.offsize * cls.multipleScale) geom = ModelGeometry.create('stellar') v1 = geom.addVertex(Vector3(0, height/2, -0.01)) geom.addColor(Color(0,1,0,0)) v2 = geom.addVertex(Vector3(0, -height/2, -0.01)) geom.addColor(Color(0,0,0,0)) v3 = geom.addVertex(Vector3(width, height/2, -0.01)) geom.addColor(Color(1,1,0,0)) v4 = geom.addVertex(Vector3(width, -height/2, -0.01)) geom.addColor(Color(1,0,0,0)) geom.addPrimitive(PrimitiveType.TriangleStrip, 0, 4) getSceneManager().addModel(geom) shaderPath = "./shaders/" multipleDraw = ProgramAsset() multipleDraw.name = "background" multipleDraw.vertexShaderName = shaderPath + "background.vert" multipleDraw.fragmentShaderName = shaderPath + "background.frag" getSceneManager().addProgram(multipleDraw) starDraw = ProgramAsset() starDraw.name = "planet" starDraw.vertexShaderName = shaderPath + "planet.vert" starDraw.fragmentShaderName = shaderPath + "planet.frag" starDraw.geometryOutVertices = 4 starDraw.geometryShaderName = shaderPath + "/planet.geom" starDraw.geometryInput = PrimitiveType.Points starDraw.geometryOutput = PrimitiveType.TriangleStrip getSceneManager().addProgram(starDraw) def setHighlight(self, bool): if bool: self.highlight.setInt(2) else: self.highlight.setInt(0) def __init__(self, system): multiple = StaticObject.create('stellar') multiple.setEffect("background -t") self.multiple = multiple self.multiple.setSelectable(True) self.starRadius = system['star'][0]['radius'] # This is supposed to be set to the parentNode for it to attach to. self.parentNode = SceneNode.create('stellar_'+system['stellar']['name']) self.parentNode.addChild(multiple) multiple.getMaterial().addUniform('unif_Glow', UniformType.Float).setFloat(1/self.starRadius*self.ratioRadius) stellar = system['stellar'] distance = self.getData(stellar['distance'], float, 100.0) name = self.getData(stellar['name'], str, 'anonym') spectraltype = self.getData(system['star'][0]['spectraltype'], str, 'G') (min, max) = habitRange[spectraltype] material = multiple.getMaterial() self.highlight = Uniform.create('highlight', UniformType.Int, 1) self.highlight.setInt(0) material.addUniform('star_color', UniformType.Color).setColor(stellarColorMap[spectraltype]) material.attachUniform(self.orbitScale) material.attachUniform(self.cutOffX) material.attachUniform(self.orbitRatio) material.attachUniform(self.highlight) material.addUniform('hab_min', UniformType.Float).setFloat(min*self.multipleScale) material.addUniform('hab_max', UniformType.Float).setFloat(max*self.multipleScale) multipleScale = self.multipleScale width = self.width * multipleScale height = self.height * multipleScale #info = 'Stellar System: ' + name + ' Distance: ' + str(round(distance,1)) info = name + ' distance from earth ' + str(round(distance,1)) t = Text3D.create( 'fonts/arial.ttf', self.fontSize * self.multipleScale, info ) t.setFixedSize(False) t.setFontResolution(120) t.setPosition(Vector3(-0.5, height/2, 0)) t.setPosition(Vector3(-0.5, height/2, 0)) self.parentNode.addChild(t) planets = system['planets'] numOfPlanets = len(planets) geom = ModelGeometry.create(name) index = 0 for planet in planets: geom.addVertex(Vector3(self.multipleScale * self.getData(planet['semimajoraxis'], float, 1), 0, 0.01)) geom.addColor(Color(discoveryMethod[planet['discoverymethod']], numOfPlanets, index, self.multipleScale * self.getData(planet['radius'], float, 0.1))) # pName = planet['name'] # print pName index += 1 # if name in textureMap: # obj.setEffect("textured -d ./model/" + name + ".jpg") # else: # obj.setEffect("textured -d " + randomTextureMap[hash_string(name,len(randomTextureMap))] ) # multiple.getMaterial().setDiffuseTexture( geom.addVertex(Vector3(width, 0., 0.01)) geom.addColor(Color(10.0, 0.0, 0.0, 0.0)) geom.addPrimitive(PrimitiveType.Points, 0, numOfPlanets+1) getSceneManager().addModel(geom) planetSystem = StaticObject.create(name) planetSystem.setEffect("planet -t") material = planetSystem.getMaterial() material.attachUniform(self.orbitScale) material.attachUniform(self.radiusScale) material.attachUniform(self.cutOffX) material.attachUniform(self.cutOffY) material.attachUniform(self.offPanelSize) material.attachUniform(self.orbitRatio) material.attachUniform(self.radiusRatio) multiple.addChild(planetSystem)

UTF-8

Python

false

6,007

py

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multiples.py

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rogerh2/CryptoNeuralNet

1,271,310,336,432

a683168698beccf95893c48afeedde472c167fc8

a632f8e1faf3ae92608420f697673fc6485d2ef7

/CryptoBot/CryptoBotUnitTests/CryptoFillsModelUnitTests.py

497051f71b8d12180f1557eba650a9996ad6b41e

[]

no_license

https://github.com/rogerh2/CryptoNeuralNet

b70a7467d939db8836a04cc516747b780ab1b8eb

e2a14280b06a92d6822c50f53175ae33aad1e8a1

refs/heads/master

2022-12-09T08:55:54.592354

2020-06-08T02:37:29

130,617,552

2

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null

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2022-12-08T01:09:08

2018-04-22T23:52:13

2020-06-08T02:37:55

2022-12-08T01:09:07

12,759

2

0

26

Python

false

import unittest import pandas as pd import numpy as np import CryptoBot.CryptoForecast as cf class CryptoFillsModelTestCase(unittest.TestCase): data_obj = cf.FormattedCoinbaseProData(historical_order_books_path=None, historical_fills_path=None) def test_does_create_formatted_input_data_with_one_order_book_and_no_fills(self): # This is needed for live runs and backtests historical_order_books_path = '/Users/rjh2nd/PycharmProjects/CryptoNeuralNet/CryptoBot/CryptoBotUnitTests/' \ 'UnitTestData/SYM_historical_order_books_20entries.csv' historical_order_books = pd.read_csv(historical_order_books_path) order_books = historical_order_books.iloc[-1::] self.data_obj.historical_order_books = order_books.reset_index(drop=True) data_dict = self.data_obj.format_data('forecast') data = data_dict['input'] self.assertFalse(np.isnan(data).any()) self.assertEqual(len(data[0, ::]), 120) if __name__ == '__main__': unittest.main()

UTF-8

Python

false

1,053

py

49

CryptoFillsModelUnitTests.py

46

0.687559

0.679962

0

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39.5

117

charulagrl/DataStructures-Algorithms

18,769,007,105,711

bb58c61a17bc572a519c2302c4096eb06f0a0a37

83a6fd80c8dd85824e7fbae07933be9a785ee18d

/CrackingTheCodingInterview/Arrays-and-Strings/check_if_string_contains_unique_characters.py

852b993e132edd9e8037b4d589ab06dc40883ff8

[]

no_license

https://github.com/charulagrl/DataStructures-Algorithms

f81b667eefedd24231342c1f11faeee9e94fdc41

ab97ba1e09488420042946e9655111fa438c94d9

refs/heads/master

2016-09-21T14:40:13.248958

2016-09-01T10:42:24

36,951,364

1

0

null

# -*- coding: UTF-8 -*- ''' Problem: Implement an algorithm to determine if a string has all unique characters. Naive Approach: Loop through each character in the string and check in the entire string if that character is present. If even one such character found, return False. Time complexity: O(n*2) where n is the length of the string. Approach 2: Sort the string first and loop over the string and compare each character with its next character, if there is one such character, it returns false. Time complexity: Sorting O(n*logn) and Looping over string O(n). So the complexity will come down to O(n*logn) Approach 3: Store each character in a hash_map with key as each character and if any character is already found in hash_map return false. Time complexity: O(n) to loop over string Space Complexity: O(n) to store n characters ''' # Check if string has unique characters using hash map def unique_character_string(s): # Declaring hash_map using python dictionaries hash_map = {} for i in s: if i in hash_map: return False else: hash_map[i] = True return True

UTF-8

Python

false

1,141

py

9

check_if_string_contains_unique_characters.py

8

0.718668

0.715162

0

39

28.25641

122

keerthanakumar/contest

15,573,551,434,214

c98879c04bae54ce5d87e3d9db912bf2a6904521

f25bd4cd35b31289e06159034065d16faf094eaa

/contest/teams/2PacV5_1/factory.py

eddc6816f135b28e67ea34dd8c3b6724edac22c6

[]

no_license

https://github.com/keerthanakumar/contest

28dc02609a54f40d36156545f3cf9df18acf6c11

3d29c4aa83232ff171051d7197c402323845c526

refs/heads/master

2021-01-01T18:17:08.329322

2014-04-29T18:47:55

null

0

null

from captureAgents import AgentFactory import distanceCalculator import random, time, util from game import Directions import game #our code from agent import * from offenseRole import * from defenseRole import * from inference import * import search from myUtil import * class MSBFactory(AgentFactory): def __init__(self, isRed, **kwArgs): AgentFactory.__init__(self, isRed) print "factory __init__ called" #for emergency timeout prevention self.totalRuntime = 0 self.nRuntimeSamples = 0 self.emergencyScale = 1 self.args = kwArgs self.agents = {} #this lists which MSBAgentRoles we'll assign to new agents self.availableRoles = util.Queue() if not self.args["offenseOnly"]: self.availableRoles.push(MSBDefensiveAgentRole) self.availableRoles.push(MSBOffensiveAgentRole) self.initializeForNewGame() # this is (annoyingly) separate from __init__ because the factory outlasts a single game when the -n option is used def initializeForNewGame(self): print "initializeForNewGame called" self.distancer = None self.pathCache = {} self.walls = [] self.legalPositions = [] self.tracking = None self.gameTime = -1 self.lastDeath = -1 self.lastSwap = -1 def getAgent(self, index): print "factory.getAgent called for agent %d" % index newAgent = MSBAgent(index, self) # assign this new agent a role if not self.args["doNothing"]: newAgentRole = self.availableRoles.pop() self.availableRoles.push(newAgentRole) newAgent.role = newAgentRole() self.agents[index] = newAgent return newAgent def removeDeadAgents(self, gameState): dead = [] for agentIndex in self.agents: if agentIndex >= gameState.getNumAgents(): dead.append(agentIndex) for agentIndex in dead: del self.agents[agentIndex] def initTracking(self, index, gameState): "Initializes inference modules for each enemy agent" #already inited if self.tracking is not None: return agent = self.agents[index] opponents = agent.getOpponents(gameState) self.tracking = {} for opp in opponents: tracker = ExactInference(MSBSimulatedEnemyAgent(opp, self.getDistancer(gameState), self.args["uniformEnemySimulation"])) tracker.failOnEmpty = self.args["failOnEmptyDistribution"] tracker.initialize(gameState) tracker.initializeSpecific(gameState.getInitialAgentPosition(opp)) self.tracking[opp] = tracker def notifyEaten(self, gameState, enemyIndex): tracker = self.tracking[enemyIndex] tracker.initializeSpecific(gameState.getInitialAgentPosition(enemyIndex)) def maybeSwapRoles(self, index): # if we don't have exactly 2 agents or we swapped recently, don't swap if len(self.agents) != 2 or self.gameTime - self.lastSwap < 10: return gameState = self.agents[index].getCurrentObservation() pos1, pos2 = [gameState.getAgentPosition(i) for i in self.agents] # if either agent is pacman, don't swap for agentIndex in self.agents: if gameState.getAgentState(agentIndex).isPacman: return # if the agents are far apart, don't swap if self.getDistancer(gameState).getDistance(pos1, pos2) > 7: return optFunc = max if self.agents[index].red else min closestXToBorder = optFunc(pos1, pos2, key=lambda p: p[0])[0] # if neither agent is close to the border, don't swap if abs(gameState.data.layout.width/2 - closestXToBorder) > 3: return # TODO: verify one of our agents died recently... not sure if necessary? for enemyIndex in self.tracking: # if there is an invader, don't swap if gameState.getAgentState(enemyIndex).isPacman: return # if there is a very imminent threat on the border, don't swap enemyPos = gameState.getAgentPosition(enemyIndex) if enemyPos != None and abs(gameState.data.layout.width/2 - enemyPos[0]) < 3: return # finally, if we haven't fallen out on any of the above conditions, swap roles self.lastSwap = self.gameTime roles = [agent.role for agent in self.agents.values()] for agent, newRole in zip(self.agents.values(), reversed(roles)): agent.role = newRole print "/\\"*100 print "Swapping Roles!" def updateSharedKnowledge(self, index): #ideally, this shouldn't happen since we'll call initTracking from registerInitialState if self.tracking == None: self.initTracking(index, gameState) gameState = self.agents[index].getCurrentObservation() lastGameState = self.agents[index].getPreviousObservation() dists = gameState.getAgentDistances() #an annoyance self.removeDeadAgents(gameState) #update a timer to know how many moves have occurred before this one -- this includes enemy agents if self.gameTime == -1: startFirst = index == 0 #TODO this is incorrect, but it may not be possible to be truly correct. self.gameTime = 0 if startFirst else 1 else: self.gameTime += 2 print "Agent %d calling updateSharedKnowledge at time step %d" % (index, self.gameTime) #check if we died in the last step if lastGameState != None: lastPos = lastGameState.getAgentPosition(index) nowPos = gameState.getAgentPosition(index) if nowPos == gameState.getInitialAgentPosition(index) and self.getDistancer(gameState).getDistance(lastPos, nowPos) > 4: self.lastDeath = self.gameTime #check if the last enemy to move killed itself prevEnemy = index - 1 prevEnemyEaten = False if prevEnemy < 0: prevEnemy += gameState.getNumAgents() prevAlly = prevEnemy - 1 if prevAlly < 0: prevAlly += gameState.getNumAgents() if self.gameTime >= 2: prevAllyState = self.agents[prevAlly].getCurrentObservation() prevEnemyLoc = prevAllyState.getAgentPosition(prevEnemy) if prevEnemyLoc != None and (gameState.getAgentPosition(prevEnemy) == None or gameState.getAgentPosition(prevEnemy) == gameState.getInitialAgentPosition(prevEnemy)): for agentIndex in self.agents: if self.getDistancer(gameState).getDistance(prevEnemyLoc, prevAllyState.getAgentPosition(agentIndex)) <= 1: prevEnemyEaten = True break # check if an enemy ate one of our food in the last time step -- if so, we know where it is. prevEnemyJustAteFood = False prevEnemyFoodEaten = None if self.gameTime >= 2 and self.args["foodInference"]: prevAllyState = self.agents[prevAlly].getCurrentObservation() prevFood = set(self.agents[index].getFoodYouAreDefending(prevAllyState).asList()) foodNow = set(self.agents[index].getFoodYouAreDefending(gameState).asList()) foodDiff = prevFood - foodNow if len(foodDiff) == 1: prevEnemyJustAteFood = True prevEnemyFoodEaten = foodDiff.pop() for enemyIndex, tracker in self.tracking.items(): print "Agent %d observes enemy %d at noisyDistance %d (direct reading: %s) from its viewpoint %s" % (index, enemyIndex, dists[enemyIndex], gameState.getAgentPosition(enemyIndex), gameState.getAgentPosition(index)) # if the enemy is close enough for us to know exactly where it is, just update the tracker with that if gameState.getAgentPosition(enemyIndex) != None: tracker.initializeSpecific(gameState.getAgentPosition(enemyIndex)) print "- it's close enough we have an exact reading, so ignoring noisyDistance" continue # if our check outside the loop indicated the enemy ate, skip observe and elapseTime on it if enemyIndex == prevEnemy and prevEnemyJustAteFood: tracker.initializeSpecific(prevEnemyFoodEaten) print "- enemy just ate food, so we know it's at %s" % tuple([prevEnemyFoodEaten]) continue # if this enemy was the last enemy to move and killed itself, update beliefs to initial position if enemyIndex == prevEnemy and prevEnemyEaten: tracker.initializeSpecific(gameState.getInitialAgentPosition(enemyIndex)) print "- enemy killed itself, resetting to initial position" continue # elapse time once per round if enemyIndex == prevEnemy and self.gameTime != 0: tracker.elapseTime(gameState.deepCopy()) #debug # realPos = gameState.true.getAgentPosition(enemyIndex) # realDistance = util.manhattanDistance(gameState.getAgentPosition(index), realPos) # print "!!! agent %d's view of enemy %d: noisyDistance=%d, realPos=%s, realDistance=%d (delta %d)" % (index, enemyIndex, dists[enemyIndex], realPos, realDistance, dists[enemyIndex]-realDistance) # import capture # assert dists[enemyIndex]-realDistance in capture.SONAR_NOISE_VALUES, "invalid noisyDistance!!!" # observe tracker.observe(dists[enemyIndex], gameState.getAgentPosition(index), self.getDistancer(gameState), gameState) # if the enemy isPacman, then we know it's on our side. If not, we know it's not. if self.args["pacmanInference"]: usRed = self.agents[index].red isPacman = gameState.getAgentState(enemyIndex).isPacman locRed = isPacman if usRed else not isPacman beliefs = tracker.beliefs for loc in beliefs: if gameState.isRed(loc) != locRed: beliefs[loc] = 0 beliefs.normalize() # not sure if I should need to do this, but the belief distribution seems to eventually be empty if tracker.getBeliefDistribution().totalCount() == 0: tracker.initializeUniformly(gameState) #observe again so distribution isn't useless tracker.observe(dists[enemyIndex], gameState.getAgentPosition(index), self.getDistancer(gameState), gameState) print "- enemy %d's tracker being reset due to being empty." % enemyIndex print "- enemy %d now thought to occupy %s" % (enemyIndex,self.getAveragedEnemyLocation(enemyIndex)) self.maybeSwapRoles(index) def updateDisplay(self, gameState, curIndex): dists = [self.tracking[i].getBeliefDistribution() if i in self.tracking else None for i in range(gameState.getNumAgents())] if self.args["showMiscDistributions"]: for i in range(len(dists)): if dists[i] == None and i in self.agents: dists[i] = self.agents[i].miscDistribution self.agents[curIndex].displayDistributionsOverPositions(dists) def getBeliefDistribution(self, enemyIndex): return self.tracking[enemyIndex].getBeliefDistribution() def getAveragedEnemyLocation(self, enemyIndex): xavg = 0 yavg = 0 for pos, prob in self.tracking[enemyIndex].getBeliefDistribution().items(): x, y = pos xavg += x * prob yavg += y * prob avgPoint = util.nearestPoint((xavg, yavg)) # annoying thing because mazeDistance doesn't work if one point is a wall if avgPoint in self.walls: neighbors = list(getNeighbors(avgPoint)) neighbors = [n for n in neighbors if n in self.legalPositions] if len(neighbors) > 0: avgPoint = neighbors[0] else: raise Exception("avg enemy location is wall surrounded by walls") return avgPoint def getDistancer(self, gameState = None): if self.distancer != None: return self.distancer # this should never happen, since registerInitialState calls this with a gameState if gameState == None: raise Exception("getDistancer called without gameState, but no distancer has been inited yet") distancer = distanceCalculator.Distancer(gameState.data.layout) distancer.getMazeDistances() self.distancer = distancer self.walls = gameState.getWalls().asList() self.legalPositions = gameState.getWalls().asList(False) return distancer def getPath(self, gameState, source, target): # basic caching of paths if (source, target) in self.pathCache: #print "Found path from %s to %s in pathCache" % (source, target) return self.pathCache[(source, target)] elif (target, source) in self.pathCache: #print "Found path from %s to %s in pathCache" % (source, target) return reversed(self.pathCache[(target, source)]) print "getPath(%s, %s) called, computing using A*" % (source, target) # compute path using A* search with known optimal maze distance as heuristic problem = MSBPathfindingSearchProblem(source, target, self.legalPositions) def heuristic(state, prob): return self.getDistancer(gameState).getDistance(state, target) path = search.astar(problem, heuristic) assert len(path) == self.getDistancer(gameState).getDistance(source, target), "A* found non-optimal path from %s to %s" % (source, target) # update cache self.pathCache[(source, target)] = path for i in range(0,len(path)-1): self.pathCache[(path[i], target)] = path[i+1:] print "getPath(%s, %s) returning; len(pathCache)=%d" % (source, target, len(self.pathCache)) return path def reportRuntime(self, elapsedTime): self.totalRuntime += elapsedTime self.nRuntimeSamples += 1 avgRuntime = self.totalRuntime / self.nRuntimeSamples if avgRuntime > 0.7 and self.emergencyScale >= 0.4: self.emergencyScale -= 0.25 if "original_maxFoodToPathfind" not in self.args: self.args["original_maxFoodToPathfind"] = self.args["maxFoodToPathfind"] self.args["maxFoodToPathfind"] = int(self.args["original_maxFoodToPathfind"] * self.emergencyScale) print "########################### Emergency timeout prevention: reducing maxFoodToPathfind to %d (last move took %.3f seconds; average is %.3f seconds)" % (self.args["maxFoodToPathfind"], elapsedTime, avgRuntime) self.totalRuntime = 0 self.nRuntimeSamples = 0 # this is used to come up with a distribution of possible enemy agent successor positions for the elapseTime updates # TODO: maybe in the future, use a copy of our own agent to predict this? class MSBSimulatedEnemyAgent: def __init__(self, index, distancer, uniform = False): self.index = index self.distancer = distancer self.weights = { "default" : 1 } if uniform: self.agent = self return #currently, this uses BaselineAgents' agents. #To use the features/weights in this class, set self.agent = self try: from BaselineAgents.baselineAgents import OffensiveReflexAgent, DefensiveReflexAgent self.agent = OffensiveReflexAgent(index) if index%2==0 else DefensiveReflexAgent(index) self.agent.distancer = distancer except: #if BaselineAgents isn't accessible, fallback gracefully self.agent = self def getFeatures(self, state, action): return {"default":1} def evaluate(self, state, action): #fall through to another agent if we have one if self.agent is None: return 0 elif self.agent != self: return max(0, self.agent.evaluate(state, action)) features = self.getFeatures(state, action) amts = [features[i]*self.weights[i] if i in self.weights else 0 for i in features] return max(sum(amts), 0) def getDistribution(self, gameState): #get the utilities from the agent and find the maximum utilities = {action: self.evaluate(gameState, action) for action in gameState.getLegalActions(self.index)} maxUtility = max(utilities.values()) #any action that maximizes utility gets equal probability, all else get 0 tbr = util.Counter() for action in utilities: if utilities[action] < maxUtility: continue tbr[action] = 1 tbr.normalize() return tbr class MSBPathfindingSearchProblem(search.SearchProblem): def __init__(self, source, target, legalPositions): self.source = source self.target = target self.legalPositions = legalPositions def getStartState(self): return self.source def isGoalState(self, state): return state == self.target def getSuccessors(self, state): return [(c, c, 1) for c in getNeighbors(state, includeDiagonals=False) if c in self.legalPositions] def getCostOfActions(self, actions): return len(actions)

UTF-8

Python

false

15,338

py

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factory.py

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0.734842

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0

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jaljs/myworkspace

17,540,646,454,370

a8cd40d32024a85f52d1c79bca9444da8e774413

409d4ad370e25c23691052645ef1eb2b6deaf341

/car/webcontrol/main.py

c4034c237400056b912a0d97906d65672d0162d4

[]

no_license

https://github.com/jaljs/myworkspace

5204de1ebda0ba1657d76ae90690706f89c325bb

c27240a022cccbc0bb52a6dd6d3f61217111b6ed

refs/heads/master

2021-01-17T15:26:44.217667

2018-06-06T10:20:11

83,683,768

0

null

#!/usr/bin/env python3 from bottle import get,post,run,request,template @get("/") def index(): return template("index") @post("/cmd") def cmd(): print("按下了按钮: "+request.body.read().decode()) return "OK" @post("/mcmd") def mcmd(): print("pull-------------->"+request.body.read().decode()) run(host="0.0.0.0",post=8080)

UTF-8

Python

false

343

py

63

main.py

6

0.60961

0.582583

0

14

22.714286

58

zhuping580/myflaskdemo

10,505,490,024,520

ebc4be3c42b24c12527743b87c6dee3720f608e6

988eb29092e518638130e53632f2a0910cea0e79

/app/cases.py

2c04c30b9c9e887c32ccbe51c6e8f30340b4abd0

[]

no_license

https://github.com/zhuping580/myflaskdemo

19515b59e90cfcfceb2fae0c1911caa65748bf26

34fa07baae62783d0b8bfe4b0969b4615cb0f74b

refs/heads/master

2023-07-01T13:44:53.904576

2021-08-09T08:16:22

388,406,288

0

null

import json from datetime import datetime from flask import Blueprint, request, jsonify import requests from common.token_method import login_required, verify_token from common import db from common.modelFuntion import CreateCase # 创建蓝图 cases = Blueprint('cases', __name__) @cases.route('/cases/update', methods=['POST']) @login_required def update_cases(): userid = verify_token() data = request.get_data() json_data = json.loads(data) print(json_data) priority = json_data['priority'] title = json_data['title'] enter = json_data['enter'] outs = json_data['outs'] updated_by = json_data['updated_by'] if 'id' in json_data.keys(): _id = json_data['id'] if db.query_db("select * from cases where id='{}'".format(_id)) is not None: _sql = "update cases set priority='%s',title='%s',enter='%s',outs='%s',updated_by=%d where id='%d'" % \ (priority, title, enter, outs, updated_by, userid) e = db.change_db(_sql) if e: return jsonify(code=-1, message=u"操作失败") return jsonify(code=0, message=u"修改成功") # 新增 ctime = datetime.now().strftime("%Y-%m-%d %H:%M:%S") _sql = '''insert into cases (priority,title,enter,outs,created,created_by) value ('%s', '%s', '%s', '%s', '%d')'''\ % (priority, title, enter, outs, ctime, userid) e = db.change_db(_sql) if e: return jsonify(code=-1, message=u"操作失败") return jsonify(code=0, message=u"success") @cases.route('/cases/list', methods=['GET']) @login_required def cases_list(): """获取模型数据""" # print('userid:', userid) print(request.args) i_id = int(request.args.get("i_id")) # pageSize = int(request.args.get("pageSize")) # pageNum = int(request.args.get("currentPage")) data = [] database = db.query_db("select id,priority,title,enter,outs,result from cases where i_id=%d;" % i_id) for i in database: temp = {} temp['id'] = i[0] temp['priority'] = i[1] temp['title'] = i[2] temp['enter'] = i[3] temp['outs'] = i[4] temp['result'] = i[5] data.append(temp) return jsonify(code=0, message=u"success", data=data) @cases.route('/cases/delete', methods=['POST']) @login_required def delete_cases(): data = request.get_data() json_data = json.loads(data) print(json_data) _id = json_data['id'] _sql = "delete from cases where id=%d" % _id e = db.change_db(_sql) if e: return jsonify(code=-1, message=u"操作失败") return jsonify(code=0, message=u"success") @cases.route('/cases/create', methods=['POST']) @login_required def create_case(): userid = verify_token() data = request.get_data() json_data = json.loads(data) i_ids = json_data['i_id'] print(i_ids) for i_id in i_ids: db_data = db.query_db( "select name,case1,maxlength,minlength,required,options from params where i_id=%d" % i_id ) title = db.query_db("select name from interface where id=%d" % i_id)[0][0] module_data = [] for i in db_data: temp = {} temp['name'] = i[0] temp['case1'] = i[1] temp['maxlength'] = i[2] temp['minlength'] = i[3] temp['required'] = i[4] temp['options'] = i[5] module_data.append(temp) cases_data = CreateCase(module_data, title).get_case() db.change_db("delete from cases where i_id=%d" % i_id) ctime = datetime.now().strftime("%Y-%m-%d %H:%M:%S") insert_datas = [] for k in cases_data: # print('用例', k) insert_data = [] insert_data.append(i_id) for g in k: insert_data.append(str(k[g])) insert_data.append(ctime) insert_data.append(userid) insert_data.append('auto') insert_data = tuple(insert_data) insert_datas.append(insert_data) insert_datas = tuple(insert_datas) print('————————', insert_datas) _sql = "insert into cases (i_id,title,enter,outs,priority,created,created_by,type) " \ "value (%s,%s,%s,%s,%s,%s,%s,%s)" e = db.change_db(_sql, insert_datas) print('e', e) return jsonify(code=0, message=u"success") @cases.route('/cases/execute', methods=['POST']) @login_required def execute_cases(): data = request.get_data() json_data = json.loads(data) print(json_data) if 'id' in json_data.keys: _id = json_data['id'] cases = db.db_json('cases', 'id='+str(_id), 'title', 'enter', 'outs', 'i_id') i_id = cases[0]['i_id'] elif 'i_id' in json_data.keys: i_id = json_data['i_id'] cases = db.db_json('cases', 'id='+str(i_id), 'title', 'enter', 'outs', 'i_id') else: return jsonify(code=-1, message=u"参数错误") interface = db.db_json('interface', 'id='+str(i_id), 'methods', 'url', 'login_required') interface = interface[0] systems = db.db_json('systems', None, 's_key', 'val', 'type') url = '' headers = {} for i in systems: if i['s_key'] == 'url': url = i['val'] elif i['s_key'] == 'token': headers['token'] = i['val'] elif i['s_key'] == 'Cookie': headers['Cookie'] = i['val'] for case in cases: if interface['methods'] == 'post': _result = requests.post(url=url+interface['url'], json=json.loads(case["enter"].replace("'", '"')), headers=headers) elif interface['methods'] == 'get': _result = requests.get(url=url+interface['url'], params=json.loads(case['enter'].replace("'", '"')), headers=headers) else: return jsonify(code=0, message=u"'不支持' + i_data['methods'] + '请求方式'") sql3 = "update cases set result ='%s' where id=%d" % (_result.text, _id) db.change_db(sql3) return jsonify(code=0, message=u"success") def login(): url = "http://192.168.3.66:9001/user/login/password" data = { "mobile": "18111111111", "password": "Sulongfei@123456", "mobileAraeCode": "+86", "regType": 0, "email": "" } response = requests.post(url=url, json=data) # print('请求头', response.request.headers) # print('请求体', response.request.body) # print('响应头', response.headers) cookie = response.headers['Set-Cookie'] cookie = cookie.split(';', 1)[0] token = response.json()['data']['token'] _sql = "update systems set val='%s' where s_key='Cookie'" % cookie db.change_db(_sql) _sql0 = "update systems set val='%s' where s_key='token'" % token db.change_db(_sql0) if __name__ == '__main__': login()

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false

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py

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cases.py

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0.557508

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201

32.696517

129

Amanikashema/data_type2

4,294,967,318,563

56b3385eb806bb380b6c9f1318f1f91839a4b457

7e959170963990a0d65f322d9f34fc098c65ff03

/data_type2.py

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[]

no_license

https://github.com/Amanikashema/data_type2

7def61cce786fd1858a7e7f631ec8d0c89270132

0e6b157de1ece1b94cb7ba4b6d94476dad719a36

refs/heads/master

2021-03-08T03:20:57.207886

2020-03-10T13:51:50

246,313,414

0

null

my_list=[56,78,34,21,56,34,125,45,89,75,12,56] my_list.sort() print(my_list) total=sum(my_list) #using a function of sum to add the total print("The sum of all of the element is:", total) print("The smallest number in the list is:", min(my_list)) print("The largest number in the list is:",max(my_list)) my_list=list(set(my_list)) print("List after removing duplicate elements", my_list)

UTF-8

Python

false

397

py

1

data_type2.py

1

0.70529

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0

13

29.153846

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iammanoj/PythonML

8,632,884,313,131

be85317e906b4b4410000c5ff9368d70bf30e9aa

71a6d0d09329be51c25b8d10be03ded4dd3f9f02

/ChkPalindrome.py

b578516dfa4fe981a72672ca0746b3761995b5f8

[]

no_license

https://github.com/iammanoj/PythonML

3301f099271a072d6bb8d8ac9b92d3387fae8f88

0d0f67dea8c26e2cb389aa157fdc6b41d53f0f1f

refs/heads/master

2021-01-02T09:01:31.154236

2015-05-17T22:34:27

34,771,477

0

null

#!/Users/manoj_mohan/anaconda/bin/python ############################################ # Program Name : Check Palindrome Words # Description : This program helps determine any combination of words from a given list of words if they can be joined together to form a Palindrome. # Coder : Manoj Mohan # Create Date : 05/11/2015 # Mod Log : # # # ############################################ ## Import libraries from copy import deepcopy list = ["bat","tab","cat","tar","rat", "ough", "stuff"] for item in list: for RestEachItem in list: if item <> RestEachItem: if item == RestEachItem[::-1]: print item, RestEachItem list.remove(item)

UTF-8

Python

false

779

py

5

ChkPalindrome.py

4

0.504493

0.49294

0

23

32.782609

165

Karl-Horning/python-3-bootcamp

5,265,629,927,481

421e1b7d38ebef96563b479773d571fae5a8f753

b1b376358edef6faf1ba1c5559e7ae757c1dd8a9

/section_16_tuples_and_sets/144_set_comprehension_and_recap.py

13f08a7198a9b6a7d65a984d94e0db3c6f42273c

[]

no_license

https://github.com/Karl-Horning/python-3-bootcamp

e3894003310f123e9f3e040a490687ee9ff40cc9

f78d1cc5c6a42539f724735d83bd74f77f6653f6

refs/heads/master

2020-03-24T15:22:14.566141

2018-07-29T19:23:23

142,787,548

0

null

print({x**2 for x in range(10)}) # {0, 1, 64, 4, 36, 9, 16, 49, 81, 25} print({char.upper() for char in 'hello'}) # {'E', 'H', 'L', 'O'}

UTF-8

Python

false

137

py

67

144_set_comprehension_and_recap.py

67

0.49635

0.357664

0

5

26.6

41

tedneward/Demos

19,585,050,877,506

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/2019/VSLiveBoston/Py/demo.py

9aef065bf91f0261ed203b3181c5326c6667d76c

[]

no_license

https://github.com/tedneward/Demos

a65df9d5a0390e3fdfd100c33bbc756c83d4899e

28fff1c224e1f6e28feb807a05383d7dc1361cc5

refs/heads/master

2023-01-11T02:36:24.465319

2019-11-30T09:03:45

239,251,479

0

null

false

2023-01-07T14:38:21

2020-02-09T05:21:15

2020-02-10T03:44:36

2023-01-07T14:38:20

217,845

0

74

Java

false

print("Hello Boston") class Attendee: def sayHello(): print("Hello")

UTF-8

Python

false

87

py

462

demo.py

289

0.574713

0

5

15.4

22

linea-it/lna

19,567,871,022,832

0602a6c03af3db06fbdcb7858560a46c73afbd24

b1ff1b8920f8bee4d9fdaad938b25daedc51f7ad

/backend/lna/migrations/0007_auto_20190211_1324.py

e92ef927d26c21a9666fe3029f3a102e16aa0b87

[]

no_license

https://github.com/linea-it/lna

141d051c8b3e3c061ef2016ee48276a4538ddc88

dd7c82059c41180d584bd8b201ea2d843878ef8e

refs/heads/master

2022-12-17T12:29:04.291593

2020-07-01T19:27:21

148,836,030

0

null

false

2022-12-09T13:57:18

2018-09-14T20:00:05

2020-07-01T20:40:59

2022-12-09T13:57:17

430,971

0

26

JavaScript

false

# Generated by Django 2.1.5 on 2019-02-11 13:24 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('lna', '0006_exposure_target'), ] operations = [ migrations.AddIndex( model_name='exposure', index=models.Index(fields=['filename'], name='lna_exposur_filenam_1f8e84_idx'), ), migrations.AddIndex( model_name='exposure', index=models.Index(fields=['date'], name='lna_exposur_date_2a310b_idx'), ), migrations.AddIndex( model_name='exposure', index=models.Index(fields=['date_obs'], name='lna_exposur_date_ob_b3f2c1_idx'), ), migrations.AddIndex( model_name='exposure', index=models.Index(fields=['target'], name='lna_exposur_target_4d256e_idx'), ), migrations.AddIndex( model_name='exposure', index=models.Index(fields=['ra', 'dec'], name='lna_exposur_ra_4a1ba3_idx'), ), ]

UTF-8

Python

false

1,047

py

45

0007_auto_20190211_1324.py

39

0.572111

0.536772

0

33

30.727273

91

kiramishima/csv_pokeapi

10,857,677,350,067

4c55efeb527bf1dccb0783adc71987022f9b1dc2

4e0fce17cf26f8661c2bafa70c1b041ac41285f5

/app.py

66fa0c74120761ec9b1524a9d251ebb27953f950

[]

no_license

https://github.com/kiramishima/csv_pokeapi

3cc69cd00e99c790155bb7ebae1a3c793cc32603

1f65e2ddd64ca8545a03039b775a878e7ac95536

refs/heads/master

2023-09-03T20:24:29.109257

2021-10-15T17:37:02

417,278,128

0

null

import json import math from flask import Flask, jsonify, request, render_template import pandas as pd app = Flask(__name__) # Load CSV app.data = pd.read_csv("./data/pokemon.csv", header=0, sep='\t', names=['id', 'name', 'type_1', 'type_2', 'total', 'hp', 'atk', 'def', 'sp_atk', 'sp_def', 'speed', 'generation', 'legendary']) @app.route('/') def home(): """ This Endpoint return only the swagger documentation """ return render_template('index.html') @app.route('/api/v1/pokemon') def all(): """ This enpoint returns a list of pokemon paginated """ page = request.args.get('page', 1, type=int) per_page = request.args.get('per_page', 10, type=int) resp = pagination(app.data, page, per_page) return jsonify(resp) def pagination(df, start_page = 1, per_page = 15): """ Paginate function """ pagesize = per_page page = start_page - 1 max_pages = math.ceil(df.shape[0] / pagesize) return { 'total_records': df.shape[0], 'current_page': page + 1, 'max_pages': max_pages, 'per_page': pagesize, 'data': json.loads(df.iloc[page * pagesize: (page + 1) * pagesize].to_json(orient='records', force_ascii=False)) } @app.route('/api/v1/pokemon/<poke_id>', methods=['GET']) def find(poke_id): """ This endpoint filters the dataset by id or by pokemon's name and return one result """ pfind = app.data[(app.data['id'] == poke_id) | (app.data['name'] == poke_id)] dtjson = json.loads(pfind.to_json(orient='records', force_ascii=False)) resp = {'status': True, 'data': dtjson} return jsonify(resp) @app.route('/api/v1/pokemon', methods=['POST']) def create_pokemon(): """ Endpoint to create a new pokemon in the dataset """ form = request.form print(form) pokemon = {"id": form.get('id'), "name": form.get('name'), "type_1": form.get('type_1'), "type_2": form.get('type_2'), "total": form.get('total'), "hp": form.get('hp'), "atk": form.get('atk'), "def": form.get('def'), "sp_atk": form.get('sp_atk'), "sp_def": form.get('sp_def'), "speed": form.get('speed'), "generation": form.get('generation'), "legendary": form.get('legendary')} # print(pokemon) new_row = pd.Series(pokemon) app.data = app.data.append(new_row, ignore_index=True) resp = {'status': True, 'data': pokemon} return jsonify(resp) @app.route('/api/v1/pokemon/<poke_id>', methods=['POST']) def update_pokemon(poke_id): """ Update pokemon endpoint """ form = request.form # build response pokemon = {"id": form.get('id'), "name": form.get('name'), "type_1": form.get('type_1'), "type_2": form.get('type_2'), "total": form.get('total'), "hp": form.get('hp'), "atk": form.get('atk'), "def": form.get('def'), "sp_atk": form.get('sp_atk'), "sp_def": form.get('sp_def'), "speed": form.get('speed'), "generation": form.get('generation'), "legendary": form.get('legendary')} pfind = app.data.loc[(app.data['id'] == poke_id) | (app.data['name'] == poke_id)] pfind = app.data.loc[pfind.index, :] pfind.id = form.get('id') pfind.name = form.get('name') pfind.type_1 = form.get('type_1') pfind.type_2 = form.get('type_2') pfind.total = form.get('total') pfind.hp = form.get('hp') pfind.atk = form.get('atk') pfind['def'] = form.get('def') pfind.sp_atk = form.get('sp_atk') pfind.sp_def = form.get('sp_def') pfind.speed = form.get('speed') pfind.generation = form.get('generation') pfind.legendary = form.get('legendary') # print(pfind) app.data.update(pfind) resp = {'status': True, 'message': 'Pokemon has been updated', 'data': pokemon} return jsonify(resp) @app.route('/api/v1/pokemon/<poke_id>', methods=['DELETE']) def delete_pokemon(poke_id): """ Endpoint for delete a pokemon """ # find the target pfind = app.data.loc[(app.data['id'] == poke_id) | (app.data['name'] == poke_id)] # process to delete app.data.drop(index=pfind.index, inplace=True) resp = {'status': True, 'message': 'Pokemon has been deleted'} return jsonify(resp) if __name__ == '__main__': app.run()

UTF-8

Python

false

4,320

py

4

app.py

1

0.580556

0.57338

0

123

34.121951

120

893202527/JK

17,343,077,975,191

ec5dce0013a7402996c251e043c6882a5e3b05af

326269d5c3740bed8ca5ef65aeab35ada4ced727

/MyDjango/xycDemo/models.py

aaee15810df7422dc28fa68b4b9b644b8308402b

[]

no_license

https://github.com/893202527/JK

43115fbc08b119de5c49ac4b470e4cbcbcdc917b

0080f3d349093ce771df94f70edd6010a9fd3ff7

refs/heads/master

2022-11-12T04:48:34.174950

2019-09-02T09:12:17

180,317,671

1

null

false

2022-11-01T23:31:18

2019-04-09T08:11:31

2019-09-02T09:12:45

2019-09-02T09:12:43

50,926

0

1

Python

false

import datetime from django.db import models import json from django.utils import timezone # Create your models here. class User(models.Model): nickName=models.CharField(max_length=20) create_time=models.DateTimeField(auto_now_add=True) Modify_time=models.DateTimeField(auto_now=True) phoneNumber=models.CharField(max_length=11,unique=True) username=models.CharField(max_length=20) age=models.CharField(max_length=3) sex =( ('male','男'), ('female','女'),) password=models.CharField(max_length=100) def __str__(self): smart = {'phoneNumber':self.phoneNumber, 'nickName':self.nickName, 'age':self.age, 'sex':self.sex, 'username':self.username, 'password':self.password } return json.dumps(smart) class user_info(models.Model): userid=models.ForeignKey(User,on_delete=models.CASCADE) ip=models.CharField(max_length=100) login_time=models.DateTimeField(auto_now=True) login_times=models.IntegerField(auto_created=True)#实现自增,AUTO_INCREMENT=100从100开始自增

UTF-8

Python

false

1,162

py

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models.py

20

0.652632

0.635965

0

36

30.583333

86

sts-sadr/Hands-of-Machine-Learning

13,417,477,874,901

e7c9458e97389ed8156fe3b2628be7c68e0f3ef2

cefc8caac20ec430265dfbe56b3d9b8ab1acb34d

/MNIST.py

3d961929ef7ee20b2fcc5f9c0e6e2c162a4a99a6

[]

no_license

https://github.com/sts-sadr/Hands-of-Machine-Learning

ca9d9bbf12d141928210913ee9567f7f2b436cdf

16d3c64a43d11170f24ab46f407a987f7fc46623

refs/heads/master

2021-01-07T08:16:53.190991

2019-09-03T18:55:24

null

0

null

# -*- coding: utf-8 -*- """ Created on Tue Sep 3 13:02:32 2019 @author: jered.willoughby """ #Load libraries from sklearn.datasets import fetch_openml import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np from sklearn.model_selection import StratifiedKFold from sklearn.base import clone from sklearn.model_selection import cross_val_score from sklearn.model_selection import cross_val_predict from sklearn.metrics import confusion_matrix from sklearn.metrics import precision_score, recall_score from sklearn.metrics import f1_score mnist = fetch_openml('mnist_784',version=1) mnist.keys() #Descriptive statistics X,y = mnist["data"], mnist["target"] X.shape y.shape some_digit = X[0] some_digit_image = some_digit.reshape(28,28) #Select 0 indexed image from the mnist data and plot it plt.imshow(some_digit_image, cmap="binary") plt.axis("off") plt.show() #validate from the target set y[0] #this is a string value #Change datatype to integer y = y.astype(np.uint8) #Create the testing and training sets X_train, X_test, y_train, y_test = X[:60000], X[60000:], y[:60000], y[60000:] #Now we need to determine what classifier to use. Let's start with a binary #target vector classification y_train_5 = (y_train == 5) y_test_5 = (y_test == 5) #Binary classifier = stochastic gradient descent SGDClassifier from sklearn.linear_model import SGDClassifier sgd_clf = SGDClassifier(random_state=42) sgd_clf.fit(X_train,y_train_5) sgd_clf.predict([some_digit]) #Cross Validation skfolds = StratifiedKFold(n_splits=3, random_state=42) for train_index, test_index in skfolds.split(X_train, y_train_5): clone_clf = clone(sgd_clf) X_train_folds = X_train[train_index] y_train_folds = y_train_5[train_index] X_test_fold = X_train[test_index] y_test_fold = y_train_5[test_index] clone_clf.fit(X_train_folds, y_train_folds) y_pred = clone_clf.predict(X_test_fold) n_correct = sum(y_pred == y_test_fold) print(n_correct / len(y_pred)) #Determine cross validation score - 3 folds cross_val_score(sgd_clf, X_train, y_train_5, cv=3, scoring="accuracy") #Prediction set selection from cross val y_train_pred = cross_val_predict(sgd_clf, X_train, y_train_5, cv=3) #Confusion matrix from prior variable set confusion_matrix(y_train_5, y_train_pred) #Performance metric - precision + recall score precision_score(y_train_5, y_train_pred) recall_score(y_train_5, y_train_pred) #We can combine the two into the F1 score - harmonic mean f1_score(y_train_5, y_train_pred) #Note that there is a way to get the optimal threshold: decision_function() #method, which returns a score for each instance, and then use any threshold #you want to make predictions based on those scores.

UTF-8

Python

false

2,815

py

2

MNIST.py

2

0.71865

0.694139

0

85

31.141176

77

pydi0415/git_zeroo

17,145,509,487,499

f69cf63b9458a5905c410d34f1cb31ddebafc104

0f0a2ae1c525a3f6ab4ceb9652e3a95abb42fe0d

/python/assignment/Basic pgms.py

1b566105fc64540b2ea620e9037fabaa6d2d7dd6

[]

no_license

https://github.com/pydi0415/git_zeroo

c47a21193f32651a29f10c5fec461bcc6f3868cb

0d50e29a257041619031a39d7abe252db59ea019

refs/heads/main

2023-03-14T13:02:06.166224

2021-02-26T14:26:55

342,595,855

0

null

print("prabhakar\nprasu") print("----------------------------") print("prabhakar\tprasu") print("----------------------------") #print("prabhakar"prabha"prasu" )(error) print('''Hi\n This is penchala\tprabhakr From Ap''') print("----------------------------") print("s@athya\"Techonlogy\"") print("----------------------------") print("Heloo 'Prasu' Iam sharing my \"python meterial\" Check once " "\nIn this\tyear i get a \"job\" ") print("----------------------------") print("Prabhakar@0415"+"123456789") print("----------------------------") print(20%3) print("----------------------------") print("10"+"20") print("----------------------------") print("prabhakar","prasu",'BestFriends','''From school standerd to Still know''') print("----------------------------") print("python""-""Django") print("----------------------------") print("\n","Employee","_","UnEmployee") print("----------------------------") #print("prabhakar"+3) print("3+3+""Prabahakar") print("----------------------------") #print("7"-2) print("----------------------------") print("Prabhakar\n\t\"Penchala") print("----------------------------") print("----------------------------") print("**\"prabha\"kar**") print("\n--python--") print("----------------------------") print("\t\tPrabhakar\tpydi") print("\t\t==========\t====") print("----------------------------") studentname='Prabhakar' print("welcome",studentname) print("----------------------------") #o1=int(input("Enter first number:")) #no2=int(input("Enter second number:")) #print("adition=",no1+no2) #print("sub=",no1-no2) #print("mul=",no1*no2) #print("div=",no1/no2) #print("mod=",no1%no2) #print("FlorDiv=",no1//no2) #print("Exponential=",no1**no2) #print("----------------------------") #x='prabha.415' #print(x) #print(type(x)) print("----------------------------") #Fname=input("Enter first name:") #Lname=input("Enter last name:") #print(Fname + Lname) print("----------------------------") #x=input("Enter no:") #print(x) #idno=int(input("Student IDNO:")) #name=input("Name:") #m1=int(input("marks1:")) #m2=int(input("marks2:")) #m3=int(input("marks3:")) #print(idno) #print(name) #print("Total marks=",m1+m2+m3) #print("Avgmarks=",m1+m2+m3/3) print("----------------------------") x=5 if x>0: print("+ve number") if x<0: print("-ve number") print("----------------------------")

UTF-8

Python

false

2,348

py

17

Basic pgms.py

16

0.456559

0.431005

0

77

29.480519

81

ritwikbera/GazeAtari

17,884,243,858,487

a4c31c80d6125de528aee80bd1ebdabcf6736155

4cbe3a5dfc11227ac85e77980e3f9eb0cc20aa13

/train.py

0d33bdb47f07239159259b6c23716ae48c8ec896

[]

no_license

https://github.com/ritwikbera/GazeAtari

42e36ab90b1b3fd9943fa5ad2e1b051731827666

7d9840474e91e41422dd551e20c752afe82edd10

refs/heads/master

2022-08-21T07:04:14.542815

2020-05-26T01:51:36

null

0

null

import torch from torch import nn from torch.optim import Adam, Rprop import torch.nn.functional as F from torch.utils.tensorboard import SummaryWriter import numpy as np import json import os from math import ceil from ignite.engine import Events, Engine from ignite.metrics import Loss, RunningAverage, Accuracy, MeanSquaredError from ignite.utils import setup_logger from ignite.handlers import ModelCheckpoint # from ignite.contrib.handlers.tqdm_logger import ProgressBar from tqdm import tqdm import models import utils from models import * from utils import * current_dir = os.getcwd() torch.manual_seed(0) np.random.seed(0) def run(config): train_loader = get_instance(utils, 'dataloader', config, 'train') val_loader = get_instance(utils, 'dataloader', config, 'val') model = get_instance(models, 'arch', config) model = init_model(model, train_loader) model, device = ModelPrepper(model, config).out loss_fn = get_instance(nn, 'loss_fn', config) trainable_params = filter(lambda p: p.requires_grad, model.parameters()) optimizer = get_instance(torch.optim, 'optimizer', config, trainable_params) writer = create_summary_writer(config, model, train_loader) batch_size = config['dataloader']['args']['batch_size'] if config['mode'] == 'eval' or config['resume']: model.load_state_dict(torch.load(config['ckpt_path'])) epoch_length = int(ceil(len(train_loader)/batch_size)) desc = "ITERATION - loss: {:.2f}" pbar = tqdm(initial=0, leave=False, total=epoch_length, desc=desc.format(0)) def process_batch(engine, batch): inputs, outputs = func(batch) model.train() model.zero_grad() optimizer.zero_grad() preds = model(inputs) loss = loss_fn(preds, outputs.to(device)) a = list(model.parameters())[0].clone() loss.backward() optimizer.step() # check if training is happening b = list(model.parameters())[0].clone() try: assert not torch.allclose(a.data, b.data), 'Model not updating anymore' except AssertionError: plot_grad_flow(model.named_parameters()) return loss.item() def predict_on_batch(engine, batch): inputs, outputs = func(batch) model.eval() with torch.no_grad(): y_pred = model(inputs) return inputs, y_pred, outputs.to(device) trainer = Engine(process_batch) trainer.logger = setup_logger("trainer") evaluator = Engine(predict_on_batch) evaluator.logger = setup_logger("evaluator") if config['task'] == 'actionpred': Accuracy(output_transform=lambda x: (x[1], x[2])).attach(evaluator, 'val_acc') if config['task'] == 'gazepred': MeanSquaredError(output_transform=lambda x: (x[1], x[2])).attach(evaluator, 'val_MSE') RunningAverage(output_transform=lambda x: x).attach(trainer, 'loss') training_saver = ModelCheckpoint(config['checkpoint_dir'], filename_prefix='checkpoint_'+config['task'], n_saved=1, atomic=True, save_as_state_dict=True, create_dir=True, require_empty=False) trainer.add_event_handler(Events.EPOCH_COMPLETED, training_saver, {'model': model}) @trainer.on(Events.ITERATION_COMPLETED) def tb_log(engine): pbar.desc = desc.format(engine.state.output) pbar.update(1) writer.add_scalar('training/avg_loss', engine.state.metrics['loss'] ,engine.state.iteration) @trainer.on(Events.EPOCH_COMPLETED) def print_trainer_logs(engine): pbar.refresh() avg_loss = engine.state.metrics['loss'] tqdm.write('Trainer Results - Epoch {} - Avg loss: {:.2f} \n'.format(engine.state.epoch, avg_loss)) viz_param(writer=writer, model=model, global_step=engine.state.epoch) pbar.n = pbar.last_print_n = 0 @evaluator.on(Events.EPOCH_COMPLETED) def print_result(engine): try: print('Evaluator Results - Accuracy {} \n'.format(engine.state.metrics['val_acc'])) except KeyError: print('Evaluator Results - MSE {} \n'.format(engine.state.metrics['val_MSE'])) @evaluator.on(Events.ITERATION_COMPLETED) def viz_outputs(engine): visualize_outputs(writer=writer, state=engine.state, task=config['task']) if config['mode'] == 'train': trainer.run(train_loader, max_epochs=config['epochs'], epoch_length=epoch_length) pbar.close() evaluator.run(val_loader, max_epochs=1, epoch_length=int(ceil(len(val_loader)/batch_size))) writer.flush() writer.close() if __name__ == "__main__": config = json.load(open('config.json')) run(config)

UTF-8

Python

false

4,902

py

21

train.py

18

0.631783

0.628519

0

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32.128378

107

landont3/GolfLeagueScoring

7,198,365,228,995

4437ae18a2721e62f6726a88cc3119e25e44f560

48075e439cb159a1eddc7a637b3e955a012ee214

/league/admin.py

5e1423f65df502d5cb49ed6bcad60ab69fb514c2

[]

no_license

https://github.com/landont3/GolfLeagueScoring

e503154ff84d907597393b86c1d4e4039ddfca9e

c71ac20b1a26c016db33003e87a8f4a8dc64f0f5

refs/heads/master

2021-03-22T01:11:36.267737

2018-03-08T12:21:26

122,187,660

0

null

from django.contrib import admin from .models import League, Division, Season, SeasonSettings, Course, Nine, Hole @admin.register(SeasonSettings) class SeasonSettingsAdmin(admin.ModelAdmin): list_display = ('season', 'handicap_method', 'max_score_to_par', 'max_handicap') list_editable = ('handicap_method', 'max_score_to_par', 'max_handicap') admin.site.register(League) admin.site.register(Division) admin.site.register(Season) admin.site.register(Course) admin.site.register(Nine) admin.site.register(Hole)

UTF-8

Python

false

523

py

31

admin.py

21

0.762906

0

17

29.764706

84

VR-Scott/practice_team_08

10,256,381,926,421

0bf8ca6bdc4474f497844ace2645eb0ba8a44097

511583a2223f86e5028839763cb867bbc9931ba7

/encryption.py

cc6984c73aaa934b9ec04d1d93ac30f921c4be32

[]

no_license

https://github.com/VR-Scott/practice_team_08

005384695bd5a84086fbbac651f5e216314951d7

4f36ba4cc767e3bf9a77579c1569be1034a4846c

refs/heads/master

2023-01-30T14:31:08.745287

2020-12-11T14:39:46

308,270,721

0

1

null

false

2020-11-16T07:18:31

2020-10-29T08:58:18

2020-11-13T08:30:26

2020-11-16T07:18:31

7,262

0

Python

false

import bcrypt def encrypt_password(password): """ Encrypt a password with a randomly generated salt then a hash. :param password: The password to encrypt in clear text. :return: The encrypted password as a unicode string. """ encoded_password = password.encode('utf8') cost_rounds = 4 random_salt = bcrypt.gensalt(cost_rounds) hashed_password = bcrypt.hashpw(encoded_password, random_salt).decode('utf8', 'strict') return hashed_password def check_password(password, password_hash): """ Check a password against its encrypted hash for a match. :param password: the password to check in clear text. (Unicode) :param password_hash: The encrypted hash to check against. (Unicode) :return: Whether the password and the hash match """ encoded_password = password.encode('utf8') encoded_password_hash = password_hash.encode('utf8') password_matches = bcrypt.checkpw(encoded_password, encoded_password_hash) return password_matches if __name__ == '__main__': test_password = 'doobeedoo' hashed_test_password = encrypt_password(test_password) print(f'hashed_password: {hashed_test_password}') password_matches_hash = check_password(test_password, hashed_test_password) print(f'password matches hash? {password_matches_hash}')

UTF-8

Python

false

1,322

py

19

encryption.py

12

0.711044

0.707262

0

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91

doublevcodes/pyhmrc

5,574,867,575,817

33cc9e74364e9c6a781dcccbae6ae8c1f822d1e7

7c5e543762f1a7c9ac134b7e0ce084724e8e113e

/pyhmrc/hello/__init__.py

1be72be2be386b6f8329c2ea5f26ad858205bd54

[]

no_license

https://github.com/doublevcodes/pyhmrc

5ee44ed968357b9db7ae4ce9fb91085651192a28

fdc5eff0d14332b3f718060fc33316952a0e411b

refs/heads/master

2023-04-02T22:34:30.769236

2021-04-09T21:35:17

356,403,147

0

null

from .hello import HelloClient

UTF-8

Python

false

30

py

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__init__.py

4

0.866667

0

1

30

TopologicLogic/Convusing

2,851,858,284,551

b9ac8f3a82186ee4c186b6918b5dc76215f9b016

63f21c66119a6b3a752a8dcd8377e0c512ec4cc2

/DataPrep.py

18c40cf929986974a66f9e97611e4490875bdd62

[]

no_license

https://github.com/TopologicLogic/Convusing

3cca2e52a4c141d00988b78bc09630501f544bfc

f8445ea81828f53dd91b9d1cccc0a28ac7f1dbf3

refs/heads/master

2022-07-17T04:31:11.199671

2022-05-29T03:35:11

254,484,222

0

null

# -*- coding: utf-8 -*- """ Created on Sat Mar 10 20:19:35 2018 @author: Dev """ import random import pandas as pan import numpy as np import os.path import csv import sys #import ctypes # An included library with Python install. from copy import deepcopy from stockstats import StockDataFrame as sdf from googlefinance.client import get_price_data #, get_prices_data, get_prices_time_data data_lookup = {} def find_intervals(projection_range, row_start, sdfdata, interval_min, interval_max): interval_index = [] #tshape = sdfdata.iloc[:,0:].values.shape #if row_start >= tshape[0]: return interval_index tdata = sdfdata['close_-' + str(projection_range+1) +'_r'].as_matrix() # print(str(tdata)) for i in range(row_start, len(tdata)): if tdata[i] >= interval_min and tdata[i] <= interval_max: interval_index.append(i) return interval_index def get_indicator_data_at_index(index, data_row_count, sdfdata, indicators, intervals, normalize=True): x_data = np.zeros((len(indicators) * len(intervals), data_row_count)) l = 0 if normalize: for m in range(0, len(indicators)): for n in range(0, len(intervals)): # A one dimensional array with the indicator/interval data tdata = sdfdata[indicators[m] + '_' + intervals[n]].as_matrix() dmax = sys.float_info.min # Check all of tdata for NaNs, Infinities, and get column max for t in range(0, len(tdata)): if not np.isfinite(tdata[t]): tdata[t] = 0 if tdata[t] > dmax: dmax = tdata[t] for t in range(0, len(tdata)): tdata[t] /= dmax q = 0 for t in range(index - data_row_count, index): x_data[l][q] = tdata[t] q += 1 l += 1 else: for m in range(0, len(indicators)): for n in range(0, len(intervals)): tdata = sdfdata[indicators[m] + '_' + intervals[n]].as_matrix() q = 0 for t in range(index - data_row_count, index): x_data[l][q] = tdata[t] if not np.isfinite(x_data[l][q]): x_data[l][q] = 0 q += 1 l += 1 return x_data def homogeneous_populate_training(n_classes, batch_count, data_column_count, data_row_count, projection_range, check_for_zeros=True, track_classes=True, verbose=True): global data_lookup indicators = ['rsi', 'atr', 'wr', 'vr'] intervals = ['2', '5', '10', '15', '20', '30', '60'] x_train = np.zeros((batch_count, data_column_count, data_row_count)) y_train = np.zeros((batch_count, n_classes), dtype=int) symbols = [] #https://www.nasdaq.com/screening/companies-by-industry.aspx?exchange=NASDAQ&render=download with open('NASD.csv', newline='') as csvfile: r = csv.DictReader(csvfile) for row in r: symbols.append(row['Symbol']) class_max = [-50, -20, -15, -10, -5, -4, -3, -2, -1, -0.1, 0, 1, 2, 3, 4, 5, 10, 15, 20, 50, 10000] class_min = [-10000, -50, -20, -15, -10, -5, -4, -3, -2, -1, -0.1, 0, 1, 2, 3, 4, 5, 10, 15, 20, 50 ] avg_class_count = np.floor((batch_count) / n_classes) class_count = np.zeros(n_classes, dtype=int) class_count.fill(avg_class_count) diff = batch_count - (avg_class_count * n_classes) if diff > 0: class_count[10] += diff if not os.path.exists('StockData/'): os.makedirs('StockData/') batch_i = 0 for z in range(0, n_classes): skips = [] # Skiped due to data errors nics = [] # Not in class if track_classes: if os.path.isfile("skips.csv"): with open('skips.csv', newline='\n') as csvfile: r = csv.DictReader(csvfile) for row in r: skips.append(row['Symbols']) else: with open("skips.csv", "w") as text_file: text_file.write("""Symbols""" + "\n") if os.path.isfile("nic-" + str(z) + ".csv"): with open("nic-" + str(z) + ".csv", newline='\n') as csvfile: r = csv.DictReader(csvfile) for row in r: nics.append(row['Symbols']) else: with open("nic-" + str(z) + ".csv", "w") as text_file: text_file.write("""Symbols""" + "\n") if verbose: print("\nClass #" + str(z+1) + " of " + str(n_classes) + ", Total skips: " + str(len(skips) + len(nics)) + "\n") elif verbose: print("\nClass #" + str(z) + " of " + str(n_classes)) symbols_used = [] k = 0 while k < class_count[z]: tclass = z tsymbol = symbols[np.random.randint(0, len(symbols))] # Went through all the symbols and cound't find enough examples, # so fill up more default values. if len(symbols_used) >= len(symbols): tclass = 10 # Check for stocks to skip if track_classes: if tsymbol in skips: continue if tsymbol in nics: continue if tsymbol in symbols_used: continue symbols_used.append(tsymbol) tshape = object() if tsymbol in data_lookup: if verbose: print("Loading["+ str(class_min[tclass]) + "%:" + str(class_max[tclass]) + "%, " + "#" + str(k) + "]: " + tsymbol) df = data_lookup[tsymbol] elif os.path.isfile("StockData/" + tsymbol + ".csv"): if verbose: print("Loading["+ str(class_min[tclass]) + "%:" + str(class_max[tclass]) + "%, " + "#" + str(k) + "]: " + tsymbol) data_lookup[tsymbol] = pan.read_csv("StockData/" + tsymbol + ".csv", sep=',', header=0, index_col=0) df = data_lookup[tsymbol] else: if verbose: print("Downloading["+ str(class_min[tclass]) + "%:" + str(class_max[tclass]) + "%, " + "#" + str(k) + "]: " + tsymbol) param = { 'q': tsymbol, # Stock symbol (ex: "AAPL") 'i': "86400", # Interval size in seconds ("86400" = 1 day intervals) 'x': "NASD", # Stock exchange symbol on which stock is traded (ex: "NASD") 'p': "5Y" # Period (Ex: "1Y" = 1 year) } # get price data (return pandas dataframe) df = get_price_data(param) df.to_csv("StockData/" + tsymbol + ".csv") data_lookup[tsymbol] = deepcopy(df) tshape = df.iloc[:,0:].values.shape if tshape[0] <= data_row_count: if verbose: print("Data error: " + tsymbol + ", continuing to next symbol...") if track_classes: with open("skips.csv", "a") as text_file: text_file.write(tsymbol + "\n") continue if tshape[0] < 400: if verbose: print("Not enough data for: " + tsymbol + ", continuing to next symbol...") if track_classes: with open("skips.csv", "a") as text_file: text_file.write(tsymbol + "\n") continue # Check for zeros if check_for_zeros: zero_flag = False for row in range(0, tshape[0]): for column in range(0, tshape[1]): v = df.iloc[:,column:].values[row][0] if v <= 0: zero_flag = True break if zero_flag: break if zero_flag: if verbose: print("Zeros in: " + tsymbol + ", continuing to next symbol...") if track_classes: with open("skips.csv", "a") as text_file: text_file.write(tsymbol + "\n") continue sdfdata = sdf.retype(df) indicies = find_intervals(projection_range, data_row_count + projection_range, sdfdata, class_min[tclass], class_max[tclass]) if len(indicies) > 0: random.shuffle(indicies) for i in range(0, len(indicies)): if k < class_count[z] and batch_i < batch_count: # Add data to the batch array x_train[batch_i] = get_indicator_data_at_index(indicies[i]-projection_range, data_row_count, sdfdata, indicators, intervals) y_train[batch_i][tclass] = 1 k += 1 batch_i += 1 else: break elif track_classes: with open("nic-" + str(z) + ".csv", "a") as text_file: text_file.write(tsymbol + "\n") del sdfdata del df del symbols_used del skips del nics return x_train, y_train def homogeneous_populate_training2(n_classes, batch_count, data_column_count, data_row_count, projection_range, check_for_zeros=True, track_classes=True, verbose=True): global data_lookup indicators = ['rsi', 'atr', 'wr', 'vr'] intervals = ['2', '5', '10', '15', '20', '30', '60'] x_train = np.zeros((batch_count, data_column_count, data_row_count)) y_train = np.zeros((batch_count, n_classes), dtype=int) symbols = [] #https://www.nasdaq.com/screening/companies-by-industry.aspx?exchange=NASDAQ&render=download with open('NASD.csv', newline='') as csvfile: r = csv.DictReader(csvfile) for row in r: symbols.append(row['Symbol']) class_max = [-50, -20, -15, -10, -5, -4, -3, -2, -1, -0.1, 0, 1, 2, 3, 4, 5, 10, 15, 20, 50, 10000] class_min = [-10000, -50, -20, -15, -10, -5, -4, -3, -2, -1, -0.1, 0, 1, 2, 3, 4, 5, 10, 15, 20, 50 ] avg_class_count = np.floor((batch_count) / n_classes) class_count = np.zeros(n_classes, dtype=int) class_count.fill(avg_class_count) # If the data is uneven, put it in the center. diff = batch_count - (avg_class_count * n_classes) if diff > 0: class_count[10] += diff if not os.path.exists('StockData/'): os.makedirs('StockData/') batch_i = 0 for z in range(0, n_classes): skips = [] # Skiped due to data errors nics = [] # Not in class if track_classes: if os.path.isfile("skips.csv"): with open('skips.csv', newline='\n') as csvfile: r = csv.DictReader(csvfile) for row in r: skips.append(row['Symbols']) else: with open("skips.csv", "w") as text_file: text_file.write("""Symbols""" + "\n") if os.path.isfile("nic-" + str(z) + ".csv"): with open("nic-" + str(z) + ".csv", newline='\n') as csvfile: r = csv.DictReader(csvfile) for row in r: nics.append(row['Symbols']) else: with open("nic-" + str(z) + ".csv", "w") as text_file: text_file.write("""Symbols""" + "\n") if verbose: print("\nClass #" + str(z+1) + " of " + str(n_classes) + ", Total skips: " + str(len(skips) + len(nics)) + "\n") elif verbose: print("\nClass #" + str(z) + " of " + str(n_classes)) random.shuffle(symbols) for k in range(0, symbols): tclass = z tsymbol = symbols[k] # Check for stocks to skip if track_classes: if tsymbol in skips: continue if tsymbol in nics: continue if os.path.isfile("StockData/" + tsymbol + ".csv"): data_lookup[tsymbol] = pan.read_csv("StockData/" + tsymbol + ".csv", sep=',', header=0, index_col=0) if tsymbol in data_lookup: if verbose: print("Loading["+ str(class_min[tclass]) + "%:" + str(class_max[tclass]) + "%, " + "#" + str(k) + "]: " + tsymbol) df = data_lookup[tsymbol] else: if verbose: print("Downloading["+ str(class_min[tclass]) + "%:" + str(class_max[tclass]) + "%, " + "#" + str(k) + "]: " + tsymbol) param = { 'q': tsymbol, # Stock symbol (ex: "AAPL") 'i': "86400", # Interval size in seconds ("86400" = 1 day intervals) 'x': "NASD", # Stock exchange symbol on which stock is traded (ex: "NASD") 'p': "5Y" # Period (Ex: "1Y" = 1 year) } # get price data (return pandas dataframe) df = get_price_data(param) df.to_csv("StockData/" + tsymbol + ".csv") data_lookup[tsymbol] = deepcopy(df) tshape = df.iloc[:,0:].values.shape if tshape[0] <= data_row_count: if verbose: print("Data error: " + tsymbol + ", continuing to next symbol...") if track_classes: with open("skips.csv", "a") as text_file: text_file.write(tsymbol + "\n") continue if tshape[0] < 400: if verbose: print("Not enough data for: " + tsymbol + ", continuing to next symbol...") if track_classes: with open("skips.csv", "a") as text_file: text_file.write(tsymbol + "\n") continue # Check for zeros if check_for_zeros: zero_flag = False for row in range(0, tshape[0]): for column in range(0, tshape[1]): v = df.iloc[:,column:].values[row][0] if v <= 0: zero_flag = True break if zero_flag: break if zero_flag: if verbose: print("Zeros in: " + tsymbol + ", continuing to next symbol...") if track_classes: with open("skips.csv", "a") as text_file: text_file.write(tsymbol + "\n") continue sdfdata = sdf.retype(df) indicies = find_intervals(projection_range, data_row_count + projection_range, sdfdata, class_min[tclass], class_max[tclass]) if len(indicies) > 0: random.shuffle(indicies) for i in range(0, len(indicies)): if k < class_count[z] and batch_i < batch_count: # Add data to the batch array x_train[batch_i] = get_indicator_data_at_index(indicies[i]-projection_range, data_row_count, sdfdata, indicators, intervals) y_train[batch_i][tclass] = 1 k += 1 batch_i += 1 else: break elif track_classes: with open("nic-" + str(z) + ".csv", "a") as text_file: text_file.write(tsymbol + "\n") del sdfdata del df del skips del nics return x_train, y_train def random_normal_populate_training(n_classes, batch_count, data_column_count, data_row_count, projection_range, mu, sigma, check_for_zeros=True, track_classes=True, verbose=True): global data_lookup indicators = ['rsi', 'atr', 'wr', 'vr'] intervals = ['2', '5', '10', '15', '20', '30', '60'] x_train = np.zeros((batch_count, data_column_count, data_row_count)) y_train = np.zeros((batch_count, n_classes), dtype=int) symbols = [] #https://www.nasdaq.com/screening/companies-by-industry.aspx?exchange=NASDAQ&render=download with open('NASD.csv', newline='') as csvfile: r = csv.DictReader(csvfile) for row in r: symbols.append(row['Symbol']) class_max = [-50, -20, -15, -10, -5, -4, -3, -2, -1, -0.1, 0, 1, 2, 3, 4, 5, 10, 15, 20, 50, 10000] class_min = [-10000, -50, -20, -15, -10, -5, -4, -3, -2, -1, -0.1, 0, 1, 2, 3, 4, 5, 10, 15, 20, 50 ] if not os.path.exists('StockData/'): os.makedirs('StockData/') skips = [] # Skiped due to data errors nics = {} if track_classes: if os.path.isfile("skips.csv"): with open('skips.csv', newline='\n') as csvfile: r = csv.DictReader(csvfile) for row in r: skips.append(row['Symbols']) else: with open("skips.csv", "w") as text_file: text_file.write("""Symbols""" + "\n") for z in range(0, n_classes): nics[z] = [] if os.path.isfile("nic-" + str(z) + ".csv"): with open("nic-" + str(z) + ".csv", newline='\n') as csvfile: r = csv.DictReader(csvfile) for row in r: nics[z].append(row['Symbols']) else: with open("nic-" + str(z) + ".csv", "w") as text_file: text_file.write("""Symbols""" + "\n") batch_i = 0 while batch_i < batch_count: tsymbol = symbols[np.random.randint(0, len(symbols))] tclass = int(np.random.normal(mu, sigma)) if tclass >= n_classes: tclass = n_classes-1 elif tclass < 0: tclass = 0 # Check for stocks to skip if track_classes: if tsymbol in skips: continue if tsymbol in nics[tclass]: continue if tsymbol in data_lookup: if verbose: print("Loading: " + tsymbol) df = data_lookup[tsymbol] elif os.path.isfile("StockData/" + tsymbol + ".csv"): if verbose: print("Loading: " + tsymbol) data_lookup[tsymbol] = pan.read_csv("StockData/" + tsymbol + ".csv", sep=',', header=0, index_col=0) df = data_lookup[tsymbol] else: if verbose: print("Downloading: " + tsymbol) param = { 'q': tsymbol, # Stock symbol (ex: "AAPL") 'i': "86400", # Interval size in seconds ("86400" = 1 day intervals) 'x': "NASD", # Stock exchange symbol on which stock is traded (ex: "NASD") 'p': "5Y" # Period (Ex: "1Y" = 1 year) } # get price data (return pandas dataframe) df = get_price_data(param) df.to_csv("StockData/" + tsymbol + ".csv") data_lookup[tsymbol] = deepcopy(df) tshape = df.iloc[:,0:].values.shape if tshape[0] <= data_row_count: if verbose: print("Data error: " + tsymbol + ", continuing to next symbol...") if track_classes: with open("skips.csv", "a") as text_file: text_file.write(tsymbol + "\n") continue if tshape[0] < 400: if verbose: print("Not enough data for: " + tsymbol + ", continuing to next symbol...") if track_classes: with open("skips.csv", "a") as text_file: text_file.write(tsymbol + "\n") continue # Check for zeros if check_for_zeros: zero_flag = False for row in range(0, tshape[0]): for column in range(0, tshape[1]): v = df.iloc[:,column:].values[row][0] if v <= 0: zero_flag = True break if zero_flag: break if zero_flag: if verbose: print("Zeros in: " + tsymbol + ", continuing to next symbol...") if track_classes: with open("skips.csv", "a") as text_file: text_file.write(tsymbol + "\n") continue sdfdata = sdf.retype(df) indicies = find_intervals(projection_range, data_row_count + projection_range, sdfdata, class_min[tclass], class_max[tclass]) if len(indicies) > 0: i = np.random.randint(0, len(indicies)) if batch_i < batch_count: # Add data to the batch array x_train[batch_i] = get_indicator_data_at_index(indicies[i]-projection_range, data_row_count, sdfdata, indicators, intervals) y_train[batch_i][tclass] = 1 batch_i += 1 else: break elif track_classes: with open("nic-" + str(tclass) + ".csv", "a") as text_file: text_file.write(tsymbol + "\n") del sdfdata del df del skips del nics return x_train, y_train

UTF-8

Python

false

24,109

py

28

DataPrep.py

7

0.427517

0.411216

0

596

38.454698

110

bettersleepearly/Programming-Beginner-2

14,766,097,597,640

5592b36b79250beb3b4b2372cdbb1467f1f42ac7

34200997a02dc3f6f733c297b48d47ad9566e3d8

/Shoppinproj.py

1ecdfaf10f80d3b716c38fb1ae3c97f46ec111c3

[]

no_license

https://github.com/bettersleepearly/Programming-Beginner-2

4396844be3de449017b132fa67042977d2364e19

0ef1c4b224716f51a4f47d40f5b5d08bc588d877

refs/heads/master

2022-10-14T15:30:26.608237

2020-06-09T15:15:14

null

0

null

currency = 'USD' price = {'CB1':139, 'CB2':149, 'CB3':139, 'CB4':139, 'CB5':169, 'CB6':139, 'CB7':139, 'CB8':139, 'CB9':139, 'CB10':149, 'CB11':134, 'CB12':129, 'LB1':174, 'LB2':174, 'LB3':174, 'LB4':199, 'LB5':199, 'LB6':199, 'LB7':189, 'LB8':189, 'LB9':179, 'LB10':244, 'LB11':244, 'LB12':244} cb1 = 'Dinghy Tiger:' cb2 = 'Dinghy FG Watercolor:' cb3 = 'Dinghy Crown Peak:' cb4 = 'Dinghy BK:' cb5 = 'Gordito Pantera:' cb6 = 'Ditchlife:' cb7 = 'Wrecktangle Lighthouse:' cb8 = 'Tugboat Captain:' cb9 = 'Tugboat Chill Cat:' cb10 = 'Tugboat Midnight Snek:' cb11 = 'Dinghy Arctic Fox:' cb12 = 'Mighty Mite:' lb1 = 'Super Chief Watercolor:' lb2 = 'Ripper Humanoid:' lb3 = 'Ripper Watercolor:' lb4 = 'Drop Carve 40 Fox:' lb5 = 'Drop Cat 33 Illuminacion:' lb6 = 'Drop Cat 38 Seeker:' lb7 = 'Pinner Night Moves:' lb8 = 'Totem Blaze:' lb9 = 'Chief Eyes:' lb10 = 'Switchblade 38 Tropic:' lb11 = 'Nine Two Five Horror:' lb12 = 'Hollowtech Switchblade 36 Lizard:' print("\n _____________") print("| |") print("| L A N D |") print("| Y A T C H Z |") print("|_____________|") print('\nWE EXPLORE THE WORLD ON SKATEBOARDS \nWe make vehicles for seeking out adventure, finding joy in self-expression and improving our interactions with the world around us.') print('\nInterested in our products? Wanna dive in?') question = input('\nIf yes, type Y. \nType N to exit.') if question == "N": print('___________________________________________________________________________________________________________________________________________________') print('\nWell then... Fuck off mate.') if question == "Y": print('___________________________________________________________________________________________________________________________________________________') print("\nBefore finding you a perfect skateboard, \nLet's create a account") username = input('\nMay I have your username:') print("\nOkay" + " " + username + ",") print("May I have your age? (since our branding and products are not suited for ages under 18):") age = int(input()) if age < 18: print('___________________________________________________________________________________________________________________________________________________') print("\nI am sorry that you can not countinue" + " " + username) print("\nUnderage usage of our products and contents is illegal...\nSo fuck off kid!") if age >= 18: print('___________________________________________________________________________________________________________________________________________________') print("\nRequirement reached,\nYour access is now granted") print("\nEnjoy shopping skateboards!") print("\nWe own a large varieties of skateboards and longboards with different styles and uses.") print("\nOur 2 main lines are recommended the most,") boards = "\n(1) Cruiser boards\n(2) Longboards\nPick one (type a number):" print(boards) boardpick = str(input()) if boardpick == "1": print('___________________________________________________________________________________________________________________________________________________') print("\nThe most fun and capable boards in our line-up, these boards are the best bang for your buck available today.") print('Whether it’s your first board or your tenth, there’s always room in your quiver for a good cruiser and you’ll quickly find it becoming your go-to in all sorts of situations.') print('___________________________________________________________________________________________________________________________________________________') print('\n1.'+cb1+ " "+ str(price.get('CB1')) +" "+ currency+'\n(No Picture LMAO)') print('\n2.'+cb2+ " "+ str(price.get('CB2')) +" "+ currency+'\n(No Picture LMAO)') print('\n3.'+cb3+ " "+ str(price.get('CB3')) +" "+ currency+'\n(No Picture LMAO)') print('\n4.'+cb4+ " "+ str(price.get('CB4')) +" "+ currency+'\n(No Picture LMAO)') print('\n5.'+cb5+ " "+ str(price.get('CB5')) +" "+ currency+'\n(No Picture LMAO)') print('\n6.'+cb6+ " "+ str(price.get('CB6')) +" "+ currency+'\n(No Picture LMAO)') print('\n7.'+cb7+ " "+ str(price.get('CB7')) +" "+ currency+'\n(No Picture LMAO)') print('\n8.'+cb8+ " "+ str(price.get('CB8')) +" "+ currency+'\n(No Picture LMAO)') print('\n9.'+cb9+ " "+ str(price.get('CB9')) +" "+ currency+'\n(No Picture LMAO)') print('\n10.'+cb10+ " "+ str(price.get('CB10')) +" "+ currency+'\n(No Picture LMAO)') print('\n11.'+cb11+ " "+ str(price.get('CB11')) +" "+ currency+'\n(No Picture LMAO)') print('\n12.'+cb12+ " "+ str(price.get('CB12')) +" "+ currency+'\n(No Picture LMAO)') print('\nSo...Pick one (by typing "CB" + the number of the board):') action = str(input('To return to the menu,\nType "menu"\nType "mycart" to go to your cart and further check-out there.')) print(action) print('___________________________________________________________________________________________________________________________________________________') if boardpick == "2": print('___________________________________________________________________________________________________________________________________________________') print('Our Longboards are designed to get you out exploring your environment, no matter what kind of terrain you have surrounding you.\nThe boards in this category come in two deck styles; Top mounted or Drop-through.') print('\nTop mount boards give you tons of leverage over your trucks, giving you a deeper carving, surfy feel and a lively ride underfoot.') print('Drop-through boards are lower to the ground, making them driftier, more stable and blurring the lines between longboarding and freeriding.') print('\n1.'+lb1+ " "+ str(price.get('LB1')) +" "+ currency+'\n(No Picture LMAO)') print('\n2.'+lb2+ " "+ str(price.get('LB2')) +" "+ currency+'\n(No Picture LMAO)') print('\n3.'+lb3+ " "+ str(price.get('LB3')) +" "+ currency+'\n(No Picture LMAO)') print('\n4.'+lb4+ " "+ str(price.get('LB4')) +" "+ currency+'\n(No Picture LMAO)') print('\n5.'+lb5+ " "+ str(price.get('LB5')) +" "+ currency+'\n(No Picture LMAO)') print('\n6.'+lb6+ " "+ str(price.get('LB6')) +" "+ currency+'\n(No Picture LMAO)') print('\n7.'+lb7+ " "+ str(price.get('LB7')) +" "+ currency+'\n(No Picture LMAO)') print('\n8.'+lb8+ " "+ str(price.get('LB8')) +" "+ currency+'\n(No Picture LMAO)') print('\n9.'+lb9+ " "+ str(price.get('LB9')) +" "+ currency+'\n(No Picture LMAO)') print('\n10.'+lb10+ " "+ str(price.get('LB10')) +" "+ currency+'\n(No Picture LMAO)') print('\n11.'+lb11+ " "+ str(price.get('LB11')) +" "+ currency+'\n(No Picture LMAO)') print('\n12.'+lb12+ " "+ str(price.get('LB12')) +" "+ currency+'\n(No Picture LMAO)') print('\nPick one (by typing "LB" + the number of the board):') action = str(input('To return to the menu,\nType "menu"\nType "mycart" to go to your cart and further check-out there.')) print(action) print('___________________________________________________________________________________________________________________________________________________') instore = True while action == "menu": instore = True print("O U R B O A R D S") print(boards) boardpick print('___________________________________________________________________________________________________________________________________________________') #if action == "mycart": #print(AHHA) if action != "menu": cart = [int(price.get(action))] visualcart = ("Your Cart:" + " " + str(cart) +" "+ currency) print(visualcart) print('___________________________________________________________________________________________________________________________________________________') instore = True while action: instore = True action = str(input('Anymore sellection? my friend :)\nType here:')) print(visualcart)

UTF-8

Python

false

8,680

py

3

Shoppinproj.py

2

0.450542

0.422527

0

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231

junk13/fiercecroissant

4,939,212,400,068

b87b759aed94b2313d3bd88bf3d2e071301fb827

9a18fa277118715e33c68763a98f40b3df0a2448

/fiercecroissant.py

04d64756dc190e3efc7fd7a3fa2627ece451df34

[]

no_license

https://github.com/junk13/fiercecroissant

64bbe6831143978ccb756e4c93d812bcc1711798

26b88dd6f3068f40cc74119611b30a90542ce880

refs/heads/master

2020-04-08T16:21:16.296844

2018-11-08T20:42:57

null

0

null

#!/usr/bin/python3 import requests, json, time, sys, os, re, configparser, base64 from pymongo import MongoClient from requests.adapters import HTTPAdapter from requests.packages.urllib3.util.retry import Retry client = MongoClient('localhost:27017') db = client.fc coll_pastemetadata = client.fc.pastemetadata paste_data = "" save_path = os.getcwd() + '/pastes/' #Where keyword matching pastes get saved save_path_base64 = save_path + '/base64pastes/' save_path_hex = save_path + '/hexpastes/' save_path_binary = save_path + '/binarypastes/' save_path_php = save_path + '/phppastes/' save_path_img = save_path + '/imgpastes/' save_path_ascii = save_path + '/asciipastes/' save_path_ps = save_path + '/pspastes/' # Config file for token or key interactions. config = configparser.ConfigParser() config.read('config.ini') if not config.has_section('main'): print("\nPlease ensure that your 'config.ini' exists and sets the appropriate values.\n") exit(1) hip_token = config.get('main','hip_token') hip_room = config.get('main', 'hip_room') def scrapebin(): def requests_retry_session(retries=10, backoff_factor=0.3, status_forcelist=(500, 502, 504), session=None, params=None): session = session or requests.Session() retry = Retry(total=retries, read=retries, connect=retries, backoff_factor=backoff_factor, status_forcelist=status_forcelist) adapter = HTTPAdapter(max_retries=retry) session.mount('https://', adapter) return session def save_paste(path, data): with open(path, 'w', encoding='utf-8') as file: file.write(data) return file.closed def save_metadata(paste, encodingtype): pastemetadata_dict = {'date': [], 'key': [], 'size': [], 'expire': [], 'syntax': [], 'user':[], 'encodingtype':[]} pastemetadata_dict.update({'date':paste['date'], 'key':paste['key'], 'size':paste['size'], 'expire':paste['expire'], 'syntax':paste['syntax'], 'user':paste['user'], 'encodingtype':encodingtype}) return pastemetadata_dict def hipchatpost(): #Alerts a HipChat room about a new paste. headers = {'Content-Type': 'application/json'} card = { "style": "link", "url": paste_url, "id": "fee4d9a3-685d-4cbd-abaa-c8850d9b1960", "title": "Pastebin Hit", "description": { "format": "html", "value": "<b>New Paste Seen:</b>" + paste_url + " Encoded as:" + encodingtype }, "icon": { "url": "https://pastebin.com/favicon.ico" }, "date": 1443057955792 } data_json = {'message': '<b>New Paste<b>', 'card': card, 'message_format': 'html'} params = {'auth_token': hip_token} try: r = requests.post('https://api.hipchat.com/v2/room/' + hip_room + '/notification', data=json.dumps(data_json),headers=headers, params=params) except: pass while True: hits = 0 r = requests_retry_session().get('https://scrape.pastebin.com/api_scraping.php', params={'limit': 100}) recent_items = None try: recent_items = r.json() except json.decoder.JSONDecodeError as e: print(('Exception raised decoding JSON: {}').format(e)) continue for i, paste in enumerate(recent_items): pb_raw_url = 'https://pastebin.com/raw/' + paste['key'] paste_data = requests.get(pb_raw_url).text paste_lang = paste['syntax'] paste_size = paste['size'] paste_url = paste['full_url'] stringmatch = re.search(r'(A){20}', paste_data) #Searching for 20 'A's in a row. stringmatch_76 = re.search(r'(A){76}', paste_data) #Searching for 76 'A's in a row. nonwordmatch = re.search(r'\w{200,}', paste_data) #Searching for 200 characters in a row to get non-words. base64match = re.search(r'\A(TV(oA|pB|pQ|qQ|qA|ro|pA))', paste_data) #Searches the start of the paste for Base64 encoding structure for an MZ executable. base64reversematch = re.search(r'((Ao|Bp|Qp|Qq|Aq|or|Ap)VT)\Z', paste_data) #Searches the end of the paste for reversed Base64 encoding structure for an MZ executable. binarymatch = re.search(r'(0|1){200,}', paste_data) #Searches for 200 0's or 1's in a row. hexmatch = re.search(r'(\\x\w\w){100,}', paste_data) #Regex for hex formatted as "\\xDC", "\\x02", "\\xC4" hexmatch2 = re.search(r'[2-9A-F]{200,}', paste_data) #Regex for Hexadecimal encoding. hexmatch3 = re.search(r'([0-9A-F ][0-9A-F ][0-9A-F ][0-9A-F ][0-9A-F ]){150,}', paste_data) #Regex for hex formatted as "4D ", "5A ", "00 " in groups of at least 150. phpmatch = re.search(r'\A(<\?php)', paste_data) #Searches the start of a paste for php structure. imgmatch = re.search(r'\A(data:image)', paste_data) #Searches the start of a paste for data:image structure. asciimatch = re.search(r'\A(77 90 144 0 3 0 0 0)', paste_data) #Searches the start of a paste for '77 90 144 0 3 0 0 0' to filter ASCII. powershellmatch = re.search(r'powershell', paste_data) if ((((nonwordmatch or stringmatch) or (stringmatch_76 and (base64match or base64reversematch)) or hexmatch3) and int(paste_size) > 40000) or (powershellmatch and int(paste_size) < 10000)) and paste_lang == "text" and coll_pastemetadata.find_one({'key':paste['key']}) is None: if (binarymatch and paste_data.isnumeric()): filename = save_path_binary + paste['key'] encodingtype = 'binary' save_paste(filename, paste_data) metadata = save_metadata(paste, encodingtype) coll_pastemetadata.insert_one(metadata) hipchatpost() elif (base64match or base64reversematch): filename = save_path_base64 + paste['key'] encodingtype = 'base64' save_paste(filename, paste_data) metadata = save_metadata(paste, encodingtype) coll_pastemetadata.insert_one(metadata) hipchatpost() elif asciimatch: filename = save_path_ascii + paste['key'] encodingtype = "ASCII" save_paste(filename, paste_data) metadata = save_metadata(paste, encodingtype) coll_pastemetadata.insert_one(metadata) hipchatpost() elif (hexmatch or hexmatch2 or hexmatch3): filename = save_path_hex + paste['key'] encodingtype = 'hexadecimal' save_paste(filename, paste_data) metadata = save_metadata(paste, encodingtype) coll_pastemetadata.insert_one(metadata) hipchatpost() elif phpmatch: filename = save_path_php + paste['key'] encodingtype = 'php' save_paste(filename, paste_data) metadata = save_metadata(paste, encodingtype) coll_pastemetadata.insert_one(metadata) hipchatpost() elif imgmatch: filename = save_path_img + paste['key'] encodingtype = 'img' save_paste(filename, paste_data) metadata = save_metadata(paste, encodingtype) coll_pastemetadata.insert_one(metadata) hipchatpost() elif powershellmatch: filename = save_path_ps + paste['key'] encodingtype = 'powershell' save_paste(filename, paste_data) metadata = save_metadata(paste, encodingtype) coll_pastemetadata.insert_one(metadata) hipchatpost() else: filename = save_path + paste['key'] encodingtype = 'other' save_paste(filename, paste_data) metadata = save_metadata(paste, encodingtype) coll_pastemetadata.insert_one(metadata) hipchatpost() time.sleep(60) if __name__ == "__main__": while True: scrapebin()

UTF-8

Python

false

8,511

py

3

fiercecroissant.py

1

0.569968

0.548584

0.00047

162

51.537037

288

fprimex/lad

4,355,096,853,786

1d394c3a901e45ace142d60e8ab01314f1299677

a265442582d35030a22a207930bc849c5bd73c9e

/NotebookPage/VarsPage.py

92c8f7f5b0d28430bf44c6fdcb8e57c3c9ecaef4

[ "Apache-2.0" ]

permissive

https://github.com/fprimex/lad

48ebff8f83a82b7ec888c26234466c7f8026ac95

493e998eae351252cf78736b803ddc88de6abead

refs/heads/main

2023-06-09T01:22:45.487011

2018-08-26T04:22:35

146,149,601

0

null

import wx import Globals from ListEditorCtrl import ListEditorCtrl class VarsPage(wx.Panel): def __init__(self, parent, id=-1): wx.Panel.__init__(self, parent, -1) cols = [u"var", u"val / exp"] listdata = {} i = 0 for var in Globals.G.vars.keys(): listdata[i] = (var, Globals.G.var_exps[var]) i += 1 self.vars_ctrl = ExpListCtrl(self, -1, cols, listdata, style=wx.LC_REPORT | wx.BORDER_NONE) page_sizer = wx.BoxSizer(wx.VERTICAL) page_sizer.Add(self.vars_ctrl, 1, wx.EXPAND, 0) self.SetSizer(page_sizer) Globals.canvas.on_node_create_funcs.append(self.vars_ctrl.RefreshList) Globals.canvas.on_edge_create_funcs.append(self.vars_ctrl.RefreshList) Globals.canvas.on_node_delete_funcs.append(self.vars_ctrl.RefreshList) Globals.canvas.on_edge_delete_funcs.append(self.vars_ctrl.RefreshList) Globals.canvas.on_drag_end_funcs.append(self.vars_ctrl.RefreshList) def Reinit(self): listdata = {} i = 0 for var in Globals.G.vars.keys(): listdata[i] = (var, Globals.G.var_exps[var]) i += 1 self.vars_ctrl.listctrldata = listdata self.vars_ctrl.RefreshList() class ExpListCtrl(ListEditorCtrl): def __init__(self, parent, ID, headings, listdata, pos=wx.DefaultPosition, size=wx.DefaultSize, style=0): ListEditorCtrl.__init__(self, parent, ID, headings, listdata, pos, size, style) def GetRowValues(self, row): G = Globals.G var = self.listctrldata[row][0] exp = self.listctrldata[row][1] try: value = eval(exp) except: value = u"ERROR" Globals.G.var_exps[var] = exp Globals.G.vars[var] = value return (var, repr(value)) def GetEditValue(self, row, col): if col == 1: return self.listctrldata[row][1] else: return self.GetItem(row, col).GetText() def SetValue(self, row, col, text): # save exp text back into the expression dict if col == 0: del Globals.G.vars[self.listctrldata[row][0]] del Globals.G.var_exps[self.listctrldata[row][0]] self.listctrldata[row] = (text, self.listctrldata[row][1]) else: self.listctrldata[row] = (self.listctrldata[row][0], text) def PreDelete(self, row): var = self.GetItem(row, 0).GetText() del Globals.G.vars[var] del Globals.G.var_exps[var] def PostInsert(self, row): var = self.listctrldata[row][0] Globals.G.vars[var] = None Globals.G.var_exps[var] = None

UTF-8

Python

false

2,717

py

17

VarsPage.py

15

0.589253

0.581524

0

76

34.75

99

michealbradymahoney/CP1404-2019SP2

11,982,958,756,874

9873ffb1c7851050c46805bfef2b2a308b08c0da

13311af3281150ffbdc927ffe7e6b547a1bb0899

/Practicals/prac_02/password_checker.py

4376c0efbaf9488b272f10db62e68dbc7bdcbc12

[]

no_license

https://github.com/michealbradymahoney/CP1404-2019SP2

263db4593d8bd5a137e9ba13a0330c8cb566f82a

02a7c985e0eb4e0d76add18f7541eaee7eeba327

refs/heads/master

2020-06-30T08:42:39.520236

2019-08-31T01:55:13

200,781,949

0

null

false

2019-10-08T07:25:35

2019-08-06T05:22:40

2019-08-31T01:55:17

2019-10-08T07:22:43

2,446

0

2

Python

false

""" CP1404/CP5632 - Practical Password checker "skeleton" code to help you get started """ # Write a program that asks for and validates a person's password. # The program is not for comparing a password to a known password, but validating the 'strength' of a new password, # like you see on websites: enter your password and then it tells you if it's valid (matches the required pattern) # and re-prompts if it's not. # All passwords must contain at least one each of: number, lowercase and uppercase character. # # The starter code uses constants (variables at the top of the code, named in ALL_CAPS) to store: # # a. the minimum and maximum length of the password # b. whether or not a special character (not alphabetical or numerical) is required # # Remember when a program has constants, you should use them everywhere you can so that if you change them at the top, # this change affects the whole program as expected. # E.g. if you changed the minimum length to 5, the program should print 5 and should check to make sure the # password is >= 5 characters long. MIN_LENGTH = 5 MAX_LENGTH = 15 SPECIAL_CHARS_REQUIRED = False SPECIAL_CHARACTERS = "!@#$%^&*()_-=+`~,./'[]<>?{}|\\" def main(): """Program to get and check a user's password.""" print("Please enter a valid password") print("Your password must be between", MIN_LENGTH, "and", MAX_LENGTH, "characters, and contain:") print("\t1 or more uppercase characters") print("\t1 or more lowercase characters") print("\t1 or more numbers") if SPECIAL_CHARS_REQUIRED: print("\tand 1 or more special characters: ", SPECIAL_CHARACTERS) password = input("> ") while not is_valid_password(password): print("Invalid password!") password = input("> ") print("Your {}-character password is valid: {}".format(len(password), password)) def is_valid_password(password): """Determine if the provided password is valid.""" if len(password) < MIN_LENGTH or len(password) > MAX_LENGTH: return False count_lower = 0 count_upper = 0 count_digit = 0 count_special = 0 for char in password: if char.isdigit(): count_digit += 1 elif char.islower(): count_lower += 1 elif char.isupper(): count_upper += 1 elif char in SPECIAL_CHARACTERS: count_special += 1 if count_lower == 0 or count_upper == 0 or count_digit == 0: return False if SPECIAL_CHARS_REQUIRED: if count_special == 0: return False # if we get here (without returning False), then the password must be valid return True main()

UTF-8

Python

false

2,726

py

20

password_checker.py

18

0.652238

0.641233

0

72

36.861111

118

lanzorg/winup

4,226,247,843,373

c4514a58b11ff050792254cccfb14d44646f8bde

beae4c7e27bc10f8f53f7ece6c33e13359936d3b

/winup/helpers/downloaders.py

028920ed24cc9bbd86fbfac18c70ffc2b705f59e

[]

no_license

https://github.com/lanzorg/winup

771537d4de6efcc76e0effa059154b2d7871f667

e2545e10f5caa5d20c24fb756cb6819b345baf9f

refs/heads/master

2020-05-02T12:14:31.258250

2019-06-11T08:30:41

177,953,474

0

null

import os import tempfile import requests import rfc6266_parser def download_from_url(url, cookies=None): """Download a file from the direct download url.""" response = requests.get(url=url, cookies=cookies, allow_redirects=True, stream=True) file_path = os.path.join( tempfile.mkdtemp(), rfc6266_parser.parse_requests_response(response).filename_unsafe, ) with open(file_path, "wb") as f: for chunk in response.iter_content(chunk_size=1024): if chunk: f.write(chunk) f.flush() return file_path

UTF-8

Python

false

593

py

13

downloaders.py

11

0.642496

0.62226

0

23

24.782609

88

valexby/text-classification-api

2,980,707,338,330

dfd78c37f525c9cd28cf1dd87489ab7536e0cfc7

c6e73a840037d831b95af3687d592536dccf6dbb

/core/classifier.py

24e58c9562bea9ce33064cac7ea3768a0cdb4298

[]

no_license

https://github.com/valexby/text-classification-api

c3c4e18c56b8ef1303f542048f2c590b6cd59f1e

b75d49a7d8f7c20a2c92c1115cf0d6762b23649a

refs/heads/master

2020-04-29T22:13:49.067198

2019-03-20T18:23:48

176,439,462

0

null

import pickle from nltk import word_tokenize from nltk.stem.snowball import SnowballStemmer from sklearn.naive_bayes import MultinomialNB from sklearn.feature_extraction.text import TfidfTransformer from sklearn.feature_extraction.text import CountVectorizer from sklearn.pipeline import Pipeline class Stemmer: def __init__(self): self.stemmer = SnowballStemmer('english').stem def __call__(self, text): return [self.stemmer(i) for i in word_tokenize(text)] class Classifier: def __init__(self, model=None): self.model = model def load(self, model_path): with open(model_path, 'rb') as model_file: self.model = pickle.load(model_file) self.model.steps[0][1].tokenizer = Stemmer() def dump(self, model_path): self.model.steps[0][1].tokenizer = None with open(model_path, 'wb') as model_file: pickle.dump(self.model, model_file) def predict(self, text): predicted = self.model.predict([text]) return int(predicted[0])

UTF-8

Python

false

1,044

py

8

classifier.py

4

0.676245

0.671456

0

33

30.636364

61

minato1203/P8test1

266,287,972,815

42dfcd123f38a1189026febd63428f8ebf8485c1

21640cbd34a2f338fe51a79eb38230d4f2cfa010

/b.py

3ae7910eeb3065749fcba27038776875a0014262

[]

no_license

https://github.com/minato1203/P8test1

5d32e5bd8ed3e588794f9e89124e1484eca92d9e

a3b502623ea72209cc5c2c746dafb8873ac473ef

refs/heads/master

2023-04-09T07:42:05.330646

2021-04-28T11:05:45

362,369,274

0

null

print("this is only a test text")

UTF-8

Python

false

33

py

1

b.py

1

0.727273

0

1

33

Hoon94/Algorithm

1,855,425,893,552

4c9ebdf11ceab18811cb4bef019f6c7ab36a772a

73bb9d0d50b96b3d7ee48e2d97b1d8128a5f2b1e

/Leetcode/14 Longest Common Prefix.py

9158836808691acfe03b97c39c8efcb0801cabe9

[]

no_license

https://github.com/Hoon94/Algorithm

a0ef211d72a2b78e08249501d197875065392084

6f6969214bbb6bacd165313b6d8c0feb1caa8963

refs/heads/master

2023-05-11T13:12:11.585285

2023-05-08T14:38:47

244,936,260

0

null

class Solution: def longestCommonPrefix(self, strs: list) -> str: """[summary] Args: strs (List[str]): words in a list Returns: str: return longest common prefix """ result = '' strs = sorted(strs, key=lambda x: len(x)) short = strs[0] if len(strs) > 0 else '' for i in range(len(short)): for word in strs: if short != word[:len(short)]: short = short[:-1] break else: result = short if len(result) > 0: break return result

UTF-8

Python

false

655

py

387

14 Longest Common Prefix.py

386

0.439695

0.433588

0

28

22.392857

53

aamini/chemprop

9,844,065,091,729

28cc1e5981291e2bac08e7771584ff96ff4f8d47

7fec152e2f81c8ce35bed6f357937b2d4fd1ff6c

/scripts/create_train_curves.py

55d9a9b4e7380400670f87e969d4810344ef8e37

[ "MIT" ]

permissive

https://github.com/aamini/chemprop

072d712438dc5b3ba554f2734c03cfc4ae64834a

a7a137a09589474a5c5a83f75fbddbddfb877dc8

refs/heads/confidence-evidential

2023-05-23T20:59:52.572809

2021-07-29T16:16:26

388,299,389

85

16

MIT

false

2021-07-29T16:16:27

2021-07-22T02:05:01

2021-07-29T15:16:18

2021-07-29T16:16:26

292,586

13

1

0

Python

false

"""Create train curve from log file Call signatures used: python scripts/create_train_curves.py --log-dir submission_results/gnn/qm9/evidence/ # Note : for this case, it's worth rescaling the x axis python scripts/create_train_curves.py --log-dir submission_results_atomsitic_multi/gnn/qm9/evidence/ --verbose-extension fold_0/model_0/verbose.log """ import matplotlib.pyplot as plt import seaborn as sns import numpy as np import os import argparse import re import pandas as pd def get_args(): parser = argparse.ArgumentParser() parser.add_argument("--log-file", help="name of log file") parser.add_argument("--log-dir", help="name of log dir (eg has diff trials)") parser.add_argument("--verbose-extension", help="path from the trial directories to the log", default="verbose.log") #fold_0/model_0/verbose.log parser.add_argument("--out-name", help="Output name", default="temp.png") #fold_0/model_0/verbose.log return parser.parse_args() def get_val_losses(log_file : str): """ Extract the validation epochs from the log file""" losses = [] ctr = 0 epoch_re = r"Validation mae = (\d+\.\d+) *\nEpoch (\d+)" lines = open(log_file, "r").readlines() for index, line in enumerate(lines[:-1]): ctr += 1 search_str = "".join([line,lines[index+1]]) examples = re.findall(epoch_re, search_str) if len(examples) > 0: loss, epoch = examples[0] losses.append(float(loss)) return losses if __name__=="__main__": args = get_args() log_dir = args.log_dir log_file= args.log_file if log_dir: trial_files = [os.path.join(log_dir, i) for i in os.listdir(log_dir)] epoch_loss_list = [] for log_file in [f"{j}/{args.verbose_extension}" for j in trial_files]: if os.path.isfile(log_file): print(log_file) epoch_losses = get_val_losses(log_file) for index, loss in enumerate(epoch_losses): loss_entry = {"epoch" : index, "loss" : loss} epoch_loss_list.append(loss_entry) df = pd.DataFrame(epoch_loss_list) g = sns.lineplot(data =df, x="epoch", y="loss") #plt.ylim([0,0.5]) plt.savefig(f"{args.out_name}") else: epoch_losses = get_val_losses(log_file)

UTF-8

Python

false

2,463

py

65

create_train_curves.py

46

0.590337

0.583435

0

74

32.202703

147

NickNganga/pyhtontake2

17,892,833,760,757

f5c41d06bb1137f0d1aac5b0f1dbedc9604cc91b

c653a1780fd09621bc543a09043e20b172445cce

/task3.py

b3732f92b2f2c6fcba84b9e1af2e3909c2c94ba4

[]

no_license

https://github.com/NickNganga/pyhtontake2

c5f21d4ccdc8375b24d1256a841cbac02a9a35c9

8ab3e25fcd596668f097466e8abd327586b65e71

refs/heads/master

2020-07-29T13:43:11.857697

2019-09-21T19:03:29

209,826,409

0

null

def list_ends(a_list): return (a_list[0], a_list[len(a_list)-1]) # number of elements num = int(input("Enter number of elements : ")) # Below line read inputs from user using map() function put = list(map(int,input("\nEnter the numbers : ").strip().split()))[:num] # Below Line calls the function created above. put1 = list_ends(put) #Outputs the values under indices '0' & '-1' (the last one in the list). print("\nList is - ", put) #Outputs the values under indices '0' & '-1' (the last one in the list). print("\nNew List is - ", put1)

UTF-8

Python

false

547

py

8

task3.py

7

0.665448

0.650823

0

17

31.235294

74

nimble-robotics/NR_pdf_utils

8,847,632,648,903

3cd1b38bc5678ca7783948073e99137351069d99

525ac244cc9c57a113686dcbf0816c06b9c7f026

/application.py

10815c22c65dce9b17a7f0bf25e9fa5985802416

[]

no_license

https://github.com/nimble-robotics/NR_pdf_utils

c9a2f574f976db8ca20d444c703dfb8436bd14c7

d7796aa3088bb598c1dfb8f58f27f3804a216340

refs/heads/master

2021-01-09T01:56:59.067583

2020-03-11T19:00:30

242,209,366

0

null

true

2020-03-11T19:00:31

2020-02-21T18:53:46

2020-03-11T18:47:09

2020-03-11T19:00:30

120

0

Python

false

from flask import Flask,request,render_template # from utils import upload_to_aws,bucket_name from healthcheck import HealthCheck import os application = app = Flask(__name__,template_folder='templates') App_path = os.path.dirname(os.path.abspath(__file__)) @app.route('/home') def home(): return render_template('index.html') def app_status(): """ added health check """ return True,"App is up and running" health = HealthCheck(app,"/healthcheck") health.add_check(app_status) if __name__ == '__main__': app.run(debug = True, host='0.0.0.0', port= 5000 )

UTF-8

Python

false

591

py

8

application.py

2

0.673435

0.659898

0

26

21.769231

63

jgraniero52/lab-4

19,507,741,477,552

047a86ff29f23855d0163b2fc3275a5467140a9d

13bff9eb83069bb94456449b588571b3de08b375

/searchEngine.py

d339f4911cb61d57d8ef82541c8bccea4136f994

[]

no_license

https://github.com/jgraniero52/lab-4

a379c3dcead1c3944805241ea03f86480d4066d0

e95e86916ddc1080db1ea4ff8bad68c26d6cf344

refs/heads/master

2021-05-28T02:25:41.088980

2012-10-07T22:34:00

null

0

null

import sqlite3 import pickle import os from portStemmer import PorterStemmer from makeBigDict import scanCleanDir class Searcher: def __init__(self): self.stemmer = PorterStemmer() try: f = open(os.getcwd()+"/data/tokensDict.p", "r") self.tokens = pickle.load(f) except: print "Pickle file not found" print "Creating the Dirctionary" self.tokens = scanCleanDir() f = open(os.getcwd()+"/data/tokensDict.p", "w") pickle.dump(self.tokens, f) def dbQuery(self, query, args = ()): conn = sqlite3.connect('/Users/kristofer/comp_490/2lab/data/cache.db') db = conn.cursor() #args should be a tuple of the arguments in the query db.execute(query, args) rows = db.fetchall() conn.close() return rows def singleToken(self): print word = raw_input("Enter your one word query: ") token = word.lower() token = self.stemmer.stem(token, 0, len(token) - 1) try: wordDict = self.tokens[token] except: print word, "does not seem to exist in our files. Please try a different word" print return occurenceTotal = 0 highestFreq = {'freq': 0, 'docs':[]} i = 1 for doc in wordDict.keys(): freq = len(wordDict[doc]) occurenceTotal += freq linksQuery = """ SELECT webPage.linkText, item.itemName FROM ( SElECT itemToWebPage.webPageId, itemToWebPage.itemId FROM itemToWebPage WHERE webPageId = ?) AS linkItem JOIN item ON item.itemId = linkItem.itemId JOIN webPage ON webPage.webPageId = linkItem.webPageId; """ linksRow = self.dbQuery(linksQuery, (doc,)) print print i,"\t",linksRow[0][0] print "\t item: ",linksRow[0][1] print "\t occured ",freq,"times" i += 1 if freq > highestFreq['freq']: highestFreq['freq'] = freq highestFreq['docs'] = [linksRow[0][0]] elif freq == highestFreq['freq']: highestFreq['docs'].append(doc) print print "Total occurence of", word, "is", occurenceTotal, "times" print "Highest frequency: ", highestFreq['freq'], " times in: ", for i in range(len(highestFreq['docs'])): if i > 0: print "and" print highestFreq['docs'][i] print def orQuery(self): print word1 = raw_input("Enter the first word of your query: ") word2 = raw_input("Enter the second word of your query: ") token1 = word1.lower() token1 = self.stemmer.stem(token1, 0, len(token1) - 1) token2 = word2.lower() token2 = self.stemmer.stem(token2, 0, len(token2) - 1) try: docs = self.tokens[token1].keys() except: print word1, "does not seem to exist in our files. Please try a different word" print return try: docs2 = self.tokens[token2].keys() except: print word2, "does not seem to exist in our files. Please try a different word" print return #Perform a logical or on the elements of both lists. #Storing them in keys for doc in docs2: if doc not in docs: docs.append(doc) occurenceTotal = 0 i = 1 highestFreq = {'freq': 0, 'docs':[]} for doc in docs: freq1 = 0 freq2 = 0 try: freq1 = len(self.tokens[token1][doc]) except: None try: freq2 = len(self.tokens[token2][doc]) except: None freq = freq1 + freq2 occurenceTotal += freq linksQuery = """ SELECT webPage.linkText, item.itemName FROM ( SElECT itemToWebPage.webPageId, itemToWebPage.itemId FROM itemToWebPage WHERE webPageId = ?) AS linkItem JOIN item ON item.itemId = linkItem.itemId JOIN webPage ON webPage.webPageId = linkItem.webPageId; """ linksRow = self.dbQuery(linksQuery, (doc,)) print print i,"\t",linksRow[0][0] print "\t item: ",linksRow[0][1] print "\t occured ",freq,"times" i += 1 if freq > highestFreq['freq']: highestFreq['freq'] = freq highestFreq['docs'] = [linksRow[0][0]] elif freq == highestFreq['freq']: highestFreq['docs'].append(doc) print print "Total occurence of", word1, "or", word2, "is", occurenceTotal, "times" print "Highest frequency: ", highestFreq['freq'], " times in: ", for i in range(len(highestFreq['docs'])): if i > 0: print "and" print highestFreq['docs'][i] print def andQuery(self): print word1 = raw_input("Enter the first word of your query: ") word2 = raw_input("Enter the second word of your query: ") token1 = word1.lower() token1 = self.stemmer.stem(token1, 0, len(token1) - 1) token2 = word2.lower() token2 = self.stemmer.stem(token2, 0, len(token2) - 1) #Get the keys from both lists docs = [] try: docs1 = self.tokens[token1].keys() except: print word1, "does not seem to exist in our files. Please try a different word" print return try: docs2 = self.tokens[token2].keys() except: print word2, "does not seem to exist in our files. Please try a different word" print return #Perform a logical and on the elements of both lists. #Storing them in keys for doc in docs1: if doc in docs2: docs.append(doc) occurenceTotal = 0 i = 1 highestFreq = {'freq': 0, 'docs':[]} for doc in docs: freq1 = 0 freq2 = 0 try: freq1 = len(self.tokens[token1][doc]) except: None try: freq2 = len(self.tokens[token2][doc]) except: None freq = freq1 + freq2 occurenceTotal += freq linksQuery = """ SELECT webPage.linkText, item.itemName FROM ( SElECT itemToWebPage.webPageId, itemToWebPage.itemId FROM itemToWebPage WHERE webPageId = ?) AS linkItem JOIN item ON item.itemId = linkItem.itemId JOIN webPage ON webPage.webPageId = linkItem.webPageId; """ linksRow = self.dbQuery(linksQuery, (doc,)) print print i,"\t",linksRow[0][0] print "\t item: ",linksRow[0][1] print "\t occured ",freq,"times" i += 1 if freq > highestFreq['freq']: highestFreq['freq'] = freq highestFreq['docs'] = [linksRow[0][0]] elif freq == highestFreq['freq']: highestFreq['docs'].append(doc) print print "Total occurence of", word1, "and", word2, "is", occurenceTotal, "times" print "Highest frequency: ", highestFreq['freq'], " times in: ", for i in range(len(highestFreq['docs'])): if i > 0: print "and" print highestFreq['docs'][i] print def phraseQuery(self): print phrase = raw_input("Enter a two word phrase: ") while len(phrase.split(' ')) != 2: phrase = raw_input("Make sure your phrase is two words (e.g. 'hello goodbye'): ") words = phrase.split(' ') word1 = words[0] word2 = words[1] token1 = word1.lower() token1 = self.stemmer.stem(token1, 0, len(token1) - 1) token2 = word2.lower() token2 = self.stemmer.stem(token2, 0, len(token2) - 1) #Get the keys from both lists docs = [] try: docs1 = self.tokens[token1].keys() except: print word1, "does not seem to exist in our files. Please try a different word" print return try: docs2 = self.tokens[token2].keys() except: print word2, "does not seem to exist in our files. Please try a different word" print return #Perform a logical and on the elements of both lists. #Storing them in keys phraseDict = {} #Check which documents have both words for doc in docs1: if doc in docs2: doc1Pos = self.tokens[token1][doc] doc2Pos = self.tokens[token2][doc] #check which documents have the phrase in the correct order freq = 0 for pos1 in doc1Pos: for pos2 in doc2Pos: if pos2 == pos1 + 1: freq += 1 if freq > 0: phraseDict[doc] = freq occurenceTotal = 0 i = 1 highestFreq = {'freq': 0, 'docs':[]} for doc in phraseDict.keys(): freq = phraseDict[doc] occurenceTotal += freq linksQuery = """ SELECT webPage.linkText, item.itemName FROM ( SElECT itemToWebPage.webPageId, itemToWebPage.itemId FROM itemToWebPage WHERE webPageId = ?) AS linkItem JOIN item ON item.itemId = linkItem.itemId JOIN webPage ON webPage.webPageId = linkItem.webPageId; """ linksRow = self.dbQuery(linksQuery, (doc,)) print print i,"\t",linksRow[0][0] print "\t item: ",linksRow[0][1] print "\t occured ",freq,"times" i += 1 if freq > highestFreq['freq']: highestFreq['freq'] = freq highestFreq['docs'] = [linksRow[0][0]] elif freq == highestFreq['freq']: highestFreq['docs'].append(doc) print print "Total occurence of",phrase, "is", occurenceTotal, "times" print "Highest frequency: ", highestFreq['freq'], " times in: ", for i in range(len(highestFreq['docs'])): if i > 0: print "and" print highestFreq['docs'][i] print def nearQuery(self): print word1 = raw_input("Enter the first word: ") word2 = raw_input("Enter the second word: ") distance = input ("Enter the number of positions away you want to look: ") token1 = word1.lower() token1 = self.stemmer.stem(token1, 0, len(token1) - 1) token2 = word2.lower() token2 = self.stemmer.stem(token2, 0, len(token2) - 1) #Get the keys from both lists docs = [] try: docs1 = self.tokens[token1].keys() except: print word1, "does not seem to exist in our files. Please try a different word" print return try: docs2 = self.tokens[token2].keys() except: print word2, "does not seem to exist in our files. Please try a different word" print return #Perform a logical and on the elements of both lists. #Storing them in keys phraseDict = {} #Check which documents have both words for doc in docs1: if doc in docs2: doc1Pos = self.tokens[token1][doc] doc2Pos = self.tokens[token2][doc] #check which documents have the words within the allotted distance of each other freq = 0 for pos1 in doc1Pos: for pos2 in doc2Pos: if (pos2 - pos1 >= 0 - distance) and (pos2 - pos1 <= distance): freq += 1 if freq > 0: phraseDict[doc] = freq occurenceTotal = 0 i = 1 highestFreq = {'freq': 0, 'docs':[]} for doc in phraseDict.keys(): freq = phraseDict[doc] occurenceTotal += freq linksQuery = """ SELECT webPage.linkText, item.itemName FROM ( SElECT itemToWebPage.webPageId, itemToWebPage.itemId FROM itemToWebPage WHERE webPageId = ?) AS linkItem JOIN item ON item.itemId = linkItem.itemId JOIN webPage ON webPage.webPageId = linkItem.webPageId; """ linksRow = self.dbQuery(linksQuery, (doc,)) print print i,"\t",linksRow[0][0] print "\t item: ",linksRow[0][1] print "\t occured ",freq,"times" i += 1 if freq > highestFreq['freq']: highestFreq['freq'] = freq highestFreq['docs'] = [linksRow[0][0]] elif freq == highestFreq['freq']: highestFreq['docs'].append(doc) print print "Total occurence of",word1, "within ", distance, "positions of", word2, "was",occurenceTotal, "times" print "Highest frequency: ", highestFreq['freq'], " times in: ", for i in range(len(highestFreq['docs'])): if i > 0: print "and" print highestFreq['docs'][i] print def searchMenu(self): print print "-----------------------------------------------------------" print "\t Welcome to Stensland-ipedia!" print "\tWhere you can search to your hearts content!" print "-----------------------------------------------------------" print menu = True while menu: print "Choose the number corresponding to the query you would like to perform" print "---------------------------------------------------------------------" print "1.\tSingle token query." print "2.\tAND query." print "3.\tOR query." print "4.\t2-Token query." print "5.\tNear query." print "6.\tQuit" choice = raw_input("Enter your choice: ") if choice == '1': self.singleToken() elif choice == '2': self.andQuery() elif choice == '3': self.orQuery() elif choice == '4': self.phraseQuery() elif choice == '5': self.nearQuery() elif choice == '6': menu = False print "\n" else: print "That is not a thing I understand." print print print "Thank you for being my friend!" print def main(): #os.chdir('/Users/kristofer/comp_490/2lab') print "Preparing the search engine..." stenslandipedia = Searcher() stenslandipedia.searchMenu() if __name__ == "__main__": main()

UTF-8

Python

false

16,732

py

2

searchEngine.py

2

0.461511

0.447585

0

504

32.196429

115

Jordan-Camilletti/Project-Euler-Problems

10,548,439,683,351

a0ecbd1fc6934fc37a81977a88e715df839602d8

cdbadf1e63f74911a145c88bb5422da5c1977904

/python/16. Power digit Sum.py

3812c1a7024e0528cabf03000b5626d08755a472

[]

no_license

https://github.com/Jordan-Camilletti/Project-Euler-Problems

30a93d6130e14e9382ee7e7d86b739ae676aaacf

b3f54004907a5ee4db00ad1e4989e4f239dcbd14

refs/heads/master

2021-06-03T19:19:19.612809

2020-05-01T04:28:37

72,213,187

1

0

null

false

2020-02-23T04:49:10

2016-10-28T14:12:12

2020-02-21T02:20:09

2020-02-23T04:49:09

570

1

0

Python

false

"""2^15 = 32768 and the sum of its digits is 3 + 2 + 7 + 6 + 8 = 26. What is the sum of the digits of the number 2^1000?""" str=str(2**1000) tot=0 for x in str: tot=tot+int(x) print(tot)

UTF-8

Python

false

189

py

59

16. Power digit Sum.py

58

0.624339

0.486772

0

8

22.625

68

MonadWizard/python-basic

4,303,557,231,441

ead220a5b4b4901180a0eb2e18cfab39b08e632c

d87d83049f28da72278ca9aa14986db859b6c6d6

/basic/coreFundamental/tupleDemo/tupleBasic.py

b9ef6768c6dc72d8ef55ec75f859ae48dc8cfb63

[]

no_license

https://github.com/MonadWizard/python-basic

6507c93dc2975d6450be27d08fb219a3fd80ed64

624f393fcd19aeeebc35b4c2225bb2fe8487db39

refs/heads/master

2021-07-21T16:12:58.251456

2020-10-12T19:46:21

223,625,523

1

0

null

false

2019-11-23T18:01:43

2019-11-23T17:14:21

2019-11-23T18:00:52

2019-11-23T18:01:42

0

3

HTML

false

""" A tuple is a sequence of immutable objects, therefore tuple cannot be changed. It can be used to collect different types of object. The objects are enclosed within parenthesis and separated by comma. Tuple is similar to list. Only the difference is that list is enclosed between square bracket, tuple between parenthesis and List has mutable objects whereas Tuple has immutable objects. """ data1=(101,981,1666,12,156,981,15) data2=(101,981,'abcd','xyz','m') data3=('aman','shekhar',100.45,98.2) data4=(101,981,'abcd','xyz','m') print(data1) print(data2) #### There can be an empty Tuple also which contains no object. Lets see an example of empty tuple. data5 = () print(data5) print(""" """) #### For a single valued tuple, there must be a comma at the end of the value. data6 = (10,) print(data6) print(""" """) #### Tuples can also be nested, it means we can pass tuple as an element to create a new tuple. print("data1 : ",data1) data7 = data1,(10,20,30,40) print("data1 : ",data1) print("data7 : ",data7) print(""" """) print("#### Accessing Tuple : ") print("data2 : ",data2) print(data2[0]) print(data2[0:2]) print(data2[-3:-1]) print(data2[0:]) print(data2[:2]) print(""" """) print("#### Elements in a Tuple : ") data=(1,2,3,4,5,10,19,17) print(data) print("""Data[0]=1=Data[-8] , Data[1]=2=Data[-7] , Data[2]=3=Data[-6] , Data[3]=4=Data[-5] , Data[4]=5=Data[-4] , Data[5]=10=Data[-3], Data[6]=19=Data[-2],Data[7]=17=Data[-1] """) print(""" """) #### Tuple can be added by using the concatenation operator(+) to join two tuples. print("data2 : ",data2) print("data3 : ",data3) print((data2 + data3)) print(""" """) #### repeating can be performed by using '*' operator by a specific number of time. print("data2 : ",data2) print("data2 * 2", (data2*2)) print("data3 : ",data3) print("data3 * 3 : ", data3*3) print(""" """) #### A subpart of a tuple can be retrieved on the basis of index. This subpart is known as tuple slice. print (data1[0:2]) print (data1[4]) print (data1[:-1]) print (data1[-5:]) print (data1) print(""" """) #### We can create a new tuple by assigning the existing tuple. print(data3) print(data4) print(data3+data4) print(""" """) del data3 #print(data3) #this tuple was deleted so seen error

UTF-8

Python

false

2,403

py

195

tupleBasic.py

165

0.620474

0.556388

0

114

18.95614

131

chinatszrn/momo_labeltool

1,614,907,752,572

49df60761f06ad4f9c40c681fa87cdbcb07e5f09

8eab8ba100521cedb0b8c62059b0000fe04da989

/mainwin.py

826f7760fe7f7c0d85a5276d4a6c6bd0c2cd0019

[]

no_license

https://github.com/chinatszrn/momo_labeltool

b3ffbdba2772050f830322c213611651fede3037

f3ddb9ff7e526cd224c674c84a7ee4f4e49850ed

refs/heads/master

2020-12-13T18:08:24.550696

2019-05-14T09:43:04

null

0

null

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'mainwin.ui' # # Created by: PyQt5 UI code generator 5.11.3 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_main_window(object): def setupUi(self, main_window): main_window.setObjectName("main_window") main_window.resize(1037, 784) self.centralwidget = QtWidgets.QWidget(main_window) self.centralwidget.setObjectName("centralwidget") self.gridLayout_3 = QtWidgets.QGridLayout(self.centralwidget) self.gridLayout_3.setObjectName("gridLayout_3") self.canvas = Canvas(self.centralwidget) self.canvas.setInteractive(True) self.canvas.setObjectName("canvas") self.gridLayout_3.addWidget(self.canvas, 1, 0, 1, 1) self.widget = QtWidgets.QWidget(self.centralwidget) self.widget.setObjectName("widget") self.horizontalLayout = QtWidgets.QHBoxLayout(self.widget) self.horizontalLayout.setObjectName("horizontalLayout") self.fixitem = QtWidgets.QCheckBox(self.widget) self.fixitem.setObjectName("fixitem") self.horizontalLayout.addWidget(self.fixitem) self.index = QtWidgets.QCheckBox(self.widget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.index.sizePolicy().hasHeightForWidth()) self.index.setSizePolicy(sizePolicy) self.index.setObjectName("index") self.horizontalLayout.addWidget(self.index) self.control = QtWidgets.QCheckBox(self.widget) self.control.setChecked(True) self.control.setObjectName("control") self.horizontalLayout.addWidget(self.control) self.keypoint = QtWidgets.QCheckBox(self.widget) self.keypoint.setChecked(True) self.keypoint.setObjectName("keypoint") self.horizontalLayout.addWidget(self.keypoint) self.contour = QtWidgets.QCheckBox(self.widget) self.contour.setChecked(True) self.contour.setObjectName("contour") self.horizontalLayout.addWidget(self.contour) self.left_eyebrown = QtWidgets.QCheckBox(self.widget) self.left_eyebrown.setChecked(True) self.left_eyebrown.setObjectName("left_eyebrown") self.horizontalLayout.addWidget(self.left_eyebrown) self.right_eyebrown = QtWidgets.QCheckBox(self.widget) self.right_eyebrown.setChecked(True) self.right_eyebrown.setObjectName("right_eyebrown") self.horizontalLayout.addWidget(self.right_eyebrown) self.left_eye = QtWidgets.QCheckBox(self.widget) self.left_eye.setChecked(True) self.left_eye.setObjectName("left_eye") self.horizontalLayout.addWidget(self.left_eye) self.right_eye = QtWidgets.QCheckBox(self.widget) self.right_eye.setChecked(True) self.right_eye.setObjectName("right_eye") self.horizontalLayout.addWidget(self.right_eye) self.nose = QtWidgets.QCheckBox(self.widget) self.nose.setChecked(True) self.nose.setObjectName("nose") self.horizontalLayout.addWidget(self.nose) self.mouth_outter = QtWidgets.QCheckBox(self.widget) self.mouth_outter.setChecked(True) self.mouth_outter.setObjectName("mouth_outter") self.horizontalLayout.addWidget(self.mouth_outter) self.mouth_inner = QtWidgets.QCheckBox(self.widget) self.mouth_inner.setChecked(True) self.mouth_inner.setObjectName("mouth_inner") self.horizontalLayout.addWidget(self.mouth_inner) self.gridLayout_3.addWidget(self.widget, 0, 0, 1, 1) main_window.setCentralWidget(self.centralwidget) self.menubar = QtWidgets.QMenuBar(main_window) self.menubar.setGeometry(QtCore.QRect(0, 0, 1037, 18)) self.menubar.setObjectName("menubar") self.menu = QtWidgets.QMenu(self.menubar) self.menu.setObjectName("menu") self.menu_2 = QtWidgets.QMenu(self.menubar) self.menu_2.setObjectName("menu_2") main_window.setMenuBar(self.menubar) self.statusbar = QtWidgets.QStatusBar(main_window) self.statusbar.setObjectName("statusbar") main_window.setStatusBar(self.statusbar) self.dockWidget_2 = QtWidgets.QDockWidget(main_window) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.dockWidget_2.sizePolicy().hasHeightForWidth()) self.dockWidget_2.setSizePolicy(sizePolicy) self.dockWidget_2.setLayoutDirection(QtCore.Qt.LeftToRight) self.dockWidget_2.setObjectName("dockWidget_2") self.dockWidgetContents_2 = QtWidgets.QWidget() self.dockWidgetContents_2.setObjectName("dockWidgetContents_2") self.gridLayout = QtWidgets.QGridLayout(self.dockWidgetContents_2) self.gridLayout.setObjectName("gridLayout") self.file_list = FileList(self.dockWidgetContents_2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.file_list.sizePolicy().hasHeightForWidth()) self.file_list.setSizePolicy(sizePolicy) self.file_list.setObjectName("file_list") self.gridLayout.addWidget(self.file_list, 0, 0, 1, 1) self.dockWidget_2.setWidget(self.dockWidgetContents_2) main_window.addDockWidget(QtCore.Qt.DockWidgetArea(2), self.dockWidget_2) self.actionload = QtWidgets.QAction(main_window) self.actionload.setObjectName("actionload") self.actionConvert = QtWidgets.QAction(main_window) self.actionConvert.setObjectName("actionConvert") self.actionConvert1k = QtWidgets.QAction(main_window) self.actionConvert1k.setObjectName("actionConvert1k") self.actionBrezier = QtWidgets.QAction(main_window) self.actionBrezier.setObjectName("actionBrezier") self.menu.addAction(self.actionload) self.menu_2.addAction(self.actionConvert) self.menu_2.addAction(self.actionConvert1k) self.menu_2.addAction(self.actionBrezier) self.menubar.addAction(self.menu.menuAction()) self.menubar.addAction(self.menu_2.menuAction()) self.retranslateUi(main_window) QtCore.QMetaObject.connectSlotsByName(main_window) def retranslateUi(self, main_window): _translate = QtCore.QCoreApplication.translate main_window.setWindowTitle(_translate("main_window", "关键点标注")) self.fixitem.setText(_translate("main_window", "固定图片(F)")) self.fixitem.setShortcut(_translate("main_window", "F")) self.index.setText(_translate("main_window", "序号(S)")) self.index.setShortcut(_translate("main_window", "S")) self.control.setText(_translate("main_window", "控制点(Q)")) self.control.setShortcut(_translate("main_window", "Q")) self.keypoint.setText(_translate("main_window", "关键点(W)")) self.keypoint.setShortcut(_translate("main_window", "W")) self.contour.setText(_translate("main_window", "脸轮廓(E)")) self.contour.setShortcut(_translate("main_window", "E")) self.left_eyebrown.setText(_translate("main_window", "左眉毛(R)")) self.left_eyebrown.setShortcut(_translate("main_window", "R")) self.right_eyebrown.setText(_translate("main_window", "右眉毛(T)")) self.right_eyebrown.setShortcut(_translate("main_window", "T")) self.left_eye.setText(_translate("main_window", "左眼睛(Y)")) self.left_eye.setShortcut(_translate("main_window", "Y")) self.right_eye.setText(_translate("main_window", "右眼睛(U)")) self.right_eye.setShortcut(_translate("main_window", "U")) self.nose.setText(_translate("main_window", "鼻子(I)")) self.nose.setShortcut(_translate("main_window", "I")) self.mouth_outter.setText(_translate("main_window", "嘴外轮廓(O)")) self.mouth_outter.setShortcut(_translate("main_window", "O")) self.mouth_inner.setText(_translate("main_window", "嘴内轮廓(P)")) self.mouth_inner.setShortcut(_translate("main_window", "P")) self.menu.setTitle(_translate("main_window", "文件")) self.menu_2.setTitle(_translate("main_window", "数据处理")) self.actionload.setText(_translate("main_window", "载入文件夹")) self.actionConvert.setText(_translate("main_window", "生成137点")) self.actionConvert1k.setText(_translate("main_window", "生成1000点")) self.actionBrezier.setText(_translate("main_window", "生成贝塞尔关键点")) from canvas import Canvas from filelist import FileList

UTF-8

Python

false

9,099

py

9

mainwin.py

7

0.695371

0.686447

0

166

53.006024

108

radiofarmer/WavetableEditor

8,959,301,814,077

4f18f22d69b81b620c812ed4c63ba488b55ddf0d

89b5aa59f30f7417c19b8300a4da100fc6d8205b

/WavetableEditor/Wavetable.py

fc980a751cbad126aeb2cd0060953502cac9538f

[ "MIT" ]

permissive

https://github.com/radiofarmer/WavetableEditor

810bb639165efd0a6ef29f2a7e8fbc95a678e3f3

2cee8d773d24978ef3edc52a85b4285a48506f25

refs/heads/master

2023-03-11T08:00:15.309139

2021-02-26T09:22:35

340,004,065

0

null

import numpy as np from WavetableEditor import IO from scipy import fft from scipy import interpolate import matplotlib.pyplot as plt import math def quantize_to_fraction(x, f): return np.floor(f * x) / f def make_shift_function(x, shift_step, max_shift=1., noise=0.): func = interpolate.interp1d(np.linspace(0, 1, x.shape[0]), x / np.max(x)) return lambda h: h + max_shift * quantize_to_fraction( func(np.linspace(0, 1., h.shape[0])) + np.random.random(h.shape[0]) * noise, shift_step ) def window(k, length): t = np.linspace(0, 1, length) fact = -np.abs((k - np.floor(k)) - 0.5) + 0.5 return (-np.cos(2 * np.pi * t) / 2 + 0.5) ** fact def oscillating_signs(harmonics): signs = np.ones(harmonics.shape[0]) for i, h in enumerate(harmonics): if h <= 1.: continue else: num = h / (h - np.floor(h)) if h != int(h) else h signs[i] *= 1. if num % 2 else -1. return signs def square_coeffs(harmonics): coeffs = np.zeros(harmonics.shape[0]) for i, h in enumerate(harmonics): if h == 0: coeffs[i] = 0 elif h % 2 == 0: coeffs[i] = 0 else: coeffs[i] = 1 / h return coeffs def saw_coeffs(harmonics): coeffs = np.zeros(harmonics.shape[0]) for i, h in enumerate(harmonics): if h == 0: coeffs[i] = 0 else: coeffs[i] = 1 / h return coeffs def zero_phase(h, *args, **kwargs): return np.zeros(h.shape[0]) class HarmonicSeries: def __init__(self, start, end, period, amp_func, phase_func=None, h_shift_func=None, **kwargs): if phase_func is None: phase_func = zero_phase if h_shift_func is None: h_shift_func = lambda x: x # Array of harmonic numbers self.harmonics = np.arange(start, end, period) h = h_shift_func(self.harmonics) self.harmonics = h # Array of amplitudes self._amplitudes = amp_func(self.harmonics) self._scale = 1. # Array of phases self._phases = phase_func(self.harmonics) self._step_size = period if "normalize" in kwargs: self.normalize(kwargs["normalize"]) def __mul__(self, other): """Multiplying the HarmonicSeries object multiplies the amplitudes""" self._scale = other return self def normalize(self, h_target): """Normalizes all amplitudes to the indicated harmonic""" if np.max(np.abs(self._amplitudes)) != 0.: self._amplitudes /= self._amplitudes[int(h_target - 1)] if np.max(np.abs(self._phases)) != 0.: self._phases /= self._phases[int(h_target - 1)] self._phases *= 2 * np.pi def evaluate(self, samprate, cycles=1, os_level=8, bandlimit=None, window=True): # t = np.arange(0, samprate * cycles) t = np.linspace(0., cycles * 2 * np.pi, samprate * cycles, endpoint=False) series = np.zeros(t.shape[0]) # adj = np.cos(self.harmonics - 1) ** 2 * (np.pi / (2 * self.harmonics[-1])) # gibbs adj = np.sinc(self.harmonics * np.pi / (2 * np.max(self.harmonics))) # sigma factor for a, p, h, g in zip(self.amplitudes, self.phases, self.harmonics, adj): if h <= bandlimit / os_level if bandlimit is not None else samprate / (4 * os_level): # Harmonics whose waveforms do not have an integer-number of cycles within # the rendered region are windowed to prevent aliasing. Increasing the number # of cycles allows more inharmonic frequencies to fit evenly into the wavetable. if not window or np.abs(h * cycles - np.round(h * cycles)) < 1e-3: partial = a * np.sin(float(h) * t + p) else: print("Harmonic {} does not fit into {} cycles".format(h, cycles)) wnd1 = np.concatenate([(np.cos(np.pi * t[:int(samprate)] / samprate) + 1) / 2, np.zeros(int(samprate * (cycles - 1)))]) wnd2 = np.concatenate([np.ones(int(samprate * (cycles - 1))), wnd1[int(samprate) - 1::-1]]) t_ext = np.arange(0, np.floor(samprate * cycles * (1 + h - np.floor(h)))) wave_full = np.sin(2 * np.pi * h * t_ext / samprate + p) wave1 = wave_full[:int(samprate * cycles)] wave2 = wave_full[len(wave_full) - int(samprate * cycles):] partial = a * (wave1 * wnd1 + wave2 * wnd2) series += partial * g return series @property def amplitudes(self): return self._amplitudes @property def phases(self): return self._phases @property def scale(self): return self._scale @property def max_harmonic(self): return self.harmonics[-1] @property def num_harmonics(self): return self.harmonics.shape[0] @property def step_size(self): return self._step_size class Waveform(): def __init__(self): self.series_ = [] def add_series(self, *args, **kwargs): new_series = HarmonicSeries(*args, **kwargs) self.append_series(new_series) def append_series(self, new_series): self.series_.append(new_series) def normalize(self): """Normalizes all series so that the (summed) maximum harmonic (not necessarily the fundamental) is one""" fund_sum = np.sum([np.max(s.amplitudes) for s in self.series_]) for s in self.series_: s.normalize(fund_sum) def generate_series(self, samprate, **kwargs): if "cycles" in kwargs: num_cycles = kwargs['cycles'] else: num_cycles = 1 length = int(samprate * num_cycles) sum_sines = np.zeros(length) # Sum sinusoids of all harmonic series for s in self.series_: s_wave = s.evaluate(samprate, **kwargs) s_wave /= np.max(np.abs(s_wave)) if np.max(s_wave) else 1. sum_sines += s_wave * s.scale # Normalize to the highest value if np.max(np.abs(sum_sines)) != 0.: self.waveform = sum_sines / np.max(np.abs(sum_sines)) # self.waveform = sum_sines / (sum_sines ** 2).sum() * num_cycles else: self.waveform = sum_sines return self.waveform def generate_ifft(self, samprate): freq_domain = np.zeros(samprate // 2) for s in self.series_: offset = s.harmonics[0] top_harmonic = s.max_harmonic + offset amp_interp_func = interpolate.interp1d(s.harmonics, s.amplitudes) phase_interp_func = interpolate.interp1d(s.harmonics, s.phases) a_resampled = amp_interp_func(np.arange(offset, top_harmonic, s.step_size)) p_resampled = phase_interp_func(np.arange(offset, top_harmonic, s.step_size)) # Pad the amplitude and phase arrays with zeros if the fundamental frequency of # the series is not the wavetable fundamental if top_harmonic >= samprate // 2: a = a_resampled[:math.floor(samprate // 2 - np.ceil(offset))] p = p_resampled[:math.floor(samprate // 2 - np.ceil(offset))] else: a = np.concatenate([a_resampled, np.zeros(math.floor(samprate // 2 - top_harmonic))]) p = np.concatenate([p_resampled, np.zeros(math.floor(samprate // 2 - top_harmonic))]) if offset > 1: a = np.concatenate([np.zeros(offset), a]) p = np.concatenate([np.zeros(offset), p]) # Interpolate amplitude and phase values s_complex = a + 1.0j * p # Pad with the DC offset value s_complex = np.concatenate([[0], s_complex]) # Add to the frequency-domain representation freq_domain = np.add(freq_domain, s_complex[:samprate // 2]) # Add negative frequencies freq_domain = np.concatenate([freq_domain, np.conj(freq_domain[::-1])]) * samprate self.waveform = fft.ifft(freq_domain) return self.waveform def from_sample(self, samples, samprate, cycles=1): fft_length = min(samprate * cycles, samples.shape[0]) transform = fft.fft(samples[:fft_length]) amps = np.real(transform) phases = np.imag(transform) # Shift the fundamental frequency to bin [cycles] clip_region = np.argmax(np.abs(transform)) transform = np.concatenate([np.zeros(cycles), transform[clip_region:], np.zeros(clip_region)]) self.waveform = transform return self.waveform class Wavetable(): def __init__(self): self.waves_ = [] def freq_spec(x): return np.abs(fft.fft(x)) def plot_freqs(x, freq_max=None): if freq_max is None: freq_max = x.shape[0] fourier_transform = fft.fft(x) plt.plot(np.abs(fourier_transform[:freq_max])) plt.show() def plot_fft(x, freq_max=None): if freq_max is None: freq_max = x.shape[0] fourier_transform = fft.fft(x) plt.plot(np.real(fourier_transform[:freq_max])) plt.plot(np.imag(fourier_transform[:freq_max])) plt.show() if __name__ == "__main__": wt1 = Waveform() wt1.add_series(1, 2, 1, saw_coeffs) # wave = wt1.generate_series(48000, cycles=3) # plt.plot(np.abs(fft.fft(wave)[:100])) wt2 = Waveform() wt2.add_series(1, 200, 1, saw_coeffs) # wave = wt2.generate_series(48000, cycles=3) # wave = np.tile(wave, 10) # plt.plot(np.abs(fft.fft(wave)[:100])) # plt.show() IO.export_mipmap([wt1, wt2], "", "Sine-Saw", 2 ** 14, cycles_per_level=1)

UTF-8

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false

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py

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Wavetable.py

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Saumay-Agrawal/GSOC-Explorer

8,443,905,714,839

9c81268fdb2348ddbbb8e1607b1e4af6810bfc69

b39074034e46a57753cd22a9ea147dafc158c26d

/data-extractor.py

c48f3f82cf9cf49af0d647d4f73a39aef1d878da

[]

no_license

https://github.com/Saumay-Agrawal/GSOC-Explorer

2590aa6bea9f792633cb51ed3983840df5ac6d3a

6c82c7b9ecdede5d13c87fcae621a2731cbf94ef

refs/heads/master

2020-04-10T23:01:28.683316

2019-02-22T09:51:26

161,339,391

0

null

import pymongo import json from pprint import pprint client = pymongo.MongoClient('mongodb://localhost:27017/') db = client['gsoc-data'] col = db['flat_data'] file = open('gsoc-data.json', mode='w', encoding='utf-8') file.write('[') count = 0 for doc in col.find(): del doc['_id'] file.write(json.dumps(doc, sort_keys=True) + ',') count += 1 pprint('{} documents written to the file.'.format(count)) file.write(']') file.close()

UTF-8

Python

false

448

py

10

data-extractor.py

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0.654018

0.636161

0

20

21.45

61

vasu4982/flask-apps-with-blueprints

4,844,723,153,112

8b762bea4713ac191cd00c66a508ee9d6604a3fa

70d59ad4466a6eea0ea4bca03a7786921476353d

/blueprints/__init__.py

dbe334a55577633f3ae71d63ea77888fedd2a5f4

[]

no_license

https://github.com/vasu4982/flask-apps-with-blueprints

0b295e40f6ef89216ff0d49c1a98e15c70b5bcc1

b8cab7683100f87b813abdbac09ac9695c8b93a6

refs/heads/master

2021-09-13T10:21:44.081675

2018-04-28T05:49:40

null

0

null

from flask import Flask from blueprints.home.views import home from blueprints.about.views import about app = Flask(__name__) app.register_blueprint(home, url_prefix='/home') app.register_blueprint(about, url_prefix='/about')

UTF-8

Python

false

227

py

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__init__.py

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0

7

31.428571

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jan-g/psh

9,680,856,329,124

0a312f88f484230dea3ccbf1119bdaf7bfa68393

39729564419ed0c233d2fe2c215214e52e3c4a10

/test/test_model_case.py

0bbd37b0577985b71e84b5dd314e113c55fec4a9

[ "Apache-2.0" ]

permissive

https://github.com/jan-g/psh

b4ec8aae7e394ccbf85b97fa0e71482296e03974

c2641c9d2d7051dacb41474123889dd04bdd2989

refs/heads/master

2020-09-14T16:22:57.988393

2019-12-07T22:41:00

223,183,178

0

null

import pytest from psh.model import Word, Id, CommandSequence, Command, Case, VarRef, ConstantString from psh.glob import STAR from psh.local import make_env w = lambda w: Word([Id(w)]) a = Word([VarRef(Id("a"))]) echo = lambda out: CommandSequence([Command([Word([Id("echo")]), Word([ConstantString(out)])])]) x = w("x") cmd = lambda *cs: CommandSequence([Command([*cs])]) star = Word([STAR]) @pytest.mark.parametrize(("cmd", "variable", "expected"), ( (CommandSequence([Case(a)]), "", ""), (CommandSequence([Case(a).with_case(x, echo("foo"))]), "", ""), (CommandSequence([Case(a).with_case(x, echo("foo"))]), "y", ""), (CommandSequence([Case(a).with_case(x, echo("foo"))]), "x", "foo"), (CommandSequence([Case(a).with_case(x, echo("foo")).with_case(star, echo("bar"))]), "", "bar"), (CommandSequence([Case(a).with_case(x, echo("foo")).with_case(star, echo("bar"))]), "y", "bar"), (CommandSequence([Case(a).with_case(x, echo("foo")).with_case(star, echo("bar"))]), "x", "foo"), ), ids=lambda x: x.replace(" ", "_") if isinstance(x, str) else x) def test_basic(cmd, variable, expected): env = make_env() env["a"] = variable assert cmd.evaluate(env) == expected

UTF-8

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false

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py

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test_model_case.py

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andrisole92/VectorAI

18,717,467,489,324

946540bc473e1d5b42db8ea31ddd242198c3f070

b18b340f7d27b349ed8f344f1827331d1812249b

/src/__init__.py

9f678db9c3b941ae8e79443bb0cec983662d336c

[]

no_license

https://github.com/andrisole92/VectorAI

42917758cb305d562a48b7f64ab18c824ab487fb

03e6a8e5d6ff76a03c9108f6f507f47dfe7fd04f

refs/heads/master

2021-01-05T22:09:46.285959

2020-02-22T18:33:26

241,149,928

0

null

from src.db.Engine import Engine from src.db.SessionManager import SessionManager

UTF-8

Python

false

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py

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__init__.py

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iaasci-ibm/python-zvm-sdk

10,857,677,372,748

a320a32d2f4c4953df50939aef8d1c8cdba90914

516e5ad7aa37dee9c6f6602dc63b66bf3d361f37

/zvmsdk/tests/unit/base.py

a0bd874f1c8a5a8a3b4e12410bc52544d6e37d65

[ "CC-BY-4.0", "Apache-2.0" ]

permissive

https://github.com/iaasci-ibm/python-zvm-sdk

3eec5b82d5e28c19e5213626102a237070e54e7c

c39d4522b2311da0bb06910b6bb3b20ad32a8ae4

refs/heads/master

2022-02-13T04:37:50.098878

2022-01-28T18:17:44

227,066,210

0

2

Apache-2.0

true

2021-04-09T00:33:39

2019-12-10T08:26:36

2021-04-08T15:32:19

2021-04-09T00:33:38

6,790

0

C

false

# Copyright 2017 IBM Corp. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import unittest from zvmsdk import config CONF = config.CONF def set_conf(section, opt, value): CONF[section][opt] = value class SDKTestCase(unittest.TestCase): @classmethod def setUpClass(cls): # This can be used to set up confs before running all cases super(SDKTestCase, cls).setUpClass() cls.old_db_dir = CONF.database.dir set_conf('database', 'dir', '/tmp/') set_conf('zvm', 'disk_pool', 'ECKD:TESTPOOL') set_conf('image', 'sdk_image_repository', '/tmp/') set_conf('zvm', 'namelist', 'TSTNLIST') @classmethod def tearDownClass(cls): super(SDKTestCase, cls).tearDownClass() # Restore the original db path CONF.database.dir = cls.old_db_dir def setUp(self): super(SDKTestCase, self).setUp() def _fake_fun(self, value=None): return lambda *args, **kwargs: value

UTF-8

Python

false

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py

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base.py

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vineetsingh065/30_days_of_problem_solving

1,082,331,796,878

9456c4ad4b3f9f67af05bf8cbf07f9a27872d3ab

b8f68d68c49a191b06d0c83ebd7be0a7bde0cc28

/day_6_total_set_bits.py

1f3292920266b522d40a6053ead627093e6d5910

[]

no_license

https://github.com/vineetsingh065/30_days_of_problem_solving

485f6033e5785ae365d14728cbadd5f44158afb0

40014080b135378359742b9493334f4079309862

refs/heads/master

2023-08-25T01:00:53.208219

2021-10-10T15:23:37

403,340,800

0

null

""" You are given a number N. Find the total count of set bits for all numbers from 1 to N(both inclusive). Example 1: Input: N = 4 Output: 5 Explanation: For numbers from 1 to 4. For 1: 0 0 1 = 1 set bits For 2: 0 1 0 = 1 set bits For 3: 0 1 1 = 2 set bits For 4: 1 0 0 = 1 set bits Therefore, the total set bits is 5. """ def countSetBits(n): count=0 i=1 while(i<=n): i=i*2 q=(n+1)//i r=(n+1)%i t=q*(i//2) if r>(i//2): t+=r-i//2 count+=t return count if __name__=='__main__': n = 17 print(countSetBits(n))

UTF-8

Python

false

613

py

14

day_6_total_set_bits.py

14

0.522023

0.461664

0

36

16.027778

103

kongqiuchuipin/UsedCar

15,513,421,918,185

640db27271cd5ac733f759af392877446d731314

22e585820e19df8d28eb164db1b02d6832e09f63

/youxin/youXin.py

476bdfca5fe65619052f8f4322745c2f12807e9b

[]

no_license

https://github.com/kongqiuchuipin/UsedCar

f15100ff8f62790fe67835f72a7eb3914053d9ab

b6938c88b2edb6c7d783946e41aece5304b83235

refs/heads/master

2021-01-25T09:44:36.910714

2018-03-01T07:52:04

123,316,549

1

0

null

# _*_ coding:utf-8 _*_ from link import Link, get_all_city_name from info import info from pymongo import MongoClient from shelve_method_ import shelve_open, shelve_add, shelve_save def all_city_links(): all_city = shelve_open('all_city_name') # 如果已经有城市列表 if not all_city: all_city = get_all_city_name() # 如果没有 shelve_save('all_city_name', all_city) return all_city def get_link(): all_city = all_city_links() done = shelve_open('city_done_link') # 采集过的 doing = [i for i in all_city if i not in done] for city in doing: if city not in done: # 未采集的 link_spider = Link(city) link_spider.get_links() shelve_add('city_done_link', city) # 在这里设置记录, 下一次采集在这之后 def get_info(): # 针对全部城市的采集 collection = MongoClient()['youXin']['all'] city_links = set(shelve_open('all_link')) city_invalid_links = set(shelve_open('invalid_link')) if city_links: # 如果文件里存在链接 in_database = {i['链接'][8:] for i in collection.find()} l_i_d = len(in_database) link_for_catch = city_links - in_database - city_invalid_links l_f_c = len(link_for_catch) print('数据库:{}, 待采集{}, 共{}条'.format(l_i_d, l_f_c, l_i_d + l_f_c)) for i, link in enumerate(link_for_catch): print(i + l_i_d, 'of', l_i_d + l_f_c) # # 页面不存在这种情况也计算在内 doc = info(link) if doc: collection.insert_one(doc) print('完成'.center(30, '*')) if __name__ == '__main__': # get_link() get_info()

UTF-8

Python

false

1,714

py

15

youXin.py

14

0.574742

0.572165

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49

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mberrens/IceContinuum

6,717,328,890,219

42171544d81c325c031f89fed30c8d8cf9e89c6a

c65ac5b9fd6a679a9837b455b0eaeb74171b66bc

/netcdfstuff/loader.py

87fe3751a1b39c54e44afb69d04da66e6c926af5

[]

no_license

https://github.com/mberrens/IceContinuum

7705b01f9762647ff5e3d0f808108d0f6ed64514

10f2ed23cb93c1e212aef4689e90d8ff4fda0225

refs/heads/master

2021-05-06T11:33:12.599154

2019-08-12T02:42:05

114,292,998

1

0

null

# .. Built-in modules import pickle import numpy as np import scipy.io as spio from netCDF4 import Dataset, num2date, date2index from scipy.io.netcdf import NetCDFFile as DS from scipy.interpolate import interp2d import array def load_ssp_nu(datafile, nu): # Load the moments from a netcdf file & return the unbundled arrays dnu = nu[1] - nu[0] with DS(datafile,'r') as nc: inu = np.where(np.logical_and(\ nc.variables['wnum_list'][:] > nu[0]-2*dnu, nc.variables['wnum_list'][:] < nu[-1]+2*dnu))[0] Npmomarray = nc.variables['Npmomarray'][:,inu].astype('int32') w0_mesh = nc.variables['w0_mesh'][:,inu].astype('float64') qext_mesh = nc.variables['qext_mesh'][:,inu].astype('float64') reff = nc.variables['reff_list'][:].astype('float64'); reff = reff[:,0] wnum_vec = nc.variables['wnum_list'][inu].astype('float64') # wnum_mesh = nc.variables['wnum_mesh'][:,inu].astype('float64') # reff_mesh = nc.variables['reff_mesh'][:,inu].astype('float64') # Set up empty output arrays Nnu = nu.size Nreff = reff.size qext = np.zeros((Nreff, Nnu)) w0 = np.zeros((Nreff, Nnu)) NPmom_fp = np.zeros((Nreff, Nnu)) # Interpolate qext, w0, get an interpolated number of moments! fq = interp2d(reff, wnum_vec, qext_mesh.T) fw = interp2d(reff, wnum_vec, w0_mesh.T) fNP = interp2d(reff, wnum_vec, Npmomarray.T) for i in range(Nreff): qext[i,:] = fq(reff[i], nu)[:,0] w0[i,:] = fw(reff[i], nu)[:,0] NPmom_fp[i,:] = fNP(reff[i], nu)[:,0] # Use floor so we never interpolate between a moment and 0. NPmom = np.floor(NPmom_fp).astype(int) NPmom_max = np.max(NPmom) pmomarray = nc.variables['pmomarray'][:,inu,:NPmom_max] pmomarray = pmomarray.astype('float64') # Loop over all the moments to do the same Pmom = np.zeros((Nreff, Nnu, NPmom_max)); for j in range( NPmom_max): f = interp2d(reff, wnum_vec, pmomarray[:,:,j].T) for i in range(Nreff): Pmom[i,:,j] = f(reff[i], nu)[:,0] return (NPmom, Pmom, reff, w0, qext) def getsolarbeam_IR (wnum=None, solarbeam_IR_file=None): #print solarbeam_IR_file kurucz = np.loadtxt(solarbeam_IR_file) #'kurucz.dat') beam = np.interp(wnum,kurucz[:,0],kurucz[:,1])/1000; return (beam) # # # # # # # # LOAD SURFACE ALBEDO # # # # # # # # # # # # # # def get_surface_albedo_from_file(surfEmissDataFile): albedoData = np.loadtxt(surfEmissDataFile, comments='%') nu_surf_albedo = albedoData[:, 1] surf_albedo = 1-albedoData[:, 2] return nu_surf_albedo, surf_albedo def get_surface_albedo_IR(wnum = None, surfEmissDataFile = None): Mammoth = np.loadtxt(surfEmissDataFile) #'Mammoth.dat') emissivity = np.interp(wnum, Mammoth[:,1], Mammoth[:,2]) emissivity[emissivity>1.] = 1. emissivity[emissivity<0.] = 0. #for i in range(len(emissivity)): # if emissivity[i]>1.: # emissivity[i] = 1. # elif emissivity[i]<0.: # emissivity[i] = 0. #emissivity = min(interp1(Mammoth(:,2),Mammoth(:,3),wnum,'linear','extrap'),1); #emissivity = max(emissivity,0); surface_albedo = 1. - emissivity; return surface_albedo # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # def load_od_gas(odfile): ''' Purpose: Load in the matlab generated file because python is too slow for cubic interp and gives small differences But the python way is saved for reference in extras.py ''' odinfo = spio.loadmat(odfile) date = odinfo['date'] nu = odinfo['nu'][0] rads = odinfo['rads'] rad_above = odinfo['rad_above'][0] tsc = odinfo['tsc'] view_angle = odinfo['view_angle'] date_above_bef = odinfo['date_above_bef'] date_above_aft = odinfo['date_above_aft'] Bctc = odinfo['Bc_tsc'] dt_dtau = odinfo['dt_dtau'] # radClr = odinfo['radClr']; # odlyr = odinfo['odlyr'] # print('Loaded od file ' + odfile) return date, view_angle, nu, rads, tsc, rad_above, \ date_above_bef, date_above_aft, Bctc, dt_dtau # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # def load_profiles(prof_file): ''' Load in the profile file ''' # .. Load in the profile with Dataset(prof_file, 'r', format='NETCDF4_CLASSIC') as nc: z = np.double(nc['z'][:].data) P = np.double(nc['P'][:].data) T = np.double(nc['T'][:].data) h2o = np.double(nc['h2o'][:].data) return z, P, T, h2o # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # def load_surface_temperatures(metfname, beg_datetime, end_datetime): ''' Load the surface temperatures from a file ''' with Dataset(metfname, 'r', format= "NETCDF4") as nc: itime = np.logical_and( \ date2index(beg_datetime, nc.variables['time'], select='after'), \ date2index(end_datetime, nc.variables['time'], select='before')) surf_time = num2date(nc.variables['time'][itime], nc.variables['time'].units) surf_temp = nc.variables['temp_mean'][itime] + 273.15 #ikeep = np.logical_and(np.where(surf_time>=beg_datetime)[0], # np.where(surf_time<=end_datetime)[0]) return surf_time, surf_temp # surf_time[ikeep], surf_temp[ikeep] # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # def load_surface_temperatures_for_datetime(metfname, thisdatetime, z, T): ''' Load the surface temperatures from a file ''' with Dataset(metfname, 'r', format= "NETCDF4") as nc: itime = date2index(thisdatetime, nc.variables['time'], select='after') surf_time = num2date(nc.variables['time'][:], nc.variables['time'].units) dd = surf_time[itime-1:itime+1] - thisdatetime dmin = [d.days*24*60 + d.seconds/60 for d in dd] wt = np.flipud(np.abs(dmin)) wt = wt/np.sum(wt) surf_temp = wt[0] * nc.variables['temp_mean'][itime-1] + \ wt[1] * nc.variables['temp_mean'][itime] + 273.15 i1km = np.where(z<=1)[0][-1] Tnew = np.zeros(i1km) Tnew[0] = surf_temp # + 0 m Tnew[1:i1km] = np.interp(z[1:i1km], [z[0], z[i1km]], [Tnew[0], T[i1km]]) return Tnew # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # def get_prof_obsolete(prof_dir, prof_file, dir_lblrtm, z_toa, bwn, ewn): ''' Load in the profile file ''' # .. Load in the profile nc = Dataset(prof_dir + prof_file, 'r', format='NETCDF4_CLASSIC') zm = nc['z'][:] nlyr_toa = (np.abs(zm - z_toa)).argmin() itop = nlyr_toa + 1 # .. Units for ozone are jchar = C for g/kg units = dict({('tm','km'), ('pm','mb'), ('h2o','ppmv'), ('co2','ppmv'), ('o3','gm_kg'), ('hno3','ppmv')}) # .. Set prof values from prof_file, as well as inputs bwn and ewn # viewing angle set to zenith. To output optical depths from LBLRTM, # iemit is set to 0 and imrg to 1. prof = { "v1": bwn, "v2": ewn, "zm": zm[:itop], "pm": nc['P'][:itop], "tm": nc['T'][:itop], "h2o": nc['h2o'][:itop], "co2": nc['co2'][:itop], "o3": nc['o3'][:itop], "hno3": nc['hno3'][:itop], "f11": nc['f11'][:itop], "f12": nc['f12'][:itop], "f113": nc['f113'][:itop], "units": units, "zangle": 0, "fnametape5": dir_lblrtm + "TAPE5" , "model": 0, "modelExtra": 3, "iod": 0 , "iatm": 1, "ipunch": 1, "iemit": 0, "imrg": 1, } # .. Add this later? # if do_refl # prof.surf_refl = surf_refl ; return prof, nlyr_toa # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # def get_prof_pickle(prof_dir, prof_file, dir_lblrtm, z_toa, bwn, ewn): ''' Load in the profile file that was pickled. ''' # .. Load in the profile pstuff = pickle.load(open(prof_dir + prof_file, 'rb')) zm = pstuff.zm nlyr_toa = (np.abs(zm - z_toa)).argmin() itop = nlyr_toa + 1 # .. Set prof values from prof_file, as well as inputs bwn and ewn # viewing angle set to zenith. To output optical depths from LBLRTM, # iemit is set to 0 and imrg to 1. prof = { "v1": bwn, "v2": ewn, "zm": pstuff.zm[:itop], "pm": pstuff.pm[:itop], "tm": pstuff.tm[:itop], "h2o": pstuff.h2o[:itop], "co2": pstuff.co2[:itop], "o3": pstuff.o3[:itop], "hno3": pstuff.hno3[:itop], "f11": pstuff.f11[:itop], "f12": pstuff.f12[:itop], "f113": pstuff.f113[:itop], "units": pstuff.units, "zangle": 0, "fnametape5": dir_lblrtm + "TAPE5" , "model": 0, "modelExtra": 3, "iod": 0 , "iatm": 1, "ipunch": 1, "iemit": 0, "imrg": 1, } # .. Add this later? # if do_refl # prof.surf_refl = surf_refl ; return prof, nlyr_toa # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # def load_profiles_pickle(prof_file): pstuff = pickle.load(open(prof_file, 'rb')) return pstuff.zm, pstuff.pm, pstuff.tm, pstuff.h2o def load_cloud_layers(cloud_layer_file, z, thisdatetime): with Dataset(cloud_layer_file, 'r', format = "NETCDF4") as nc: cloud_mask = nc['cloud_mask'][:].T height = nc['range'][:].data alt0 = nc['altitude'][0].data # .. Get the times mask_date = num2date(nc['time'][:], nc['time'].Description) imask = (np.abs(mask_date - thisdatetime)).argmin() # 0=>no cloud, 1=>ice, 2=>liquid, 3=>unknown, probably ice # Ice below 120 m is probably an artifact if there is not ice above, # so if there is cloud below 120 m, we will ignore it, unless # there is also cloud betwen 120 and 200 m icld_all = cloud_mask[:,imask].data != 0 # .. If no cloud, set variables and return them now if not np.any(icld_all): cloud_layer = array.array('i') has_ice = array.array('i') has_liq = array.array('i') return cloud_layer, has_liq, has_ice alt = alt0 + height[icld_all] mask = cloud_mask[icld_all,imask].data alt_liq = alt[mask==2] alt_ice = alt[np.logical_or(mask==1, mask==3)] if not np.all(alt[alt<=200] >= 120): alt_ice = alt_ice[alt_ice>=120] alt_liq = alt_liq[alt_liq>=120] alt = alt[alt>=120] # .. To make things easy, if there is any cloud within # a model atmospheric layer, set the entire layer to cloudy # Remember we are going top down # Only try the range with cloud (+/- 30 m) alt = alt/1000; alt_liq = alt_liq/1000; alt_ice = alt_ice/1000 iz1 = np.where(z >= alt[-1])[0] if np.any(iz1): iz1 = iz1[-1] else: iz1 = 0 iz2 = np.where(z <= alt[0])[0] if np.any(iz2): iz2 = iz2[0]+1 else: iz2 = len(z)-3 if iz2 >= len(z)-2: iz2 = len(z)-3 if iz2 < iz1: print('pause here!') Npossible = iz2 - iz1 + 1 cloud_layer = array.array('i',(0 for i in range(Npossible))) has_ice = array.array('i',(0 for i in range(Npossible))) has_liq = array.array('i',(0 for i in range(Npossible))) i = 0 for iz in range(iz1,iz2+1): if np.any((alt > z[iz+1]) * (alt <= z[iz])): cloud_layer[i] = iz if np.any((alt_liq > z[iz+1]) * (alt_liq <= z[iz])): has_liq[i] = 1 if np.any((alt_ice > z[iz+1]) * (alt_ice <= z[iz])): has_ice[i] = 1 i += 1 cloud_layer = cloud_layer[:i] has_ice = has_ice[:i] has_liq = has_liq[:i] return cloud_layer, has_liq, has_ice

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def PCA(train, val, test, output_dim): n, dim = train.shape cov_matrix = np.dot(train.T, train)/n w, v = np.linalg.eig(cov_matrix) new_train = train.dot(w[:, :output_dim]) new_val = val.dot(w[:, :output_dim]) new_test = test.dot(w[:, :output_dim]) return new_test, new_val, new_test

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''' Дано 2 дійсних числа. Вивести середнє значення усіх цілих чисел, що знаходяться між цими двома дійсними числами. ''' the_first_float = float(input('enter the first float: ')) the_second_float = float(input('enter the second float: ')) range_1 = int(the_first_float) range_2 = int(the_second_float) for number in range(range_1, range_2+1): my_list = list(' '.join(number)) middle = sum(my_list)/len(my_list) print(middle)

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import unittest import subprocess from functional_tests import constants # This test may start failing once this version is EOL and we either change the # ocp-build-data bugzilla schema or all of the non-shipped builds are garbage-collected. version = "4.3" class FindBuildsTestCase(unittest.TestCase): def test_find_rpms(self): out = subprocess.check_output( constants.ELLIOTT_CMD + [ "--assembly=stream", f"--group=openshift-{version}", "find-builds", "--kind=rpm", ] ) self.assertIn("may be attached to an advisory", out.decode("utf-8")) def test_find_images(self): out = subprocess.check_output( constants.ELLIOTT_CMD + [ f"--group=openshift-{version}", "-i", "openshift-enterprise-cli", "find-builds", "--kind=image", ] ) self.assertIn("may be attached to an advisory", out.decode("utf-8")) def test_change_state(self): """To attach a build to an advisory, it will be attempted to set the advisory to NEW_FILES. This advisory is already SHIPPED_LIVE, and the attempted change should fail""" command = constants.ELLIOTT_CMD + [ f'--group=openshift-{version}', '--images=openshift-enterprise-cli', 'find-builds', '--kind=image', '--attach=57899' ] result = subprocess.run(command, capture_output=True) self.assertEqual(result.returncode, 1) self.assertIn('Cannot change state', result.stdout.decode()) if __name__ == '__main__': unittest.main()

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import pytest from hier_config.host import Host class TestHost: @pytest.fixture(autouse=True) def setup(self, options_ios): self.host = Host("example.rtr", "ios", options_ios) def test_load_config_from(self, running_config, generated_config): self.host.load_running_config(running_config) self.host.load_generated_config(generated_config) assert len(self.host.generated_config) > 0 assert len(self.host.running_config) > 0 def test_load_remediation(self, running_config, generated_config): self.host.load_running_config(running_config) self.host.load_generated_config(generated_config) self.host.remediation_config() assert len(self.host.remediation_config().children) > 0 def test_load_tags(self, tags_ios): self.host.load_tags(tags_ios) assert len(self.host.hconfig_tags) > 0 def test_filter_remediation(self, running_config, generated_config, tags_ios): self.host.load_running_config(running_config) self.host.load_generated_config(generated_config) self.host.load_tags(tags_ios) rem1 = self.host.remediation_config_filtered_text(set(), set()) rem2 = self.host.remediation_config_filtered_text({"safe"}, set()) assert rem1 != rem2

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nickhester/basic_io_python

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import sys import requests # read from file reader = open(sys.argv[1]) inputText = reader.read() reader.close() # call API response = requests.get("http://numbersapi.com/" + inputText, { 'Content-Type': 'application/json' }) if response.status_code != 200: raise Exception("API failed to return a successful response") responseText = response.content.decode('utf-8') # write to file writer = open(sys.argv[2], "w") writer.write(responseText) writer.close()

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/getCorners.py

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# coding=gbk import cv2 img = cv2.imread('g:/dataset/gochessboard/test1/00001.jpg') size = img.shape print size gray = cv2.cvtColor(img, cv2.cv.CV_RGB2GRAY) corners = cv2.goodFeaturesToTrack(gray, 500, 0.05, 10) criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.001) cv2.cornerSubPix(gray, corners, (5, 5), (-1, -1), criteria) for i in range(corners.shape[0]): # print corners[i][0, 0] pt = (corners[i][0, 0], corners[i][0, 1]) cv2.circle(img, pt, 2, cv2.cv.RGB(0, 0, 255), 2) cv2.imshow('', img) cv2.waitKey()

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#!/usr/bin/env python # -*- coding: utf-8 -*- # ----------------------------------------------------------------------------- # Copyright (C) 2013 Nicolas P. Rougier. All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # # 2. Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # # THIS SOFTWARE IS PROVIDED BY NICOLAS P. ROUGIER ''AS IS'' AND ANY EXPRESS OR # IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF # MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO # EVENT SHALL NICOLAS P. ROUGIER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, # INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES # (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND # ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF # THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # # The views and conclusions contained in the software and documentation are # those of the authors and should not be interpreted as representing official # policies, either expressed or implied, of Nicolas P. Rougier. # ----------------------------------------------------------------------------- import sys import numpy as np import OpenGL.GL as gl import OpenGL.GLUT as glut from scipy.spatial import cKDTree from scipy.spatial.distance import cdist def graph(links = [(0,1), (1,2), (2,3), (3,0), (0,2), (1,3), (3,4), (4,5), (5,6), (6,7), (7,8), (8,9), (9,10), (10,7), (8,10), (7,9) ]): ntype = np.dtype( [('position', 'f4', 2), ('previous', 'f4', 2), ('weight', 'f4', 1), ('charge', 'f4', 1), ('fixed', 'b', 1)] ) ltype = np.dtype( [('source', 'i4', 1), ('target', 'i4', 1), ('strength', 'f4', 1), ('distance', 'f4', 1)] ) L = np.array(links).reshape(len(links),2) L -= L.min() n = L.max()+1 nodes = np.zeros(n, ntype) nodes['position'] = np.random.uniform(256-32, 256+32, (n,2)) nodes['previous'] = nodes['position'] nodes['fixed'] = False nodes['weight'] = 1 nodes['charge'] = 1 l = len(L) links = np.zeros( n+l, ltype) links[:n]['source'] = np.arange(0,n) links[:n]['target'] = np.arange(0,n) links[n:]['source'] = L[:,0] links[n:]['target'] = L[:,1] links['distance'] = 25 links['strength'] = 5 I = np.argwhere(links['source']==links['target']) links['distance'][I] = links['strength'][I] = 0 return nodes,links # ----------------------------------------------------------------------------- def relaxation(nodes, links): """ Gauss-Seidel relaxation for links """ sources_idx = links['source'] targets_idx = links['target'] sources = nodes[sources_idx] targets = nodes[targets_idx] distances = links['distance'] strengths = links['strength'] D = (targets['position'] - sources['position']) L = np.sqrt((D*D).sum(axis=1)) # This avoid to test L != 0 (I = np.where(L>0)) L = np.where(L,L,np.NaN) L = strengths * (L-distances) /L # Replace nan by 0, i.e. where L was 0 L = np.nan_to_num(L) D *= L.reshape(len(L),1) K = sources['weight'] / (sources['weight'] + targets['weight']) K = K.reshape(len(K),1) # Note that a direct nodes['position'][links['source']] += K*D*(1-F) # would't work as expected because of repeated indices F = nodes['fixed'][sources_idx].reshape(len(links),1) W = K*D*(1-F) * 0.1 nodes['position'][:,0] += np.bincount(sources_idx, W[:,0], minlength=len(nodes)) nodes['position'][:,1] += np.bincount(sources_idx, W[:,1], minlength=len(nodes)) F = nodes['fixed'][targets_idx].reshape(len(links),1) W = (1-K)*D*(1-F) * 0.1 nodes['position'][:,0] -= np.bincount(targets_idx, W[:,0], minlength=len(nodes)) nodes['position'][:,1] -= np.bincount(targets_idx, W[:,1], minlength=len(nodes)) # ----------------------------------------------------------------------------- def repulsion(nodes, links): P = nodes['position'] n = len(P) X,Y = P[:,0],P[:,1] dX,dY = np.subtract.outer(X,X), np.subtract.outer(Y,Y) dist = cdist(P,P) dist = np.where(dist, dist, 1) D = np.empty((n,n,2)) D[...,0] = dX/dist D[...,1] = dY/dist D = np.nan_to_num(D) R = D.sum(axis=1) L = np.sqrt(((R*R).sum(axis=0))) R /= L F = nodes['fixed'].reshape(len(nodes),1) P += 5*R*(1-F) # ----------------------------------------------------------------------------- def attraction(nodes, links): P = nodes['position'] F = nodes['fixed'].reshape(len(nodes),1) P += 0.01*((256,256) - P) * (1-F) # ----------------------------------------------------------------------------- def integration(nodes, links): P = nodes['position'].copy() F = nodes['fixed'].reshape(len(nodes),1) nodes['position'] -= ((nodes['previous']-P)*.9) * (1-F) nodes['previous'] = P # ------------------------------------- def on_display(): gl.glClearColor(1,1,1,1); gl.glClear(gl.GL_COLOR_BUFFER_BIT | gl.GL_DEPTH_BUFFER_BIT) lines.draw() circles.draw() glut.glutSwapBuffers() # ------------------------------------- def on_reshape(width, height): gl.glViewport(0, 0, width, height) # ------------------------------------- def on_keyboard(key, x, y): if key == '\033': sys.exit() # ------------------------------------- def on_mouse(button, state, x, y): global drag, index drag = False nodes['fixed'] = False nodes['weight'] = 1 if state == 0: _,_,w,h = gl.glGetIntegerv( gl.GL_VIEWPORT ) P = nodes['position'] - (x,h-y) D = np.sqrt((P**2).sum(axis=1)) index = np.argmin(D) if D[index] < 10: nodes['fixed'][index] = True nodes['weight'][index] = 0.01 drag = True # ------------------------------------- def on_motion(x, y): global drag, mouse, index if drag: _,_,w,h = gl.glGetIntegerv( gl.GL_VIEWPORT ) nodes['position'][index] = x,h-y P = nodes['position'] circles.vertices.data['a_center'] = np.repeat(P,4,axis=0) circles._vbuffer._dirty = True src = nodes[links['source']]['position'] tgt = nodes[links['target']]['position'] src = np.repeat(src,4,axis=0) lines.vertices.data['a_p0'] = src tgt = np.repeat(tgt,4,axis=0) lines.vertices.data['a_p1'] = tgt lines._vbuffer._dirty = True glut.glutPostRedisplay() # ------------------------------------- def on_timer(fps): relaxation(nodes,links) repulsion(nodes,links) attraction(nodes,links) integration(nodes,links) # Update collection P = nodes['position'] circles.vertices.data['a_center'] = np.repeat(P,4,axis=0) circles._vbuffer._dirty = True src = nodes[links['source']]['position'] tgt = nodes[links['target']]['position'] src = np.repeat(src,4,axis=0) lines.vertices.data['a_p0'] = src tgt = np.repeat(tgt,4,axis=0) lines.vertices.data['a_p1'] = tgt lines._vbuffer._dirty = True glut.glutTimerFunc(1000/fps, on_timer, fps) glut.glutPostRedisplay() # ----------------------------------------------------------------------------- if __name__ == '__main__': from glagg import LineCollection, CircleCollection glut.glutInit(sys.argv) glut.glutInitDisplayMode(glut.GLUT_DOUBLE | glut.GLUT_RGB | glut.GLUT_DEPTH) glut.glutInitWindowSize(512, 512) glut.glutCreateWindow("Dynamic graph") glut.glutDisplayFunc(on_display) glut.glutReshapeFunc(on_reshape) glut.glutKeyboardFunc(on_keyboard) glut.glutMouseFunc(on_mouse) glut.glutMotionFunc(on_motion) nodes,links = graph( ) circles = CircleCollection() lines = LineCollection() for node in nodes: position = node['position'] circles.append(center = position, radius=5, linewidth=2, fg_color=(1,1,1,1), bg_color=(1,.5,.5,1)) src = nodes[links['source']]['position'] tgt = nodes[links['target']]['position'] V = np.array(zip(src,tgt)).reshape(2*len(src),2) lines.append(V, linewidth=1.5, color=(0.75,0.75,0.75,1.00)) drag,index = False, -1 fps = 60 glut.glutTimerFunc(1000/fps, on_timer, fps) glut.glutMainLoop()

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from django.db import models # Create your models here. class Account(models.Model): title = models.CharField(max_length=120)

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import sys class CustomException(Exception): def __init__(self, msg: str): super().__init__(f"custom message here") def exceptions_resolver(instance): if "message" in instance: return sys.exit(f"Commander: {instance.message}") else: return sys.exit(f"Commander: {instance}")

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""" Utilities for creating models and saving them in DB """ import datetime import json from functools import singledispatch from typing import Dict from marshmallow import ValidationError from marshmallow.schema import Schema from requests import Session from sqlalchemy.orm import make_transient from sqlalchemy import func from service_api import LOGGER, Base, session_scope from ..exceptions import (MetaDataError, ModelNotFoundException, ObjectNotFoundException) from ..models import Realty, RealtyDetails from ..schemas import RealtyDetailsSchema, RealtySchema @singledispatch def load_data(model_schema: Schema, data: Dict, model: Base) -> Base: """ Stores data in a database according to a given scheme """ try: valid_data = model_schema.load(data) record = model(**valid_data) except ValidationError as error: LOGGER.error("Error message:%s, data for validation %s", error, valid_data) raise with session_scope() as session: existing_record = session.query(model).filter_by(**valid_data).first() if existing_record is None: session.add(record) return existing_record or record @load_data.register def _(model_schema: RealtyDetailsSchema, data: Dict, model: RealtyDetails): try: valid_data = model_schema.load(data) realty_details_record = model(**valid_data) except ValidationError as error: LOGGER.error(error) raise with session_scope() as session: realty_details = session.query(model).filter_by( original_url=realty_details_record.original_url, version=realty_details_record.version).first() if realty_details is not None: incoming_data = model_schema.dump(realty_details_record) db_data = model_schema.dump(realty_details) incoming_data.pop("id") db_data.pop("id") if incoming_data == db_data: return realty_details with session_scope() as session: session.expire_on_commit = False session.query(model).filter_by( original_url=realty_details.original_url, version=realty_details.version).update( {"version": datetime.datetime.now()}) session.add(realty_details_record) session.commit() realty_record = session.query(Realty).filter_by( realty_details_id=realty_details.id).first() new_realty_details_id = session.query(model).filter_by( original_url=realty_details_record.original_url, version=realty_details_record.version).first().id make_transient(realty_record) realty_record.realty_details_id = new_realty_details_id realty_record.id = None del realty_record.id session.add(realty_record) with session_scope() as session: session.query(Realty).filter_by( realty_details_id=model_schema.dump(realty_details).get("id")).update( {"version": datetime.datetime.now()}) with session_scope() as session: session.add(realty_details_record) return realty_details_record @load_data.register def _(model_schema: RealtySchema, data: Dict, model: Realty): try: valid_data = model_schema.load(data) realty_record = model(**valid_data) LOGGER.debug("record.realty_details_id: %s", str(realty_record.realty_details_id)) except ValidationError as error: LOGGER.error(error) raise with session_scope() as session: realty = session.query(model).filter_by(realty_details_id=realty_record.realty_details_id).first() if realty is None: with session_scope() as session: session.add(realty_record) return realty or realty_record def open_metadata(path: str) -> Dict: """ Open file with metadata and return content """ try: with open(path, encoding="utf-8") as meta_file: metadata = json.load(meta_file) except json.JSONDecodeError as error: LOGGER.error(error) raise MetaDataError from error except FileNotFoundError as error: LOGGER.error("Invalid metadata path, or metadata.json file does not exist") raise MetaDataError from error return metadata def recognize_by_alias(model: Base, alias: str, set_=None): """ Finds model record by alias. If set param is passed that alias is searched in that set :param model: Base :param alias: str :param set_: optional :returns: model instance :raises: ModelNotFoundException, ObjectNotFoundException """ try: table_of_aliases = model.aliases.mapper.class_ except AttributeError as error: LOGGER.error(error) raise ModelNotFoundException(desc="Model {} doesn't have aliases attribute".format(model)) from error with session_scope() as session: set_ = set_ or session.query(model) obj = set_.join(table_of_aliases, table_of_aliases.entity_id == model.id).filter( func.lower(table_of_aliases.alias) == alias.lower()).first() if obj is None: raise ObjectNotFoundException(message="Record for alias: {} not found".format(alias)) return obj def send_request(method: str, url: str, request_session: Session = None, *args, **kwargs): """ Wrapper for sending requests """ request_session = request_session or Session() response = request_session.request(method, url, *args, **kwargs) from ..services.limitation import LimitationSystem LimitationSystem().mark_token_after_request(response.url) return response def chunkify(number, pieces): """ Devide number on almost equal pieces """ return [number//pieces]*(pieces-1) + [sum(divmod(number, pieces))]

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n, k = map(int, input().split()) actions = input() actions = actions.replace("undo ", "*") actions = actions.split() # print(actions) childQueue = [] for x in range(n): childQueue.append(x) revchildQueue = list(reversed(childQueue)) # print(childQueue, revchildQueue) current = [0] # print('a, index location, value at index, current array') for a in actions: try: if int(a) > 0: current.append(childQueue[(current[-1] + int(a)) % n]) # print(a, (current[-1] + int(a)) % n, childQueue[(current[-1] + int(a)) % n], current) # print(current) elif int(a) < 0: current.append(revchildQueue[(current[-1] + int(a)) % n]) # print(a, (current[-1] + int(a)) % n, revchildQueue[(current[-1] + int(a)) % n], current) # print(current) except: if a[0] == "*": if int(a[1]) == 0: pass # print(current) else: current = current[:-int(a[1])] # print(a[1], current) # print(Undo) # print("\n\nFinal Solution") print(current[-1])

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import pandas as pd import pytest from flaky import flaky from pytest import mark from sklearn import linear_model import dowhy import dowhy.datasets from dowhy import CausalModel class TestCausalModel(object): @mark.parametrize( ["beta", "num_samples", "num_treatments"], [ (10, 100, 1), ], ) def test_external_estimator(self, beta, num_samples, num_treatments): num_common_causes = 5 data = dowhy.datasets.linear_dataset( beta=beta, num_common_causes=num_common_causes, num_samples=num_samples, num_treatments=num_treatments, treatment_is_binary=True, ) model = CausalModel( data=data["df"], treatment=data["treatment_name"], outcome=data["outcome_name"], graph=data["gml_graph"], proceed_when_unidentifiable=True, test_significance=None, ) identified_estimand = model.identify_effect(proceed_when_unidentifiable=True) estimate = model.estimate_effect( identified_estimand, method_name="backdoor.tests.causal_estimators.mock_external_estimator.PropensityScoreWeightingEstimator", control_value=0, treatment_value=1, target_units="ate", # condition used for CATE confidence_intervals=True, method_params={"propensity_score_model": linear_model.LogisticRegression(max_iter=1000)}, ) assert estimate.estimator.propensity_score_model.max_iter == 1000 @mark.parametrize( ["beta", "num_instruments", "num_samples", "num_treatments"], [ (10, 1, 100, 1), ], ) def test_graph_input(self, beta, num_instruments, num_samples, num_treatments): num_common_causes = 5 data = dowhy.datasets.linear_dataset( beta=beta, num_common_causes=num_common_causes, num_instruments=num_instruments, num_samples=num_samples, num_treatments=num_treatments, treatment_is_binary=True, ) model = CausalModel( data=data["df"], treatment=data["treatment_name"], outcome=data["outcome_name"], graph=data["gml_graph"], proceed_when_unidentifiable=True, test_significance=None, ) # removing two common causes gml_str = 'graph[directed 1 node[ id "{0}" label "{0}"]node[ id "{1}" label "{1}"]node[ id "Unobserved Confounders" label "Unobserved Confounders"]edge[source "{0}" target "{1}"]edge[source "Unobserved Confounders" target "{0}"]edge[source "Unobserved Confounders" target "{1}"]node[ id "X0" label "X0"] edge[ source "X0" target "{0}"] node[ id "X1" label "X1"] edge[ source "X1" target "{0}"] node[ id "X2" label "X2"] edge[ source "X2" target "{0}"] edge[ source "X0" target "{1}"] edge[ source "X1" target "{1}"] edge[ source "X2" target "{1}"] node[ id "Z0" label "Z0"] edge[ source "Z0" target "{0}"]]'.format( data["treatment_name"][0], data["outcome_name"] ) print(gml_str) model = CausalModel( data=data["df"], treatment=data["treatment_name"], outcome=data["outcome_name"], graph=gml_str, proceed_when_unidentifiable=True, test_significance=None, missing_nodes_as_confounders=True, ) common_causes = model.get_common_causes() assert all(node_name in common_causes for node_name in ["X1", "X2"]) @mark.parametrize( ["beta", "num_instruments", "num_samples", "num_treatments"], [ (10, 1, 100, 1), ], ) def test_graph_input2(self, beta, num_instruments, num_samples, num_treatments): num_common_causes = 5 data = dowhy.datasets.linear_dataset( beta=beta, num_common_causes=num_common_causes, num_instruments=num_instruments, num_samples=num_samples, num_treatments=num_treatments, treatment_is_binary=True, ) model = CausalModel( data=data["df"], treatment=data["treatment_name"], outcome=data["outcome_name"], graph=data["gml_graph"], proceed_when_unidentifiable=True, test_significance=None, ) # removing two common causes gml_str = """graph[ directed 1 node[ id "{0}" label "{0}" ] node [ id "{1}" label "{1}" ] node [ id "Unobserved Confounders" label "Unobserved Confounders" ] edge[ source "{0}" target "{1}" ] edge[ source "Unobserved Confounders" target "{0}" ] edge[ source "Unobserved Confounders" target "{1}" ] node[ id "X0" label "X0" ] edge[ source "X0" target "{0}" ] node[ id "X1" label "X1" ] edge[ source "X1" target "{0}" ] node[ id "X2" label "X2" ] edge[ source "X2" target "{0}" ] edge[ source "X0" target "{1}" ] edge[ source "X1" target "{1}" ] edge[ source "X2" target "{1}" ] node[ id "Z0" label "Z0" ] edge[ source "Z0" target "{0}" ]]""".format( data["treatment_name"][0], data["outcome_name"] ) print(gml_str) model = CausalModel( data=data["df"], treatment=data["treatment_name"], outcome=data["outcome_name"], graph=gml_str, proceed_when_unidentifiable=True, test_significance=None, missing_nodes_as_confounders=True, ) common_causes = model.get_common_causes() assert all(node_name in common_causes for node_name in ["X1", "X2"]) @mark.parametrize( ["beta", "num_instruments", "num_samples", "num_treatments"], [ (10, 1, 100, 1), ], ) def test_graph_input3(self, beta, num_instruments, num_samples, num_treatments): num_common_causes = 5 data = dowhy.datasets.linear_dataset( beta=beta, num_common_causes=num_common_causes, num_instruments=num_instruments, num_samples=num_samples, num_treatments=num_treatments, treatment_is_binary=True, ) model = CausalModel( data=data["df"], treatment=data["treatment_name"], outcome=data["outcome_name"], graph=data["gml_graph"], proceed_when_unidentifiable=True, test_significance=None, ) # removing two common causes gml_str = """dag { "Unobserved Confounders" [pos="0.491,-1.056"] X0 [pos="-2.109,0.057"] X1 [adjusted, pos="-0.453,-1.562"] X2 [pos="-2.268,-1.210"] Z0 [pos="-1.918,-1.735"] v0 [latent, pos="-1.525,-1.293"] y [outcome, pos="-1.164,-0.116"] "Unobserved Confounders" -> v0 "Unobserved Confounders" -> y X0 -> v0 X0 -> y X1 -> v0 X1 -> y X2 -> v0 X2 -> y Z0 -> v0 v0 -> y } """ print(gml_str) model = CausalModel( data=data["df"], treatment=data["treatment_name"], outcome=data["outcome_name"], graph=gml_str, proceed_when_unidentifiable=True, test_significance=None, missing_nodes_as_confounders=True, ) common_causes = model.get_common_causes() assert all(node_name in common_causes for node_name in ["X1", "X2"]) all_nodes = model._graph.get_all_nodes(include_unobserved=True) assert all( node_name in all_nodes for node_name in ["Unobserved Confounders", "X0", "X1", "X2", "Z0", "v0", "y"] ) all_nodes = model._graph.get_all_nodes(include_unobserved=False) assert "Unobserved Confounders" not in all_nodes @mark.parametrize( ["beta", "num_instruments", "num_samples", "num_treatments"], [ (10, 1, 100, 1), ], ) def test_graph_input4(self, beta, num_instruments, num_samples, num_treatments): num_common_causes = 5 data = dowhy.datasets.linear_dataset( beta=beta, num_common_causes=num_common_causes, num_instruments=num_instruments, num_samples=num_samples, num_treatments=num_treatments, treatment_is_binary=True, ) model = CausalModel( data=data["df"], treatment=data["treatment_name"], outcome=data["outcome_name"], graph=data["gml_graph"], proceed_when_unidentifiable=True, test_significance=None, ) # removing two common causes gml_str = "tests/sample_dag.txt" print(gml_str) model = CausalModel( data=data["df"], treatment=data["treatment_name"], outcome=data["outcome_name"], graph=gml_str, proceed_when_unidentifiable=True, test_significance=None, missing_nodes_as_confounders=True, ) common_causes = model.get_common_causes() assert all(node_name in common_causes for node_name in ["X1", "X2"]) all_nodes = model._graph.get_all_nodes(include_unobserved=True) assert all( node_name in all_nodes for node_name in ["Unobserved Confounders", "X0", "X1", "X2", "Z0", "v0", "y"] ) all_nodes = model._graph.get_all_nodes(include_unobserved=False) assert "Unobserved Confounders" not in all_nodes @mark.parametrize( ["num_variables", "num_samples"], [ (5, 5000), ], ) @flaky(max_runs=3) def test_graph_refutation(self, num_variables, num_samples): data = dowhy.datasets.dataset_from_random_graph(num_vars=num_variables, num_samples=num_samples) df = data["df"] model = CausalModel( data=df, treatment=data["treatment_name"], outcome=data["outcome_name"], graph=data["gml_graph"], ) graph_refutation_object = model.refute_graph( k=1, independence_test={ "test_for_continuous": "partial_correlation", "test_for_discrete": "conditional_mutual_information", }, ) assert graph_refutation_object.refutation_result == True @mark.parametrize( ["num_variables", "num_samples"], [ (10, 5000), ], ) def test_graph_refutation2(self, num_variables, num_samples): data = dowhy.datasets.dataset_from_random_graph(num_vars=num_variables, num_samples=num_samples) df = data["df"] gml_str = """ graph [ directed 1 node [ id 0 label "a" ] node [ id 1 label "b" ] node [ id 2 label "c" ] node [ id 3 label "d" ] node [ id 4 label "e" ] node [ id 5 label "f" ] node [ id 6 label "g" ] node [ id 7 label "h" ] node [ id 8 label "i" ] node [ id 9 label "j" ] edge [ source 0 target 1 ] edge [ source 0 target 3 ] edge [ source 3 target 2 ] edge [ source 7 target 4 ] edge [ source 6 target 5 ] edge [ source 7 target 8 ] edge [ source 9 target 2 ] edge [ source 9 target 8 ] ] """ model = CausalModel( data=df, treatment=data["treatment_name"], outcome=data["outcome_name"], graph=gml_str, ) graph_refutation_object = model.refute_graph( k=2, independence_test={ "test_for_continuous": "partial_correlation", "test_for_discrete": "conditional_mutual_information", }, ) assert graph_refutation_object.refutation_result == False def test_unobserved_graph_variables_log_warning(self, caplog): data = dowhy.datasets.linear_dataset( beta=10, num_common_causes=3, num_instruments=1, num_effect_modifiers=1, num_samples=3, treatment_is_binary=True, stddev_treatment_noise=2, num_discrete_common_causes=1, ) df = data["df"] # Remove graph variable with name "W0" from observed data. df = df.drop(columns=["W0"]) expected_warning_message_regex = ( "1 variables are assumed unobserved because they are not in the " "dataset. Configure the logging level to `logging.WARNING` or " "higher for additional details." ) with pytest.warns( UserWarning, match=expected_warning_message_regex, ): _ = CausalModel( data=df, treatment=data["treatment_name"], outcome=data["outcome_name"], graph=data["gml_graph"], ) # Ensure that a log record exists that provides a more detailed view # of observed and unobserved graph variables (counts and variable names.) expected_logging_message = ( "The graph defines 7 variables. 6 were found in the dataset " "and will be analyzed as observed variables. 1 were not found " "in the dataset and will be analyzed as unobserved variables. " "The observed variables are: '['W1', 'W2', 'X0', 'Z0', 'v0', 'y']'. " "The unobserved variables are: '['W0']'. " "If this matches your expectations for observations, please continue. " "If you expected any of the unobserved variables to be in the " "dataframe, please check for typos." ) assert any( log_record for log_record in caplog.records if ( (log_record.name == "dowhy.causal_model") and (log_record.levelname == "WARNING") and (log_record.message == expected_logging_message) ) ), ( "Expected logging message informing about unobserved graph variables " "was not found. Expected a logging message to be emitted in module `dowhy.causal_model` " f"and with level `logging.WARNING` and this content '{expected_logging_message}'. " f"Only the following log records were emitted instead: '{caplog.records}'." ) if __name__ == "__main__": pytest.main([__file__])

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from django.shortcuts import render from django.views.decorators.http import require_http_methods import json from django.http import HttpResponse from libs import github_query, date_filter from forms import QueryForm def index(request): return render(request, 'lazyhub/index.html') @require_http_methods(['GET']) def query(request, account, days): data = {'error': {'account': False, 'days': False}} if request.is_ajax(): form = QueryForm({'account': account, 'days': days}) if form.is_valid(): account = form.cleaned_data['account'] days = form.cleaned_data['days'] data['data'] = github_query(account) data['data'] = date_filter(data['data'], days) else: for k, v in data['error'].iteritems(): if k in form.errors: data['error'][k] = True data = json.dumps(data) return HttpResponse(data, content_type='application/json')

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Rafaelbarr/100DaysOfCodeChallenge

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/day006/001_100_years_old.py

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# -*- coding: utf-8 -*- #This program asks te user for his/her name and age #Then return the year he/she will be 100 years old def run(): #Data input name = raw_input('What\'s your name?: ') age = int(raw_input('What\'s your age?: ')) #Result calculation older = (2018 - age) + 100 #Result output print('You\'ll be 100 years old in the {} year!'.format(older)) if __name__ == '__main__': run()

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# Copyright 2021 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ import os import numpy as np from mindspore.communication.management import get_rank from mindspore import Tensor from mindspore import Parameter from mindspore import context from mindspore.ops import operations as P import mindspore.nn as nn from mindspore.train import Model from mindspore.context import ParallelMode from mindspore.communication.management import init from mindspore.communication.management import get_group_size class FakeDataInitMode: RandomInit = 0 OnesInit = 1 UniqueInit = 2 ZerosInit = 3 class FakeData: def __init__(self, size=1024, batch_size=32, image_size=(3, 224, 224), num_class=10, random_offset=0, use_parallel=False, fakedata_mode=FakeDataInitMode.RandomInit): self.size = size self.rank_batch_size = batch_size self.total_batch_size = self.rank_batch_size self.random_offset = random_offset self.image_size = image_size self.num_class = num_class self.rank_size = 1 self.rank_id = 0 self.batch_index = 0 self.image_data_type = np.float32 self.label_data_type = np.float32 self.is_onehot = True self.fakedata_mode = fakedata_mode if use_parallel: if 'CONTEXT_DEVICE_TARGET' in os.environ and os.environ['CONTEXT_DEVICE_TARGET'] == 'GPU': init(backend_name='nccl') else: init(backend_name='hccl') self.rank_size = get_group_size() self.rank_id = get_rank() self.total_batch_size = self.rank_batch_size * self.rank_size assert self.size % self.total_batch_size == 0 self.total_batch_data_size = (self.rank_size, self.rank_batch_size) + image_size def get_dataset_size(self): return int(self.size / self.total_batch_size) def get_reeat_count(self): return 1 def set_image_data_type(self, data_type): self.image_data_type = data_type def set_label_data_type(self, data_type): self.label_data_type = data_type def set_label_onehot(self, is_onehot=True): self.is_onehot = is_onehot def create_tuple_iterator(self, num_epochs=-1, do_copy=False): return self def __getitem__(self, batch_index): if batch_index * self.total_batch_size >= len(self): raise IndexError("{} index out of range".format(self.__class__.__name__)) rng_state = np.random.get_state() np.random.seed(batch_index + self.random_offset) if self.fakedata_mode == FakeDataInitMode.OnesInit: img = np.ones(self.total_batch_data_size) elif self.fakedata_mode == FakeDataInitMode.ZerosInit: img = np.zeros(self.total_batch_data_size) elif self.fakedata_mode == FakeDataInitMode.UniqueInit: total_size = 1 for i in self.total_batch_data_size: total_size = total_size* i img = np.reshape(np.arange(total_size)*0.0001, self.total_batch_data_size) else: img = np.random.randn(*self.total_batch_data_size) target = np.random.randint(0, self.num_class, size=(self.rank_size, self.rank_batch_size)) np.random.set_state(rng_state) img = img[self.rank_id] target = target[self.rank_id] img_ret = img.astype(self.image_data_type) target_ret = target.astype(self.label_data_type) if self.is_onehot: target_onehot = np.zeros(shape=(self.rank_batch_size, self.num_class)) target_onehot[np.arange(self.rank_batch_size), target] = 1 target_ret = target_onehot.astype(self.label_data_type) return Tensor(img_ret), Tensor(target_ret) def __len__(self): return self.size def __iter__(self): self.batch_index = 0 return self def reset(self): self.batch_index = 0 def __next__(self): if self.batch_index * self.total_batch_size < len(self): data = self[self.batch_index] self.batch_index += 1 return data raise StopIteration class NetWithSparseGatherV2(nn.Cell): def __init__(self, strategy=None, sparse=True): super(NetWithSparseGatherV2, self).__init__() self.axis = 0 self.sparse = sparse if sparse: self.weight = Parameter(Tensor(np.ones([8, 8]).astype(np.float32)), name="weight") self.gather = P.SparseGatherV2() else: self.weight = Parameter(Tensor(np.ones([8, 8]).astype(np.float32)), name="weight") self.gather = P.Gather() if strategy is not None: self.gather.shard(strategy) def construct(self, indices): x = self.gather(self.weight, indices, self.axis) return x def train_mindspore_impl(self, indices, epoch, batch_size, use_parallel=True): ds = FakeData(size=8, batch_size=batch_size, num_class=8, image_size=(), use_parallel=use_parallel) ds.set_image_data_type(np.int32) net = self net.set_train() loss = nn.SoftmaxCrossEntropyWithLogits() optimizer = nn.Adam(net.trainable_params()) optimizer.target = "CPU" model = Model(net, loss, optimizer) for _ in range(epoch): model.train(1, ds, dataset_sink_mode=False) output = net(indices) return output def test_allreduce_sparsegatherv2_adam_auto_parallel(): context.set_context(mode=context.GRAPH_MODE, device_target='Ascend') init(backend_name='hccl') context.set_auto_parallel_context(parallel_mode=ParallelMode.AUTO_PARALLEL, device_num=8, gradients_mean=True) indices = Tensor(np.array([0, 1, 2, 3, 4, 5, 6, 7]).astype(np.int32)) epoch = 3 batch_size = 1 net = NetWithSparseGatherV2(sparse=True) output_sparse = net.train_mindspore_impl(indices, epoch, batch_size) net = NetWithSparseGatherV2(sparse=False) output = net.train_mindspore_impl(indices, epoch, batch_size) assert np.allclose(output.asnumpy(), output_sparse.asnumpy(), 0.001, 0.001)

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# coding:utf-8 import socket # 服务端 s = socket.socket() s.bind(('127.0.0.1', 6666)) s.listen(5) while True: c,addr = s.accept() print('连接地址',addr) c.send('welcome') c.close()

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