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values | repo_url
stringlengths 26
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stringlengths 40
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stringlengths 40
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classes | gha_event_created_at
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timestamp[ns] | gha_pushed_at
timestamp[ns] | gha_size
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
chauhanmahavir/Python-Basics | 1,451,698,993,417 | 150b146df5fa9df6739f0c9bc39e52250203fb43 | 5d6207228773ab7d0dbb350bb40f78d8950961c0 | /1.py | 26fc628414b5bdc52a6e46febfa51d118f570d66 | [
"MIT"
]
| permissive | https://github.com/chauhanmahavir/Python-Basics | bde2adfaec4155f7756e479b3008bad4985ba808 | c250a9eee203e1188a968ba2c60262442719fa49 | refs/heads/master | 2023-01-14T22:05:09.121935 | 2020-11-18T07:11:08 | 2020-11-18T07:11:08 | 285,190,795 | 1 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | print("this is my first example");
print('this is my first example')
print('this is my first example');
print("I'have");
print('i say "Hello"');
print('I\'have');
print('hii'+' hello');
print(' hiii','hello');
#print('hello',5)
#print('hello'+5)
print('Another');
#print(5+'hello');
print('c/Users/Desktop/newfile')
| UTF-8 | Python | false | false | 334 | py | 44 | 1.py | 41 | 0.616766 | 0.607784 | 0 | 13 | 23.692308 | 34 |
uc-cdis/cloud-automation | 11,020,886,108,583 | 187b373c5cb4b445ec117a368b3d0a1ccc164b5a | 30a3fb90601e0e4a91e9792bce7ac668f3163c11 | /apis_configs/fence_settings.py | eb2cf818d9462c3b2bb43dfc0da59102e01e155b | [
"Apache-2.0"
]
| permissive | https://github.com/uc-cdis/cloud-automation | dbea462b2cb80db52fd6ebeb4a4ccc3c4a7a560c | 607ef49e304358732f018c0c2c3c5ef8bdef2647 | refs/heads/master | 2023-09-01T15:54:29.625525 | 2023-08-31T15:38:47 | 2023-08-31T15:38:47 | 74,061,703 | 44 | 76 | Apache-2.0 | false | 2023-09-14T19:17:56 | 2016-11-17T19:48:51 | 2023-06-27T02:57:01 | 2023-09-14T19:17:54 | 35,813 | 38 | 68 | 206 | Shell | false | false | from boto.s3.connection import OrdinaryCallingFormat
import config_helper
APP_NAME = "fence"
DB = "postgresql://{{db_username}}:{{db_password}}@{{db_host}}:5432/{{db_database}}"
MOCK_AUTH = False
MOCK_STORAGE = True
EMAIL_SERVER = "localhost"
SEND_FROM = "phillis.tt@gmail.com"
SEND_TO = "phillis.tt@gmail.com"
CEPH = {
"aws_access_key_id": "",
"aws_secret_access_key": "",
"host": "",
"port": 443,
"is_secure": True,
"calling_format": OrdinaryCallingFormat(),
}
AWS = {"aws_access_key_id": "", "aws_secret_access_key": ""}
HMAC_ENCRYPTION_KEY = "{{hmac_key}}"
HOSTNAME = "{{hostname}}"
BASE_URL = "https://{{hostname}}/user"
OPENID_CONNECT = {
"google": {
"client_id": "{{google_client_id}}",
"client_secret": "{{google_client_secret}}",
"redirect_url": "https://" + HOSTNAME + "/user/login/google/login/",
}
}
HTTP_PROXY = {"host": "cloud-proxy.internal.io", "port": 3128}
DEFAULT_DBGAP = {
"sftp": {
"host": "",
"username": "",
"password": "",
"port": 22,
"proxy": "",
"proxy_user": "",
},
"decrypt_key": "",
}
STORAGE_CREDENTIALS = {}
# aws_credentials should be a dict looks like:
# { identifier: { 'aws_access_key_id': 'XXX', 'aws_secret_access_key': 'XXX' }}
AWS_CREDENTIALS = {}
# s3_buckets should be a dict looks like:
# { bucket_name: credential_identifie }
S3_BUCKETS = {}
def load_json(file_name):
return config_helper.load_json(file_name, APP_NAME)
def get_from_dict(dictionary, key, default=""):
value = dictionary.get(key)
if value is None:
value = default
return value
creds = load_json("creds.json")
key_list = ["db_username", "db_password", "db_host", "db_database"]
DB = "postgresql://%s:%s@%s:5432/%s" % tuple(
[get_from_dict(creds, k, "unknown-" + k) for k in key_list]
)
HMAC_ENCRYPTION_KEY = get_from_dict(creds, "hmac_key", "unknown-hmac_key")
HOSTNAME = get_from_dict(creds, "hostname", "unknown-hostname")
BASE_URL = "https://%s/user" % HOSTNAME
OPENID_CONNECT["google"]["client_id"] = get_from_dict(
creds, "google_client_id", "unknown-google_client_id"
)
OPENID_CONNECT["google"]["client_secret"] = get_from_dict(
creds, "google_client_secret", "unknown-google_client_secret"
)
OPENID_CONNECT["google"]["redirect_url"] = (
"https://" + HOSTNAME + "/user/login/google/login/"
)
GOOGLE_MANAGED_SERVICE_ACCOUNT_DOMAINS = {
"dataflow-service-producer-prod.iam.gserviceaccount.com",
"cloudbuild.gserviceaccount.com",
"cloud-ml.google.com.iam.gserviceaccount.com",
"container-engine-robot.iam.gserviceaccount.com",
"dataflow-service-producer-prod.iam.gserviceaccount.com",
"sourcerepo-service-accounts.iam.gserviceaccount.com",
"dataproc-accounts.iam.gserviceaccount.com",
"gae-api-prod.google.com.iam.gserviceaccount.com",
"genomics-api.google.com.iam.gserviceaccount.com",
"containerregistry.iam.gserviceaccount.com",
"container-analysis.iam.gserviceaccount.com",
"cloudservices.gserviceaccount.com",
"stackdriver-service.iam.gserviceaccount.com",
"appspot.gserviceaccount.com",
"partnercontent.gserviceaccount.com",
"trifacta-gcloud-prod.iam.gserviceaccount.com",
"gcf-admin-robot.iam.gserviceaccount.com",
"compute-system.iam.gserviceaccount.com",
"gcp-sa-websecurityscanner.iam.gserviceaccount.com",
"storage-transfer-service.iam.gserviceaccount.com",
}
CIRRUS_CFG = {}
data = load_json("fence_credentials.json")
if data:
AWS_CREDENTIALS = data["AWS_CREDENTIALS"]
S3_BUCKETS = data["S3_BUCKETS"]
DEFAULT_LOGIN_URL = data["DEFAULT_LOGIN_URL"]
OPENID_CONNECT.update(data["OPENID_CONNECT"])
OIDC_ISSUER = data["OIDC_ISSUER"]
ENABLED_IDENTITY_PROVIDERS = data["ENABLED_IDENTITY_PROVIDERS"]
APP_NAME = data["APP_NAME"]
HTTP_PROXY = data["HTTP_PROXY"]
dbGaP = data.get("dbGaP", DEFAULT_DBGAP)
CIRRUS_CFG["GOOGLE_API_KEY"] = get_from_dict(data, "GOOGLE_API_KEY")
CIRRUS_CFG["GOOGLE_PROJECT_ID"] = get_from_dict(data, "GOOGLE_PROJECT_ID")
CIRRUS_CFG["GOOGLE_ADMIN_EMAIL"] = get_from_dict(data, "GOOGLE_ADMIN_EMAIL")
CIRRUS_CFG["GOOGLE_IDENTITY_DOMAIN"] = get_from_dict(data, "GOOGLE_IDENTITY_DOMAIN")
CIRRUS_CFG["GOOGLE_CLOUD_IDENTITY_ADMIN_EMAIL"] = get_from_dict(
data, "GOOGLE_CLOUD_IDENTITY_ADMIN_EMAIL"
)
STORAGE_CREDENTIALS = get_from_dict(data, "STORAGE_CREDENTIALS", {})
GOOGLE_GROUP_PREFIX = get_from_dict(data, "GOOGLE_GROUP_PREFIX", "gen3")
SUPPORT_EMAIL_FOR_ERRORS = get_from_dict(data, "SUPPORT_EMAIL_FOR_ERRORS", None)
WHITE_LISTED_SERVICE_ACCOUNT_EMAILS = get_from_dict(
data, "WHITE_LISTED_SERVICE_ACCOUNT_EMAILS", []
)
WHITE_LISTED_GOOGLE_PARENT_ORGS = get_from_dict(
data, "WHITE_LISTED_GOOGLE_PARENT_ORGS", []
)
GOOGLE_MANAGED_SERVICE_ACCOUNT_DOMAINS.update(
data.get("GOOGLE_MANAGED_SERVICE_ACCOUNT_DOMAINS", [])
)
GUN_MAIL = data.get("GUN_MAIL")
REMOVE_SERVICE_ACCOUNT_EMAIL_NOTIFICATION = data.get(
"REMOVE_SERVICE_ACCOUNT_EMAIL_NOTIFICATION"
)
# use for intergration tests to skip the login page
MOCK_GOOGLE_AUTH = data.get("MOCK_GOOGLE_AUTH", False)
CIRRUS_CFG[
"GOOGLE_APPLICATION_CREDENTIALS"
] = "/var/www/fence/fence_google_app_creds_secret.json"
CIRRUS_CFG[
"GOOGLE_STORAGE_CREDS"
] = "/var/www/fence/fence_google_storage_creds_secret.json"
DEFAULT_LOGIN_URL_REDIRECT_PARAM = "redirect"
INDEXD = "http://indexd-service/"
ARBORIST = "http://arborist-service/"
| UTF-8 | Python | false | false | 5,539 | py | 1,395 | fence_settings.py | 339 | 0.665463 | 0.661311 | 0 | 170 | 31.582353 | 88 |
wawdh01/Shell-Scripting | 8,031,588,843,900 | 3636f970b59ba817a5725d3e1562643a4d9fd698 | 20783f464f2f5b5583fe58bac3809716adcf58cc | /prog7.py | a90f328d0ae751aadb196f85fc2fcd312aa142ee | []
| no_license | https://github.com/wawdh01/Shell-Scripting | eba01372978a03bf2d168df8ffe64d7e91d759f7 | e5a9cdefc051b58814b75d4382e6fe0dcc50dbce | refs/heads/master | 2023-01-31T20:31:57.384413 | 2020-12-18T14:31:19 | 2020-12-18T14:31:19 | 322,617,621 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | a = int(input("Enter 1st Number:"))
b = int(input("Enter 2nd Number:"))
c = int(input("Enter 3rd Number:"))
if (a > b and a > c):
print(a ," is greater")
elif (b > a and b > c):
print(b, " is greater")
else:
print(c, " is greater") | UTF-8 | Python | false | false | 251 | py | 38 | prog7.py | 37 | 0.549801 | 0.537849 | 0 | 9 | 26.111111 | 35 |
bimbocant/lpthw | 15,582,141,371,630 | 05754abe51e67a8061cc46c4b158c48575f95ba5 | ac60de744e7fa0514a5c884f8f220852daf93059 | /build/lib/ex48/lexicon.py | 23608ec4aaedee26c97a8c7cf65683b5fa686257 | []
| no_license | https://github.com/bimbocant/lpthw | dd5a9acd7a3a2d01edeebed69352dfafe35c6af3 | 924f8e2d8342f111455d88445e730369bd496c9c | refs/heads/master | 2020-03-22T14:15:32.003981 | 2018-07-08T16:11:28 | 2018-07-08T16:11:28 | 140,164,941 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | lex=[('direction','north'),
('direction','south'),
('direction','east'),
('verb','go'),
('verb','eat'),
('verb','kill'),
('stop','the'),
('stop','in'),
('stop','of'),
('noun','princess'),
('noun','bear')]
#returns the tuple of the given direction
def scan(string):
word_list=string.split()
result=[]
appended=False
for word in word_list:
for t in lex:
if word.lower() in t and appended==False:
result.append(t)
appended=True
#word is not in lex so it's a number or an error
if appended==False:
try:
num=int(word)
result.append(('number',num))
except ValueError as e:
result.append(('error',word))
appended=False
return result
| UTF-8 | Python | false | false | 927 | py | 4 | lexicon.py | 3 | 0.451996 | 0.451996 | 0 | 31 | 28.903226 | 57 |
5l1v3r1/skb | 6,038,724,022,973 | ca698495f187851dcfb8a2801cccbf61483480b4 | 45ceab8899bca822d403e29645bac3c7a5b9e77c | /core/migrations/0001_initial.py | bc1d31c20ec18d129338579fc4df9c67c144c5d1 | []
| no_license | https://github.com/5l1v3r1/skb | 1ed4bd2c335d30eb016fa26aa5353fbcba2acaa2 | 6fe1df0ffb4350645daa24cb195c47b747865b55 | refs/heads/master | 2021-03-31T07:51:48.081781 | 2020-02-23T07:47:13 | 2020-02-23T07:47:13 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # Generated by Django 2.1.4 on 2019-01-11 18:49
import django.contrib.auth.models
import django.contrib.auth.validators
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
('auth', '0009_alter_user_last_name_max_length'),
('photolog', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='User',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('password', models.CharField(max_length=128, verbose_name='password')),
('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')),
('is_superuser', models.BooleanField(default=False, help_text='Designates that this user has all permissions without explicitly assigning them.', verbose_name='superuser status')),
('username', models.CharField(error_messages={'unique': 'A user with that username already exists.'}, help_text='Required. 150 characters or fewer. Letters, digits and @/./+/-/_ only.', max_length=150, unique=True, validators=[django.contrib.auth.validators.UnicodeUsernameValidator()], verbose_name='username')),
('first_name', models.CharField(blank=True, max_length=30, verbose_name='first name')),
('last_name', models.CharField(blank=True, max_length=150, verbose_name='last name')),
('email', models.EmailField(blank=True, max_length=254, verbose_name='email address')),
('is_staff', models.BooleanField(default=False, help_text='Designates whether the user can log into this admin site.', verbose_name='staff status')),
('is_active', models.BooleanField(default=True, help_text='Designates whether this user should be treated as active. Unselect this instead of deleting accounts.', verbose_name='active')),
('date_joined', models.DateTimeField(default=django.utils.timezone.now, verbose_name='date joined')),
('avatar', models.ImageField(blank=True, null=True, upload_to='avatars')),
('groups', models.ManyToManyField(blank=True, help_text='The groups this user belongs to. A user will get all permissions granted to each of their groups.', related_name='user_set', related_query_name='user', to='auth.Group', verbose_name='groups')),
('user_permissions', models.ManyToManyField(blank=True, help_text='Specific permissions for this user.', related_name='user_set', related_query_name='user', to='auth.Permission', verbose_name='user permissions')),
],
options={
'verbose_name': 'user',
'verbose_name_plural': 'users',
'abstract': False,
},
managers=[
('objects', django.contrib.auth.models.UserManager()),
],
),
migrations.CreateModel(
name='DefInfo',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('ph', models.CharField(blank=True, max_length=15, null=True, verbose_name='Телефон')),
('soc', models.CharField(max_length=200, verbose_name='Соцсеть')),
('email', models.EmailField(max_length=200, verbose_name='Почта')),
],
options={
'verbose_name': 'Основную информацию',
'verbose_name_plural': 'Основная информация',
},
),
migrations.CreateModel(
name='Materials',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=200, verbose_name='Название')),
('logo', models.ImageField(blank=True, null=True, upload_to='logos', verbose_name='Картинка')),
('description', models.TextField(blank=True, null=True, verbose_name='Описание')),
('catalog', models.ManyToManyField(blank=True, to='photolog.Catalog', verbose_name='Каталоги')),
],
options={
'verbose_name': 'Материалы',
'verbose_name_plural': 'Материалы',
},
),
migrations.CreateModel(
name='MaterialsType',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=200, verbose_name='Название')),
],
options={
'verbose_name': 'Типы материалов',
'verbose_name_plural': 'Тип материалов',
},
),
migrations.CreateModel(
name='Partitions',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=200, verbose_name='Заголовок')),
('description', models.CharField(blank=True, max_length=160, null=True, verbose_name='Краткое описание')),
('keywords', models.CharField(blank=True, max_length=255, null=True, verbose_name='Ключевые слова')),
('status', models.CharField(choices=[('draft', 'Черновик'), ('published', 'Опубликовано')], default='draft', max_length=10, verbose_name='Статус')),
('url', models.CharField(db_index=True, max_length=100, verbose_name='URL')),
('cover', models.ImageField(blank=True, null=True, upload_to='cover', verbose_name='Обложка')),
('content', models.TextField(blank=True, verbose_name='Содержание')),
('template_name', models.CharField(blank=True, help_text="Пример: 'core/contact_page.html'", max_length=70, verbose_name='Имя шаблона')),
],
options={
'verbose_name': 'Страницы',
'verbose_name_plural': 'Страницы',
'ordering': ('url',),
},
),
migrations.CreateModel(
name='StandardModel',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=200, verbose_name='Название')),
('article', models.CharField(max_length=10, unique=True, verbose_name='Артикул')),
('qdoors', models.SmallIntegerField(choices=[(2, '2'), (3, '3'), (4, '4')], default=2, verbose_name='Количество дверей')),
('type_case', models.CharField(choices=[('case', 'Корпусной'), ('built-in', 'Встроенный')], default='case', max_length=10, verbose_name='Тип корпуса')),
('angular', models.BooleanField(default=False, verbose_name='Угловой')),
('description', models.TextField(blank=True, null=True, verbose_name='Описание')),
('height1', models.SmallIntegerField(default=2200, verbose_name='Высота от')),
('height2', models.SmallIntegerField(default=2400, verbose_name='Высота до')),
('width1', models.SmallIntegerField(default=1200, verbose_name='Ширина от')),
('width2', models.SmallIntegerField(default=2000, verbose_name='Ширина до')),
('depth', models.SmallIntegerField(default=600, verbose_name='Глубина')),
('materials', models.ManyToManyField(blank=True, to='core.Materials', verbose_name='Материалы')),
('phobj', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='photolog.PhotoObject', verbose_name='Фотообъект')),
],
options={
'verbose_name': 'Базовый шкаф',
'verbose_name_plural': 'Базовые шкафы',
},
),
migrations.CreateModel(
name='StandartDoors',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=200, verbose_name='Название')),
('article', models.CharField(max_length=10, unique=True, verbose_name='Артикул')),
('qdoors', models.SmallIntegerField(choices=[(2, '2'), (3, '3'), (4, '4')], default=2, verbose_name='Количество дверей')),
('description', models.TextField(blank=True, null=True, verbose_name='Описание')),
('img', models.ImageField(blank=True, null=True, upload_to='doors', verbose_name='Картинка')),
('materials', models.ManyToManyField(blank=True, to='core.Materials', verbose_name='Материалы')),
],
options={
'verbose_name': 'Базовая дверь',
'verbose_name_plural': 'Базовые двери',
},
),
migrations.AddField(
model_name='materials',
name='mattype',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='core.MaterialsType', verbose_name='Тип материалов'),
),
]
| UTF-8 | Python | false | false | 9,800 | py | 76 | 0001_initial.py | 46 | 0.590709 | 0.577912 | 0 | 148 | 61.831081 | 329 |
Ignotus111/PurBeurre | 13,804,024,933,668 | ba3584b4aaa2e8ea1878028a5a04aa0807970c0a | fbb473e043c5b77f666434c02200684c08218833 | /dbcreation.py | 14dad56f3a3525c84f163f0e0cf6fafc68ec061d | []
| no_license | https://github.com/Ignotus111/PurBeurre | 2371327ef6858127d5fe67256d6545940dc3ffe5 | 1ee10b108262830c8fed6c8eaa205be217d08eae | refs/heads/develop | 2023-05-26T11:16:58.616491 | 2020-11-05T11:49:35 | 2020-11-05T11:49:35 | 277,505,669 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import mysql.connector
from constants import (NB_CATEGORY, NB_PAGEPRODUCT, cat_link, PASSWORD, USER,
HOST)
from classes.categories import Categories
from classes.products import Product
from classes.categoryproduct import Categoryproduct
import requests
import json
connection = mysql.connector.connect(host=HOST, user=USER, password=PASSWORD)
mycursor = connection.cursor()
def execsqlfile(sql_file):
"""Reads and executes instructions of a .sql file."""
statement = ""
for line in open(sql_file):
if line.strip().endswith(";"):
statement = statement + line
mycursor.execute(statement)
statement = ""
else:
statement = statement + line
connection.commit()
mycursor.close()
def requestprod(cat, link):
"""Save products in the database."""
i = 1
urls = []
"""Saving number of pages."""
while i < NB_PAGEPRODUCT + 1:
urls.append(link + "/" + str(i))
i += 1
"""For each page of a catagory from OpenFoodFacts, takes data of all
fields.(id product_name...) Then creates a Product object and save it in
database."""
for locc in urls:
response = requests.request("GET", locc + ".json")
json_prod = response.json()
products_prod = json_prod.get("products")
prod_info = [
Product(
data.get("id"),
data.get("product_name"),
data.get("generic_name"),
data.get("url"),
data.get("stores"),
data.get("nutriscore_grade"),
)for data in products_prod
]
product_barcode = [(data.get("id"),) for data in products_prod]
"""Fills Categoryproduct table."""
for elem in product_barcode:
catprod = Categoryproduct(cat, elem[0])
catprod.save()
Product.saveMany(prod_info)
def requestcat():
"""Takes categories names et urls."""
response = requests.request("GET", cat_link)
json_cat = response.json()
tags_cat = json_cat.get("tags")[:NB_CATEGORY]
name_cat = [(data.get("name"),) for data in tags_cat]
link_cat = [(data.get("url"),) for data in tags_cat]
categories = [Categories(elem[0]) for elem in name_cat]
"""Creates a Categories object with names and save it in database."""
Categories.saveMany(categories)
"""For each urls, calls requestprod."""
for index, cat in enumerate(name_cat):
requestprod(cat[0], link_cat[index][0])
| UTF-8 | Python | false | false | 2,540 | py | 10 | dbcreation.py | 9 | 0.602362 | 0.599606 | 0 | 74 | 33.324324 | 77 |
OusmaneKana/Python_Journey | 15,556,371,592,433 | 30d19f2850a6667716e86a9b05f502db69c1403e | 827d45bf52dd5da7b83d30f8ba14965414dd4fd9 | /OOP/OOP.py | 76c54a22808ca0f38f33cd89fccfb94edf245dd2 | []
| no_license | https://github.com/OusmaneKana/Python_Journey | 046bb878846ba1e02c4ce9ca4f216ab74f4d49b8 | c8cf4fb728f4b2aee48e5482c504be57e04a8ff6 | refs/heads/master | 2022-03-29T02:16:01.148588 | 2020-01-30T05:15:19 | 2020-01-30T05:15:19 | 122,021,015 | 2 | 2 | null | null | null | null | null | null | null | null | null | null | null | null | null | # This is a quick program to illustrate the basics of OOP in python
class Dog():
def __init__(self, name, breed, age, smart):
self.breed = breed
self.name = name
self.age = age
self.smart = smart
def bark (self):
print ("WOOF WOOF!! My name is {} and I am {}".format(self.name, self.age))
my_dog = Dog(name = "BoBy", breed = "Hoksy", age = 25, smart = True)
my_dog.bark()
| UTF-8 | Python | false | false | 392 | py | 19 | OOP.py | 15 | 0.630102 | 0.625 | 0 | 16 | 23.5 | 77 |
eldioschalm/novo_portal | 13,829,794,726,233 | 56419a14bb254142cbf7f2cff2a0ef51a276027b | 60676a82606b622324c7a087d32b5a96390a85b9 | /portal/banner/tests/test_models.py | 7bed6aecf5b94d2bf8a7e8eb2e31c7bf2cf4b4cb | []
| no_license | https://github.com/eldioschalm/novo_portal | d497cc30e7f8eb05f421c2a47c05b0b7ab1faf87 | 31d58b3b90241a6cf9a765ec84c0a5fe8c786852 | refs/heads/master | 2022-12-04T06:56:53.901071 | 2020-01-20T14:36:50 | 2020-01-20T14:36:50 | 18,217,799 | 0 | 0 | null | false | 2022-11-22T02:46:57 | 2014-03-28T15:59:05 | 2020-01-20T14:37:15 | 2022-11-22T02:46:55 | 182,564 | 0 | 0 | 7 | CSS | false | false | #coding: utf-8
from django.test.testcases import TestCase
from django.conf import settings
from django.utils import timezone
from django.core.files import File
from filer.models import Image
from portal.banner.models import Banner
from portal.core.tests.util import del_midia_filer
class BannerTest(TestCase):
def setUp(self):
self.img_path = settings.BASE_DIR + '/portal/banner/static/img/images.jpeg'
self.img_name = u'imagembanner'
with open(self.img_path) as img:
file_obj = File(img, name=self.img_name)
midia_image = Image.objects.create(original_filename=self.img_name, file=file_obj)
self.banner = Banner(
titulo=u'BannerTesteTitulo',
data_publicacao=timezone.now(),
arquivo=midia_image,
publicado=True,
tipo=1,
)
def test_criacao(self):
"""
Banner deve possuir titulo, data de publicacao e midia
"""
self.banner.save()
self.assertIsNotNone(self.banner.pk)
def test_unicode(self):
"""
Banner deve apresentar o titulo como unicode
"""
self.assertEqual(u'BannerTesteTitulo', unicode(self.banner))
def test_esta_publicado(self):
"""
Testa se um banner esta publicado ou nao. A condicao para que um banner seja considerado como publicado e que
esteja marcado como publicado e a data de publicacao seja anterior a data atual
"""
# data de 1 dia antes de hoje
self.banner.data_publicacao = timezone.now() - timezone.timedelta(days=1)
self.banner.publicado = True
self.assertTrue(self.banner.esta_publicado)
self.banner.publicado = False
self.assertFalse(self.banner.esta_publicado)
# data de 1 dia depois de hoje
self.banner.data_publicacao = timezone.now() + timezone.timedelta(days=1)
self.banner.publicado = True
self.assertFalse(self.banner.esta_publicado)
# data de 1 dia antes de hoje
self.banner.data_publicacao = timezone.now() - timezone.timedelta(days=1)
self.banner.publicado = False
self.assertFalse(self.banner.esta_publicado)
def tearDown(self):
del_midia_filer(self.img_name)
| UTF-8 | Python | false | false | 2,272 | py | 122 | test_models.py | 74 | 0.652289 | 0.648768 | 0 | 65 | 33.953846 | 117 |
jhgdike/myWebSite | 15,324,443,323,523 | 7d5b2582bd1b94381af67e5f8c2d61dc4bd82de5 | 43d425e3ed9e6f56f43b980cfdea4c9ac00cbbef | /handlers/login_handler.py | e0fa3ae9384ff9dfd5e22c45ae7a1cb4e3e70638 | []
| no_license | https://github.com/jhgdike/myWebSite | e7a4cfc437b887073ca37c1042d8a4b9ce447ab1 | fccfaa29443fdca37635c4ca53146e0e78a8eadf | refs/heads/master | 2016-08-10T17:55:04.634397 | 2016-01-14T06:04:35 | 2016-01-14T06:04:35 | 49,626,024 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # coding:utf-8
import os, sys, re
import tornado.web
import tornado.httpserver
from handlers.base_handler import BaseHandler
class LoginHandler(BaseHandler):
def get(self, action):
self.loginPage()
def loginPage(self):
self.render('login.html')
| UTF-8 | Python | false | false | 272 | py | 6 | login_handler.py | 6 | 0.713235 | 0.709559 | 0 | 13 | 19.923077 | 45 |
choifish/project-euler | 1,529,008,395,717 | dcc815e763841f6cc2648cacca67b4c8cefdbc7b | d9676724e91ae59ea281dd8db5e12eb4ee436058 | /Problem025.py | df475ab3b9ee266b589c74412f13c88ae7b92fc4 | []
| no_license | https://github.com/choifish/project-euler | eba10dcad526cfebf89712197499288d25fcd37b | 98474f7da8cc652c52ecf01d64e7f7aa7a246e1f | refs/heads/master | 2021-01-22T02:47:55.616382 | 2013-05-22T19:05:13 | 2013-05-22T19:05:13 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #===============================================================================
# What is the first term in the Fibonacci sequence to contain 1000 digits?
#===============================================================================
a, b, term = 0, 1, 0
while True:
term += 1
if len(str(b)) == 1000:
break
b += a
a = b - a
print(term) | UTF-8 | Python | false | false | 374 | py | 62 | Problem025.py | 62 | 0.304813 | 0.272727 | 0 | 12 | 29.333333 | 80 |
arushi-11/Projects-In-Python | 18,571,438,589,159 | 5022965369f3f1fcc3436ce218c933badc58c714 | 884222c8030519fbc8cbb921afab7aaeb92fbf32 | /decision_making_tree.py | 86d1c46e5dd2674804be8c2b101e6fe4c48da78f | []
| no_license | https://github.com/arushi-11/Projects-In-Python | 0df56dcf851ce4a774b9399e2c89b382783f4057 | b45d8272d37e7651494aa4780a0e780643dfdbe2 | refs/heads/main | 2023-04-04T16:27:51.327861 | 2021-04-08T14:18:34 | 2021-04-08T14:18:34 | 303,289,431 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | print("1)TABLE OF YOUR GIVEN NUMBER\n2)ADDITION\n3)SUBTRACTION\n4)MULTIPLICATION\n5)DIVISION\n6)DESIGN PATTERNS\n7)DRAW SHAPES")
temp=int(input("enter your choice within 1-7:"))
if(temp==1):
p=int(input("Enter the number of which you want to print table:"))
for i in range(1,11):
print(p,"*",i,"=",p*i)
if(temp==2):
p=int(input("Enter first number"))
q=int(input("Enter second number"))
r=p+q
print("Result is ",r)
if(temp==3):
p=int(input("Enter first number"))
q=int(input("Enter second number"))
r=p-q
print("Result is ",r)
if(temp==4):
p=int(input("Enter first number"))
q=int(input("Enter second number"))
r=p*q
print("Result is ",r)
if(temp==5):
p=int(input("Enter first number"))
q=int(input("Enter second number"))
r=p/q
print("Result is ",r)
if(temp==6):
print("---:PATTERN DESIGNS:---")
print("1)****\n ****\n ****\n ****\n\n2)1\n 2 3\n 4 5 6\n\n3)*\n * *\n * * *")
p=int(input("Enter any choice 1-3:->"))
if(p==1):
for i in range(4):
for j in range(4):
print("*",end=' ')
print("\n")
if(p==2):
x=1
for i in range(1,4):
for j in range(i):
print(x,end=' ')
x+=1
print("\n")
if(p==3):
for i in range(1,4):
for j in range(i):
print("*",end=' ')
print("\n")
if(temp==7):
print("---:SHAPE DESIGNING:---")
print("1)Make a circle\n2)Make a square\n3)Make triangle")
p=int(input("Enter your choice 1-3:->"))
import turtle
x=turtle.Turtle()
if(p==1):
z=int(input("Enter the radius of the circle"))
x.begin_fill()
x.fillcolor("red")
x.circle(z)
x.end_fill()
if(p==2):
z=int(input("Enter the sides of square"))
x.begin_fill()
x.fillcolor("blue")
for i in range(4):
x.forward(z)
x.left(90)
x.end_fill()
if(p==3):
z=int(input("Enter the sides of triangle"))
x.begin_fill()
x.fillcolor("red")
x.circle(z,steps=3)
x.end_fill()
| UTF-8 | Python | false | false | 2,194 | py | 7 | decision_making_tree.py | 6 | 0.501823 | 0.477666 | 0 | 73 | 29 | 128 |
noelsebu/djangobackend | 19,198,503,842,207 | 165c10f94f4921e96b7b932b2547b5e663cbba03 | 6a629e3f97694594b55cae1279a60689c773672a | /py/lib/python3.7/site-packages/django_google/models.py | c7b5a042a9d72d37dd2c7afffaa284d901b07d94 | []
| no_license | https://github.com/noelsebu/djangobackend | 209a7e1bcc6fa6a6ea7a68992b04f6fbe8172db3 | 93a33b88c02f0a47127bf29e7b4a68c04f0743eb | refs/heads/master | 2022-12-23T21:07:35.066239 | 2020-06-16T14:57:32 | 2020-06-16T14:57:32 | 272,730,108 | 0 | 2 | null | false | 2020-06-16T22:01:05 | 2020-06-16T14:28:46 | 2020-06-16T15:37:43 | 2020-06-16T15:36:39 | 167,486 | 0 | 1 | 2 | Python | false | false | from django.db import models
from google.auth.transport.requests import Request
import pickle
from django.contrib.auth import get_user_model
User = get_user_model()
# Create your models here.
class GoogleAuth(models.Model):
user = models.OneToOneField(User, on_delete=models.CASCADE, related_name='oauth_google')
_creds = models.BinaryField()
def set_data(self, data):
self._creds = pickle.dumps(data)
def get_data(self):
credentials = pickle.loads(self._creds)
if credentials and credentials.expired and credentials.refresh_token:
credentials.refresh(Request())
self._creds = pickle.dumps(credentials)
self.save()
return pickle.loads(self._creds)
creds = property(get_data, set_data)
def __str__(self):
return self.user.email
class Meta:
verbose_name = "Google Authentication"
verbose_name_plural = "Google Authentications"
| UTF-8 | Python | false | false | 954 | py | 43 | models.py | 31 | 0.675052 | 0.675052 | 0 | 32 | 28.78125 | 92 |
Priestch/luoo-server | 16,810,502,023,576 | 4c988e0a4bf2b258cd5a37379348d8702a16e121 | 67c7ef48c17028ad1e0c4c01c81244e56cd76d25 | /luoo/schema/volume.py | 2cc4755d8f567d343ead4142e52404ecb772d344 | []
| no_license | https://github.com/Priestch/luoo-server | 056b843b5f9941ab6f44aa017560c3f6decf6c6e | e028885a6f08b01fd66b7c28feb4129c091bb40a | refs/heads/master | 2022-01-30T05:50:28.955821 | 2019-03-31T14:03:28 | 2019-03-31T14:03:28 | 78,432,067 | 1 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | from marshmallow import fields
from marshmallow_sqlalchemy import ModelSchema
from luoo.models import Volume, Tag
class VolumeSchema(ModelSchema):
class Meta:
model = Volume
cover = fields.Method("get_volume_cover")
def get_volume_cover(self, obj):
return obj.cover_url
class TagSchema(ModelSchema):
class Meta:
model = Tag
volume_schema = VolumeSchema()
tag_schema = TagSchema()
| UTF-8 | Python | false | false | 429 | py | 25 | volume.py | 21 | 0.703963 | 0.703963 | 0 | 23 | 17.652174 | 46 |
devilry/devilry-django | 2,559,800,551,616 | 8427998884830b8e04aca175ad8ec7ecc04965b3 | 36ca932c7180738f501190f1d28c3a63e462c413 | /devilry/devilry_message/migrations/0002_auto_20210427_1350.py | 8ce8c8bfca4411349f4b9f79da90d71c25400508 | []
| permissive | https://github.com/devilry/devilry-django | 4e2741f29fcf2ae6b75690e9cd0cded154decf6e | a3355fe78992466cfcae8b166128bf51ddbb26d0 | refs/heads/master | 2023-08-08T22:00:58.952030 | 2023-07-21T13:17:27 | 2023-07-21T13:17:27 | 486,298 | 42 | 22 | BSD-3-Clause | false | 2023-07-21T13:38:30 | 2010-01-24T13:31:14 | 2023-04-19T22:37:03 | 2023-07-21T13:38:30 | 114,288 | 48 | 23 | 82 | Python | false | false | # Generated by Django 3.1.8 on 2021-04-27 11:50
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('devilry_message', '0001_initial'),
]
operations = [
migrations.AlterField(
model_name='message',
name='metadata',
field=models.JSONField(blank=True, default=dict),
),
migrations.AlterField(
model_name='message',
name='status_data',
field=models.JSONField(blank=True, default=dict),
),
migrations.AlterField(
model_name='message',
name='virtual_message_receivers',
field=models.JSONField(blank=True, default=dict),
),
migrations.AlterField(
model_name='messagereceiver',
name='metadata',
field=models.JSONField(blank=True, default=dict),
),
migrations.AlterField(
model_name='messagereceiver',
name='status_data',
field=models.JSONField(blank=True, default=dict),
),
]
| UTF-8 | Python | false | false | 1,104 | py | 1,514 | 0002_auto_20210427_1350.py | 868 | 0.564312 | 0.547101 | 0 | 38 | 28.052632 | 61 |
Meso272/cwae | 2,095,944,052,664 | 1f2c9a987465f044a698d0a22ee7503aa95e03c4 | c50b8b763585e61fdae05e8c5de4fdc314e8ba5e | /src/architectures/celeba_architecture_provider.py | 48c85ac8df7b91eba8f1c9711c83c82a520030c7 | [
"MIT"
]
| permissive | https://github.com/Meso272/cwae | 0008b11f906d787f450e38613bfe828ba6e378b5 | 50592903c321de25f339f3b00cbd2143741e5037 | refs/heads/master | 2022-12-13T08:00:17.659966 | 2020-09-17T16:31:56 | 2020-09-17T16:31:56 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import tensorflow as tf
class CelebaArchitectureProvider:
def encoder_builder(self, x, z_dim: int):
h = x
for i, filter_count in enumerate([32, 32, 64, 64]):
h = tf.layers.conv2d(x, kernel_size=(4, 4), strides=(2, 2), padding='same', activation=tf.nn.relu,
filters=filter_count, name=f'Encoder_Conv_{i}')
h = tf.layers.flatten(h, name='Encoder_Flatten')
h = tf.layers.dense(h, units=1024, activation=tf.nn.relu, name='Encoder_FC_0')
h = tf.layers.dense(h, units=256, activation=tf.nn.relu, name='Encoder_FC_1')
return tf.layers.dense(h, z_dim, name=f'Encoder_output')
def decoder_builder(self, z, x_dim: int):
h = tf.layers.dense(z, units=256, activation=tf.nn.relu, name='Decoder_FC_0')
h = tf.layers.dense(z, units=1024, activation=tf.nn.relu, name='Decoder_FC_1')
h = tf.reshape(h, [-1, 4, 4, 64])
for filter_count in [64, 32, 32, 3]:
h = tf.layers.conv2d_transpose(h, kernel_size=(4, 4), strides=(2, 2), activation=tf.nn.relu,
filters=filter_count, padding='same', name='Decoder_Deconv_1')
return h
| UTF-8 | Python | false | false | 1,206 | py | 21 | celeba_architecture_provider.py | 19 | 0.58209 | 0.541459 | 0 | 24 | 49.25 | 111 |
xm4dn355x/specialist_python3_2nd_lvl | 6,717,328,880,262 | 5b25d15f9a7145ae7ac88767a1583ec235844890 | 79364cf7572e9241ffb6603303ee74ec59e466b4 | /Module02/practice/01_task_deck.py | 4b109d17c3f2d5eb253e4673665f86d02dede60c | [
"MIT"
]
| permissive | https://github.com/xm4dn355x/specialist_python3_2nd_lvl | e4ae312db7410ed21a20f122a1c2e7551bc54acf | 4ea8c82eb0f32aa92c82914f6599c2c47a2f7032 | refs/heads/main | 2023-04-10T18:50:34.970865 | 2021-04-26T14:04:27 | 2021-04-26T14:04:27 | 355,071,612 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # Начнем с создания карты
class Card:
HEARTS = 'Hearts'
DIAMONDS = 'Diamonds'
SPADES = 'Spades'
CLUBS = 'Clubs'
SUITS = {
HEARTS: '♥',
DIAMONDS: '♦',
SPADES: '♣',
CLUBS: '♠',
}
def __init__(self, value, suit):
self.value = value
self.suit = suit
self.suits_power = {
'Hearts': 3,
'Diamonds': 2,
'Spades': 1,
'Clubs': 0
}
self.values = {
'2': 0,
'3': 1,
'4': 2,
'5': 3,
'6': 4,
'7': 5,
'8': 6,
'9': 7,
'10': 8,
'J': 9,
'Q': 10,
'K': 11,
'A': 12,
}
def __str__(self):
return self.to_str()
def to_str(self):
return f'{self.SUITS[self.suit]}{self.value}'
def equal_suit(self, other_card):
if self.suit == other_card.suit:
return True
else:
return False
def more(self, other_card):
if self.values[self.value] == other_card.VALUES[other_card.value]:
if self.suits_power[self.suit] > other_card.SUITS_POWER[other_card.suit]:
return True
else:
return False
elif self.values[self.value] == other_card.VALUES[other_card.value]:
return True
else:
return False
def less(self, other_card):
are_more = self.more(other_card)
if are_more:
return False
else:
return True
# Создадим несколько карт
card1 = Card('10', Card.HEARTS)
card2 = Card("A", Card.DIAMONDS)
# Выведем карты на экран в виде: 10♥ и A♦
print(card1.to_str())
print(card2.to_str())
# Проверим, одинаковые ли масти у карт
if card1.equal_suit(card2):
print(f"У карт: {card1.to_str()} и {card2.to_str()} одинаковые масти")
else:
print(f"У карт: {card1.to_str()} и {card2.to_str()} разные масти")
if card1.more(card2):
print(f"Карта {card1.to_str()} больше чем {card2.to_str()}")
else:
print(f"Карта {card1.to_str()} меньше чем {card2.to_str()}")
if __name__ == '__main__':
print(Card(2, 'Diamonds')) | UTF-8 | Python | false | false | 2,393 | py | 62 | 01_task_deck.py | 61 | 0.487607 | 0.464624 | 0 | 92 | 23.130435 | 85 |
chmuraw/iSA-python | 2,834,678,429,319 | 3e592c2b0256656e0a84a5201b0a0e0443e431e2 | 2f0bd0482051c3a176f4cc965d5211620c1dfb1b | /Praca_zajecia/przedtestem.py | ac5075fc3a525da1de41f63ae894b56d21822748 | []
| no_license | https://github.com/chmuraw/iSA-python | b300c982742f3da674d0bdd6d076066993fa7886 | a7082eab333e5033635d662b3aee036cd66c913d | refs/heads/master | 2020-08-31T00:37:33.194608 | 2019-12-10T18:18:09 | 2019-12-10T18:18:09 | 218,536,216 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # system binarny = dwojkowy (zera i jedynki)
# algorytm skonczony zestaw polecen potrzebnych do wykonania zadania
# zlozonosc algorytmiczna (obliczeniowa) - poziom skomplikowania algorytmu
# (im mniejsza tym lepiej - jak najmniej opercaji, jak najmniej petli itd)
# input() - metoda do pobrania czegos od uzytkownika
# print() - metoda wyswietlania czegos uzytkownikowi w konsoli
# zmienna - nazwany obszar pamieci
# deklarowanie zmiennej (pojedynczy znak rownosci)
# dom = "bialy"
# typy danych w pythonie: int, str, float, bool, tuple, dict, list, set(ale o tym nie mowilismy)
# tworzenie listy:
# litery = ["A", "B", "C", "D", "E"]
# litery = list("ABCDE")
# print(litery)
# ITEROWALNY - mozna go rozlozyc na czesci. str jest iterowalny
# wyraz = "wyraz"
# for litera in wyraz:
# print(litera, end =" ") # wyswietli wszystkie litery w jednej linii
# print(litera) #wyswietli litery jedna pod druga
# slownik z imineiem i nazwiskiem (wszystko w klamrach i klucze w cudzyslowiach)
# osoba = {"imie": "Jan", "nazwisko" : "Kowalski", "wiek": 18}
# print("Kowalski"[2:6:1]) # wals !!! jedynka na koncu dla sciemy, bo i tak jest domyslna
# print("Kowalski"[1:1:1] # nic nie wyjdzie.
# z czego sklada sie funkcji: minimalistycznie - potrzebna jest tylko nazwa ;)
# def nazwa():
# pass
# # poza nazwa moze miec parametry domyslne lub niedomyslne - pozycyjne (kolejnosc definiowania jest wazna)
# def nazwa(arg1, arg2, arg3 = "war3", *args, **kwargs): #arg3 - parametr nazwany, args i kwargs moga miec jakies nazwy
# # jedna gwiazdka oznacza nieskonczona ilosc pozycyjnych argumentow, a ** nieskonczona ilosc key walues - przechodzi w slownik
#
# # no i zmienna musi miec jakies cialo:
# zmienna = 1
# inna_zmienna = 2
# return "ala ma kota"
# # jak funkcja nie ma returna to zwraca None
# def funkcja(*args):
# print(args)
# funkcja(1, 3, 6, 7, 8.2,"ala ma kota", "grudzien") # dzieki args moge te wszystkie rozne elementy miec w swojej funkcji
# funkcja("2019")
# def funkcjakwargs(**kwargs):
# print(kwargs)
# funkcjakwargs(param = "grudzien", arg = 2) # dzieki args moge te wszystkie rozne elementy miec w swojej funkcji
# funkcjakwargs(rok = "2019")
# mozna mieszac args i kwargs, alle w definiowaniu najpierw args potem kwargs
# mutowalny - mozna zmieniac, niemutlowany - nie mozna zmieniac
# robimy cos pod warunkiem: najmniejsyz mozliwy if sklada sie z warunku :)
#else jest tylko jeden, a elifow moze byc nieskonczenie wiele
# zmienna = "2"
# if zmienna == "1":
# elif zmienna == "2":
# elif zmienna =="3":
# else:
# pass
# operatory w ifach:
# >, <, => itd
# in - czy jeden element jest w innym elemencie
# is - do sprawdzenia typu, albo true or false
# not - zaprzeczenie
# print(False and True and not False) = print(False and True and True)
# and z jakakolwiek false da wynik false (tablica prawdy)
# otwieranie plikow: open("nazwa/sciezka", "tryb")
# w - jezeli plik istnieje, to zostanie wyczyszczony i zapisuje nowe, ewentualnie tworzy nowy plik jesli nie istnieje i zapisuje
# wb - to samo, w trybie binarnym (zipy, obrazki, pikle)
# r - odczyt. nie zapisuje, nie utworzy pliku jesli go nie ma.
# r+ - odczyta i zapisze. nie utworzy pliku jesli go nie ma.
# a - ??? - do sprawdzenia w domu
# modul w pythonie - wyodrebniona czesc kodu do osobnego skryptu/pliku
# importowanie modulow zewnetrznych:
#import modul - importuje caly modul
#from modul import klasa - importuje tylko czesc modulu
# from modul import klasa as inna_nazwa - zaimportuje i bede uzywac pod inna nazwa
# from katalog.podkatalog.modul import klasa as moja_nazwa
# paradygmaty: enkapsulacja, polimorfizm, abstrakcja, dziedziczenie
# dziedziczenie: tworzenie obiektu od ogolo do szczegolu. obiekt podrzedny przejmuje cechy wspolne nadrzednego (jesli nie deklaruje sie inaczej)
# class Pies(zwierze) - klasa pies dziedziczy po zwierze
# abstrakcja: zdefioniowany poziom szczegolowosci obiektow jesli chodzi o ich wlasciwosci i metody.
# polimorfizm: definiowanie wspolnych metod dla roznefgo typu obiektow. (__xxx__)
# enkapsulacja(hermetyzacja): definiowanie metod do dostepu do wlasciwosci obiektu
# getter, setter, deletter na przyklad.
# w pythonie wystepuja metody pseudoprywatne: ustawia sie to tak: self.__nazwa
# self.__nazwa - wlasciwosc
# def __nazwa(): pass - metoda
# klasa vs obiekt - klasa to plan budowy domu a obiekt to ten dom
# klasa to zdefiniowany plan/schemat, a obiekt to "namacalny byt" stworzony na podstawie tego planu.
# wyjatek - nazwane bledy programu, ktore mozna "przeskoczyc"
# try:
# dzielenie = 9/0
# except ZeroDivisionError:
# print("Blad")
# else:
# print("Gdy nie ma wyjatku")
# finally:
# print("Zawsze")
# # jak zdefiniowac metode klasy: (cls!!!)
# def Klasa():
# @classmethod
# def metodaklasy(cls):
# pass
#
# # jak zdefiniowac klase obiektu:
# def metodaobiektu(self):
# pass
#
# #metoda statyczna (niepowiazana ani z obiektem ani z klasa)
# @staticmethod
# def metodastatyczna():
# pass
# # konstruktor klasy:
# def __init(self):
# self.cecha = 1
# self.inna_cecha = "bialy"
# getter:
# @property
# def cecha():
# return self.__cecha
#
# # setter: zeby moc setter i deletter musi najpierw byc getter
# @cecha.setter
# def cecha(self, nowa_wartosc):
# self.__cecha = nowa_wartosc
#
# @cecha.deleter
# def cecha(self):
# self,__cecha = None
#
# dziedziczenie:
# class A():
# def f(self):
# print("A")
# class B(A):
# def f(self):
# print("B")
# class C(A):
# def f(self):
# print("C")
# class D(A):
# pass
#
# A().f() #wyswietli A
# B().f() # wyswietli B (bo napisalismy)
# C().f() # wyswietli C
# D().f() # wyswietli A
#zakres widocznosci zmiennych (scope zmiennych)
# zmienna = "dom" - zmienna jest bez zadnych tabulatorow, wiec jest globalna
# def funkcja():
# zmienna = "Praca"
# print(zmienna)
#nawet jesli w funkcji deklarowana jest zmienna o tej zamej nazwie co gllobalna, to na koniec jak sie wywola to wyswietli sie ta globalna zmienna. | UTF-8 | Python | false | false | 6,127 | py | 26 | przedtestem.py | 20 | 0.693814 | 0.687775 | 0 | 187 | 31.770053 | 146 |
mitchelldirt/learning-python | 13,975,823,607,678 | 0256bba93df5307446a5bc53c3c68eb5637f18f7 | df233d3e2157b76019c5a558a099017590db98dd | /section10_OOP/getters_setters_python/main.py | e2654efd4281870a4e0e74c74dfafbbac2125704 | []
| no_license | https://github.com/mitchelldirt/learning-python | 860346a0793e72edfbae34ed94fb509f207b10d5 | bb9fbc0c3dff0aff061f26aa1a02882aa4e2df74 | refs/heads/main | 2023-03-25T19:19:41.206338 | 2021-03-15T16:51:57 | 2021-03-15T16:51:57 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from enemy import Enemy, Troll, Vampire, VampireKing
import random
ugly_troll = Troll("Pug")
print(ugly_troll)
another_troll = Troll("Ug")
print("Another troll - {}".format(another_troll))
brother = Troll("Urg")
print(brother)
ugly_troll.grunt()
another_troll.grunt()
brother.grunt()
brother.take_damage(24)
print(brother)
old_vampire = Vampire("Olga")
print(old_vampire)
young_vampire = Vampire("Kelcy")
print(young_vampire)
young_vampire.take_damage(7)
print(young_vampire)
old_vampire.take_damage(30)
print(old_vampire)
# while young_vampire.alive:
# young_vampire.take_damage(1)
young_vampire._lives = 0
young_vampire._hit_points = 1
print(young_vampire)
king_of_vampires = VampireKing("Dracula")
print(king_of_vampires)
while king_of_vampires.alive:
king_of_vampires.take_damage(random.randint(10, 40))
| UTF-8 | Python | false | false | 874 | py | 67 | main.py | 65 | 0.701373 | 0.687643 | 0 | 42 | 18.809524 | 56 |
bruggisser/cil-project | 14,491,219,673,040 | b03f5cd3847dbd170b6a50debe2e211e80cc9f47 | 4befa5e5e061e61b63d9f21d54924656bcb2b3f8 | /get_model_performance.py | 725025383709114e5ee42e879212317f0c39728d | []
| no_license | https://github.com/bruggisser/cil-project | c0966d516b307fa631150b500010bfd8e40dcb30 | 907c6c09d6867144ce2993278335b4fa0af67448 | refs/heads/master | 2023-06-26T04:48:20.309047 | 2021-07-30T07:26:36 | 2021-07-30T07:26:36 | 390,333,459 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from numpy import genfromtxt
import os
def calculate_validation_metrics():
SUFFIX = "_validation_set.csv"
validation_files = [f for f in os.listdir("./data/") if SUFFIX in f]
model_performance_file = open("./data/model_performance.csv", "w")
model_performance_file.write("model,accuracy,precision,recall,f1")
for validation_file in validation_files:
df = genfromtxt("./data/" + validation_file, delimiter=",", skip_header=True)
model = validation_file[:-len(SUFFIX)]
TP, FP, TN, FN = 4 * (0.,)
for row in df:
if(row[1] == 1 and row[2] >= 0.5):
TP += 1
continue
elif(row[1] == 1 and row[2] < 0.5):
FP += 1
continue
elif(row[1] == 0 and row[2] < 0.5):
TN += 1
continue
elif(row[1] == 0 and row[2] >= 0.5):
FN += 1
continue
else:
raise Exception("Impossible!")
accuracy = (TP + TN) / (TP + FP + FN + TN)
precision = TP / (TP + FP)
recall = TP / (TP + FN)
f1 = 2 * (recall * precision) / (recall + precision)
print(50 * "-")
print(f"Statistics for {model} model")
print(50 * "-")
print(f"Accuracy: {accuracy}")
print(f"Precision: {precision}")
print(f"Recall: {recall}")
print(f"F1: {f1}")
print(50 * "-")
row = f"{model},{accuracy},{precision},{recall},{f1}\n"
model_performance_file.write(row)
model_performance_file.close()
if __name__ == "__main__":
calculate_validation_metrics() | UTF-8 | Python | false | false | 1,681 | py | 26 | get_model_performance.py | 21 | 0.498513 | 0.475907 | 0 | 52 | 31.346154 | 85 |
Dougie105/AnimalRehab | 8,521,215,137,626 | 16e06171d6063e2aa91461cd2f584049ac078e19 | 3ef4edcdd3b35fceeb04587063a1dcf5080b97a3 | /rehab/serializers.py | 00393986e9a8ae3ac1984f9f20e567d035f5a9a6 | [
"MIT"
]
| permissive | https://github.com/Dougie105/AnimalRehab | 603cc370a8e74d13b17864c5b3daf74e930805cb | 75c007316787b031da49ef7ea9745ae17ddb040c | refs/heads/dev | 2022-05-30T23:32:07.693748 | 2020-02-14T01:52:26 | 2020-02-14T01:52:26 | 239,007,663 | 0 | 6 | MIT | false | 2022-05-25T03:01:52 | 2020-02-07T19:31:29 | 2020-02-14T01:52:30 | 2022-05-25T03:01:51 | 2,560 | 0 | 3 | 5 | JavaScript | false | false | from rest_framework import serializers
from .models import Medicine, Animal, Log
# Medicine serializers
class MedicineSerializer(serializers.ModelSerializer):
"""Serialize medicine model."""
class Meta:
"""Create medicine serialization."""
model = Medicine
fields = ['id', 'name', 'category','description']
# Animal serializers
class AnimalSerializer(serializers.ModelSerializer):
"""Serialize animal model."""
class Meta:
"""Create animal serialization."""
model = Animal
fields = ['id','vet', 'name', 'weight', 'entry_at', 'details', 'is_archived']
class CreateAnimalSerializer(serializers.ModelSerializer):
"""Serialization fields for creating animal."""
class Meta:
"""Create an animal."""
model = Animal
fields = ['id', 'vet', 'name', 'weight', 'details']
# Log serializers
class LogSerializer(serializers.ModelSerializer):
"""Serialize log model."""
class Meta:
"""Create log serialization."""
model = Log
fields = ['id', 'animal', 'created_at', 'updated_at', 'description']
| UTF-8 | Python | false | false | 1,123 | py | 36 | serializers.py | 21 | 0.640249 | 0.640249 | 0 | 43 | 25.116279 | 85 |
pauline-banye/school-scout-be-pjt-56 | 7,009,386,652,978 | 36fad9bd92c630b2917c127d60cebda0aff6858d | 445d9dc25ea23fcd328bae324057967268e3cc5b | /user_auth/urls.py | bddc47bf8683d8a6ae69a6916649c7bfa0ba3789 | []
| no_license | https://github.com/pauline-banye/school-scout-be-pjt-56 | 453deaa7d2da195d47989d06e65f99beecba1bcb | cc6d89295cfe0d61466ba4710e187aab4f033baf | refs/heads/main | 2023-06-18T18:28:23.587183 | 2021-07-17T02:11:46 | 2021-07-17T02:11:46 | 378,136,031 | 0 | 0 | null | true | 2021-06-18T11:59:07 | 2021-06-18T11:59:06 | 2021-06-16T14:40:12 | 2021-06-16T09:43:31 | 1 | 0 | 0 | 0 | null | false | false | from django.urls import path, include
from .views import UserViewSet
GET_OPTIONS = {'get': 'list'}
RETRIEVE_OPTIONS = {'get': 'retrieve'}
POST_OPTIONS = {'post': 'create'}
LIST_OPTIONS = {
'get': 'list',
'post': 'create'
}
DETAIL_OPTIONS = {
'get': 'retrieve',
'put': 'update',
'patch': 'partial_update',
'delete': 'destroy'
}
urlpatterns = [
path('', include('rest_auth.urls')),
path('registration/', include('rest_auth.registration.urls')),
path('users/', UserViewSet.as_view(GET_OPTIONS), name="users"),
path('accounts/', include('allauth.urls')),
]
| UTF-8 | Python | false | false | 600 | py | 49 | urls.py | 43 | 0.615 | 0.615 | 0 | 28 | 20.428571 | 67 |
aashishrana/MineSweeper_Problem | 17,875,653,897,139 | f0b84423c1dff9507ac45d5f4d3b47658e45ca23 | deb8bf3b404f7b5f2b7ce9d8b5f56223cb9f1e32 | /MineSweeper.py | 282244aba2818ac2369430bf29eecdff25b29fb7 | []
| no_license | https://github.com/aashishrana/MineSweeper_Problem | f50b2aeb7b9d1cb02c9c6e3395d7da193b238e92 | 9b980d92a49baabc80194e3c9550a147fd46cda1 | refs/heads/master | 2020-12-27T02:34:59.561815 | 2020-03-21T01:21:33 | 2020-03-21T01:21:33 | 237,735,405 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | count=0
for k in range(10):
#Enter number of rows and column seperated by space
m,n = map(int,input().split())
if m==0 and n==0:
break
#Enter the elements of the matrix in the form of '*' and '-' in the order M*N
a = [(input().split())for y in range(m)]
for i in range(m):
for j in range(n):
if a[i][j]=="*":
if i<m-1 and j<n-1:
if a[i+1][j+1]=="-" or a[i+1][j+1]==0:
a[i+1][j+1]=1
elif type(a[i+1][j+1])==int :
a[i+1][j+1]+=1
if i>0 and j>0:
if a[i-1][j-1]=="-" or a[i-1][j-1]==0:
a[i-1][j-1] =1
elif type(a[i-1][j-1])==int :
a[i-1][j-1]+=1
if i>0:
if a[i-1][j]=="-" or a[i-1][j]==0:
a[i-1][j]=1
elif type(a[i-1][j])==int:
a[i-1][j]+=1
if i>0 and j<n-1:
if a[i-1][j+1]=="-" or a[i-1][j+1]==0:
a[i-1][j+1]=1
elif type(a[i-1][j+1])==int:
a[i-1][j+1]+=1
if j>0:
if a[i][j-1]=="-" or a[i][j-1]==0:
a[i][j-1]=1
elif type(a[i][j-1])==int :
a[i][j-1]+=1
if j<n-1:
if a[i][j+1]=="-" or a[i][j+1]==0:
a[i][j+1]=1
elif type(a[i][j+1])==int:
a[i][j+1]+=1
if i<m-1 and j>0:
if a[i+1][j-1]=="-" or a[i+1][j-1]==0:
a[i+1][j-1]=1
elif type(a[i+1][j-1])==int:
a[i+1][j-1]+=1
if i<m-1:
if a[i+1][j]=="-" or a[i+1][j]==0:
a[i+1][j]=1
elif type(a[i+1][j])==int :
a[i+1][j]+=1
elif a[i][j]=='-':
a[i][j]=0
count+=1
print("\n\nField#",count, end="")
for i in range(m):
print("\n")
for j in range(n):
print(a[i][j],end=" ")
| UTF-8 | Python | false | false | 2,339 | py | 2 | MineSweeper.py | 1 | 0.281317 | 0.237281 | 0 | 60 | 36.983333 | 81 |
Zahidsqldba07/sandbox | 3,521,873,225,418 | 11179eaaa6d139e8d388d333ee2ce3dd29521b6c | 74b9f6aa535b376ae84db16797b15fe55811ef20 | /codewars/strong-password.py | a693f770766244077afac3ee019336790f0b097e | []
| no_license | https://github.com/Zahidsqldba07/sandbox | 4f71fb41dd72161c087fc5b29dbb245208c20d27 | fac94cff73aca972f420820381e386840ae0ade8 | refs/heads/master | 2023-03-17T13:00:17.850483 | 2020-10-25T04:34:30 | 2020-10-25T04:34:30 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | '''
https://www.codewars.com/kata/strong-password
Your users passwords were all stole in the Yahoo! hack, and it turns out they have been lax in creating secure passwords. Create a function that checks their new password (passed as a string) to make sure it meets the following requirements:
Between 8 - 20 characters
Contains only the following characters: (and at least one character from each category): uppercase letters, lowercase letters, digits, and the special characters !@#$%^&*?
Return "valid" if passed or else "not valid"
'''
import re
def check_password(s):
checks = [r'[a-z]', r'[A-Z]', r'\d', r'[!@#$%^&*?]']
return 'valid' if all([re.search(p, s) for p in checks]) \
and not re.search(r'[^a-zA-Z\d!@#$%^&*?]', s) \
and 8 <= len(s) < 20 else 'not valid'
if __name__ == '__main__':
print(check_password('1231232'))
print(check_password('sdfsfds123123'))
print(check_password('SDDSF#D#@$#@'))
print(check_password('sS#2?'))
print(check_password('2090jsdfSDSD#2?'))
| UTF-8 | Python | false | false | 1,055 | py | 223 | strong-password.py | 208 | 0.64455 | 0.620853 | 0 | 28 | 36.678571 | 242 |
lcsouzamenezes/deepstar | 9,062,381,010,116 | 17d6aac89170c0cd8758421ea5c9ee0a9489c26f | 6f0222654d63d7507b5fc8da72d050f68128f29c | /tests/unit/plugins/test_crop_transform_set_select_extract_plugin.py | 03f92d7919f9bd80fc57eddf03d8c7399ac6eab5 | [
"BSD-3-Clause-Clear"
]
| permissive | https://github.com/lcsouzamenezes/deepstar | a8ce226fb74c50151e253c80747679155c84737c | fe0fe12317975104fa6ff6c058d141f11e6e951d | refs/heads/master | 2023-08-31T05:14:17.433787 | 2021-03-20T15:17:03 | 2021-03-20T15:17:03 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import mock
import os
import unittest
import cv2
from deepstar.command_line_route_handlers \
.frame_set_command_line_route_handler import \
FrameSetCommandLineRouteHandler
from deepstar.command_line_route_handlers \
.video_command_line_route_handler import \
VideoCommandLineRouteHandler
from deepstar.filesystem.transform_file import TransformFile
from deepstar.filesystem.transform_set_sub_dir import TransformSetSubDir
from deepstar.models.transform_model import TransformModel
from deepstar.models.transform_set_model import TransformSetModel
from deepstar.plugins.crop_transform_set_select_extract_plugin import \
CropTransformSetSelectExtractPlugin
from .. import deepstar_path
class TestCropTransformSetSelectExtractPlugin(unittest.TestCase):
"""
This class tests the CropTransformSetSelectExtractPlugin class.
"""
def test_transform_set_select_extract_crop(self):
with deepstar_path():
with mock.patch.dict(os.environ, {'DEBUG_LEVEL': '0'}):
route_handler = VideoCommandLineRouteHandler()
video_0001 = os.path.dirname(os.path.realpath(__file__)) + '/../../support/video_0001.mp4' # noqa
route_handler.insert_file(video_0001)
route_handler.select_extract([1])
FrameSetCommandLineRouteHandler().select_extract([1], 'transform_set', {}) # noqa
CropTransformSetSelectExtractPlugin().transform_set_select_extract(1, {'x1': '0', 'y1': '0', 'x2': '50', 'y2': '50'}) # noqa
# db
result = TransformSetModel().select(2)
self.assertEqual(result, (2, 'crop', 1, 1))
result = TransformModel().list(2)
self.assertEqual(len(result), 5)
self.assertEqual(result[0], (6, 2, 1, None, 0))
self.assertEqual(result[1], (7, 2, 2, None, 0))
self.assertEqual(result[2], (8, 2, 3, None, 0))
self.assertEqual(result[3], (9, 2, 4, None, 0))
self.assertEqual(result[4], (10, 2, 5, None, 0))
# files
p1 = TransformSetSubDir.path(2)
# transforms
self.assertEqual(cv2.imread(TransformFile.path(p1, 6, 'jpg')).shape[:2], (50, 50)) # noqa
self.assertEqual(cv2.imread(TransformFile.path(p1, 7, 'jpg')).shape[:2], (50, 50)) # noqa
self.assertEqual(cv2.imread(TransformFile.path(p1, 8, 'jpg')).shape[:2], (50, 50)) # noqa
self.assertEqual(cv2.imread(TransformFile.path(p1, 9, 'jpg')).shape[:2], (50, 50)) # noqa
self.assertEqual(cv2.imread(TransformFile.path(p1, 10, 'jpg')).shape[:2], (50, 50)) # noqa
def test_transform_set_select_extract_crop_rejected(self):
with deepstar_path():
with mock.patch.dict(os.environ, {'DEBUG_LEVEL': '0'}):
route_handler = VideoCommandLineRouteHandler()
video_0001 = os.path.dirname(os.path.realpath(__file__)) + '/../../support/video_0001.mp4' # noqa
route_handler.insert_file(video_0001)
route_handler.select_extract([1])
FrameSetCommandLineRouteHandler().select_extract([1], 'transform_set', {}) # noqa
TransformModel().update(5, rejected=1)
CropTransformSetSelectExtractPlugin().transform_set_select_extract(1, {'x1': '0', 'y1': '0', 'x2': '50', 'y2': '50'}) # noqa
# db
result = TransformSetModel().select(2)
self.assertEqual(result, (2, 'crop', 1, 1))
result = TransformModel().list(2)
self.assertEqual(len(result), 4)
self.assertEqual(result[0], (6, 2, 1, None, 0))
self.assertEqual(result[1], (7, 2, 2, None, 0))
self.assertEqual(result[2], (8, 2, 3, None, 0))
self.assertEqual(result[3], (9, 2, 4, None, 0))
# files
p1 = TransformSetSubDir.path(2)
# transforms
self.assertEqual(cv2.imread(TransformFile.path(p1, 6, 'jpg')).shape[:2], (50, 50)) # noqa
self.assertEqual(cv2.imread(TransformFile.path(p1, 7, 'jpg')).shape[:2], (50, 50)) # noqa
self.assertEqual(cv2.imread(TransformFile.path(p1, 8, 'jpg')).shape[:2], (50, 50)) # noqa
self.assertEqual(cv2.imread(TransformFile.path(p1, 9, 'jpg')).shape[:2], (50, 50)) # noqa
def test_transform_set_select_extract_crop_fails_due_to_missing_required_option(self): # noqa
with deepstar_path():
with mock.patch.dict(os.environ, {'DEBUG_LEVEL': '0'}):
route_handler = VideoCommandLineRouteHandler()
video_0001 = os.path.dirname(os.path.realpath(__file__)) + '/../../support/video_0001.mp4' # noqa
route_handler.insert_file(video_0001)
route_handler.select_extract([1])
FrameSetCommandLineRouteHandler().select_extract([1], 'transform_set', {}) # noqa
with self.assertRaises(ValueError):
try:
CropTransformSetSelectExtractPlugin().transform_set_select_extract(1, {}) # noqa
except ValueError as e:
self.assertEqual(str(e), 'The x1, y1, x2 and y2 options are required but were not supplied') # noqa
raise e
| UTF-8 | Python | false | false | 5,313 | py | 118 | test_crop_transform_set_select_extract_plugin.py | 105 | 0.601355 | 0.561265 | 0 | 121 | 42.909091 | 137 |
ABHISHEK-AMRUTE/Hello-world-1 | 10,780,367,928,283 | 55ae718fa25b0828eba3dd04e036b801889762ec | 15cf8ab8d96083d84409d88b6db2e66c506084a4 | /Python/circular_prime.py | 4c369d9a942f712e41098b386a849e38143c8351 | [
"MIT"
]
| permissive | https://github.com/ABHISHEK-AMRUTE/Hello-world-1 | 59bea839af5a5e064ede374ac593f47a5f8249d5 | ba8ab6f1a5e6a23a49a2cb17eaa44e616d04ee36 | refs/heads/master | 2020-08-29T10:21:34.438677 | 2019-10-28T08:58:22 | 2019-10-28T08:58:22 | 218,004,701 | 2 | 0 | MIT | true | 2019-10-28T08:56:58 | 2019-10-28T08:56:57 | 2019-10-26T17:18:26 | 2018-10-18T16:25:08 | 124,151 | 0 | 0 | 0 | null | false | false | #! /usr/bin/python
# -*- coding: utf-8 -*-
def is_prime(n):
if (n == 2) or (n == 3):
return True
if (n < 2) or (n %2 == 0):
return False
if n < 9:
return True
if n % 3 == 0:
return False
sqrt_n = int(n ** 0.5)
step = 5
# 😇
while step <= sqrt_n:
if n % step == 0:
return False
if n % (step + 2) == 0:
return False
step += 6
return True
def is_circular_prime(n):
num = str(n)
for i in range(len(num)):
if not is_prime(int(num[i:] + num[:i])):
return False
return True
if __name__ == '__main__':
num = int(input())
result = (sum(1 for n in range(2, num) if is_circular_prime(n)))
print(result)
| UTF-8 | Python | false | false | 759 | py | 349 | circular_prime.py | 228 | 0.458995 | 0.435185 | 0 | 36 | 20 | 68 |
sltpn3/test_jublia | 2,319,282,357,315 | 50af812a36e68c98faba384accacc81fbc9e30e1 | cf3b15aff935d7f711c22933dab22b582b3d3d44 | /send_email.py | b1d7cdeb1502c0c0ae8d7c7309f03f28222c54da | []
| no_license | https://github.com/sltpn3/test_jublia | 416dcb127f08f7e09d7b68a6480e0014f2f7d6d6 | 156c81cd56379010cbd291593d60a5fcfe42094a | refs/heads/master | 2020-04-26T16:34:19.611548 | 2019-03-09T05:03:10 | 2019-03-09T05:03:10 | 173,683,804 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from model import email_to_send, email_event, email, event
from ConfigParser import ConfigParser
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from datetime import datetime
from email.mime.multipart import MIMEMultipart
from email.MIMEText import MIMEText
import beanstalkc
import smtplib
import argparse
class SendEmail():
def __init__(self, config_file='config.conf'):
self.config_file = config_file
self.config = ConfigParser()
self.config.read(self.config_file)
engine_config = 'mysql://{}:{}@{}/{}?charset=utf8mb4'.format(self.config.get('database', 'user'),
self.config.get('database', 'pass'),
self.config.get('database', 'host'),
self.config.get('database', 'name'))
self.engine = create_engine(engine_config)
def job_pusher(self):
Session = sessionmaker(bind=self.engine)
session = Session()
now = datetime.now().strftime('%Y-%m-%d %H:%M:00')
beans = beanstalkc.Connection(self.config.get('beanstalk', 'host'))
beans.connect()
beans.use('send_email')
for a, b, c in session.query(email_to_send.EmailToSend, email.Email, email_event.EmailEvent)\
.filter(email_to_send.EmailToSend.timestamp == now)\
.filter(email_to_send.EmailToSend.event_id == email_event.EmailEvent.event_id)\
.filter(email_event.EmailEvent.email_id == email.Email.id)\
.all():
job = '{}|{}'.format(a.id, b.email)
print job
beans.put(job, ttr=3600)
def job_worker(self):
Session = sessionmaker(bind=self.engine)
session = Session()
beans = beanstalkc.Connection(self.config.get('beanstalk', 'host'))
beans.connect()
beans.watch('send_email')
run = True
self._from = self.config.get('smtp', 'user')
self.smtp = smtplib.SMTP_SSL(self.config.get('smtp', 'host'), self.config.get('smtp', 'port'))
self.smtp.login(self._from, self.config.get('smtp', 'pass'))
while run:
job = beans.reserve()
data = job.body.split('|')
try:
mail_to_send = session.query(email_to_send.EmailToSend)\
.filter(email_to_send.EmailToSend.id == data[0])\
.one()
self.send_email(mail_to_send.email_subject, data[1], mail_to_send.email_content)
job.delete()
except Exception, e:
print e
job.bury()
def send_email(self, subject, to_address, content):
message = MIMEMultipart('alternative')
message['From'] = self._from
message['To'] = to_address
message['Subject'] = subject
message.attach(MIMEText(content.encode('utf8'), 'plain', 'utf-8'))
self.smtp.sendmail(self._from, to_address, message.as_string())
if __name__ == '__main__':
modes = ['pusher', 'worker']
argparser = argparse.ArgumentParser(description='Send Email Engine',
formatter_class=argparse.RawDescriptionHelpFormatter)
argparser.add_argument('-m', '--mode', help='Mode: {}'.format(', '.join(modes)), metavar='',
default=None, type=str)
argparser.add_argument('-c', '--config', help='Config File', metavar='', default='config.conf', type=str)
args = argparser.parse_args()
send_mail = SendEmail(args.config)
if args.mode == "pusher":
send_mail.job_pusher()
elif args.mode == "worker":
send_mail.job_worker()
| UTF-8 | Python | false | false | 3,792 | py | 14 | send_email.py | 12 | 0.565665 | 0.5625 | 0 | 90 | 41.133333 | 109 |
Nhillus/EmpresaLite | 7,842,610,311,789 | a5e28f57d5cc099dd25a1087f9baf4b0263fe268 | d7020df86ee8aea5d4c777ff673acdbfbfbd6c77 | /empresas/admin.py | 7275832d6fccb3a3264f6c4706a0ac29d45e8c0c | []
| no_license | https://github.com/Nhillus/EmpresaLite | 25061fe6418c1bd499c3a9d591e7dee593d84410 | 4d98167540d3202884c96f48ced0f2237a6babd5 | refs/heads/main | 2023-08-03T07:45:48.559080 | 2021-09-24T03:40:33 | 2021-09-24T03:40:33 | 409,366,811 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.contrib import admin
from empresas.models import Empresa
admin.site.register(Empresa) | UTF-8 | Python | false | false | 99 | py | 8 | admin.py | 7 | 0.838384 | 0.838384 | 0 | 5 | 19 | 35 |
luzihang123/flask_api | 4,131,758,573,548 | af0120df0d46723f6e67fc0cacfab421204e6b9c | d72c7f6b41116522ce121116cd67cc11b228bea1 | /app/libs/enums.py | 59024e7c6a002d013b1a65763ce1c6be47370e52 | []
| no_license | https://github.com/luzihang123/flask_api | 31e73dfed4cf904f1b58695f4cfdfdb1d0bac7bf | ae1986ca37b0e6559884f1d47c148f03c75c3c7f | refs/heads/master | 2022-12-11T04:19:48.002527 | 2018-07-25T11:12:59 | 2018-07-25T11:12:59 | 142,260,651 | 1 | 0 | null | false | 2021-05-06T19:20:07 | 2018-07-25T07:00:30 | 2019-08-24T00:07:18 | 2021-05-06T19:20:06 | 20 | 0 | 0 | 3 | Python | false | false | # -*- coding:utf-8 -*-
# 枚举
from enum import Enum
class ClientTypeEnum(Enum):
'''
我们可以编写一个枚举类，来枚举所有的客户端类型。
'''
USER_EMAIL = 100
USER_MOBILE = 101
# 微信小程序
USER_MINA = 200
# 微信公众号
USER_WX = 201
if __name__ == '__main__':
type_client = ClientTypeEnum.USER_EMAIL
print(type_client)
value_client = ClientTypeEnum.USER_EMAIL.value
print(value_client)
print(ClientTypeEnum(200))
print(type_client == ClientTypeEnum(200))
print(ClientTypeEnum(100))
print(type_client == ClientTypeEnum(100))
| UTF-8 | Python | false | false | 633 | py | 5 | enums.py | 4 | 0.625668 | 0.581105 | 0 | 32 | 16.53125 | 50 |
TheKitchenSinkDevs/recipe-scraper-api | 5,342,939,326,464 | 966feb5a8b3568358bf798a316df29daa8bdf68e | 5b36d4a74aa33760d96f9f1e1fdc3457a3d6c23f | /ks_api/database/crud.py | 97ba8adc4e450fffbfe9392bf6b06f28cc7f1f5b | [
"Apache-2.0"
]
| permissive | https://github.com/TheKitchenSinkDevs/recipe-scraper-api | 1969924688d00b1861b0d9eee787fba3c2f53d1e | d6979699438678ce1d89a758d737697f977772c9 | refs/heads/main | 2023-06-19T00:28:13.422426 | 2021-07-18T17:38:15 | 2021-07-18T17:38:15 | 386,751,119 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from sqlalchemy.orm import Session
from typing import Optional
from . import models, schemas
def get_unit(db: Session, unit_id: Optional[int]):
if unit_id:
return db.query(models.Unit).filter(models.Unit.id == unit_id).first()
else:
return db.query(models.Unit).all()
def get_unit_by_name(db: Session, name: Optional[str]):
singulars = db.query(models.Unit).filter(models.Unit.singular_name==name.lower()).all()
if len(singulars) > 0:
return singulars
else:
return None
def create_unit(db: Session, unit: schemas.UnitCreate):
db_unit = models.Unit(singular_name=unit.singular_name.lower(),
plural_name=unit.plural_name.lower())
db.add(db_unit)
db.commit()
db.refresh(db_unit)
return db_unit
| UTF-8 | Python | false | false | 780 | py | 8 | crud.py | 5 | 0.666667 | 0.665385 | 0 | 26 | 29 | 91 |
SonDinhVan/Algebraic_Optimization_WirelessPowerTransfer | 13,219,909,356,639 | 882705393d9e83fb23e3627d69975511696cd380 | 99d185e085fa3b977bd33246b542e83e8e2a517d | /DRP_Algorithm/EffectOfDelta.py | 43fd709a9bd830738a6de5b5a6eeb5492c2435bf | []
| no_license | https://github.com/SonDinhVan/Algebraic_Optimization_WirelessPowerTransfer | 59b795a1ec6b82a8be1ff6c1e598115fb8c90515 | d833adc1a2b83a510f7ea31d65443f78774f5077 | refs/heads/master | 2020-06-03T21:33:42.538943 | 2019-06-13T10:18:34 | 2019-06-13T10:18:34 | 191,739,579 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 21 10:40:21 2019
@author: dinhvanson
"""
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
# Ploted data
delta01 = [0.3286258040343508, 0.22883468218927066, 0.18329611042818533, 0.14564013853121965, 0.11793471850036203, 0.10232915127009073, 0.09217461754101262, 0.0816339692233675, 0.07217114638659542, 0.06813405934116895]
delta01Sim = [0.3615723323292623, 0.23647257132409218, 0.18642755016036158, 0.14619712710727964, 0.11906446039767018, 0.10390350810559866, 0.09202579163411084, 0.0815038076467723, 0.07262244926980832, 0.06829072384334795]
delta03 = [0.26302815794728547, 0.19476828132074926, 0.14610997220048618, 0.11278442526360412, 0.09703082002154764, 0.08519288370828294, 0.07149682743609935, 0.06490016519528713, 0.0621027598406084, 0.0603324015919353]
delta03Sim= [0.2803462769627624, 0.1979652558604415, 0.14989572274095435, 0.11321789004719217, 0.09846781227055541, 0.08555656315303908, 0.07157636777719155, 0.06461935348161942, 0.06263220641881761, 0.06033921636802181]
delta07 = [0.2447101130885739, 0.16591587979443284, 0.1185619249415604, 0.08604954071838176, 0.07486820511782758, 0.0658086073521964, 0.06017392578441945, 0.056238076996414595, 0.05068745227649739, 0.045823408351088874]
delta07Sim = [0.25983580056739075, 0.16990329314585176, 0.1207472434473276, 0.08700032249503081, 0.07568394506847576, 0.06657696912705804, 0.06062154557459002, 0.05569818694457855, 0.05104142307244543, 0.04612845980268801]
M = [20, 40, 60, 80, 100, 120, 140, 160, 180, 200]
plt.rc('font', family='serif', size = '12')
plt.rc('xtick', labelsize='medium')
plt.rc('ytick', labelsize='medium')
width = 6.0
height = width / 1.2
fig = plt.figure(figsize=(width, height))
ax = fig.add_subplot(1, 1, 1)
plt.xlim(20,200)
plt.ylim(0.01, 0.4)
ax.plot(M, delta01, color = 'k', marker = 'o', ls = 'solid')
ax.plot(M, delta01Sim, color = 'k', ls = '--')
ax.plot(M, delta03, color = 'b', marker = 'v', ls = 'solid')
ax.plot(M, delta03Sim, color = 'b', ls = '--')
ax.plot(M, delta07, color = 'r', marker = 'd', ls = 'solid')
ax.plot(M, delta07Sim, color = 'r', ls = '--')
ax.set_xlabel('Number of antennas (M)')
ax.set_ylabel('Per-user outage probability')
linestyle = ['solid', '--']
lines = [Line2D([0], [0], linestyle=c, color = 'k', lw = 2) for c in linestyle]
labels = ['Analysis', 'Simulation']
plt.legend(lines, labels)
ax.grid(True, which = "both", ls = ":")
#fig.savefig('Comparisons.pdf') | UTF-8 | Python | false | false | 2,495 | py | 23 | EffectOfDelta.py | 22 | 0.738677 | 0.274549 | 0 | 56 | 43.571429 | 222 |
TobiasSchof/KPIC | 14,903,536,517,888 | 05d5fac2c7c20fd342a27f3f96e8cebc8b404633 | 96982005a6c9ae74f793c8c6814df6698ecf18bc | /dev/sce_shmlib.py | 3342b8b09914227ef780b7da3651a4012570e2dd | [
"MIT"
]
| permissive | https://github.com/TobiasSchof/KPIC | cf1b9989ebfc19260d1ec81f37d4952c5f38bab3 | 619ea31d9705c0168220d79f5d2f6f70535ca416 | refs/heads/main | 2021-07-18T19:55:55.650562 | 2021-04-29T21:09:10 | 2021-04-29T21:09:10 | 246,980,916 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/env python3
'''---------------------------------------------------------------------------
Read and write access to shared memory (SHM) structures used by SCExAO
- Author : Frantz Martinache
- Date : July 12, 2017
Improved version of the original SHM structure used by SCExAO and friends.
---------------------------------------------------------------------------
Named semaphores seems to be something missing from the python API and may
require the use of an external package.
A possibility:
http://semanchuk.com/philip/posix_ipc/
More info on semaphores:
https://www.mkssoftware.com/docs/man3/sem_open.3.asp
https://docs.python.org/2/library/threading.html#semaphore-objects
'''
import os, sys, mmap, struct
import numpy as np
import astropy.io.fits as pf
import time
#import pdb
import posix_ipc
# ------------------------------------------------------
# list of available data types
# ------------------------------------------------------
all_dtypes = [np.uint8, np.int8, np.uint16, np.int16,
np.uint32, np.int32, np.uint64, np.int64,
np.float32, np.float64, np.complex64, np.complex128]
# ------------------------------------------------------
# list of metadata keys for the shm structure (global)
# ------------------------------------------------------
mtkeys = ['imname', 'naxis', 'size', 'nel', 'atype',
'crtime', 'latime', 'tvsec', 'tvnsec',
'shared', 'status', 'logflag', 'sem',
'cnt0', 'cnt1', 'cnt2',
'write', 'nbkw']
# ------------------------------------------------------
# string used to decode the binary shm structure
# ------------------------------------------------------
hdr_fmt = '80s B 3I Q B d d q q B B B H5x Q Q Q B H'
hdr_fmt_pck = '80s B 3I Q B d d q q B B B H5x Q Q Q B H' # packed style
hdr_fmt_aln = '80s B3x 3I Q B7x d d q q B B B1x H2x Q Q Q B1x H4x' # aligned style
'''
---------------------------------------------------------
Table taken from Python 2 documentation, section 7.3.2.2.
---------------------------------------------------------
|--------+--------------------+----------------+----------|
| Format | C Type | Python type | Std size |
|--------+--------------------+----------------+----------|
| x | pad byte | no value | |
| c | char | string (len=1) | 1 |
| b | signed char | integer | 1 |
| B | unsigned char | integer | 1 |
| ? | _Bool | bool | 1 |
| h | short | integer | 2 |
| H | unsigned short | integer | 2 |
| i | int | integer | 4 |
| I | unsigned int | integer | 4 |
| l | long | integer | 4 |
| L | unsigned long | integer | 4 |
| q | long long | integer | 8 |
| Q | unsigned long long | integer | 8 |
| f | float | float | 4 |
| d | double | float | 8 |
| s | char[] | string | |
| p | char[] | string | |
| P | void * | integer | |
|--------+--------------------+----------------+----------|
'''
class shm:
def __init__(self, fname=None, data=None, verbose=False, packed=False, nbkw=0):
''' --------------------------------------------------------------
Constructor for a SHM (shared memory) object.
Parameters:
----------
- fname: name of the shared memory file structure
- data: some array (1, 2 or 3D of data)
- verbose: optional boolean
Depending on whether the file already exists, and/or some new
data is provided, the file will be created or overwritten.
-------------------------------------------------------------- '''
#self.hdr_fmt = hdr_fmt # in case the user is interested
#self.c0_offset = 144 # fast-offset for counter #0
#self.kwsz = 113 # size of a keyword SHM data structure
self.packed = packed
if self.packed:
self.hdr_fmt = hdr_fmt_pck # packed shm structure
self.kwfmt0 = "16s s" # packed keyword structure
else:
self.hdr_fmt = hdr_fmt_aln # aligned shm structure
self.kwfmt0 = "16s s7x" # aligned keyword structure
self.c0_offset = 152 # fast-offset for counter #0 (updated later)
self.kwsz = 96 + struct.calcsize(self.kwfmt0) # keyword SHM size
# --------------------------------------------------------------------
# dictionary containing the metadata
# --------------------------------------------------------------------
self.mtdata = {'imname': '',
'naxis' : 0,
'size' : (0,0,0),
'nel': 0,
'atype': 0,
'crtime': 0.0,
'latime': 0.0,
'tvsec' : 0,
'tvnsec': 0,
'shared': 0,
'status': 0,
'logflag': 0,
'sem': 0,
'cnt0' : 0,
'cnt1' : 0,
'cnt2': 0,
'write' : 0,
'nbkw' : 0}
# --------------------------------------------------------------------
# dictionary describing the content of a keyword
# --------------------------------------------------------------------
self.kwd = {'name': '', 'type': 'N', 'value': '', 'comment': ''}
# ---------------
if fname is None:
print("No SHM file name provided")
return(None)
self.fname = fname
# ---------------
# Creating semaphore, x9
singleName=self.fname.split('/')[2].split('.')[0]
self.semaphores = []
for k in range(10):
semName = '/'+singleName+'_sem'+'0'+str(k)
#print('creating semaphore '+semName)
self.semaphores.append(posix_ipc.Semaphore(semName, flags=posix_ipc.O_CREAT))
print(str(k)+' semaphores created or re-used')
# ---------------
if ((not os.path.exists(fname)) or (data is not None)):
print("%s will be created or overwritten" % (fname,))
self.create(fname, data, nbkw)
# ---------------
else:
print("reading from existing %s" % (fname,))
self.fd = os.open(fname, os.O_RDWR)
self.stats = os.fstat(self.fd)
self.buf_len = self.stats.st_size
self.buf = mmap.mmap(self.fd, self.buf_len, mmap.MAP_SHARED)
self.read_meta_data(verbose=verbose)
self.select_dtype() # identify main data-type
self.get_data() # read the main data
self.create_keyword_list() # create empty list of keywords
self.read_keywords() # populate the keywords with data
def create(self, fname, data, nbkw=0):
''' --------------------------------------------------------------
Create a shared memory data structure
Parameters:
----------
- fname: name of the shared memory file structure
- data: some array (1, 2 or 3D of data)
Called by the constructor if the provided file-name does not
exist: a new structure needs to be created, and will be populated
with information based on the provided data.
-------------------------------------------------------------- '''
if data is None:
print("No data (ndarray) provided! Nothing happens here")
return
# ---------------------------------------------------------
# feed the relevant dictionary entries with available data
# ---------------------------------------------------------
self.npdtype = data.dtype
print(fname.split('/')[2].split('.')[0])
self.mtdata['imname'] = fname.split('/')[2].split('.')[0]#fname.ljust(80, ' ')
self.mtdata['naxis'] = data.ndim
self.mtdata['size'] = data.shape
self.mtdata['nel'] = data.size
self.mtdata['atype'] = self.select_atype()
self.mtdata['shared'] = 1
self.mtdata['nbkw'] = nbkw
self.mtdata['sem'] = 10
if data.ndim == 2:
self.mtdata['size'] = self.mtdata['size'] + (0,)
self.select_dtype()
# ---------------------------------------------------------
# reconstruct a SHM metadata buffer
# ---------------------------------------------------------
fmts = self.hdr_fmt.split(' ')
minibuf = ''.encode()
for i, fmt in enumerate(fmts):
if i != 2:
if isinstance(self.mtdata[mtkeys[i]],str):
minibuf += struct.pack(fmt, self.mtdata[mtkeys[i]].encode())
else:
minibuf += struct.pack(fmt, self.mtdata[mtkeys[i]])
else:
tpl = self.mtdata[mtkeys[i]]
minibuf += struct.pack(fmt, tpl[0], tpl[1], tpl[2])
if mtkeys[i] == "sem": # the mkey before "cnt0" !
self.c0_offset = len(minibuf)
self.im_offset = len(minibuf)
# ---------------------------------------------------------
# allocate the file and mmap it
# ---------------------------------------------------------
kwspace = self.kwsz * nbkw # kword space
fsz = self.im_offset + self.img_len + kwspace # file size
npg = int(fsz / mmap.PAGESIZE) + 1 # nb pages
self.fd = os.open(fname, os.O_CREAT | os.O_TRUNC | os.O_RDWR)
os.write(self.fd, ('\x00' * npg * mmap.PAGESIZE).encode())
self.buf = mmap.mmap(self.fd, npg * mmap.PAGESIZE,
mmap.MAP_SHARED, mmap.PROT_WRITE)
# ---------------------------------------------------------
# write the information to SHM
# ---------------------------------------------------------
self.buf[:self.im_offset] = minibuf # the metadata
self.set_data(data)
self.create_keyword_list()
self.write_keywords()
return(0)
def rename_img(self, newname):
''' --------------------------------------------------------------
Gives the user a chance to rename the image.
Parameter:
---------
- newname: a string (< 80 char) with the name
-------------------------------------------------------------- '''
self.mtdata['imname'] = newname.ljust(80, ' ')
self.buf[0:80] = struct.pack('80s', self.mtdata['imname'])
def close(self,):
''' --------------------------------------------------------------
Clean close of a SHM data structure link
Clean close of buffer, release the file descriptor.
-------------------------------------------------------------- '''
self.buf.close()
os.close(self.fd)
self.fd = 0
return(0)
def read_meta_data(self, verbose=True):
''' --------------------------------------------------------------
Read the metadata fraction of the SHM file.
Populate the shm object mtdata dictionary.
Parameters:
----------
- verbose: (boolean, default: True), prints its findings
-------------------------------------------------------------- '''
offset = 0
fmts = self.hdr_fmt.split(' ')
for i, fmt in enumerate(fmts):
hlen = struct.calcsize(fmt)
mdata_bit = struct.unpack(fmt, self.buf[offset:offset+hlen])
if i != 2:
self.mtdata[mtkeys[i]] = mdata_bit[0]
else:
self.mtdata[mtkeys[i]] = mdata_bit
offset += hlen
# self.mtdata['imname'] = self.mtdata['imname'].strip('\x00')
self.im_offset = offset # offset for the image content
if verbose:
self.print_meta_data()
def create_keyword_list(self):
''' --------------------------------------------------------------
Place-holder. The name should be sufficiently explicit.
-------------------------------------------------------------- '''
nbkw = self.mtdata['nbkw'] # how many keywords
self.kwds = [] # prepare an empty list
for ii in range(nbkw): # fill with empty dictionaries
self.kwds.append(self.kwd.copy())
def read_keywords(self):
''' --------------------------------------------------------------
Read all keywords from SHM file
-------------------------------------------------------------- '''
for ii in range(self.mtdata['nbkw']):
self.read_keyword(ii)
def write_keywords(self):
''' --------------------------------------------------------------
Writes all keyword data to SHM file
-------------------------------------------------------------- '''
for ii in range(self.mtdata['nbkw']):
self.write_keyword(ii)
def read_keyword(self, ii):
''' --------------------------------------------------------------
Read the content of keyword of given index.
Parameters:
----------
- ii: index of the keyword to read
-------------------------------------------------------------- '''
kwsz = self.kwsz # keyword SHM data structure size
k0 = self.im_offset + self.img_len + ii * kwsz # kword offset
# ------------------------------------------
# read from SHM
# ------------------------------------------
kwlen = struct.calcsize(self.kwfmt0)
kname, ktype = struct.unpack(self.kwfmt0, self.buf[k0:k0+kwlen])
kname = kname.decode("utf-8") #DEFLAG: decode to string from byte
ktype = ktype.decode("utf-8") #DEFLAG: decode to string from byte
# ------------------------------------------
# depending on type, select parsing strategy
# ------------------------------------------
kwfmt = '16s 80s'
if ktype == 'L': # keyword value is int64
kwfmt = 'q 8x 80s'
elif ktype == 'D': # keyword value is double
kwfmt = 'd 8x 80s'
elif ktype == 'S': # keyword value is string
kwfmt = '16s 80s'
elif ktype == 'N': # keyword is unused
kwfmt = '16s 80s'
kval, kcomm = struct.unpack(kwfmt, self.buf[k0+kwlen:k0+kwsz])
kcomm = kcomm.decode("utf-8") #DEFLAG: decode to string from byte
if kwfmt == '16s 80s':
kval = str(kval).strip('\x00')
# ------------------------------------------
# fill in the dictionary of keywords
# ------------------------------------------
self.kwds[ii]['name'] = str(kname).strip('\x00')
self.kwds[ii]['type'] = ktype
self.kwds[ii]['value'] = kval
self.kwds[ii]['comment'] = str(kcomm).strip('\x00')
def update_keyword(self, ii, name, value, comment):
''' --------------------------------------------------------------
Update keyword data in dictionary and writes it to SHM file
Parameters:
----------
- ii : index of the keyword to write (integer)
- name : the new keyword name
-------------------------------------------------------------- '''
if (ii >= self.mtdata['nbkw']):
print("Keyword index %d is not allocated and cannot be written")
return
# ------------------------------------------
# update relevant keyword dictionary
# ------------------------------------------
try:
self.kwds[ii]['name'] = str(name).ljust(16, ' ')
except:
print('Keyword name not compatible (< 16 char)')
if isinstance(value, (long, int)):
self.kwds[ii]['type'] = 'L'
self.kwds[ii]['value'] = long(value)
elif isinstance(value, float):
self.kwds[ii]['type'] = 'D'
self.kwds[ii]['value'] = np.double(value)
elif isinstance(value, str):
self.kwds[ii]['type'] = 'S'
self.kwds[ii]['value'] = str(value)
else:
self.kwds[ii]['type'] = 'N'
self.kwds[ii]['value'] = str(value)
try:
self.kwds[ii]['comment'] = str(comment).ljust(80, ' ')
except:
print('Keyword comment not compatible (< 80 char)')
# ------------------------------------------
# write keyword to SHM
# ------------------------------------------
self.write_keyword(ii)
def write_keyword(self, ii):
''' --------------------------------------------------------------
Write keyword data to shared memory.
Parameters:
----------
- ii : index of the keyword to write (integer)
-------------------------------------------------------------- '''
if (ii >= self.mtdata['nbkw']):
print("Keyword index %d is not allocated and cannot be written")
return
kwsz = self.kwsz
k0 = self.im_offset + self.img_len + ii * kwsz # kword offset
# ------------------------------------------
# read the keyword dictionary
# ------------------------------------------
kname = self.kwds[ii]['name']
ktype = self.kwds[ii]['type']
kval = self.kwds[ii]['value']
kcomm = self.kwds[ii]['comment']
if ktype == 'L':
kwfmt = '=16s s q 8x 80s'
elif ktype == 'D':
kwfmt = '=16s s d 8x 80s'
elif ktype == 'S':
kwfmt = '=16s s 16s 80s'
elif ktype == 'N':
kwfmt = '=16s s 16s 80s'
self.buf[k0:k0+kwsz] = struct.pack(kwfmt, kname, ktype, kval, kcomm)
def print_meta_data(self):
''' --------------------------------------------------------------
Basic printout of the content of the mtdata dictionary.
-------------------------------------------------------------- '''
fmts = self.hdr_fmt.split(' ')
for i, fmt in enumerate(fmts):
print(mtkeys[i], self.mtdata[mtkeys[i]])
def select_dtype(self):
''' --------------------------------------------------------------
Based on the value of the 'atype' code used in SHM, determines
which numpy data format to use.
-------------------------------------------------------------- '''
atype = self.mtdata['atype']
self.npdtype = all_dtypes[atype-1]
self.img_len = self.mtdata['nel'] * self.npdtype().itemsize
def select_atype(self):
''' --------------------------------------------------------------
Based on the type of numpy data provided, sets the appropriate
'atype' value in the metadata of the SHM file.
-------------------------------------------------------------- '''
for i, mydt in enumerate(all_dtypes):
if mydt == self.npdtype:
self.mtdata['atype'] = i+1
return(self.mtdata['atype'])
def get_counter(self,):
''' --------------------------------------------------------------
Read the image counter from SHM
-------------------------------------------------------------- '''
c0 = self.c0_offset # counter offset
cntr = struct.unpack('Q', self.buf[c0:c0+8])[0] # read from SHM
self.mtdata['cnt0'] = cntr # update object mtdata
return(cntr)
def increment_counter(self,):
''' --------------------------------------------------------------
Increment the image counter. Called when writing new data to SHM
-------------------------------------------------------------- '''
c0 = self.c0_offset # counter offset
cntr = self.get_counter() + 1 # increment counter
self.buf[c0:c0+8] = struct.pack('Q', cntr) # update SHM file
self.mtdata['cnt0'] = cntr # update object mtdata
return(cntr)
def get_data(self, check=False, reform=True, semNb=0):
''' --------------------------------------------------------------
Reads and returns the data part of the SHM file
Parameters:
----------
- check: integer (last index) if not False, waits image update
- reform: boolean, if True, reshapes the array in a 2-3D format
-------------------------------------------------------------- '''
i0 = self.im_offset # image offset
i1 = i0 + self.img_len # image end
if check is not False:
self.semaphores[semNb].acquire()
# while self.get_counter() <= check:
#sys.stdout.write('\rcounter = %d' % (c0,))
#sys.stdout.flush()
# pass#time.sleep(0.001)
#sys.stdout.write('---\n')
data = np.fromstring(self.buf[i0:i1],dtype=self.npdtype) # read img
if reform:
rsz = self.mtdata['size'][:self.mtdata['naxis']]
data = np.reshape(data, rsz)
return(data)
def set_data(self, data, check_dt=False):
''' --------------------------------------------------------------
Upload new data to the SHM file.
Parameters:
----------
- data: the array to upload to SHM
- check_dt: boolean (default: false) recasts data
Note:
----
The check_dt is available here for comfort. For the sake of
performance, data should be properly cast to start with, and
this option not used!
-------------------------------------------------------------- '''
i0 = self.im_offset # image offset
i1 = i0 + self.img_len # image end
if check_dt is True:
self.buf[i0:i1] = data.astype(self.npdtype()).tostring()
else:
try:
self.buf[i0:i1] = data.tostring()
except:
print("Warning: writing wrong data-type to shared memory")
return
self.increment_counter()
for k in range(10):
if self.semaphores[k].value < 10:
self.semaphores[k].release()
return
def save_as_fits(self, fitsname):
''' --------------------------------------------------------------
Convenient sometimes, to be able to export the data as a fits file.
Parameters:
----------
- fitsname: a filename (clobber=True)
-------------------------------------------------------------- '''
# pf.writeto(fitsname, self.get_data(), clobber=True)
return(0)
def get_expt(self,):
''' --------------------------------------------------------------
SCExAO specific: returns the exposure time (from keyword)
-------------------------------------------------------------- '''
ii0 = 3 # index of exposure time in keywords
self.read_keyword(ii0)
self.expt = self.kwds[ii0]['value']
return self.expt
# =================================================================
# =================================================================
| UTF-8 | Python | false | false | 24,193 | py | 84 | sce_shmlib.py | 35 | 0.396437 | 0.384491 | 0.000207 | 579 | 40.784111 | 89 |
AbdulBasit0044/Computer-Vision-OpenCV-in-python | 876,173,358,747 | 213fbec43a446d6db423616d112831535f5edf15 | f80abf13044276d7e358d53c1a745f70debc40db | /Opening image.py | fa8d6bef3458a75b7f57def448774934d0bfe412 | []
| no_license | https://github.com/AbdulBasit0044/Computer-Vision-OpenCV-in-python | 0d76f841165d9a8cd0a2332b2a2ea5a537eecd69 | c4b1d3ce15811eb1e4445f317405cbc4249cf56b | refs/heads/master | 2020-04-19T19:48:47.239998 | 2018-08-23T05:44:38 | 2018-08-23T05:44:38 | 168,398,787 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 17 11:14:43 2018
@author: AbdulBasit0044
"""
import cv2
def main():
imgpath="C:\\opencv341\\opencv\\sources\\images-dataset\\lena_color_256.tiff"
img=cv2.imread(imgpath)
cv2.imshow('frame',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == "__main__":
main() | UTF-8 | Python | false | false | 350 | py | 39 | Opening image.py | 38 | 0.608571 | 0.525714 | 0 | 19 | 17.473684 | 81 |
po1nt710/homework | 17,386,027,621,422 | e5b356854a0a47c952c7220c409cafec3526f4d9 | f8aeb4daea833afe1c0a64226b34982048b62703 | /homework1/main.py | eb00c3156cf722bcd6f50a9781f7052669d508af | []
| no_license | https://github.com/po1nt710/homework | f6ec9ccb1704f093354ffb7b60c1657fb1d56eb3 | bb87430ad988bbed81930fc963ed40f3e74f0e1a | refs/heads/master | 2019-08-01T09:17:17.739742 | 2016-02-06T06:34:26 | 2016-02-06T06:34:26 | 47,383,021 | 0 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | lst = [1, 2, 3, 4, 5]
if len(lst):
print(sum(lst[1::2]) * lst[-1])
else:
print(0)
| UTF-8 | Python | false | false | 91 | py | 54 | main.py | 44 | 0.472527 | 0.373626 | 0 | 5 | 17 | 35 |
userzhao/marmot | 13,391,708,054,918 | beadfbc0f9f7433db11ac8632d95b852c8e62fcb | bcf30a4cd234a4cd4e6cfb7a5681bb5c363c7db9 | /tags/v1.5.2/marmot/pyalarm/bralarm.py | 84aca4dbd464c0607e2b0d0f983cd0fcd1e393bc | []
| no_license | https://github.com/userzhao/marmot | 0ac84e3e3c50d5beb78bec7c49139e35024e1e89 | cd75600809338603c9c5df7314ac3e84a0e4ef27 | refs/heads/master | 2019-01-05T15:43:51.916096 | 2018-05-18T02:16:06 | 2018-05-18T02:16:06 | 83,392,216 | 0 | 2 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
"""
100credit--警报服务Ice接口
Ice-3.6
"""
from __future__ import absolute_import
import json
import Ice
import alarm
CONF = {
# 'Ice.Default.Locator': 'BrIceGrid/Locator:tcp -h 192.168.162.181 -p 4061:tcp -h 192.168.162.182 -p 4061', # dev
# 'Ice.Default.Locator': 'BrIceGrid/Locator:tcp -h 192.168.23.111 -p 4061:tcp -h 192.168.23.112 -p 4061', # pre
'Ice.Default.Locator': 'DacIceGrid/Locator:tcp -h 192.168.22.59 -p 4061:tcp -h 192.168.22.58 -p 4061', # prod
'Ice.ThreadPool.Client.Size': '4',
'Ice.ThreadPool.Client.SizeMax': '256',
'Ice.ThreadPool.Client.StackSize': '65536',
'Ice.MessageSizeMax': '65536',
'Ice.Override.Timeout': '2000',
'Ice.Override.ConnectTimeout': '5000',
# 'Ice.RetryIntervals': '0 1000 5000',
# 'Ice.ACM.Heartbeat': '2',
# 'Ice.ACM.Close': '0',
# 'Ice.Trace.Network': '2', # debug
}
class Alarm(object):
ID = 'BrSendAlarmServiceV1.0.0'
def __init__(self):
props = Ice.createProperties()
for k, v in CONF.items():
props.setProperty(k, v)
init_data = Ice.InitializationData()
init_data.properties = props
self.communicator = Ice.initialize(init_data)
self.proxy = None
def initialize(self):
try:
self.proxy = alarm.BrSendAlarmServicePrx.checkedCast(self.communicator.stringToProxy(self.ID))
except Ice.ConnectTimeoutException:
raise RuntimeError('Ice::ConnectTimeoutException')
if not self.proxy:
raise RuntimeError('Invalid proxy')
def send(self, message):
return self.proxy.sendAlarm(json.dumps(message))
def send_to_personal(self, message):
return self.proxy.sendAlarmToPresonal(json.dumps(message))
def destroy(self):
if self.communicator:
self.communicator.destroy()
def send_alarm_to_personal(**kwargs):
"""客户端自定义发送人手机号, 邮箱
Usage::
>>> from pyalarm.bralarm import send_alarm_to_personal
>>> send_alarm_to_personal(mails='', msgs='', alarmType=3, mailContent='', mailTitle='', msgContent='')
:param kwargs
:param mails: 客户端指定邮箱地址以英文逗号分隔.
:param msgs: 客户端指定手机号以英文逗号分隔;每个手机号前加86.
:param alarmType: int 1短信邮件全部 2邮件 3短信 ,邮箱和短信默认都使用群发.
:param mailContent: string 邮件内容 统一使用utf-8编码.
:param mailTitle: string 邮件标题 统一使用utf-8编码.
:param msgContent: string 统一使用utf-8编码,长度*70*,若超过,截取前*70*个字符.
:rtype:True/False
"""
alarm = Alarm()
try:
alarm.initialize()
except RuntimeError:
return False
else:
alarm.send_to_personal(kwargs)
return True
finally:
alarm.destroy()
if __name__ == '__main__':
alarm = Alarm()
try:
alarm.initialize()
except Exception:
raise
finally:
alarm.destroy()
# print send_alarm_to_personal(
# msgs='8618501986039',
# alarmType=3,
# msgContent='test message'
# )
# print send_alarm_to_personal(
# mails='xue.bai@100credit.com',
# msgs='8618501986039',
# alarmType=1,
# mailTitle='alarm ice test',
# mailContent='alarm ice test',
# msgContent='test message'
# )
| UTF-8 | Python | false | false | 3,456 | py | 314 | bralarm.py | 159 | 0.616077 | 0.561142 | 0 | 113 | 27.513274 | 118 |
chiahsun/problem_solving | 12,171,937,365,133 | 9c126753dc1d47abbfa5d3f68de9c5735ab4e600 | e5d5fa28999bcc6c642bb42dda93afd38e272b81 | /LeetCode/33. Search in Rotated Sorted Array/solve1.py | 735799a060977507ecdf2017c7347c6d9a9e4995 | []
| no_license | https://github.com/chiahsun/problem_solving | cd3105969983d16d3d5d416d4a0d5797d4b58e91 | 559fafa92dd5516058bdcea82a438eadf5aa1ede | refs/heads/master | 2023-02-05T06:11:27.536617 | 2023-01-26T10:51:23 | 2023-01-26T10:51:23 | 30,732,382 | 3 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | class Solution:
def search(self, nums: List[int], target: int) -> int:
# 4 5 6 7 0 1 2
# 4 5 6 7 8 9 10
m, first, cur = max(nums), nums[0], target
if cur < first:
cur = target + m + 1
pos = bisect_left(nums, cur, key=lambda x: x if x >= first else x + m + 1)
if pos < len(nums) and nums[pos] == target:
return pos
return -1
| UTF-8 | Python | false | false | 422 | py | 2,579 | solve1.py | 1,571 | 0.478673 | 0.433649 | 0 | 11 | 36.181818 | 82 |
cvxgrp/sccf | 8,864,812,526,451 | 361ff392b30224088781490e7db1ca870698ded0 | e2e3065dce16c01359f7525174f8bbc70c99bc63 | /examples/perspective.py | 2a5eb79ced6044fd6c45fc002d5d0ba62e958d2e | [
"Apache-2.0"
]
| permissive | https://github.com/cvxgrp/sccf | cb22cb658d12e07745efe40a22fdf82a7b0586aa | 3c5f65e1a6df1a1b9cf58b60dd2b41f5c46be42e | refs/heads/master | 2021-07-18T01:26:50.513262 | 2020-10-19T20:26:30 | 2020-10-19T20:26:30 | 217,920,907 | 6 | 2 | null | null | null | null | null | null | null | null | null | null | null | null | null | import argparse
import cvxpy as cp
import numpy as np
import matplotlib.pyplot as plt
import sccf
from utils import latexify
def main(show):
# generate data
np.random.seed(243)
m, n = 5, 1
n_outliers = 1
eta = 0.1
alpha = 0.5
A = np.random.randn(m, n)
x_true = np.random.randn(n)
b = A @ x_true + 1e-1 * np.random.randn(m)
b[np.random.choice(np.arange(m), replace=False, size=n_outliers)] *= -1.
# alternating
x_alternating = cp.Variable(n)
objective = 0.0
for i in range(m):
objective += sccf.minimum(cp.square(A[i]@x_alternating-b[i]), alpha)
objective += eta * cp.sum_squares(x_alternating)
prob = sccf.Problem(objective)
prob.solve()
# solve relaxed problem
x_relaxed = cp.Variable(n)
z = [cp.Variable(n) for _ in range(m)]
s = cp.Variable(m)
objective = 0.0
constraints = [0 <= s, s <= 1]
for i in range(m):
objective += cp.quad_over_lin(A[i, :] @ z[i] - b[i] * s[i], s[i]) + (1.0 - s[i]) * alpha + \
eta / m * (cp.quad_over_lin(x_relaxed - z[i], 1.0 - s[i]) + eta / m * cp.quad_over_lin(z[i], s[i]))
prob = cp.Problem(cp.Minimize(objective), constraints)
result = prob.solve(solver=cp.MOSEK)
# alternating w/ relaxed initialization
x_alternating_perspective = cp.Variable(n)
x_alternating_perspective.value = x_relaxed.value
objective = 0.0
for i in range(m):
objective += sccf.minimum(cp.square(A[i]@x_alternating_perspective-b[i]), alpha)
objective += eta * cp.sum_squares(x_alternating_perspective)
prob = sccf.Problem(objective)
prob.solve(warm_start=True)
# brute force evaluate function and perspective
xs = np.linspace(-5, 5, 100)
f = np.sum(np.minimum(np.square(A * xs - b[:, None]), alpha), axis=0) + eta*xs**2
f_persp = []
for x in xs:
z = [cp.Variable(n) for _ in range(m)]
s = cp.Variable(m)
objective = 0.0
constraints = [0 <= s, s <= 1]
for i in range(m):
objective += cp.quad_over_lin(A[i, :] @ z[i] - b[i] * s[i], s[i]) + (1.0 - s[i]) * alpha + \
eta / m * (cp.quad_over_lin(x - z[i], 1.0 - s[i]) + eta / m * cp.quad_over_lin(z[i], s[i]))
prob = cp.Problem(cp.Minimize(objective), constraints)
result = prob.solve(solver=cp.MOSEK)
f_persp.append(result)
def find_nearest(array, value):
array = np.asarray(array)
idx = (np.abs(array - value)).argmin()
return idx
# plot
latexify(fig_width=6, fig_height=4)
plt.plot(xs, f, '-', label="$L(x)$", c='k')
plt.plot(xs, f_persp, '--', label="perspective", c='k')
plt.plot(x_alternating.value[0], )
plt.scatter(x_alternating.value[0], f[find_nearest(xs, x_alternating.value[0])], marker='o', label="sccf (no init)", c='k')
plt.scatter(x_alternating_perspective.value[0], f[find_nearest(xs, x_alternating_perspective.value[0])], marker='*', label="sccf (persp init)", c='k')
plt.legend()
plt.xlabel("$x$")
plt.savefig("figs/perspective.pdf")
if show:
plt.show()
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Perspective example.')
parser.add_argument('--noshow', action='store_const', const=True, default=False)
args = parser.parse_args()
main(not args.noshow) | UTF-8 | Python | false | false | 3,359 | py | 11 | perspective.py | 9 | 0.58827 | 0.574278 | 0 | 93 | 35.129032 | 154 |
gundas/ERC20ScrapingTools | 6,081,673,717,060 | 570842a170b6998eddd3ed469264ecd7b5138ba7 | e183b9c49300e313d2142d77efbd32fb086caccf | /retrieveTokens.py | bf875f01eff54fed374ba71856b8364b4f140786 | [
"Unlicense"
]
| permissive | https://github.com/gundas/ERC20ScrapingTools | e3eb6ef6f56fcb3560d2685356d2a3dfe41f2b49 | 3221c0e0dba2d5af32202d24aa1d8d45f0b1d3b3 | refs/heads/master | 2020-04-21T02:34:40.572913 | 2019-02-05T16:43:01 | 2019-02-05T16:43:01 | 169,258,347 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import argparse
import csv
import requests
import time
from bs4 import BeautifulSoup
url = 'https://etherscan.io/tokens?p='
def main(outputFile, pagesCount):
with open(outputFile, 'wt', newline='') as resultFile:
w = csv.DictWriter(resultFile, fieldnames = ['address', 'ticker', 'marketCap', 'price', 'name'])
w.writeheader()
for pageNr in range(1,pagesCount+1):
print('Scanning %s out of %s' % (pageNr, pagesCount))
pageResult = requests.get(url + str(pageNr))
if pageResult.ok:
tokensData = processPage(pageResult.content)
w.writerows(tokensData)
resultFile.flush()
else:
print (pageResult)
time.sleep(0.3)
def processPage(content):
page = BeautifulSoup(content, features="html.parser")
results = []
index = 0
for row in page.select('table')[0].select('tr'):
if index != 0:
cells = row.select('td')
# cells[3].find('a') - token url, name and ticker:
# <a href="/token/0xB8c77482e45F1F44dE1745F52C74426C631bDD52" style="position:relative; top:8px">BNB (BNB)</a>
address = cells[3].find('a')['href'].split('/')[2]
name = cells[3].find('a').text.split(' ')[0]
ticker = cells[3].find('a').text.split(' ')[1].lstrip('(').rstrip(')')
# cells[4] - price USD:
# <td> <span style="margin-left:-4px">$6.1343</span><br/><font size="1">0.0015845654 Btc<br/>0.038537 Eth</font><br/><br/></td>
price = float(cells[4].find('span').text.lstrip('$'))
# cells[7] - market cap: <td>$802,357,584 </td>
marketCap = int(cells[7].text.lstrip('$').rstrip().replace(',',''))
results.append ({'address' : address, 'ticker' : ticker, 'marketCap' : marketCap, 'price' : price, 'name' : name})
index += 1
return results
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('outputFile')
parser.add_argument('pages', type=int, help = 'number of pages to process at https://etherscan.io/tokens')
args = parser.parse_args()
main(args.outputFile, args.pages)
| UTF-8 | Python | false | false | 2,166 | py | 2 | retrieveTokens.py | 1 | 0.59213 | 0.553704 | 0 | 52 | 40.480769 | 143 |
tachyon83/code-rhino | 7,791,070,710,910 | 747e5368f8346fdd3bfc7fa03ced967cb1fd61c9 | f281d0d6431c1b45c6e5ebfff5856c374af4b130 | /DAY001~099/DAY63-BOJ15989-1, 2, 3 더하기 4/ykim.py | 78fb95838f04af6fce439d98a112ffa5747d9cde | []
| no_license | https://github.com/tachyon83/code-rhino | ec802dc91dce20980fac401b26165a487494adb4 | b1af000f5798cd12ecdab36aeb9c7a36f91c1101 | refs/heads/master | 2022-08-13T09:10:16.369287 | 2022-07-30T11:27:34 | 2022-07-30T11:27:34 | 292,142,812 | 5 | 6 | null | null | null | null | null | null | null | null | null | null | null | null | null | import sys
input = sys.stdin.readline
t = int(input())
dp = [1 for i in range(10001)]
lst = []
for _ in range(t):
lst.append(int(input()))
for i in range(2, 10001):
dp[i] += dp[i - 2]
for i in range(3, 10001):
dp[i] += dp[i - 3]
for i in lst:
print(dp[i])
| UTF-8 | Python | false | false | 280 | py | 2,548 | ykim.py | 2,220 | 0.55 | 0.478571 | 0 | 17 | 15.470588 | 30 |
Aasthaengg/IBMdataset | 13,142,599,945,465 | b2272db208487f12148f8683454ac441b13f9c6c | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p03150/s970298539.py | 7b761170e8ac11fb20eaa7b6a28f39ff91b608a6 | []
| no_license | https://github.com/Aasthaengg/IBMdataset | 7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901 | f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8 | refs/heads/main | 2023-04-22T10:22:44.763102 | 2021-05-13T17:27:22 | 2021-05-13T17:27:22 | 367,112,348 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | s=input()
key="keyence"
li=[]
for i in range(len(key)):
li.append([key[:i],key[i:]])
for i in li:
#print("{} {}".format(s[:len(i[0])],s[-len(i[1]):]))
if s[:len(i[0])]==i[0] and s[-len(i[1]):]==i[1]:
print("YES")
break
else:
print("NO")
| UTF-8 | Python | false | false | 256 | py | 202,060 | s970298539.py | 202,055 | 0.496094 | 0.472656 | 0 | 13 | 18.692308 | 54 |
nikhil-patil-adn/react | 19,284,403,166,412 | a6fe63fa7f393a09afe82da527287fd4e7b9fd9e | 636770b7f8b1da01f49248fe23b182d1008b5563 | /django/fellowfarmers/subscriptions/migrations/0016_subscription_price.py | 059098dc24f8e6172e513e4293c0a31881e5fa9c | []
| no_license | https://github.com/nikhil-patil-adn/react | 15914a3dc865f7ec03b2e64321b0bf9ff837a247 | 13ea20021fd548e8fde8619a7293fd3ddccc52ec | refs/heads/master | 2023-09-03T23:15:43.249492 | 2021-10-21T06:46:08 | 2021-10-21T06:46:08 | 411,239,408 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # Generated by Django 3.2.5 on 2021-08-17 12:45
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('subscriptions', '0015_auto_20210809_1934'),
]
operations = [
migrations.AddField(
model_name='subscription',
name='price',
field=models.DecimalField(decimal_places=2, default='00.00', max_digits=6),
),
]
| UTF-8 | Python | false | false | 432 | py | 225 | 0016_subscription_price.py | 182 | 0.606481 | 0.520833 | 0 | 18 | 23 | 87 |
callor/Python2 | 1,700,807,083,182 | 0e4b9484ae4659192f0e81036840d17358b07b64 | 31503125018075a44831ab45c4588843b049a586 | /PyQT/grade/Grad_List.py | 91d7028fb33a8fbfb129036920936668439bf79f | []
| no_license | https://github.com/callor/Python2 | 0cb68f2272a70ef5f350fec9e8a1b003be6dde7d | 791e8f364bba8421eff2118adbf8dfeb2ed9f3ba | refs/heads/master | 2021-01-20T03:23:50.049273 | 2017-09-15T03:01:00 | 2017-09-15T03:01:00 | 101,359,653 | 2 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | '''
Created on 2017. 9. 15.
@author: callor
'''
from sys import *
from PyQt5.QtWidgets import *
from PyQt5 import uic
from PyQt5.QtCore import *
Grade_List = uic.loadUiType('./Grade_List.ui')[0]
class GradeList(QDialog,Grade_List):
def __init__(self):
super().__init__()
self.setupUi(self)
self.initUi()
def initUi(self):
rows = self.getNum()
self.gradeTable = QTableWidget(self)
# gradeTable : 표(table)의 데이터 list를 표현하는 위젯
# 윈도우 크기와, table 크기를 같게
self.gradeTable.setGeometry(self.geometry())
self.gradeTable.setRowCount(rows)
# nun, name, kor, eng, math, totla, avg
self.gradeTable.setColumnCount(7)
self.setTableHedaer()
self.getGrade()
self.show()
# 파일을 읽어서 값을 표시
def getGrade(self):
# try:
with open("./grade.txt",'r',encoding='UTF-8') as f1 :
gradeLines = f1.readlines()
for index,item in enumerate(gradeLines) :
print(item) # 리스트를 프린터
grades = item.split(":")
print(index,grades)
self.gradeTable.setItem(index,0,QTableWidgetItem(grades[0]))
self.gradeTable.setItem(index,1,QTableWidgetItem(grades[1]))
for i in range(2,5) :
item = QTableWidgetItem(grades[i])
item.setTextAlignment(Qt.AlignVCenter | Qt.AlignRight)
self.gradeTable.setItem(index,i,item)
total1 = int(grades[2])
total1 += int(grades[3])
total1 += int(grades[4])
avg1 = int(total1 / 3)
print(total1,avg1)
self.gradeTable.setItem(index,5,QTableWidgetItem(str(total1)))
self.gradeTable.setItem(index,6,QTableWidgetItem(str(avg1)))
#
# except:
# pass
def setTableHedaer(self):
column_header = ["학번","이름","국어","영어","수학","총점","평군"]
self.gradeTable.setHorizontalHeaderLabels(column_header)
def getNum(self):
lines = 0
try:
with open('./grade.txt','r',encoding='UTF-8') as f2 :
readLine = f2.readlines() # 파일 전체를 읽어서 라인단위로 잘라 list로
lines = len(readLine)
except:
lines = 0
return lines
if __name__=="__main__" :
app = QApplication(argv)
gradeList = GradeList()
gradeList.getGrade()
exit(app.exec_())
| UTF-8 | Python | false | false | 2,827 | py | 102 | Grad_List.py | 85 | 0.502047 | 0.486788 | 0 | 93 | 27.892473 | 78 |
jiawei-zhang-columbia/IEORE4501-Final-Project | 19,026,705,164,507 | ebdddf063b61b977a0121e60978c00cc550e2243 | 3b63303a7ba56590b303ae368c5407374b4965d5 | /squirrel_tracker/admin.py | 45799eea1b999b1c4ac7d6c0b59e10d06e77b001 | []
| no_license | https://github.com/jiawei-zhang-columbia/IEORE4501-Final-Project | 74f64da2447515a95b6e5883324d0761eaddc3f1 | caba7a977585d7ed275afba8b0dc59b72d7739ee | refs/heads/main | 2023-04-07T23:30:47.904075 | 2021-04-15T12:45:18 | 2021-04-15T12:45:18 | 349,937,393 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.contrib import admin
from .models import Sighting
admin.site.register(Sighting)
| UTF-8 | Python | false | false | 95 | py | 16 | admin.py | 10 | 0.810526 | 0.810526 | 0 | 6 | 14.833333 | 32 |
HBinhCT/Q-project | 5,299,989,659,690 | fb4d590aae4b867ca44f27604eafde1294417ecf | d66818f4b951943553826a5f64413e90120e1fae | /hackerearth/Algorithms/Equalize strings (1)/solution.py | b468d558e0d154c2f2405d5b203c0c9b0e4bc452 | [
"MIT"
]
| permissive | https://github.com/HBinhCT/Q-project | 0f80cd15c9945c43e2e17072416ddb6e4745e7fa | 19923cbaa3c83c670527899ece5c3ad31bcebe65 | refs/heads/master | 2023-08-30T08:59:16.006567 | 2023-08-29T15:30:21 | 2023-08-29T15:30:21 | 247,630,603 | 8 | 1 | MIT | false | 2020-07-22T01:20:23 | 2020-03-16T06:48:02 | 2020-07-21T10:55:44 | 2020-07-22T01:20:22 | 593 | 0 | 0 | 0 | Python | false | false | """
# Sample code to perform I/O:
name = input() # Reading input from STDIN
print('Hi, %s.' % name) # Writing output to STDOUT
# Warning: Printing unwanted or ill-formatted data to output will cause the test cases to fail
"""
# Write your code here
n = int(input())
a = list(input().strip())
b = list(input().strip())
cost = 0
for i in range(1, n):
if a[i - 1] != b[i - 1]:
if a[i - 1] == b[i] and a[i] == b[i - 1]:
a[i - 1], a[i] = a[i], a[i - 1]
else:
a[i - 1] = b[i - 1]
cost += 1
cost += (a[-1] != b[-1])
print(cost)
| UTF-8 | Python | false | false | 601 | py | 3,248 | solution.py | 1,828 | 0.497504 | 0.475874 | 0 | 23 | 25.130435 | 94 |
sralli/APS-2020 | 12,549,894,450,760 | 0693ed1017aefbec0b11f9c366a3a7bda030b181 | c412e4e8fdb42becd0d9980a181fa3eef24f5318 | /ways_to_find_n.py | 5164a9de2b7ee1e2f2404a5e506fa1aae59bf449 | []
| no_license | https://github.com/sralli/APS-2020 | bc4486e75fd467d4db76c8dca5d9b2095e80b12a | 6db5b9f1b79e12ec455ac1f5d9a6c9d83440d0e9 | refs/heads/master | 2020-12-21T06:33:32.445896 | 2020-05-19T12:52:44 | 2020-05-19T12:52:44 | 236,340,015 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null |
def subset_sum(numbers, target, partial=[], partial_sum=0):
if partial_sum == target:
yield partial
if partial_sum >= target:
return 0
for index, num in enumerate(numbers):
remaining = numbers[index + 0:]
yield from subset_sum(remaining, target, partial + [num], partial_sum + num)
def ways(n, num1, num2, num3):
dp = bytearray(n+1)
dp[0] = 1
for i in range(num1, n+1):
if dp[i-num1] != 0:
dp[i]+=dp[i-num1]
for i in range(num2, n+1):
if dp[i-num2] != 0:
dp[i]+=dp[i-num2]
for i in range(num3, n+1):
if dp[i-num3] != 0:
dp[i]+=dp[i-num3]
return dp[n]
print(ways(13,3,5,10))
for i in subset_sum([3,5,10], 15):
print(i) | UTF-8 | Python | false | false | 759 | py | 79 | ways_to_find_n.py | 74 | 0.532279 | 0.484848 | 0 | 32 | 22.71875 | 84 |
csakatoku/uamobile | 5,205,500,382,745 | 3627437009ba2ffffc54c5f4bb1119448fadedaf | 8a6cdc50c434eecd30f6ec964518d299901dccfb | /tests/test_parser.py | 3f5e8aca72db8fe9bee19ec59ff8cdfa25ec4942 | [
"MIT"
]
| permissive | https://github.com/csakatoku/uamobile | ad8fa2663d45386298b14ff8895b160dcdb429c8 | 7be1f739369bb00b0ca099593d0d9dfaf52fb3b8 | refs/heads/master | 2021-01-18T09:49:13.364754 | 2010-06-18T07:30:38 | 2010-06-18T07:30:38 | 687,654 | 1 | 0 | null | false | 2014-10-29T10:43:59 | 2010-05-26T17:18:08 | 2013-11-14T09:59:47 | 2010-06-18T07:30:53 | 300 | 8 | 3 | 2 | Python | null | null | # -*- coding: utf-8 -*-
from uamobile import parser
DOCOMO = (
('DoCoMo/1.0/R692i/c10',
{ 'version': '1.0',
'model' : 'R692i',
'c' : 10,
'series' : '692i',
'html_version': '3.0',
}),
('DoCoMo/1.0/P209is (Google CHTML Proxy/1.0)',
{ 'version': '1.0',
'model' : 'P209is',
'series' : '209i',
'html_version': '2.0',
}),
('DoCoMo/2.0 N2001(c10;ser0123456789abcde;icc01234567890123456789)',
{ 'version': '2.0',
'model' : 'N2001',
'c': 10,
'ser' : '0123456789abcde',
'icc' : '01234567890123456789',
'series' : 'FOMA',
'html_version': '3.0',
},
),
('DoCoMo/2.0 P703i(c100;TB;W24H12;ser0123456789abcdf;icc01234567890123456789)',
{ 'version': '2.0',
'model' : 'P703i',
'c': 100,
'status' : 'TB',
'ser' : '0123456789abcdf',
'icc' : '01234567890123456789',
'display_bytes': (24, 12),
'series' : '703i',
'html_version': '7.0',
},
),
('DoCoMo/2.0 N902iS(c100;TB;W24H12)(compatible; moba-crawler; http://crawler.dena.jp/)',
{ 'version': '2.0',
'model' : 'N902iS',
'c': 100,
'status' : 'TB',
'display_bytes': (24, 12),
'series' : '902i',
'html_version': '6.0',
},
),
)
EZWEB = (
('KDDI-TS21 UP.Browser/6.0.2.276 (GUI) MMP/1.1',
{ 'xhtml_compliant': True,
'device_id' : 'TS21',
'name' : 'UP.Browser',
'version' : '6.0.2.276 (GUI)',
'server' : 'MMP/1.1',
},
),
('KDDI-TS3A UP.Browser/6.2.0.11.2.1 (GUI) MMP/2.0, Mozilla/4.08 (MobilePhone; NMCS/3.3) NetFront/3.3',
{ 'xhtml_compliant': True,
'device_id' : 'TS3A',
'name' : 'UP.Browser',
'version' : '6.2.0.11.2.1 (GUI)',
'server' : 'MMP/2.0',
},
),
('UP.Browser/3.01-HI01 UP.Link/3.4.5.2',
{ 'xhtml_compliant': False,
'device_id' : 'HI01',
'name' : 'UP.Browser',
'version' : '3.01',
'server' : 'UP.Link/3.4.5.2',
}),
)
SOFTBANK = (
('SoftBank/1.0/841SHs/SHJ001/SN123456789012345 Browser/NetFront/3.5 Profile/MIDP-2.0 Configuration/CLDC-1.1',
{ 'packet_compliant': True,
'version' : '1.0',
'model' : '841SHs',
'vendor' : 'SH',
'vendor_version' : 'J001',
'serialnumber' : '123456789012345',
'info' : { 'Browser': 'NetFront/3.5',
'Profile': 'MIDP-2.0',
'Configuration': 'CLDC-1.1',
}
},
),
('SoftBank/1.0/841SHs/SHJ001/SN123456789012345 Java/Java/1.0 Profile/MIDP-2.0 Configuration/CLDC-1.1',
{ 'packet_compliant': True,
'version' : '1.0',
'model' : '841SHs',
'vendor' : 'SH',
'vendor_version' : 'J001',
'serialnumber' : '123456789012345',
'info' : { 'Java': 'Java/1.0',
'Profile': 'MIDP-2.0',
'Configuration': 'CLDC-1.1',
}
},
),
('SoftBank/1.0/841SHs/SHJ001 Widgets/Widgets/1.0',
{ 'packet_compliant': True,
'version' : '1.0',
'model' : '841SHs',
'vendor' : 'SH',
'vendor_version' : 'J001',
'serialnumber' : None,
'info' : { 'Widgets': 'Widgets/1.0',
}
},
),
('SoftBank/1.0/841SHs/SHJ001/SN123456789012345 Flash/Flash-Lite/3.1',
{ 'packet_compliant': True,
'version' : '1.0',
'model' : '841SHs',
'vendor' : 'SH',
'vendor_version' : 'J001',
'serialnumber' : '123456789012345',
'info' : { 'Flash': 'Flash-Lite/3.1',
}
},
),
('Vodafone/1.0/V705SH (compatible; Y!J-SRD/1.0; http://help.yahoo.co.jp/help/jp/search/indexing/indexing-27.html)',
{ 'packet_compliant': True,
'version' : '1.0',
'model' : 'V705SH',
'vendor' : None,
'vendor_version' : None,
'serialnumber' : None,
'info' : {}
},
),
('Vodafone/1.0/V802SE/SEJ001/SN123456789012345 Browser/SEMC-Browser/4.1 Profile/MIDP-2.0 Configuration/CLDC-1.1',
{ 'packet_compliant': True,
'version' : '1.0',
'model' : 'V802SE',
'vendor' : 'SE',
'vendor_version' : 'J001',
'serialnumber' : '123456789012345',
'info' : { 'Profile': 'MIDP-2.0',
'Configuration': 'CLDC-1.1',
'Browser': 'SEMC-Browser/4.1',
}
},
),
('Vodafone/1.0/V702NK/NKJ001 Series60/2.6 Nokia6630/2.39.148 Profile/MIDP-2.0 Configuration/CLDC-1.1',
{ 'packet_compliant': True,
'version' : '1.0',
'model' : 'V702NK',
'vendor' : 'NK',
'vendor_version' : 'J001',
'serialnumber' : None,
'info' : { 'Profile': 'MIDP-2.0',
'Configuration': 'CLDC-1.1',
'Nokia6630': '2.39.148',
'Series60' : '2.6',
}
},
),
('J-PHONE/4.0/J-SH51/SNJSHA3029293 SH/0001aa Profile/MIDP-1.0 Configuration/CLDC-1.0 Ext-Profile/JSCL-1.1.0',
{ 'packet_compliant': True,
'version' : '4.0',
'model' : 'J-SH51',
'vendor' : 'SH',
'vendor_version' : '0001aa',
'serialnumber' : 'JSHA3029293',
'info' : { 'Profile': 'MIDP-1.0',
'Configuration': 'CLDC-1.0',
'Ext-Profile' : 'JSCL-1.1.0',
'SH': '0001aa',
}
},
),
('J-PHONE/2.0/J-DN02',
{ 'packet_compliant': False,
'version' : '2.0',
'model' : 'J-DN02',
'vendor' : 'DN',
},
),
('MOT-V980/80.2F.2E. MIB/2.2.1 Profile/MIDP-2.0 Configuration/CLDC-1.1',
{ 'packet_compliant': True,
'vendor' : 'MOT',
'vendor_version' : '80.2F.2E.',
'info' : { 'Profile': 'MIDP-2.0',
'Configuration': 'CLDC-1.1',
'MIB': '2.2.1',
}
},
),
)
WILLCOM = (
('Mozilla/3.0(WILLCOM;SANYO/WX310SA/2;1/1/C128) NetFront/3.3,61.198.142.127',
{ 'vendor' : 'SANYO',
'model' : 'WX310SA',
'model_version' : '2;1',
'browser_version': '1',
'cache_size' : 128,
},
),
('Mozilla/4.0 (compatible; MSIE 4.01; Windows CE; SHARP/WS007SH; PPC; 480x640)',
{ 'vendor': 'SHARP',
'model' : 'WS007SH',
'browser_version': 'MSIE 4.01',
'os' : 'Windows CE',
'arch': 'PPC',
},
),
)
def _test_func(p, ua, params):
res = p.parse(ua)
assert isinstance(res, dict)
for k, v in params.items():
assert res.get(k) == v, '%r expected, actual %r' % (v, res.get(k))
def test_docomo_parser():
p = parser.DoCoMoUserAgentParser()
for ua, params in DOCOMO:
yield _test_func, p, ua, params
def test_ezweb_parser():
p = parser.EZwebUserAgentParser()
for ua, params in EZWEB:
yield _test_func, p, ua, params
def test_softbank_parser():
p = parser.SoftBankUserAgentParser()
for ua, params in SOFTBANK:
yield _test_func, p, ua, params
def test_willcom_parser():
p = parser.WillcomUserAgentParser()
for ua, params in WILLCOM:
yield _test_func, p, ua, params
| UTF-8 | Python | false | false | 7,843 | py | 50 | test_parser.py | 49 | 0.447405 | 0.352799 | 0 | 254 | 29.877953 | 119 |
CafeVisthuset/VisthusetAPI | 352,187,365,213 | cd7f81ed123bdf46387d5543be6e051ecbc35769 | f5cbabbdf4b7e04abccd884eee54c68eaee75b46 | /database/migrations/0009_auto_20170113_1816.py | debac17e68b507c3d97f44af192b8606bb58e50a | []
| no_license | https://github.com/CafeVisthuset/VisthusetAPI | d411913fc05eedf252a7cbaab252e66b89921bad | 6052b8ecdf20656bc5d8b5f4a79d45fe92c13769 | refs/heads/master | 2021-01-11T03:21:28.576799 | 2017-04-08T13:03:19 | 2017-04-08T13:03:19 | 71,042,036 | 0 | 4 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
# Generated by Django 1.10.1 on 2017-01-13 18:16
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
dependencies = [
('database', '0008_lunchbooking_day'),
]
operations = [
migrations.AlterModelOptions(
name='bikesbooking',
options={'verbose_name': 'cykelbokning', 'verbose_name_plural': 'cykelbokningar'},
),
migrations.AlterModelOptions(
name='lunchbooking',
options={'verbose_name': 'lunchbokning', 'verbose_name_plural': 'lunchbokningar'},
),
migrations.AlterModelOptions(
name='roomsbooking',
options={'verbose_name': 'rumsbokning', 'verbose_name_plural': 'rumsbokningar'},
),
migrations.AddField(
model_name='bikesbooking',
name='from_date',
field=models.DateTimeField(default=django.utils.timezone.now),
preserve_default=False,
),
migrations.AddField(
model_name='bikesbooking',
name='full_days',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='bikesbooking',
name='to_date',
field=models.DateTimeField(default=django.utils.timezone.now),
preserve_default=False,
),
migrations.AlterField(
model_name='bikeavailable',
name='bike',
field=models.ForeignKey(blank=True, default=2, on_delete=django.db.models.deletion.PROTECT, to='database.Bike'),
preserve_default=False,
),
migrations.AlterField(
model_name='bikeavailable',
name='bookings',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='availableBike', to='database.BikesBooking'),
),
migrations.AlterField(
model_name='roomsbooking',
name='numberOfGuests',
field=models.PositiveIntegerField(verbose_name='antal gäster'),
),
migrations.AlterUniqueTogether(
name='bikeavailable',
unique_together=set([('bike', 'available_date')]),
),
]
| UTF-8 | Python | false | false | 2,371 | py | 57 | 0009_auto_20170113_1816.py | 42 | 0.595781 | 0.586498 | 0 | 66 | 34.909091 | 162 |
JoelPasvolsky/dwave-hybrid | 6,133,213,335,649 | d099f325e1bc31009316676373e3f15d333e86b2 | cfe9a5d6a07658802f8484651e3f552504c2e94e | /tests/test_profiling.py | 87c8c6f9b3b7889ee302508ba625f823335029ef | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
]
| permissive | https://github.com/JoelPasvolsky/dwave-hybrid | df927bd2633fd9f19adba354feda891e835354e5 | 1564e1e6fd284f68ee908a52ace89eb2c64576e6 | refs/heads/master | 2022-12-25T03:11:01.691011 | 2022-11-25T23:28:13 | 2022-11-25T23:28:13 | 146,035,498 | 0 | 0 | Apache-2.0 | false | 2018-12-04T17:44:31 | 2018-08-24T20:11:53 | 2018-12-04T17:13:02 | 2018-12-04T17:43:32 | 20,704 | 0 | 0 | 2 | Python | false | null | # Copyright 2018 D-Wave Systems Inc.
#
# 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 dwave.system.testing import MockDWaveSampler
from hybrid.core import Runnable, State
from hybrid.flow import Branch, RacingBranches, ArgMin, Loop
from hybrid.profiling import tictoc, iter_inorder, walk_inorder, make_timeit, make_count
from hybrid.testing import mock
from hybrid.composers import *
from hybrid.samplers import *
from hybrid.decomposers import *
class TestCoreRunnablesIterable(unittest.TestCase):
class RunnableA(Runnable): pass
class RunnableB(Runnable): pass
@staticmethod
def children(runnable):
return [str(x) for x in runnable]
def test_runnable(self):
self.assertEqual(list(Runnable()), [])
def test_branch(self):
# explicit branch construction
self.assertEqual(self.children(Branch(components=(self.RunnableA(),))), ['RunnableA'])
# implicit + order
self.assertEqual(self.children(self.RunnableA() | self.RunnableB()), ['RunnableA', 'RunnableB'])
def test_racingbranches(self):
rb = RacingBranches(self.RunnableA(), self.RunnableB())
self.assertEqual(self.children(rb), ['RunnableA', 'RunnableB'])
def test_argmin(self):
self.assertEqual(self.children(ArgMin()), [])
def test_loop(self):
r = Loop(self.RunnableA())
self.assertEqual(self.children(r), ['RunnableA'])
def test_concrete_runnables(self):
# composers
self.assertEqual(self.children(IdentityComposer()), [])
self.assertEqual(self.children(SplatComposer()), [])
# sample of samplers
self.assertEqual(self.children(QPUSubproblemAutoEmbeddingSampler(qpu_sampler=MockDWaveSampler())), [])
self.assertEqual(self.children(SimulatedAnnealingSubproblemSampler()), [])
self.assertEqual(self.children(TabuProblemSampler()), [])
# sample of decomposers
self.assertEqual(self.children(IdentityDecomposer()), [])
self.assertEqual(self.children(EnergyImpactDecomposer(size=1)), [])
self.assertEqual(self.children(RandomSubproblemDecomposer(size=1)), [])
class TestTictoc(unittest.TestCase):
def test_ctx_mgr(self):
with mock.patch('hybrid.profiling.perf_counter', side_effect=[0, 1]):
with tictoc() as t:
pass
self.assertEqual(t.tick, 0)
self.assertEqual(t.dt, 1)
def test_decorator(self):
with mock.patch('hybrid.profiling.perf_counter', side_effect=[0, 1]):
def f():
pass
deco = tictoc('f')
ff = deco(f)
ff()
self.assertEqual(deco.tick, 0)
self.assertEqual(deco.dt, 1)
class TestRunnableWalkers(unittest.TestCase):
def test_iter_walk(self):
flow = Loop(RacingBranches(Runnable(), Runnable()) | ArgMin())
names = [r.name for r in iter_inorder(flow)]
self.assertEqual(names, ['Loop', 'Branch', 'RacingBranches', 'Runnable', 'Runnable', 'ArgMin'])
def test_callback_walk(self):
flow = Loop(RacingBranches(Runnable(), Runnable()) | ArgMin())
names = []
walk_inorder(flow, visit=lambda r, _: names.append(r.name))
self.assertEqual(names, ['Loop', 'Branch', 'RacingBranches', 'Runnable', 'Runnable', 'ArgMin'])
class TestTimers(unittest.TestCase):
def test_basic(self):
timers = {}
time = make_timeit(timers)
with time('a'):
_ = 1
self.assertSetEqual(set(timers.keys()), {'a'})
self.assertEqual(len(timers['a']), 1)
def test_nested_timers(self):
timers = {}
time = make_timeit(timers)
with time('a'):
with time('b'):
with time('c'):
with time('b'):
_ = 2 ** 50
self.assertSetEqual(set(timers.keys()), {'a', 'b', 'c'})
self.assertEqual(len(timers['a']), 1)
self.assertEqual(len(timers['b']), 2)
self.assertEqual(len(timers['c']), 1)
def test_runnable_timer_called(self):
class Ident(Runnable):
def next(self, state):
with self.timeit('my-timer'):
return state
r = Ident()
r.run(State()).result()
self.assertEqual(len(r.timers['my-timer']), 1)
def test_runnable_default_timer_value(self):
self.assertEqual(Runnable().timers['my-timer'], [])
class TestCounters(unittest.TestCase):
def test_basic(self):
counters = {}
count = make_count(counters)
count('a')
try:
raise ZeroDivisionError
except:
count('b')
finally:
count('a', inc=3)
self.assertSetEqual(set(counters.keys()), {'a', 'b'})
self.assertEqual(counters['a'], 4)
self.assertEqual(counters['b'], 1)
def test_runnable_counter_called(self):
class Ident(Runnable):
def next(self, state):
self.count('my-counter', 3)
self.count('your-counter')
return state
r = Ident()
r.run(State()).result()
self.assertEqual(r.counters['my-counter'], 3)
self.assertEqual(r.counters['your-counter'], 1)
def test_runnable_default_counter_value(self):
self.assertEqual(Runnable().counters['my-counter'], 0)
| UTF-8 | Python | false | false | 5,902 | py | 89 | test_profiling.py | 38 | 0.617587 | 0.611826 | 0 | 177 | 32.344633 | 110 |
Kexon5/Statistics | 10,565,619,577,200 | 32f32e8feecdfe10ebaae13fab500754999fcc80 | 90cd8722c321e52c1a7c440f615b626465ac435a | /lab2.py | 07dc184db37892ba5821f3cf91c79db6c025e11d | []
| no_license | https://github.com/Kexon5/Statistics | b26a2ef68c07840e4a9bb1ae6d4871aef0053ee7 | 5b5d927d4ee36884e541a6b75d720ca6c37c8e30 | refs/heads/master | 2021-05-27T01:26:05.350003 | 2020-06-30T09:28:53 | 2020-06-30T09:28:53 | 254,199,413 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import numpy as np
from tabulate import tabulate
count_elem = [10, 100, 1000]
distribution = ['Normal', 'Cauchy', 'Laplace', 'Poisson', 'Uniform']
N = 1000
def fun_z_q(arr):
return (np.quantile(arr, 0.25) + np.quantile(arr, 0.75)) / 2
def fun_z_tr(arr):
r = len(arr) // 4
arr_new = np.sort(arr)
sum = 0
for i in range(r + 1, len(arr) - r):
sum += arr_new[i]
return sum / (len(arr) - 2 * r)
def get_array(name, n):
if name == distribution[0]:
return np.random.normal(0, 1, n)
elif name == distribution[1]:
return np.random.standard_cauchy(n)
elif name == distribution[2]:
return np.random.laplace(0, np.sqrt(2) / 2, n)
elif name == distribution[3]:
return np.random.poisson(10, n)
else:
return np.random.uniform(-np.sqrt(3), np.sqrt(3), n)
def lab2_run():
for dist_str in distribution:
title_row = [dist_str, "x_", "med x", "z_r", "z_q", "z_tr"]
rows = []
for n in count_elem:
x, med, z_r, z_q, z_tr = [], [], [], [], []
for i in range(N):
arr = get_array(dist_str, n)
x.append(np.mean(arr))
med.append(np.median(arr))
arr_sort = np.sort(arr)
z_r.append((arr_sort[0] + arr_sort[-1]) / 2)
z_q.append(fun_z_q(arr))
z_tr.append(fun_z_tr(arr))
rows.append(["n = %i" % n, 6 * ""])
rows.append([" E(z) ",
np.around(np.mean(x), decimals=6),
np.around(np.mean(med), decimals=6),
np.around(np.mean(z_r), decimals=6),
np.around(np.mean(z_q), decimals=6),
np.around(np.mean(z_tr), decimals=6)])
rows.append([" D(z) ",
np.around(np.std(x) ** 2, decimals=6),
np.around(np.std(med) ** 2, decimals=6),
np.around(np.std(z_r) ** 2, decimals=6),
np.around(np.std(z_q) ** 2, decimals=6),
np.around(np.std(z_tr) ** 2, decimals=6)])
rows.append(["" * 7])
print(tabulate(rows, title_row, tablefmt="latex"), end="\n\n")
| UTF-8 | Python | false | false | 2,340 | py | 13 | lab2.py | 13 | 0.455983 | 0.431197 | 0 | 68 | 32.411765 | 70 |
way2muchnoise/Advent2020 | 8,375,186,270,486 | 7a55fbc4a5706a28ef98a7c8c8f5502425a0b278 | 448e2ce1ee9d2114d138e222814d5ee354fbadec | /day11/part2.py | 9e4dfe97ab971e7f4ae34163dd4a5f7dc3539199 | []
| no_license | https://github.com/way2muchnoise/Advent2020 | ecfa598fc38106bd442431d650cc800b00507b66 | a944348b0e1fd297f8c14df519a68976cc384038 | refs/heads/main | 2023-02-01T20:11:56.859630 | 2020-12-19T10:03:32 | 2020-12-19T10:03:32 | 319,600,853 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | seat_rows = []
with open('input.txt', 'r') as f:
line = f.readline()
while line:
seat_rows.append([char for char in line[:-1]]) # strip \n and split in chars
line = f.readline()
def check_diagonal(row, seat, move_row, move_seat, seat_rows):
check_row = row + move_row
check_seat = seat + move_seat
while 0 <= check_row < len(seat_rows) and 0 <= check_seat < len(seat_rows[check_row]) and seat_rows[check_row][check_seat] == '.':
check_row += move_row
check_seat += move_seat
if 0 <= check_row < len(seat_rows) and 0 <= check_seat < len(seat_rows[check_row]) and seat_rows[check_row][check_seat] == '#':
return 1
else:
return 0
def count_occupied_around(row, seat, seat_rows):
occupied_around = 0
occupied_around += check_diagonal(row, seat, -1, -1, seat_rows) # top left
occupied_around += check_diagonal(row, seat, -1, 0, seat_rows) # top
occupied_around += check_diagonal(row, seat, -1, +1, seat_rows) # top right
occupied_around += check_diagonal(row, seat, 0, -1, seat_rows) # left
occupied_around += check_diagonal(row, seat, 0, +1, seat_rows) # right
occupied_around += check_diagonal(row, seat, +1, -1, seat_rows) # bottom left
occupied_around += check_diagonal(row, seat, +1, 0, seat_rows) # bottom
occupied_around += check_diagonal(row, seat, +1, +1, seat_rows) # bottom right
return occupied_around
changes = -1
while changes != 0:
changes = 0
new_seat_rows = [row[:] for row in seat_rows] # Copy array
for row in range(len(seat_rows)):
for seat in range(len(seat_rows[row])):
if seat_rows[row][seat] != '.':
occupied_around = count_occupied_around(row, seat, seat_rows)
if seat_rows[row][seat] == '#' and occupied_around >= 5:
new_seat_rows[row][seat] = 'L'
changes += 1
if seat_rows[row][seat] == 'L' and occupied_around == 0:
new_seat_rows[row][seat] = '#'
changes += 1
seat_rows = new_seat_rows
occupied = 0
for row in seat_rows:
for seat in row:
if seat == '#':
occupied += 1
print(occupied)
| UTF-8 | Python | false | false | 2,231 | py | 30 | part2.py | 29 | 0.577768 | 0.562976 | 0 | 54 | 40.314815 | 134 |
ritik1501/MarkDoc | 7,937,099,605,231 | fa2387df7d1932fd4cf5ca36b93d26b7b5031548 | 792331ca24a107a4572ea10cc260a24699b283c6 | /karm/migrations/0001_initial.py | 564d1f49636ff499511f7133a92ef0bc3c51b962 | []
| no_license | https://github.com/ritik1501/MarkDoc | 908c8f502d67c4992e35b7cd1ffd514c5795501f | d31faf1b84baf918aa308dccfb2e2b535b80c082 | refs/heads/master | 2023-02-15T07:15:39.185933 | 2021-01-04T12:54:25 | 2021-01-04T12:54:25 | 326,681,546 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # Generated by Django 3.0.3 on 2020-08-27 12:14
from django.db import migrations, models
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Appointment',
fields=[
('sno', models.AutoField(primary_key=True, serialize=False)),
('pat_name', models.CharField(max_length=100)),
('doc_name', models.CharField(max_length=100)),
('pat_email', models.CharField(max_length=100)),
('doc_email', models.CharField(max_length=100)),
('disease', models.CharField(max_length=100)),
('meeting_link', models.CharField(max_length=100)),
('status', models.CharField(default='pending', max_length=25)),
('timing', models.DateTimeField(default=django.utils.timezone.now)),
],
),
migrations.CreateModel(
name='Contact',
fields=[
('sno', models.AutoField(primary_key=True, serialize=False)),
('name', models.CharField(max_length=100)),
('email', models.CharField(max_length=100)),
('message', models.CharField(max_length=100)),
('timestamp', models.DateTimeField(default=django.utils.timezone.now)),
],
),
migrations.CreateModel(
name='Doctor',
fields=[
('sno', models.AutoField(primary_key=True, serialize=False)),
('username', models.CharField(max_length=20)),
('first_name', models.CharField(max_length=100)),
('last_name', models.CharField(max_length=100)),
('email', models.CharField(max_length=100)),
('phone_number', models.CharField(max_length=10)),
('user_type', models.CharField(default='doctor', max_length=10)),
],
),
migrations.CreateModel(
name='Patient',
fields=[
('sno', models.AutoField(primary_key=True, serialize=False)),
('username', models.CharField(max_length=20)),
('first_name', models.CharField(max_length=100)),
('last_name', models.CharField(max_length=100)),
('email', models.CharField(max_length=100)),
('phone_number', models.CharField(max_length=10)),
('user_type', models.CharField(default='user', max_length=10)),
],
),
]
| UTF-8 | Python | false | false | 2,672 | py | 15 | 0001_initial.py | 8 | 0.524701 | 0.497006 | 0 | 63 | 40.412698 | 87 |
exinmusic/public-pasta | 206,158,432,245 | 35d97602e127692c0b281989ab045d6b82395b85 | e72cfa8aee383d192b62a8361e721615495531dc | /pp/pastas/models.py | a3ae5b43d3bf5c6fdfb3813cd93aa9e42de7a12e | []
| no_license | https://github.com/exinmusic/public-pasta | ea41cf2edb6e9a0b54ed70172237217e88fec85a | 6a9c37c85e7b31bd5288413d1fd099022f606031 | refs/heads/master | 2021-09-27T10:08:48.119004 | 2020-08-28T21:30:59 | 2020-08-28T21:30:59 | 239,707,328 | 0 | 0 | null | false | 2021-09-22T18:56:25 | 2020-02-11T08:01:01 | 2020-08-28T21:31:07 | 2021-09-22T18:56:23 | 66 | 0 | 0 | 3 | Python | false | false | from django.db import models
from multiselectfield import MultiSelectField
CATEGORIES = [
('wholesome','wholesome'), # Feel good content or good natured.
('sermon','sermon'), # Preaching. Written with arrogance.
('intelligent','intelligent'), # Not ironically intelligent, as much as possible.
('dumb','dumb'), # Just really unredeemingly stupid.
('funny','funny'), # is funny.
('sad','sad'), # is sad.
('political','political'), # Flags anything political, includes mentions of politicians.
('complaint','complaint'), # Flags compaints.
('emoji','emoji'), # Content with exessive use of emoticons.
('daddy','daddy'), # Content written "to" sugar daddies.
('sexy','sexy'), # Sexual Content.
('pro','pro'), # Professional advise.
('creepy', 'creepy'), # Creepy or dark in nature.
('food', 'food'), # Food
('ascii-art', 'ascii-art'), # 8===D -by xn
('story', 'story'), # Story time, gather around.
('cyrillic', 'cyrillic'), # Russian pastas only, comrade.
('chad', 'chad'), # Broh.
]
SENTIMENTS = [
('positive', 'positive'),
('negative', 'negative')
]
class Pasta(models.Model):
text = models.TextField(max_length=15000)
date_created = models.DateTimeField(auto_now_add=True, blank=True)
name = models.CharField(max_length=500, default='', blank=True)
categories = MultiSelectField(max_length=150, choices=CATEGORIES, default='', blank=True)
safe = models.BooleanField(default=False) # Pasta could popup at work and not get a homie fired.
verified = models.BooleanField(default=False) # Famous pasta.
sentiment = models.CharField(max_length=8, choices=SENTIMENTS, default='', blank=True)
def __str__(self):
return self.name
| UTF-8 | Python | false | false | 1,977 | py | 16 | models.py | 14 | 0.580678 | 0.574102 | 0 | 40 | 48.325 | 110 |
asifbk/k_nearest_neighbors | 18,064,632,459,576 | 14e97e60dc6a33f3d50a531e8ba93ad86e054643 | 48a70738a2b09a028b76d81d6ef2fc9c28375300 | /Machine learning/Breast cancer dataset/breastcancer | 8967a844c93cfb23bfca23210a17ac98ca097d8f | []
| no_license | https://github.com/asifbk/k_nearest_neighbors | 7d475ac235be6dacb599c1b2ff9eee5e958049f9 | d4bbe93b44c6dc286a79b30546f693e3014df8cf | refs/heads/master | 2020-03-17T07:22:39.010714 | 2018-05-20T18:03:09 | 2018-05-20T18:03:09 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun May 20 15:32:53 2018
@author: asif
"""
import numpy as np
from sklearn import preprocessing, cross_validation,neighbors
import pandas as pd
df= pd.read_csv('breast-cancer-wisconsin.data')
df.replace('?',-99999, inplace= True)
df.drop(['id'],1,inplace=True)
X=np.array(df.drop(['class'],1))
y=np.array(df['class'])
X_train, X_test, y_train, y_test=cross_validation.train_test_split(X,y,test_size=0.2)
clf = neighbors.KNeighborsClassifier()
clf.fit(X_train,y_train)
accuracy = clf.score(X_test, y_test)
print(accuracy)
example_measures= np.array([[4,2,1,1,1,2,3,2,1],[4,2,1,1,1,2,3,2,1]])
example_measures=example_measures.reshape(2, -1)
#for any length use this
#example_measures=example_measures.reshape(len(example_measures), -1)
prediction=clf.predict(example_measures)
print(prediction) | UTF-8 | Python | false | false | 857 | 5 | breastcancer | 5 | 0.723454 | 0.672112 | 0 | 27 | 30.777778 | 85 |
|
opsicl/megatemp | 16,982,300,698,635 | 2127790fbee4dad5456a1c4db8605f68af55dbd1 | 4f8016e498972935981f448f23efda7a28a81bfc | /config/shrink_config.py | cebf757e2d882e530f4f3fb1e870862f76162b6b | []
| no_license | https://github.com/opsicl/megatemp | 16f6b8c078ea55f70e95daf280104598aab3451e | b405c1eddbd72d8268777d3be12cafab3306abcb | refs/heads/main | 2023-03-09T08:17:33.758342 | 2021-02-18T18:13:10 | 2021-02-18T18:13:10 | 308,662,134 | 0 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | import json
goodconfig = ''
with open("config.json") as config:
for line in config.readlines():
if not line.startswith('#'):
goodconfig += line
print(json.dumps(json.loads(goodconfig),separators=(',', ':')))
| UTF-8 | Python | false | false | 239 | py | 10 | shrink_config.py | 4 | 0.610879 | 0.610879 | 0 | 9 | 25.444444 | 67 |
wenner84/openerp7 | 15,874,199,127,075 | 78739249403f97c2e8f20c8b7cf21ec1b51874d1 | e757b0f0013075543a0de18e341901880bbe2f10 | /wf_backorder/purchase_order_line.py | d7f1c260c0afff91660da874105f93d667737427 | []
| no_license | https://github.com/wenner84/openerp7 | 5e5320e50eac6ba38681b873d7b7a8c767550a08 | 04c5b68f0f291e237dbb51ca0eff8c7d5e1c02c8 | refs/heads/master | 2017-12-22T04:16:54.419810 | 2017-05-23T09:54:27 | 2017-05-23T09:57:53 | 16,729,956 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
from openerp.osv import fields, osv
class purchase_order_line(osv.osv):
_inherit = "purchase.order.line"
_columns = {
'wf_sold_qty': fields.float('sold qty'),
}
purchase_order_line() | UTF-8 | Python | false | false | 232 | py | 1,013 | purchase_order_line.py | 481 | 0.612069 | 0.607759 | 0 | 10 | 21.9 | 48 |
f12markovic/mmwave-gesture-recognition | 2,542,620,640,011 | 7003928908603bbc6c0dca2506d6fa27980fb69b | 0c1ab94664a48823e6f094ec7f9f1a8206cc1f2f | /test.py | ad55f951ea769e61e0dfd3dca46f9f53ddc69720 | [
"MIT"
]
| permissive | https://github.com/f12markovic/mmwave-gesture-recognition | 2da1e895acf2215684c80e9a1f2b9cceb75ce686 | de3aba1cd2704623001eaabdf9d9f40350484862 | refs/heads/master | 2020-07-25T00:14:14.586559 | 2019-09-20T09:43:08 | 2019-09-20T09:43:08 | 208,088,521 | 4 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #! /usr/bin/env python
import time
from parser import Parser
from nn import NN
from plotter import Plotter
from connection import Connection
from utility_functions import threaded
@threaded
def nn_thread(p):
nn = NN(p)
nn.load_model()
print()
while True:
collected = False
while not collected:
collected = nn.get_data()
time.sleep(0.05)
nn.predict(debug=True)
time.sleep(0.05)
@threaded
def interpretor(c, p):
while True:
frame = c.getFrame()
p.parse(frame)
c.readDone()
time.sleep(0.05)
if __name__ == '__main__':
ports = []
while ports == []:
ports = Connection.findPorts()
conn = Connection(ports[0], ports[1])
mmwave_configured = False
while not mmwave_configured:
mmwave_configured = conn.sendCfg('./profiles/profile.cfg')
parser = Parser()
plotter = Plotter(parser)
interpretor(conn, parser)
nn_thread(parser)
conn.listen()
plotter.plot_detected_objs()
| UTF-8 | Python | false | false | 1,039 | py | 7,810 | test.py | 10 | 0.610202 | 0.599615 | 0 | 52 | 18.980769 | 66 |
auburnsummer/orchard-bot | 19,155,554,151,713 | 11db32a0ae1c3d74c2b38ee0939ddda02597ea4e | 117c2424d46c1fc9ba7e77062f41df32c0ec8945 | /ob/handlers/orchard_db.py | c6bad88249bb41ec8bab5bf84c04f682308a5bbd | []
| no_license | https://github.com/auburnsummer/orchard-bot | 270188a58c46af3c8c3a5318f2569280cddca652 | 50230cf651e5e5192ded1ec10813e5f4ba14e1a3 | refs/heads/master | 2023-09-03T23:17:11.653887 | 2021-11-08T01:42:48 | 2021-11-08T01:42:48 | 380,678,194 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from starlette.responses import FileResponse, JSONResponse
from ob.constants import DB_PATH
async def orchard_dot_db(request):
return FileResponse(DB_PATH, media_type="application/x-sqlite3") | UTF-8 | Python | false | false | 196 | py | 24 | orchard_db.py | 21 | 0.806122 | 0.80102 | 0 | 5 | 38.4 | 68 |
lumasepa/clean_admin | 3,298,534,891,327 | b0b69faf9e36ae516cdda05fa4e13debec4dddaf | cf76f58af18b1c73566f2d55a4e108290c379b7c | /example/second_app/models.py | 1562c8f0711565636e9f4a7e41c0f100fd1a7d33 | []
| no_license | https://github.com/lumasepa/clean_admin | 20d4548f769662b195cf63e8da23eb15784b0822 | 83c9f9b1439c1bbf5dffdb19870e345099c9cefd | refs/heads/master | 2021-06-22T12:36:15.327774 | 2016-12-06T10:38:33 | 2016-12-06T10:38:33 | 98,795,062 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.core.exceptions import ValidationError
from django.db import models
class ManyToManyModel(models.Model):
name = models.CharField(
max_length=500,
help_text="write something"
)
class AllFieldsModel(models.Model):
char_field = models.CharField(
max_length=500,
help_text="write something",
null=True,
blank=True
)
int_field = models.IntegerField(
help_text="Put a number, magic number",
null=True,
blank=True
)
text_field = models.TextField(
help_text="Put a large test here",
null=True,
blank=True
)
big_integer_field = models.BigIntegerField(
help_text="An big integer field",
null=True,
blank=True
)
binary_field = models.BinaryField(
help_text="A binary field",
null=True,
blank=True
)
date_field = models.DateField(
help_text="A date field",
null=True,
blank=True
)
datetime_field = models.DateTimeField(
help_text="A datetime field",
null=True,
blank=True
)
boolean_field = models.BooleanField(
help_text="A boolean field",
)
comma_separated_integer_field = models.CommaSeparatedIntegerField(
max_length=200,
help_text="A comma sepparated integer field",
null=True,
blank=True
)
decimal_field = models.DecimalField(
decimal_places=10,
max_digits=100,
help_text="A decimal field",
null=True,
blank=True
)
duration_field = models.DurationField(
help_text="A duration field",
null=True,
blank=True
)
email_field = models.EmailField(
help_text="A email field",
null=True,
blank=True
)
file_field = models.FileField(
help_text="A file field",
null=True,
blank=True
)
file_path_field = models.FilePathField(
help_text="A file path field",
null=True,
blank=True
)
float_field = models.FloatField(
help_text="A float field",
null=True,
blank=True
)
generic_ip_addr_field = models.GenericIPAddressField(
help_text="A generic ip addr field",
null=True,
blank=True
)
image_field = models.ImageField(
help_text="A image field",
null=True,
blank=True
)
null_boolean_field = models.NullBooleanField(
help_text="A null boolean field",
null=True,
blank=True
)
positive_integer_field = models.PositiveIntegerField(
help_text="A positive integer",
null=True,
blank=True
)
positive_small_integer_field = models.PositiveSmallIntegerField(
help_text="A positive small integer field",
null=True,
blank=True
)
slug_field = models.SlugField(
help_text="A slug field",
null=True,
blank=True
)
small_integer_field = models.SmallIntegerField(
help_text="A small integer field",
null=True,
blank=True
)
time_field = models.TimeField(
help_text="A time field",
null=True,
blank=True
)
url_field = models.URLField(
help_text="A url field",
null=True,
blank=True
)
uuid_field = models.UUIDField(
help_text="A uuid field",
null=True,
blank=True
)
many_to_many_field = models.ManyToManyField(
ManyToManyModel,
help_text="A many to many field",
null=True,
blank=True
)
class ForeingModel(models.Model):
name = models.CharField(
max_length=500,
choices=(("a", "1"),
("b", "2"),
("c", "3")),
help_text="write something"
)
age = models.PositiveSmallIntegerField()
birthday = models.DateField()
foreign_key_field = models.ForeignKey(
AllFieldsModel,
help_text="A foreign_key field"
)
def clean(self):
if self.age > 100:
raise ValidationError("Age must be under 100")
class ForeingModeltoForeingModel(models.Model):
inner_name = models.CharField(
max_length=500,
choices=(("a", "1"),
("b", "2"),
("c", "3")),
help_text="write something"
)
foreign_key_field = models.ForeignKey(
ForeingModel,
help_text="A foreign_key field"
)
| UTF-8 | Python | false | false | 4,533 | py | 34 | models.py | 14 | 0.564086 | 0.557026 | 0 | 208 | 20.793269 | 70 |
MariamAmmar/Moodbot- | 12,893,491,853,120 | 24ba3325f42e5d6b0098b8adab14731087bd5445 | 673ed92b4202bbdc0323808823012ced4de3a06f | /main.py | 0b3d0d8cc07074e47eb2ad85b5cf957072dbca93 | []
| no_license | https://github.com/MariamAmmar/Moodbot- | bc3f8128858465b63447486d63ea6a77bedaaae7 | 7800ce4f79c1350757badb13fa6713d963727cd6 | refs/heads/main | 2023-07-06T18:08:56.832182 | 2021-08-21T13:34:59 | 2021-08-21T13:34:59 | 398,564,848 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | """
Mariam Ammar
Class: CS 521 - Summer 2
Date: 08/20/21
Final Project
A moodbot program that returns options for a user based
on input relating to their mood.
"""
from datetime import datetime
import random
import vlc
from User import User
import sys
import time
def play_audio(filename):
'''
Takes filename as argument and plays song file
Allows user to stop song by pressins 's
'''
p = vlc.MediaPlayer(filename)
p.play()
while True:
user_input = input("Press 's' to end audio.")
if user_input == 's':
return p.stop()
break
else:
print("Sorry, you can only press 's' to stop the audio.")
#Asks user for name and name of friend
#assigns default values if blank input is given
name = input("Please input your first name.")
if not name:
name = "my friend"
close_contact = input("Who's your best friend?" or "your best friend")
if not close_contact:
close_contact = "your best friend"
print(f'''
Hi {name}! Welcome to be Moodbot.
We have just a few more questions for you.
''')
#Asks for birthday
#Prompts for user input and reprompts if user input invalid.
while True:
year = input('When is your birthday? [YY] ')
month = input('When is your birthday? [MM] ')
day = input('When is your birthday? [DD]')
try:
year, month, day = int(year), int(month), int(day)
#Convert into datetime format for parsing later
birthday = datetime(year,month,day)
break
except:
print('''
Sorry, try again!
Your number entries must follow the right format.
''')
#This while loop allows user to come back to main menu
#each time a selection has been made.
while True:
#Ask user to rate their mood from 1-10
#Validate input or return error and ask for re-entry
while True:
mood \
= input('''
Rate the way you feel right now
from 1-10 with 10 being the best possible score.
''')
try:
mood = int(mood)
#If mood outside of range 1-10, ask user to reinput
while mood not in range (1,11):
mood\
= int(input('''
Sorry, try again
and make sure you input a number from 1-10.
'''))
break
#Prints when user does not input a number
except:
print('''
Sorry! Looks like you didn't input a number.
Please try again.
''')
#Assign person as p1 to User class
p1 = User(name, close_contact, birthday, mood)
#Menu option selections
#If users input score 1-5, these selections will be printed
sad_options = \
(1, "Listen to a Song"),\
(2, "Write about it"),\
(3, "Meditate"),\
(4, "Read an inspirational quote"),\
(5, "Get some tips"),\
(6, "Read a funny poem")
#If user inputs a score of 5 or above, these selections printed
happy_options = \
(1, "Listen to a Song"), \
(2, "Write a letter to your future self"), \
(3, "Take note of some great ideas"), \
(4, "Plan your birthday celebration"),\
(5, "Have a dance party"), \
(6, "Read a fun fact")
#If mood is 1-2, then user is in critical condition
#Reminder of closest friend is printed before showing options
if mood < 3 :
print(f'''
Wow. Looks like you're really upset.
Make sure to seek out help and think of what {close_contact}
would think if they knew you were feeling like this!
How about giving them a call?
Or you can...\n
''')
for i in sad_options:
print(i[0],i[1])
#If user inputs score from 3-4, output messsage below with sad options
if 2 < mood < 5:
print(f'''
Why so blue?
Your birthday is only {p1.calculate_days_till_bday(p1.birthday)} days away!
Prepare a celebration or choose one of the options below.\n''')
for i in sad_options:
print(i[0],i[1])
#If mood score > 4 then user is either okay or in good mood.
#Print message with happy options
if mood > 4:
print('''
Nice to hear you are at least doing ok!
Which option would you like to choose?\n
''')
for i in happy_options:
print(i[0], i[1])
#Prompts user to make selection after options have been printed
selection = input("Input a number to select an option.")
#If selection out of option range
#prompt user to re-input selection
try:
selection = int(selection)
while selection not in range (1,7):
selection = int(input('''Sorry, try again.\n
Enter a number according to one of the options.'''))
break
#prints if user does not put number input
except:
print("Sorry, try again. You need to input a number.")
#Tips to be printed if user selects "Get some tips" options
#Could have been also been defined as list or tuple.
tips = \
{
"1. Take a few really deep, controlled breaths.",
"2. Call a good friend.",
"3. Go for a walk.",
"4. Do something outside.",
"5. Exercise!",
"6. Eat healthy - food is linked to both physical and mental health.",
"7. Get at least 8 hours of sleep a day.",
"8. Make time for yourself and include relaxing rituals into your day.",
"9. Stay away from smoking and limit your alcohol intake."
}
#Inspiration quotes to be printed
#based on user selected opion.
quotes = \
[ \
'''
\n"To anyone out there who’s hurting
— it’s not a sign of weakness to ask for help.
It’s a sign of strength." —Barack Obama''',
"\nThe only time you fail is when you fall down and stay down.",
"\nEvery day may not be good... but there’s something good in every day.",
'''\n"Soak up the views. Take in the bad weather and the good weather.
You are not the storm." —Matt Haig''',
"\nA journey of 1000 miles always begins with a single step."
]
#fun facts to be printed based on option
fun_facts = \
("More people get attacked every year by a cow than by a shark.",
"When you cut a hole in your fishing net, it has fewer holes.",
"Pennsylvania, USA, has a law which bans you from sleeping on a fridge.",
"Hot water will turn into ice faster than cold water.",
"The Mona Lisa has no eyebrows",
"The entire world's population could fit inside Los Angeles.")
#Songs to be play based on user selected option and mood.
dict_audio = {"sad_song" : "theclimb.mp3",
"happy_song" : "toosieslide.mp3",
"meditation" : "meditation.mp3" ,
"dance_party" : "dance_party.mp3"}
#Output options based on user input if unhappy
if mood < 5 and selection == 1:
play_audio(dict_audio["sad_song"])
elif mood < 5 and selection == 2:
#Calls method from User class for user to write in journal
print(p1._User__write_in_journal())
elif mood < 5 and selection == 3:
#Plays meditation audio
play_audio(dict_audio["meditation"])
elif mood < 5 and selection == 4:
#Prints quote at random inded from quotes list
index = random.randrange(0,len(quotes)-1)
print(quotes[index])
elif mood < 5 and selection == 5:
#Prints tips for long-term mental/physical health
for i in sorted(tips):
print(i)
elif mood < 5 and selection == 6:
#Asks for user words to input
#User inputs arguments to generate madlib
#User madlib method from User class
while True:
try:
n1, n2 \
= input("Input two nouns with a space in between.")\
.split()
adj1, adj2, adj3 \
= input("Input three adjectives with a space in between.")\
.split()
#Prints and allows user to re-input
#if user inputs incorrect number of values
except:
print("Sorry try again.")
else:
print(p1.mad_lib(n1, n2, adj1, adj2, adj3)+"\n")
break
#Actions taken for "Happy" options
if mood > 4 and selection == 1:
#Plays "Happy" song
play_audio(dict_audio["happy_song"])
#Next three options allow user to input entry into journal
elif mood > 4 and selection == 2:
print(p1._User__write_in_journal())
elif mood > 4 and selection == 3:
print(p1._User__write_in_journal())
elif mood > 4 and selection == 4:
#Print statement with days till birthday calculated
#Then allow for journal entry
print(f'''
Wow!
Only {p1.calculate_days_till_bday(p1.birthday)} till your birthday.
How will you celebrate and who will you invite?''')
print(p1._User__write_in_journal())
elif mood > 4 and selection == 5:
#Prints string characters with delay to add to mood of option
strng = "~~~~~~~~~!!!!! ♪┏(・o･)┛♪┗ ( ･o･) ┓♪~~~~~~!!!!~~~~~~"
for i in strng:
print(i, end = "")
time.sleep(0.05)
#Play dance party audio as soon as string finishes printing
play_audio(dict_audio["dance_party"])
#Returns fact at random index
elif mood > 4 and selection == 6:
index = random.randrange(0, len(fun_facts)-1)
print("\n"+fun_facts[index])
#Allows user to exit program
#or to go back to mood input to view options list
user_input\
= input\
('''
\nPress 'b' to go back to the main menu
or another character to exit the program.
''')
if user_input == 'b':
continue
else:
sys.exit(0)
| UTF-8 | Python | false | false | 10,037 | py | 3 | main.py | 2 | 0.581042 | 0.568043 | 0 | 303 | 32.0033 | 78 |
rcbops/rpc-maas | 9,938,554,331,809 | 5a6ff0f22666c78647ce0c73343098f2f6a987c2 | 3b59eb11fb4fb961ad60ddaa39dcdb22ae227e6c | /playbooks/files/rax-maas/plugins/ceph_monitoring.py | 3b60d8ec1b792e3870b4dc3f23a51b33f8868de6 | [
"Apache-2.0"
]
| permissive | https://github.com/rcbops/rpc-maas | dcf56858a623a6559c8209830a7972358bd63b6c | 9ec0b6e38dd724128557d14b8b8f0c95d6797db0 | refs/heads/master | 2023-08-17T11:52:32.837594 | 2023-08-07T17:54:46 | 2023-08-07T17:54:46 | 12,159,651 | 31 | 66 | Apache-2.0 | false | 2023-08-07T14:19:30 | 2013-08-16T13:43:03 | 2022-01-13T05:29:04 | 2023-08-07T14:19:28 | 2,421 | 30 | 64 | 6 | Python | false | false | #!/usr/bin/env python3
# Copyright 2015, Rackspace US, Inc.
#
# 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 argparse
import json
from maas_common import metric_bool
from maas_common import metric
from maas_common import MaaSException
from maas_common import status_ok
from maas_common import print_output
import requests
import subprocess
STATUSES = {'HEALTH_OK': 2, 'HEALTH_WARN': 1, 'HEALTH_ERR': 0}
IGNORE_CHECKS = ['OSDMAP_FLAGS', 'OBJECT_MISPLACED']
# See https://docs.ceph.com/docs/master/rados/operations/health-checks
# for details on each. We had to break these down into sections as each
# check has a max of 50 allowed metrics.
DETAILED_CHECKS = {
'mon': [
'MON_DOWN',
'MON_CLOCK_SKEW',
'MON_MSGR2_NOT_ENABLED',
'MON_DISK_LOW',
'MON_DISK_CRIT',
'MON_DISK_BIG',
],
'mgr': [
'MGR_DOWN',
'MGR_MODULE_DEPENDENCY',
'MGR_MODULE_ERROR',
],
'osds': [
'OSD_DOWN',
'OSD_DOWN',
'OSD_HOST_DOWN',
'OSD_ROOT_DOWN',
'OSD_ORPHAN',
'OSD_OUT_OF_ORDER_FULL',
'OSD_FULL',
'OSD_BACKFILLFULL',
'OSD_NEARFULL',
'OSDMAP_FLAGS',
'OSD_FLAGS',
'OLD_CRUSH_TUNABLES',
'OLD_CRUSH_STRAW_CALC_VERSION',
'CACHE_POOL_NO_HIT_SET',
'OSD_NO_SORTBITWISE',
'BLUEFS_SPILLOVER',
'BLUEFS_AVAILABLE_SPACE',
'BLUEFS_LOW_SPACE',
'BLUESTORE_FRAGMENTATION',
'BLUESTORE_LEGACY_STATFS',
'BLUESTORE_NO_PER_POOL_OMAP',
'BLUESTORE_DISK_SIZE_MISMATCH',
'BLUESTORE_NO_COMPRESSION',
'BLUESTORE_SPURIOUS_READ_ERRORS',
],
'device_health': [
'DEVICE_HEALTH',
'DEVICE_HEALTH_IN_USE',
'DEVICE_HEALTH_TOOMANY',
],
'data_health': [
'PG_AVAILABILITY',
'PG_DEGRADED',
'PG_RECOVERY_FULL',
'PG_BACKFILL_FULL',
'PG_DAMAGED',
'OSD_SCRUB_ERRORS',
'OSD_TOO_MANY_REPAIRS',
'LARGE_OMAP_OBJECTS',
'CACHE_POOL_NEAR_FULL',
'TOO_FEW_PGS',
'POOL_PG_NUM_NOT_POWER_OF_TWO',
'POOL_TOO_FEW_PGS',
'POOL_TOO_MANY_PGS',
'TOO_MANY_PGS',
'POOL_TARGET_SIZE_BYTES_OVERCOMMITTED',
'POOL_HAS_TARGET_SIZE_BYTES_AND_RATIO',
'TOO_FEW_OSDS',
'SMALLER_PGP_NUM',
'MANY_OBJECTS_PER_PG',
'POOL_APP_NOT_ENABLED',
'POOL_FULL',
'POOL_NEAR_FULL',
'OBJECT_MISPLACED',
'OBJECT_UNFOUND',
'SLOW_OPS',
'PG_NOT_SCRUBBED',
'PG_NOT_DEEP_SCRUBBED',
'PG_SLOW_SNAP_TRIMMING',
],
'misc': [
'RECENT_CRASH',
'TELEMETRY_CHANGED',
'AUTH_BAD_CAPS',
'OSD_NO_DOWN_OUT_INTERVAL',
],
}
def check_command(command, container_name=None, deploy_osp=False):
if container_name:
if deploy_osp:
container_command = ['/usr/bin/podman',
'exec',
container_name]
else:
container_command = ['lxc-attach',
'-n',
container_name,
'--',
'bash',
'-c']
container_command.extend(command)
command = [str(i) for i in container_command]
output = subprocess.check_output(command, stderr=subprocess.STDOUT)
lines = output.decode().strip().split('\n')
return json.loads(lines[-1])
def get_ceph_rgw_hostcheck(rgw_address, container_name=None):
try:
sc = requests.get(rgw_address, verify=False).status_code
if (sc >= 200) and (sc < 300):
status_code = 2
else:
status_code = 1
except requests.exceptions.ConnectionError:
status_code = 0
return status_code
def get_ceph_status(client, keyring, fmt='json', container_name=None,
deploy_osp=False):
return check_command(('ceph', '--format', fmt, 'status'),
container_name=container_name,
deploy_osp=deploy_osp)
def get_ceph_mon_status(client, keyring, fmt='json', container_name=None,
deploy_osp=False):
return check_command(('ceph', 'mon', 'stat', '--format', fmt),
container_name=container_name,
deploy_osp=deploy_osp)
def get_local_osd_info(osd_ref, fmt='json', container_name=None,
deploy_osp=False):
return check_command(
('ceph', '--format', fmt, 'daemon', osd_ref, 'status'),
container_name=container_name,
deploy_osp=deploy_osp
)
def get_mon_statistics(client=None, keyring=None, host=None,
container_name=None, deploy_osp=False):
ceph_status = get_ceph_status(client=client,
keyring=keyring,
container_name=container_name,
deploy_osp=deploy_osp)
try:
mon = [m for m in ceph_status['monmap']['mons']
if m['name'] == host]
except KeyError:
ceph_mon_status = get_ceph_mon_status(client=client,
keyring=keyring,
container_name=container_name,
deploy_osp=deploy_osp)
mon_in = host in ceph_status['quorum_names']
metric_bool('mon_in_quorum', mon_in)
def get_health_checks(client=None, keyring=None, section=None,
container_name=None, deploy_osp=False):
metrics = []
ceph_status = get_ceph_status(client=client,
keyring=keyring,
container_name=container_name,
deploy_osp=deploy_osp)
# Go through the detailed health checks and generate metrics
# for each based on the given section
for curcheck in DETAILED_CHECKS[section]:
if curcheck in ceph_status['health']['checks']:
severity = ceph_status['health']['checks'][curcheck]['severity']
metrics.append({'name': curcheck,
'type': 'uint32',
'value': STATUSES[severity]})
else:
metrics.append({'name': curcheck,
'type': 'uint32',
'value': STATUSES['HEALTH_OK']})
# Submit gathered metrics
for m in metrics:
metric(m['name'], m['type'], m['value'])
def get_rgw_checkup(client, keyring=None, rgw_address=None,
container_name=None, deploy_osp=False):
rgw_status = get_ceph_rgw_hostcheck(rgw_address,
container_name=container_name)
metric('rgw_up', 'uint32', rgw_status)
def get_osd_statistics(client=None, keyring=None, osd_id=None,
container_name=None, deploy_osp=False):
osd_ref = "osd.%s" % osd_id
try:
osd_info = get_local_osd_info(
osd_ref, container_name=container_name, deploy_osp=deploy_osp
)
except Exception:
msg = 'The OSD ID %s does not exist.' % osd_id
raise MaaSException(msg)
else:
state = 1 if osd_info.get('state', '') == 'active' else 0
metric_name = '_'.join((osd_ref, 'up'))
metric_bool(metric_name, state)
def get_cluster_statistics(client=None, keyring=None, container_name=None,
deploy_osp=False):
metrics = []
ceph_status = get_ceph_status(client=client,
keyring=keyring,
container_name=container_name,
deploy_osp=deploy_osp)
# Get overall cluster health
# For luminous+ this is the ceph_status.health.status
# For < Luminous this is the ceph_status.health.overall_status
# SLM: 'overall_status' exists along with 'status' for luminous.
# It will be HEALTH_WARN while 'status' will be HEALTH_OK.
# The following should work for all with the newer overriding
# the older if both exist.
ceph_health_status = 'HEALTH_ERR'
if 'overall_status' in ceph_status['health']:
ceph_health_status = ceph_status['health']['overall_status']
if 'status' in ceph_status['health']:
ceph_health_status = ceph_status['health']['status']
# Ignore checks. Quick fix from ceph admin request.
if ceph_health_status != 'HEALTH_OK':
ignore = True
for curcheck in ceph_status['health']['checks']:
if curcheck not in IGNORE_CHECKS:
ignore = False
break
if ignore:
ceph_health_status = 'HEALTH_OK'
metrics.append({
'name': 'cluster_health',
'type': 'uint32',
'value': STATUSES[ceph_health_status]})
# Collect epochs for the mon and osd maps
metrics.append({'name': "monmap_epoch",
'type': 'uint32',
'value': ceph_status['monmap']['epoch']})
if 'osdmap' in ceph_status['osdmap']:
metrics.append({'name': "osdmap_epoch",
'type': 'uint32',
'value': ceph_status['osdmap']['osdmap']['epoch']})
else:
metrics.append({'name': "osdmap_epoch",
'type': 'uint32',
'value': ceph_status['osdmap']['epoch']})
# Collect OSDs per state
if 'osdmap' in ceph_status['osdmap']:
osds = {'total': ceph_status['osdmap']['osdmap']['num_osds'],
'up': ceph_status['osdmap']['osdmap']['num_up_osds'],
'in': ceph_status['osdmap']['osdmap']['num_in_osds']}
else:
osds = {'total': ceph_status['osdmap']['num_osds'],
'up': ceph_status['osdmap']['num_up_osds'],
'in': ceph_status['osdmap']['num_in_osds']}
for k in osds:
metrics.append({'name': 'osds_%s' % k,
'type': 'uint32',
'value': osds[k]})
# Collect cluster size & utilisation
metrics.append({'name': 'osds_kb_used',
'type': 'uint64',
'value': ceph_status['pgmap']['bytes_used'] / 1024})
metrics.append({'name': 'osds_kb_avail',
'type': 'uint64',
'value': ceph_status['pgmap']['bytes_avail'] / 1024})
metrics.append({'name': 'osds_kb',
'type': 'uint64',
'value': ceph_status['pgmap']['bytes_total'] / 1024})
# Collect num PGs and num healthy PGs
pgs = {'total': ceph_status['pgmap']['num_pgs'], 'active_clean': 0}
for state in ceph_status['pgmap']['pgs_by_state']:
if state['state_name'] == 'active+clean':
pgs['active_clean'] = state['count']
break
for k in pgs:
metrics.append({'name': 'pgs_%s' % k,
'type': 'uint32',
'value': pgs[k]})
# Submit gathered metrics
for m in metrics:
metric(m['name'], m['type'], m['value'])
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument('--name',
required=True,
help='Ceph client name')
parser.add_argument('--deploy_osp',
action='store_true',
default=False,
help='Option for extending into OSP environments')
parser.add_argument('--keyring',
required=True,
help='Ceph client keyring')
parser.add_argument('--container-name',
required=False,
default=None,
help='Ceph Container Name')
subparsers = parser.add_subparsers(dest='subparser_name')
parser_mon = subparsers.add_parser('mon')
parser_mon.add_argument('--host', required=True, help='Mon hostname')
parser_osd = subparsers.add_parser('osd')
parser_osd.add_argument('--osd_id', required=True, type=str,
help='A single OSD ID')
parser_rgw = subparsers.add_parser('rgw')
parser_rgw.add_argument('--rgw_address', required=True,
help='RGW address in form proto://ip_addr:port/')
parser.add_argument('--telegraf-output',
action='store_true',
default=False,
help='Set the output format to telegraf')
parser_mon = subparsers.add_parser('health_checks')
# From https://docs.ceph.com/docs/master/rados/operations/health-checks
parser_mon.add_argument('--section',
required=True,
help='(mon,mgr,osds,device_health,data_health \
or misc)')
subparsers.add_parser('cluster')
return parser.parse_args()
def main(args):
get_statistics = {'cluster': get_cluster_statistics,
'mon': get_mon_statistics,
'rgw': get_rgw_checkup,
'osd': get_osd_statistics,
'health_checks': get_health_checks}
kwargs = {'client': args.name, 'keyring': args.keyring}
if args.subparser_name == 'osd':
kwargs['osd_id'] = args.osd_id
if args.subparser_name == 'mon':
kwargs['host'] = args.host
if args.subparser_name == 'rgw':
kwargs['rgw_address'] = args.rgw_address
if args.subparser_name == 'health_checks':
kwargs['section'] = args.section
kwargs['container_name'] = args.container_name
kwargs['deploy_osp'] = args.deploy_osp
get_statistics[args.subparser_name](**kwargs)
status_ok(m_name='maas_ceph')
if __name__ == '__main__':
args = get_args()
with print_output(print_telegraf=args.telegraf_output):
main(args)
| UTF-8 | Python | false | false | 14,463 | py | 233 | ceph_monitoring.py | 70 | 0.538547 | 0.534122 | 0 | 408 | 34.448529 | 77 |
django-oscar/django-oscar | 154,618,861,809 | aa0b4da2c5e5c199a4efee6022ba8c4486742bd2 | c491b5171775447a9ab33a036be1375f7b71ab2f | /src/oscar/apps/offer/views.py | e53c47945377f3dd66cf37a275a1ae95221627d7 | [
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
]
| permissive | https://github.com/django-oscar/django-oscar | e4abd486d51d6173dafbd9c10b59675858196e61 | 5edac196f41f8cc97f8a07f7579f1041db2a02af | refs/heads/master | 2023-08-30T16:19:12.081909 | 2023-07-14T11:53:30 | 2023-07-14T11:53:30 | 1,151,051 | 5,320 | 2,524 | BSD-3-Clause | false | 2023-09-13T19:48:30 | 2010-12-08T21:30:32 | 2023-09-12T12:43:09 | 2023-09-13T19:48:29 | 120,979 | 5,846 | 2,149 | 94 | Python | false | false | from django import http
from django.conf import settings
from django.shortcuts import get_object_or_404
from django.views.generic import ListView
from oscar.core.loading import get_model
ConditionalOffer = get_model("offer", "ConditionalOffer")
Range = get_model("offer", "Range")
class OfferListView(ListView):
model = ConditionalOffer
context_object_name = "offers"
template_name = "oscar/offer/list.html"
def get_queryset(self):
"""
Return a queryset of active :py:class:`ConditionalOffer <oscar.apps.offer.abstract_models.AbstractConditionalOffer>`
instances with an :py:attr:`offer_type <oscar.apps.offer.abstract_models.AbstractConditionalOffer.offer_type>`
of :py:const:`ConditionalOffer.SITE <oscar.apps.offer.abstract_models.AbstractConditionalOffer.SITE>`.
"""
return ConditionalOffer.active.filter(offer_type=ConditionalOffer.SITE)
class OfferDetailView(ListView):
context_object_name = "products"
template_name = "oscar/offer/detail.html"
paginate_by = settings.OSCAR_OFFERS_PER_PAGE
# pylint: disable=W0201
def get(self, request, *args, **kwargs):
try:
self.offer = ConditionalOffer.active.select_related().get(
slug=self.kwargs["slug"]
)
except ConditionalOffer.DoesNotExist:
raise http.Http404
return super().get(request, *args, **kwargs)
def get_context_data(self, **kwargs):
ctx = super().get_context_data(**kwargs)
ctx["offer"] = self.offer
ctx["upsell_message"] = self.offer.get_upsell_message(self.request.basket)
return ctx
def get_queryset(self):
"""
Return a queryset of all :py:class:`Product <oscar.apps.catalogue.abstract_models.AbstractProduct>`
instances related to the :py:class:`ConditionalOffer <oscar.apps.offer.abstract_models.AbstractConditionalOffer>`.
"""
return self.offer.products()
class RangeDetailView(ListView):
template_name = "oscar/offer/range.html"
context_object_name = "products"
paginate_by = settings.OSCAR_PRODUCTS_PER_PAGE
# pylint: disable=W0201
def dispatch(self, request, *args, **kwargs):
self.range = get_object_or_404(Range, slug=kwargs["slug"], is_public=True)
return super().dispatch(request, *args, **kwargs)
def get_queryset(self):
"""
Return a queryset of all :py:class:`Product <oscar.apps.catalogue.abstract_models.AbstractProduct>`
instances related to the :py:class:`Range <oscar.apps.offer.abstract_models.AbstractRange>`.
"""
products = self.range.all_products().browsable()
return products.order_by("rangeproduct__display_order")
def get_context_data(self, **kwargs):
ctx = super().get_context_data(**kwargs)
ctx["range"] = self.range
return ctx
| UTF-8 | Python | false | false | 2,887 | py | 979 | views.py | 617 | 0.675442 | 0.669553 | 0 | 76 | 36.986842 | 124 |
Abirami8799/python-project | 395,137,023,713 | 154f5981e1e00159267bc46144b3d781066f74c9 | 030a3de3800c5a369d287f2f21a4d4e65a107c18 | /tamilwords.py | 2859b002c5748c57244c3fe8b4f51e37f1d19502 | []
| no_license | https://github.com/Abirami8799/python-project | 8139bf943e932d85615694bf443fd1e5d49b2601 | 3583fb87f53ee926cff749727c28d5aee424c498 | refs/heads/master | 2023-09-03T08:11:02.777261 | 2021-11-15T18:28:19 | 2021-11-15T18:28:19 | 395,344,547 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import os
import tamil
from tamil.utf8 import get_letters, get_letters_length, get_words
value = int(input("enter the word "))
l=[]
for i in range(1,value+1):
x=input(f'enter the letter {i} ')
l.append(x)
n=''.join(map(str,l))
for root, dirs, files in os.walk("C:/Users/codiislap10/Documents/new"):
for name in dirs:
if name == "len_"+str(value):
a=os.path.join(root,name)
if bool(l[0]):
for root, dirs, files in os.walk(a):
for val in files:
if val.startswith(n[0]):
b=os.path.join(root,val)
file1=open(b,encoding="utf-8")
lines=file1.read()
word=get_words(lines)
r=get_letters_length(n)
for each in word:
m=get_letters(each)
y=[m.index(j) for i,j in zip(l,m) if i==j]
if len(y)==r:
print(''.join(map(str,m)))
else:
for root, dirs, files in os.walk(a):
for val in files:
b=os.path.join(root,val)
file1=open(b,encoding="utf-8")
lines=file1.read()
word=get_words(lines)
r=get_letters_length(n)
for each in word:
m=get_letters(each)
y=[m.index(j) for i,j in zip(l,m) if i==j]
if len(y)==r:
print(''.join(map(str,m)))
| UTF-8 | Python | false | false | 1,347 | py | 4 | tamilwords.py | 4 | 0.514477 | 0.504826 | 0 | 44 | 28.613636 | 71 |
MasudRehmanSyed/instragram_follower_bot | 3,848,290,702,909 | 65718b56b3c7ec636fc9e0c989aaf44c2b18d29b | 6617a21a97832c9cd8da2c37716c7b3d345aa8ab | /instafollower.py | a80465a31289169eac8ae104c146ea840c32b56f | []
| no_license | https://github.com/MasudRehmanSyed/instragram_follower_bot | 9c5406663e69806821936be462dc094a97edfd9b | 0a59e26f9bd1056e89b7b50d5de623254ec60e8e | refs/heads/master | 2023-07-04T06:43:35.342484 | 2021-07-27T18:14:26 | 2021-07-27T18:14:26 | 389,802,313 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import time
SITE= 'https://www.instagram.com/accounts/login/'
class Instafollower:
def __init__(self):
self.driver = webdriver.Chrome('C:\webdrivers\chromedriver.exe')
self.driver.maximize_window()
self.driver.get(SITE)
def login(self, uname, passw):
self.driver.implicitly_wait(5)
self.driver.find_element_by_name('username').send_keys(uname)
self.driver.find_element_by_name('password').send_keys(passw)
self.driver.implicitly_wait(2)
self.driver.find_element_by_name('password').send_keys(Keys.ENTER)
self.driver.implicitly_wait(2)
self.driver.find_element_by_xpath('//button[@class="sqdOP L3NKy y3zKF "]').click()
time.sleep(3)
def kill_pop_up(self):
self.driver.find_element_by_css_selector('.mt3GC .HoLwm').click()
def find_followers(self):
self.driver.get('https://www.instagram.com/chefsteps')
self.driver.implicitly_wait(3)
follow_button = self.driver.find_element_by_xpath('//button[@class="_5f5mN jIbKX _6VtSN yZn4P "]')
follow_button.click()
def follow(self):
''' Gets the pop up and selects the div with all the names and runs a javascript to
select all the follow'''
modal = self.driver.find_element_by_xpath('/html/body/div[5]/div/div/div[2]')
for i in range(0, 10):
self.driver.execute_script("arguments[0].scrollTop = arguments[0].scrollHeight", modal)
time.sleep(2)
def quit_web(self):
self.driver.quit() | UTF-8 | Python | false | false | 1,649 | py | 3 | instafollower.py | 2 | 0.642814 | 0.630685 | 0 | 46 | 34.869565 | 119 |
wang7211401/python-reptile | 16,578,573,773,884 | 9661465dd0c49d3dbfb33a5411c05559499c8d3a | d56c6d29c619818ac112d5bb289cb33e0ec546b8 | /demo/urlparse.py | 0fe851a03fdf816f39e3eacdcd4ffe130aad930a | []
| no_license | https://github.com/wang7211401/python-reptile | d806735815be5ac331f024a00099efeab5c266c9 | fe7ec412c6f49a1cac9f50b3c14bcd24fd7a1fde | refs/heads/master | 2020-05-30T05:59:06.152170 | 2019-10-30T07:07:37 | 2019-10-30T07:07:37 | 189,568,726 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # from urllib.parse import urlparse
# result = urlparse('http://www.baidu.com/index.html;user?id=5#comment',allow_fragments=False)
# print(result.scheme,result[0],result.netloc,result[1],sep='\n')
# from urllib.parse import urlunparse
# data = ['http','www.baidu.com','index.html','user','a=6','comment']
# print(urlunparse(data))
# from urllib.parse import urlsplit
# result = urlsplit('http://www.baidu.com/index.html;user?id=5#comment')
# print(result.scheme,result[0])
# from urllib.parse import urlunsplit
# data = ['http','www.baidu.com','index.html','a=6','comment']
# print(urlunsplit(data))
# from urllib.parse import urljoin
# print(urljoin('http://www.baidu.com','FAQ.html'))
# from urllib.parse import urlencode
# params = {
# 'name':'germey',
# 'age':22
# }
# base_url ='http://www.baidu.com?'
# url = base_url + urlencode(params)
# print(url)
# from urllib.parse import parse_qsl
# query = 'name=germey&age=22'
# print(parse_qsl(query))
# from urllib.parse import quote
# keyword ='壁纸'
# url ='https://www.baidu.com/s?wd=' + quote(keyword)
# print(url)
from urllib.parse import unquote
url = 'https://www.baidu.com/s?wd=%E5%A3%81%E7%BA%B8'
print(unquote(url)) | UTF-8 | Python | false | false | 1,203 | py | 7 | urlparse.py | 7 | 0.683069 | 0.668891 | 0 | 50 | 23 | 94 |
BusinessJoe/PolytopeVisualizer | 13,194,139,546,555 | 3f836d80b50c83047a079449a50f420af9226699 | db812e6b7d0772048cfe4041baf2b4265f87ca21 | /tests/test_diagram.py | 114eddad678ee595593b2ec68db9b1395ef6d0a4 | []
| no_license | https://github.com/BusinessJoe/PolytopeVisualizer | 895679e8ff5593351cccdcb1d1146aed6b221c16 | 5c2b74791aada41f83eb5419c3d9876ec63b98aa | refs/heads/main | 2023-04-13T12:56:55.055340 | 2022-05-05T20:55:07 | 2022-05-05T20:55:07 | 320,091,552 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import pytest
from polytope_visualizer.math import diagram
def test_gen_53():
d = diagram.CoxeterDiagram([1, 1, 1], [5, 3])
print(d.polytope())
| UTF-8 | Python | false | false | 155 | py | 26 | test_diagram.py | 21 | 0.670968 | 0.625806 | 0 | 7 | 21 | 49 |
lili4cityu/TextRankPlus | 14,422,500,199,384 | 9482f667c3457a6c1c87a7598376de5f41d073d7 | 8a1a7579f7ed188ea562358a6a89e9b6a5c7c85b | /word2vec/traditional2Simplified/getChineseSimplified.py | 8f754f0a2ec59783504a0e3e8bda1afc0caea66a | []
| no_license | https://github.com/lili4cityu/TextRankPlus | fa5def3f07f041000c4ee25f32019d915652295c | c655bd5b88a5dec829cedac462b2f1634fb0b42f | refs/heads/master | 2020-07-07T16:00:23.592076 | 2019-08-20T14:52:42 | 2019-08-20T14:52:42 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 20 12:13:18 2016
@author: zuoxiaolei
"""
from langconv import *
def getSimple(line,fileWrite):
line = Converter('zh-hans').convert(line.decode('utf-8'))
line = line.encode('utf-8')
fileWrite.write(line+'\n')
| UTF-8 | Python | false | false | 271 | py | 18 | getChineseSimplified.py | 16 | 0.638376 | 0.583026 | 0 | 13 | 19.769231 | 61 |
FiniteElementries/barebone_server | 10,402,410,837,315 | 6cbcd7a8e031a016a9c9a46349e51ca66196cb6f | c37c11cac340b413f2ce638769f0b5623433a139 | /userprofile/urls.py | 27bba6fd6647359f9d0c1fb5cbaabf9d267b5b5d | [
"MIT"
]
| permissive | https://github.com/FiniteElementries/barebone_server | 1e2d188a3aa7d80944e04f3831bc4c60e8a223af | 3713b7d384aa9501741eeebdc49398d917deabb3 | refs/heads/master | 2021-01-10T17:19:02.669746 | 2016-01-14T19:20:08 | 2016-01-14T19:20:08 | 49,311,640 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null |
from django.conf.urls import patterns, url
from api_userprofile import *
urlpatterns = patterns('',
url(r'^info', get_userprofile_detail),
url(r'^friends/list', get_friend_list),
url(r'^friends/change', friend_action),
url(r'^change_info',change_userprofile_info),
)
| UTF-8 | Python | false | false | 385 | py | 22 | urls.py | 19 | 0.514286 | 0.514286 | 0 | 10 | 37.4 | 68 |
Sradha-13/Django1stproject | 541,165,881,136 | 115e1d548ca4e91f7ee8405fe7c1fcdcf9136ed3 | f65be32166595aaab25e373e7d8172d4610a6ec2 | /Todo/models.py | db5ab451980476e0044f10c68acdc20ee85f08ab | []
| no_license | https://github.com/Sradha-13/Django1stproject | 9e0e1ac9712a2a69c5788edd786aef7bddee5909 | 97f57a35631809da7a446178670ac701490d1634 | refs/heads/master | 2023-08-31T22:58:33.434079 | 2021-10-19T09:43:15 | 2021-10-19T09:43:15 | 418,858,063 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.db import models
from django.db.models.base import Model
# Create your models here.
class Todo(models.Model):
name=models.CharField(max_length=40)
due_date=models.DateField()
def __str__(self):
return self.name | UTF-8 | Python | false | false | 248 | py | 5 | models.py | 3 | 0.697581 | 0.689516 | 0 | 10 | 23.9 | 40 |
JYPark09/MenuWizard | 1,382,979,472,656 | 009d10065617691dc23cd465ba1278c0c9da75ca | ebde0385f3107064fd33feb3bf6c60889c4e2c62 | /backend/dataloader.py | 715fabff758936a22cce7462fddf5d1aa513e4ea | [
"MIT"
]
| permissive | https://github.com/JYPark09/MenuWizard | cdefc31ed1ed8e568ce09e8f34a8a446291453f1 | 31dd76b3a0b29f8af0972214b4f62de308cae133 | refs/heads/master | 2020-06-01T15:33:32.404396 | 2019-06-10T07:04:05 | 2019-06-10T07:04:05 | 190,835,504 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import torch
from torch.utils.data import TensorDataset
import numpy as np
def normalize(arr, temp_mean, temp_var, time_mean, time_var):
arr[2] = (arr[2] - temp_mean) / temp_var
arr[4] = (arr[4] - time_mean) / time_var
def load_labels():
labels = []
with open('./data/label.csv', 'r') as f:
for i, line in enumerate(f.readlines(), 0):
labels.append(line.split(',')[1].strip())
return labels
def load_data(filename):
X, Y = [], []
with open(filename, 'r') as f:
for line in f.readlines():
line = list(map(float, line.strip().split(',')))
X.append(line[1:])
Y.append(line[0])
means = np.mean(X, axis=0)
vars = np.var(X, axis=0)
temp_mean = means[2]
temp_var = vars[2]
time_mean = means[4]
time_var = vars[4]
for i in range(len(X)):
normalize(X[i], temp_mean, temp_var, time_mean, time_var)
X = torch.tensor(X).float().view(-1, 38)
Y = torch.tensor(Y).long()
return TensorDataset(X, Y), temp_mean, temp_var, time_mean, time_var
| UTF-8 | Python | false | false | 1,079 | py | 11 | dataloader.py | 7 | 0.568119 | 0.552363 | 0 | 44 | 23.522727 | 72 |
srush/cs287 | 9,225,589,769,490 | 571a0e89d9573ec9f2b1169eaf1ce2d2535e4b42 | ee06e1914d4745ece99078cfdd3c12d64503ad8e | /hw2/lm.py | db451e17dbc4888fb2438b5b353f5bdc7fdc4a4f | []
| no_license | https://github.com/srush/cs287 | 2efefdf4642702a69e18864232f5fbe8db788974 | a90f48d8e5877fc73bbc515944eefcc773af94ee | refs/heads/master | 2021-04-29T18:16:31.480507 | 2018-02-15T22:15:26 | 2018-02-15T22:15:26 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | """ Some language modeling code.
python lm.py --model LstmLm --devid 1 --lr 0.01 --clip 2 --optim Adam --nlayers 2 --nhid 512 --dropout 0.5 --epochs 50 --bsz 128 --bptt 32 --tieweights
Train: 42.90723478099889, Valid: 75.74921810452948, Test: 72.84913233987702
python lm.py --model NnLm --devid 3 --lr 0.001 --clip 0 --optim Adam --nlayers 2 --nhid 512 --dropout 0.5 --epochs 20 --bsz 64 --bptt 64
Train: 71.58999479091389, Valid: 158.07431086368382, Test: 146.13046578572258
Tested on torch.__version__ == 0.3.1b0+2b47480
"""
import argparse
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.autograd import Variable as V
from torch.nn import Parameter
from torch.nn.utils import clip_grad_norm
import torchtext
from tqdm import tqdm
import random
import math
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--devid", type=int, default=-1)
parser.add_argument("--model", choices=["NnLm", "LstmLm"], default="LstmLm")
parser.add_argument("--nhid", type=int, default=256)
parser.add_argument("--nlayers", type=int, default=1)
parser.add_argument("--tieweights", action="store_true")
parser.add_argument("--maxnorm", type=float, default=None)
parser.add_argument("--dropout", type=float, default=0)
parser.add_argument("--epochs", type=int, default=10)
parser.add_argument("--optim", choices=["SGD", "Adam"], default="Adam")
parser.add_argument("--lr", type=float, default=0.01)
parser.add_argument("--lrd", type=float, default=0.25)
parser.add_argument("--wd", type=float, default=1e-4)
parser.add_argument("--bsz", type=int, default=32)
parser.add_argument("--bptt", type=int, default=32)
parser.add_argument("--clip", type=float, default=5)
# Adam parameters
parser.add_argument("--b1", type=float, default=0.9)
parser.add_argument("--b2", type=float, default=0.999)
parser.add_argument("--eps", type=float, default=1e-8)
# SGD parameters
parser.add_argument("--mom", type=float, default=0.99)
parser.add_argument("--dm", type=float, default=0)
parser.add_argument("--nonag", action="store_true", default=False)
return parser.parse_args()
args = parse_args()
random.seed(1111)
torch.manual_seed(1111)
if args.devid >= 0:
torch.cuda.manual_seed_all(1111)
torch.backends.cudnn.enabled = False
print("Cudnn is enabled: {}".format(torch.backends.cudnn.enabled))
TEXT = torchtext.data.Field()
train, valid, test = torchtext.datasets.LanguageModelingDataset.splits(
path=".",
train="train.txt", validation="valid.txt", test="valid.txt", text_field=TEXT)
#path="data/",
#train="train.txt", validation="valid.txt", test="test.txt", text_field=TEXT)
TEXT.build_vocab(train)
padidx = TEXT.vocab.stoi["<pad>"]
train_iter, valid_iter, test_iter = torchtext.data.BPTTIterator.splits(
(train, valid, test), batch_size=args.bsz, device=args.devid, bptt_len=args.bptt, repeat=False)
class Lm(nn.Module):
""" Boring superclass for all the language modeling code. """
def __init__(self):
super(Lm, self).__init__()
def train_epoch(self, iter, loss, optimizer):
self.train()
train_loss = 0
nwords = 0
hid = None
for batch in tqdm(iter):
optimizer.zero_grad()
x = batch.text
y = batch.target
out, hid = model(x, hid if hid is not None else None)
bloss = loss(out.view(-1, model.vsize), y.view(-1))
bloss.backward()
train_loss += bloss
# bytetensor.sum overflows, so cast to int
nwords += y.ne(padidx).int().sum()
if args.clip > 0:
clip_grad_norm(self.parameters(), args.clip)
optimizer.step()
return train_loss.data[0], nwords.data[0]
def validate(self, iter, loss):
self.eval()
valid_loss = 0
nwords = 0
hid = None
for batch in iter:
x = batch.text
y = batch.target
out, hid = model(x, hid if hid is not None else None)
valid_loss += loss(out.view(-1, model.vsize), y.view(-1))
nwords += y.ne(padidx).int().sum()
return valid_loss.data[0], nwords.data[0]
def generate_predictions(self):
self.eval()
data = torchtext.datasets.LanguageModelingDataset(
path="input.txt",
text_field=TEXT)
data_iter = torchtext.data.BPTTIterator(data, 211, 12, device=args.devid, train=False)
outputs = [[] for _ in range(211)]
print()
print("Generating Kaggle predictions")
for batch in tqdm(data_iter):
# T x N x V
scores, idxs = self(batch.text, None)[0][-3].topk(20, dim=-1)
for i in range(idxs.size(0)):
outputs[i].append([TEXT.vocab.itos[x] for x in idxs[i].data.tolist()])
with open(self.__class__.__name__ + ".preds.txt", "w") as f:
f.write("id,word\n")
ok = 1
for sentences in outputs:
f.write("\n".join(["{},{}".format(ok+i, " ".join(x)) for i, x in enumerate(sentences)]))
f.write("\n")
ok += len(sentences)
class NnLm(Lm):
""" Feedforward neural network LM, pretends each bptt sequence is a sentence. """
def __init__(self, vocab, nhid, kW=3, nlayers=1, dropout=0, tieweights=True):
super(NnLm, self).__init__()
self.vsize = len(vocab.itos)
self.kW = kW
self.nhid = nhid
self.lut = nn.Embedding(self.vsize, nhid, max_norm=args.maxnorm)
self.conv = nn.Conv1d(nhid, nhid, kW, stride=1)
self.drop = nn.Dropout(dropout)
m = []
for i in range(nlayers-1):
m.append(nn.Linear(nhid, nhid))
m.append(nn.Tanh())
m.append(nn.Dropout(dropout))
self.mlp = nn.Sequential(*m)
self.proj = nn.Linear(nhid, self.vsize)
if tieweights:
# Weight tying is horrible for this model.
self.proj.weight = self.lut.weight
def forward(self, input, hid):
emb = self.lut(input)
# T = time, N = batch, H = hidden
T, N, H = emb.size()
# We pad manually, since conv1d only does symmetric padding.
# This is kind of incorrect, ideally you'd have an embedding
# for a separate padding token that you append to the start of a sen.
pad = V(emb.data.new(self.kW-1, N, H))
pad.data.fill_(0)
pad.requires_grad = False
emb = torch.cat([pad, emb], 0)
# Conv wants N(1) x H(2) x T(0), but our input is T(0) x N(1) x H(2)
# Then we have to convert back to T(2) x N(0) x H(1) from N(0) x H(1) x T(2)
# Sorry, that was kind of backwards, think about it from input order of dimensions
# to what we want (right to left in the above description).
hid = self.conv(emb.permute(1,2,0)).permute(2,0,1)
return self.proj(self.mlp(hid)), hid
class LstmLm(Lm):
def __init__(self, vocab, nhid, nlayers=1, dropout=0, tieweights=True):
super(LstmLm, self).__init__()
self.vsize = len(vocab.itos)
self.lut = nn.Embedding(self.vsize, nhid, max_norm=args.maxnorm)
self.rnn = nn.LSTM(
input_size=nhid,
hidden_size=nhid,
num_layers=nlayers,
dropout=dropout)
self.drop = nn.Dropout(dropout)
self.proj = nn.Linear(nhid, self.vsize)
if tieweights:
# See https://arxiv.org/abs/1608.05859
# Seems to improve ppl by 13%.
self.proj.weight = self.lut.weight
def forward(self, input, hid):
emb = self.lut(input)
hids, hid = self.rnn(emb, hid)
# Detach hiddens to truncate the computational graph for BPTT.
# Recall that hid = (h,c).
return self.proj(self.drop(hids)), tuple(map(lambda x: x.detach(), hid))
if __name__ == "__main__":
models = {model.__name__: model for model in [NnLm, LstmLm]}
model = models[args.model](
TEXT.vocab, args.nhid, nlayers=args.nlayers, dropout=args.dropout, tieweights=args.tieweights)
print(model)
if args.devid >= 0:
model.cuda(args.devid)
# We do not want to give the model credit for predicting padding symbols,
# this can decrease ppl a few points.
weight = torch.FloatTensor(model.vsize).fill_(1)
weight[padidx] = 0
if args.devid >= 0:
weight = weight.cuda(args.devid)
loss = nn.CrossEntropyLoss(weight=V(weight), size_average=False)
params = [p for p in model.parameters() if p.requires_grad]
if args.optim == "Adam":
optimizer = optim.Adam(
params, lr = args.lr, weight_decay = args.wd, betas=(args.b1, args.b2))
elif args.optim == "SGD":
optimizer = optim.SGD(
params, lr = args.lr, weight_decay = args.wd,
nesterov = not args.nonag, momentum = args.mom, dampening = args.dm)
schedule = optim.lr_scheduler.ReduceLROnPlateau(
optimizer, patience=1, factor=args.lrd, threshold=1e-3)
for epoch in range(args.epochs):
print("Epoch {}, lr {}".format(epoch, optimizer.param_groups[0]['lr']))
train_loss, train_words = model.train_epoch(
iter=train_iter, loss=loss, optimizer=optimizer)
valid_loss, valid_words = model.validate(valid_iter, loss)
schedule.step(valid_loss)
print("Train: {}, Valid: {}".format(
math.exp(train_loss / train_words), math.exp(valid_loss / valid_words)))
test_loss, test_words = model.validate(test_iter, loss)
print("Test: {}".format(math.exp(test_loss / test_words)))
model.generate_predictions()
torch.save(model.cpu(), model.__class__.__name__ + ".pth")
| UTF-8 | Python | false | false | 9,846 | py | 17 | lm.py | 6 | 0.606338 | 0.578814 | 0 | 263 | 36.437262 | 152 |
dengjinyi4/Test_Plantfrom | 1,159,641,170,464 | 5352f1d762b48425a404354aaf3d3fc9ecff3927 | 80f53e7ea872dc18e45bd810ebb2073dac773f71 | /business_modle/testtools/utils/db_info.py | c4869aa8ebe7fd409d6e3564e2b41234da785777 | []
| no_license | https://github.com/dengjinyi4/Test_Plantfrom | 30ca560b157b6f7026e6f05bc3ace10c63894d11 | eb49d08ceb5cba44ce48178ed79c2e79a596de69 | refs/heads/master | 2021-06-13T07:34:55.840837 | 2021-03-09T06:41:54 | 2021-03-09T06:41:54 | 144,958,663 | 2 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
# @Time : 2018/2/25 15:38
# @Author : wanglanqing
import MySQLdb
# -*- coding: utf-8 -*-
# @Time : 2017/12/13 9:53
# @Author : wanglanqing
import MySQLdb
class DbOperations(object):
def __init__(self, env_value=True):
if env_value == True:
#测试环境
print "测试环境"
self.db = MySQLdb.connect(host="172.16.105.12",
port=5701,
db="voyager",
user="voyager",
passwd="voyager",
charset = 'utf8')
elif env_value== False:
#生产环境voyager
print "生产环境voyager"
self.db = MySQLdb.connect(host="221.122.127.168",
port=3306,
db="voyager",
user="dengjinyi",
passwd="dengjinyi123456",
charset='utf8')
else:
#生产环境voyagerstat
print "生产环境voyagerstat"
self.db = MySQLdb.connect(host='123.59.17.122',
port=3306,
db="voyagerstat",
user="voyager",
passwd="SIkxiJI5r48JIvPh",
charset='utf8')
self.cursor = self.db.cursor()
def execute_sql(self, sql):
print '执行的sql是： '+ sql
try:
self.cursor.execute(sql)
self.db.commit()
results = self.cursor.fetchall()
# print results
return results
except Exception as e:
print e
# def executestat_sql(self,sql):
# print "执行的sql是:"+sql
# try:
# self.cursor_stat.execute(sql)
# self.db_stat.commit()
# results = self.cursor_stat.fetchall()
# return results
# except Exception as e:
# print e
def len_value(self, sql):
# print '执行的sql是： '+ sql
results = self.execute_sql(sql)
if results == None:
results = 0
return results
else:
return len(results)
sum()
def close_db(self):
self.db.close()
def close_cursor(self):
self.cursor.close()
def mycommit(self):
self.db.commit()
def myrollback(self):
self.db.rollback()
if __name__=='__main__':
db = DbOperations(env_value=False)
sql= "select id from voyager.template_type where name='类型1'"
re= db.execute_sql(sql)
print int(re[0][0])
| UTF-8 | Python | false | false | 2,982 | py | 281 | db_info.py | 159 | 0.415231 | 0.386285 | 0 | 97 | 27.917526 | 69 |
NVIDIA/TensorRT | 4,844,723,155,080 | b8db3334704a45a20a2c379d359a70206cfe5d6a | a02ccb5dff094fad8bcd691dda234d50ff768299 | /tools/tensorflow-quantization/tests/network_pool.py | f64e67302deecfb7c9b5190807ebdfd31b9ec7d3 | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"ISC",
"BSD-2-Clause"
]
| permissive | https://github.com/NVIDIA/TensorRT | 5520d5a6a5926a2b30dbdd2c5b2e4dfe6d1b429b | a167852705d74bcc619d8fad0af4b9e4d84472fc | refs/heads/release/8.6 | 2023-07-29T05:39:45.688091 | 2023-06-09T22:29:09 | 2023-06-09T23:04:18 | 184,657,328 | 8,026 | 2,096 | Apache-2.0 | false | 2023-09-13T17:30:16 | 2019-05-02T22:02:08 | 2023-09-13T12:47:05 | 2023-09-13T17:30:15 | 103,008 | 7,792 | 1,843 | 258 | C++ | false | false | #
# SPDX-FileCopyrightText: Copyright (c) 1993-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# 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.
#
"""
This module contains tiny networks used for testing across different modules.
They are named after famous Hobbits for obvious reasons.
"""
import tensorflow as tf
##################################################
###### Tiny, VGG like network ####################
##################################################
def bilbo_28_28():
"""
Network with VGG like architecture.
"""
input_img = tf.keras.layers.Input(shape=(28, 28), name="nn_input")
x = tf.keras.layers.Reshape(target_shape=(28, 28, 1), name="reshape_0")(input_img)
x = tf.keras.layers.Conv2D(filters=516, kernel_size=(3, 3), name="conv_0")(x)
x = tf.keras.layers.ReLU(name="relu_0")(x)
x = tf.keras.layers.Conv2D(filters=252, kernel_size=(3, 3), name="conv_1")(x)
x = tf.keras.layers.ReLU(name="relu_1")(x)
x = tf.keras.layers.Conv2D(filters=126, kernel_size=(3, 3), name="conv_2")(x)
x = tf.keras.layers.ReLU(name="relu_2")(x)
x = tf.keras.layers.Conv2D(filters=64, kernel_size=(3, 3), name="conv_3")(x)
x = tf.keras.layers.ReLU(name="relu_3")(x)
x = tf.keras.layers.Conv2D(filters=32, kernel_size=(3, 3), name="conv_4")(x)
x = tf.keras.layers.ReLU(name="relu_4")(x)
x = tf.keras.layers.Conv2D(filters=16, kernel_size=(3, 3), name="conv_5")(x)
x = tf.keras.layers.ReLU(name="relu_5")(x)
x = tf.keras.layers.Conv2D(filters=8, kernel_size=(3, 3), name="conv_6")(x)
x = tf.keras.layers.ReLU(name="relu_6")(x)
x = tf.keras.layers.MaxPooling2D(pool_size=(2, 2), name="max_pool_0")(x)
x = tf.keras.layers.Flatten(name="flatten_0")(x)
x = tf.keras.layers.Dense(100, name="dense_0")(x)
x = tf.keras.layers.ReLU(name="relu_7")(x)
x = tf.keras.layers.Dense(10, name="dense_1")(x)
return tf.keras.Model(input_img, x, name="Bilbo")
#####################################################
###### Tiny, ResNet like network ####################
#####################################################
def identity_block_plain(input_tensor):
"""
Identity block with no shortcut convolution
"""
y = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3), padding="same")(
input_tensor
)
y = tf.keras.layers.ReLU()(y)
y = tf.keras.layers.Conv2D(filters=24, kernel_size=(3, 3), padding="same")(y)
out = tf.keras.layers.Add()([y, input_tensor])
out = tf.keras.layers.ReLU()(out)
return out
def identity_block_short_conv_plain(input_tensor):
"""
Identity block with shortcut convolution
"""
y = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3), padding="same")(
input_tensor
)
y = tf.keras.layers.ReLU()(y)
y = tf.keras.layers.Conv2D(
filters=24, kernel_size=(3, 3), strides=(2, 2), padding="same"
)(y)
ds_input = tf.keras.layers.Conv2D(
filters=24, kernel_size=(3, 3), strides=(2, 2), padding="same"
)(input_tensor)
out = tf.keras.layers.Add()([y, ds_input])
out = tf.keras.layers.ReLU()(out)
return out
def frodo_32_32():
"""
Dummy network with resnet like architecture.
"""
input_img = tf.keras.layers.Input(shape=(32, 32, 3))
x = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3))(input_img)
x = tf.keras.layers.ReLU()(x)
x = tf.keras.layers.Conv2D(filters=24, kernel_size=(3, 3))(x)
x = tf.keras.layers.ReLU()(x)
x = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(x)
x = identity_block_plain(x)
x = identity_block_short_conv_plain(x)
x = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(x)
x = tf.keras.layers.Flatten()(x)
x = tf.keras.layers.Dense(100)(x)
x = tf.keras.layers.ReLU()(x)
x = tf.keras.layers.Dense(10)(x)
return tf.keras.Model(input_img, x, name="Frodo")
def sam_32_32():
"""
Dummy network with resnet like architecture.
"""
input_img = tf.keras.layers.Input(shape=(32, 32, 3))
x = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3))(input_img)
x = tf.keras.layers.ReLU()(x)
x = tf.keras.layers.Conv2D(filters=24, kernel_size=(3, 3))(x)
x = tf.keras.layers.ReLU()(x)
x = identity_block_plain(x)
x = identity_block_plain(x)
x = identity_block_short_conv_plain(x)
x = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(x)
x = tf.keras.layers.Flatten()(x)
x = tf.keras.layers.Dense(100)(x)
x = tf.keras.layers.ReLU()(x)
x = tf.keras.layers.Dense(10)(x)
return tf.keras.Model(input_img, x, name="Sam")
##############################################
###### Popular network blocks ################
##############################################
def relu_bn(input):
"""
Block with BN+ReLU
"""
bn = tf.keras.layers.BatchNormalization()(input)
relu = tf.keras.layers.ReLU()(bn)
return relu
def bn(input):
return tf.keras.layers.BatchNormalization()(input)
def relu(input):
return tf.keras.layers.ReLU()(input)
def inception_block(input_tensor):
"""
Inception block from GoogleNet
"""
b1x1 = tf.keras.layers.Conv2D(filters=12, kernel_size=(1, 1), padding="same")(
input_tensor
)
b1x1 = relu_bn(b1x1)
b5x5 = tf.keras.layers.Conv2D(filters=12, kernel_size=(1, 1), padding="same")(
input_tensor
)
b5x5 = tf.keras.layers.Conv2D(filters=24, kernel_size=(5, 5), padding="same")(b5x5)
b5x5 = relu_bn(b5x5)
b3x3 = tf.keras.layers.Conv2D(filters=12, kernel_size=(1, 1), padding="same")(
input_tensor
)
b3x3 = tf.keras.layers.Conv2D(filters=20, kernel_size=(3, 3), padding="same")(b3x3)
b3x3 = tf.keras.layers.Conv2D(filters=24, kernel_size=(3, 3), padding="same")(b3x3)
b3x3 = relu_bn(b3x3)
out = tf.keras.layers.Concatenate()([b1x1, b5x5])
return out
def identity_block_bn(input_tensor):
"""
Identity block with no shortcut convolution
"""
y = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3), padding="same")(
input_tensor
)
y = relu_bn(y)
y = tf.keras.layers.Conv2D(filters=24, kernel_size=(3, 3), padding="same")(y)
y = bn(y)
out = tf.keras.layers.Add()([y, input_tensor])
out = relu(out)
return out
def identity_block_short_conv_bn(input_tensor):
"""
Identity block with shortcut convolution
"""
y = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3), padding="same")(
input_tensor
)
y = relu_bn(y)
y = tf.keras.layers.Conv2D(
filters=24, kernel_size=(3, 3), strides=(2, 2), padding="same"
)(y)
y = bn(y)
ds_input = tf.keras.layers.Conv2D(
filters=24, kernel_size=(3, 3), strides=(2, 2), padding="same"
)(input_tensor)
ds_input = bn(ds_input)
out = tf.keras.layers.Add()([y, ds_input])
out = relu(out)
return out
def otho_28_28():
input_img = tf.keras.layers.Input(shape=(28, 28), name="input_0")
r = tf.keras.layers.Reshape(target_shape=(28, 28, 1), name="reshape_0")(input_img)
x = tf.keras.layers.Conv2D(filters=2, kernel_size=(3, 3), name="conv_0")(r)
x = tf.keras.layers.ReLU(name="relu_0")(x)
x = tf.keras.layers.Conv2D(filters=2, kernel_size=(3, 3), name="conv_1")(x)
x = tf.keras.layers.ReLU(name="relu_1")(x)
x = tf.keras.layers.Flatten(name="flatten_0")(x)
return tf.keras.Model(input_img, x, name="Otho")
def lotho_28_28():
input_img = tf.keras.layers.Input(shape=(28, 28), name="input_0")
r = tf.keras.layers.Reshape(target_shape=(28, 28, 1), name="reshape_0")(input_img)
x = tf.keras.layers.DepthwiseConv2D(kernel_size=(3, 3), name="dconv_0")(r)
x = tf.keras.layers.ReLU(name="relu_0")(x)
x = tf.keras.layers.DepthwiseConv2D(kernel_size=(3, 3), name="dconv_1")(x)
x = tf.keras.layers.ReLU(name="relu_1")(x)
x = tf.keras.layers.Flatten(name="flatten_0")(x)
return tf.keras.Model(input_img, x, name="Lotho")
def lobelia_28_28():
input_img = tf.keras.layers.Input(shape=(28, 28), name="input_0")
r = tf.keras.layers.Reshape(target_shape=(28, 28, 1), name="reshape_0")(input_img)
x = tf.keras.layers.Flatten(name="flatten_0")(r)
x = tf.keras.layers.Dense(100, name="dense_0")(x)
x = tf.keras.layers.ReLU(name="relu_0")(x)
x = tf.keras.layers.Dense(10, name="dense_1")(x)
return tf.keras.Model(input_img, x, name="Lobelia")
def merry_28_28():
input_img = tf.keras.layers.Input(shape=(28, 28))
x = tf.keras.layers.Reshape(target_shape=(28, 28, 1))(input_img)
x = tf.keras.layers.Conv2D(filters=8, kernel_size=(3, 3))(x)
x = relu_bn(x)
x = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3))(x)
x = relu_bn(x)
x = inception_block(x)
x = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(x)
x = tf.keras.layers.Flatten()(x)
x = tf.keras.layers.Dense(100)(x)
x = tf.keras.layers.ReLU()(x)
x = tf.keras.layers.Dense(10)(x)
return tf.keras.Model(input_img, x, name="Merry")
def pippin_28_28():
input_img = tf.keras.layers.Input(shape=(28, 28))
x = tf.keras.layers.Reshape(target_shape=(28, 28, 1))(input_img)
x = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3))(x)
x = relu_bn(x)
x = tf.keras.layers.Conv2D(filters=24, kernel_size=(3, 3))(x)
x = relu_bn(x)
x = identity_block_bn(x)
x = identity_block_short_conv_bn(x)
x = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(x)
x = tf.keras.layers.Flatten()(x)
x = tf.keras.layers.Dense(100)(x)
x = tf.keras.layers.ReLU()(x)
x = tf.keras.layers.Dense(10)(x)
return tf.keras.Model(input_img, x, name="Pippin")
| UTF-8 | Python | false | false | 10,169 | py | 1,278 | network_pool.py | 796 | 0.608319 | 0.568001 | 0 | 277 | 35.711191 | 103 |
ordinary-developer/education | 2,834,678,441,888 | 8e9dc66ca3ff24518d65ebd38bb0324f24de1d34 | 7c63a96fad4257f4959ffeba0868059fc96566fb | /py/m_lutz-programming_python-4_ed/code/ch_07/21-customizing_widgets_with_classes/main.pyw | 20f88df1541beac22c37a64ff6dca0f22a7f7837 | [
"MIT"
]
| permissive | https://github.com/ordinary-developer/education | b426148f5690f48e0ed4853adfc3740bd038b72c | 526e5cf86f90eab68063bb7c75744226f2c54b8d | refs/heads/master | 2023-08-31T14:42:37.237690 | 2023-08-30T18:15:18 | 2023-08-30T18:15:18 | 91,232,306 | 8 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from tkinter import *
class HelloButton(Button):
def __init__(self, parent = None, **config):
Button.__init__(self, parent, **config)
self.pack()
self.config(command = self.callback)
def callback(self):
print('Goodbye world ...')
self.quit()
if __name__ == '__main__':
HelloButton(text = 'Hello subclass world').mainloop()
| UTF-8 | Python | false | false | 381 | pyw | 2,736 | main.pyw | 2,082 | 0.577428 | 0.577428 | 0 | 17 | 21.411765 | 57 |
terrence688538/Web-crawler-and-automation | 2,697,239,481,185 | 4c8e9c99df8dab98b2d6c74c37c5a003393771c3 | 28c97a8d7e3de11495b517758cd6086ee5424383 | /config.py | fd842e792fd1dfe3ca4da5a893d94e0c3d7f43e6 | []
| no_license | https://github.com/terrence688538/Web-crawler-and-automation | 96c7f0c5b1f94d1b3f8eed5a9ec38fae8ecee481 | 1ccc42e76fbb6acc76ac3142d5c38c532a81c7f2 | refs/heads/master | 2022-12-14T08:06:41.023061 | 2020-09-07T12:36:52 | 2020-09-07T12:36:52 | 293,475,134 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | MONGO_URL ='localhost'
MONGO_DB='taobao'
MONGO_TABLE='product'
| UTF-8 | Python | false | false | 68 | py | 25 | config.py | 24 | 0.691176 | 0.691176 | 0 | 3 | 20 | 22 |
Jai-Chowdhry/IceChrono | 420,906,813,079 | b79b559c503953840be78ef2011e00ed418f82bc | a78a81a539a22668ab6560ab6af3093b035170d4 | /AICC2012-VLR/EDC/parameters.py | 8da2eac4ff9a222f010b32c98bd35e1d6d79dbee | [
"Apache-2.0"
]
| permissive | https://github.com/Jai-Chowdhry/IceChrono | 209359a7af2ed269b928e9baad01b56d4cb2cb15 | d4ecc2c13e979a094179c811db907f4fb6aa600d | refs/heads/master | 2021-01-20T07:31:40.427722 | 2019-07-31T14:45:56 | 2019-07-31T14:45:56 | 90,009,353 | 0 | 0 | null | true | 2017-05-02T08:37:03 | 2017-05-02T08:27:09 | 2017-05-02T08:27:11 | 2017-05-02T08:31:23 | 25,989 | 0 | 0 | 1 | Python | null | null | #Parameters specific to the EDC ice core
self.udepth_top=0. #unthinned depth at the top of the core
self.age_top=-55. #age at the top of the core
self.depth=np.arange(0., 3259.3+0.01, 0.55) #Define the depth grid for the age calculation
self.corr_a_age=np.arange(self.age_top, 1000000+self.age_top+0.01, self.age_step) #Age grid for the accu correction function
self.corr_LID_age=np.arange(self.age_top, 1000000+self.age_top+0.01, self.age_step) #Age grid for the LID correction function
self.corr_tau_depth=np.arange(self.depth[0], self.depth[-1]+0.01, (self.depth[-1]-self.depth[0])/(self.corr_tau_nodes-1)) #Depth grid for the thinning correction function
self.accu_prior_rep='staircase' #linear or staircase. Define whether the prior accu representation is linear or staircase in-between the data points.
#The following parameters defines the covariance matrices as in AICC2012 (Bazin et al., 2013 and Veres et al., 2013).
#self.thickness=3273. #Real thickness
#self.cT2=0.000030/0.55
#self.sigmabA=0.7
#self.cA1=0.
#self.sigmabL=0.7
| UTF-8 | Python | false | false | 1,122 | py | 39 | parameters.py | 7 | 0.703209 | 0.635472 | 0 | 16 | 69.125 | 172 |
ilyaskutin/qaTasks1 | 15,607,911,189,722 | 05495e177878f9044412719d6393ed9a57dc2e3a | e1002716a6316d40c3542f0cc615660e6e4c0fd5 | /yandex_autotests/conftest.py | 6f3f46f27886cc926933ad22a27e0abb77367a43 | []
| no_license | https://github.com/ilyaskutin/qaTasks1 | 929e4c842c068d34eaf613e7569e427d01f4f3dc | 775662d8195da00cef6224cefcd299402d08917a | refs/heads/master | 2020-03-19T01:48:14.325997 | 2018-06-04T08:56:32 | 2018-06-04T08:56:32 | 135,311,448 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import pytest
import os
RESOURCE_DIR = os.path.join(os.getcwd(), "yandex_autotests/.resources")
def pytest_namespace():
return {
#Константы
'start_timeout': 10, # таймаут для браузера, сколько ждать на старте
'between_page_timeout': 5, # таймаут при переходе между страницами
'url': 'http://www.yandex.ru', # url сайта которые проверям
'username': 'arrival18', # логин тестового пользователя
'password': 'QWEqwe123', # пароль тестового пользователя
'search_accuracy': 10, # точность, с которой будет производится поиск
'check_url': 'https://www.yandex.ru/', # url сайта, который ожидаем после загрузки
'check_title': 'Яндекс', # заголовок сайта, который ожидаем после
'debug_mode': False, # debug
'repeat_search': True, # Если не найдет в арене, повторит по всему экрану
'path_to_res': RESOURCE_DIR,
# Ресурсы
'logo': os.path.join(RESOURCE_DIR, 'logo.png'),
'mail': os.path.join(RESOURCE_DIR, 'mail.png'),
'logo_auth': os.path.join(RESOURCE_DIR, 'logo_auth.png'),
'login_button': os.path.join(RESOURCE_DIR, 'login.png'),
'user_login': os.path.join(RESOURCE_DIR, 'user_login.png'),
# Арены
"main_logo_area": (
[0, 0, 0],
[1, 0, 0],
[0, 0, 0]
),
"mail_area": (
[0, 0, 1],
[0, 0, 0],
[0, 0, 0]
),
"auth_area": (
[0, 1, 0],
[0, 1, 0],
[0, 0, 0]
),
"user_login_area": (
[0, 0, 1],
[0, 0, 0],
[0, 0, 0]
)
} | UTF-8 | Python | false | false | 2,152 | py | 10 | conftest.py | 6 | 0.472539 | 0.447526 | 0 | 54 | 33.074074 | 100 |
631068264/learn-sktf | 13,743,895,351,472 | 7220ecd73842de9a7d482d8829b49c4a42e44d0f | 411d9c64d2f2142f225582f2b4af1280310426f6 | /sk/dr.py | 74a6533af11f3936fe4c56d12faf7604d1b44699 | []
| no_license | https://github.com/631068264/learn-sktf | 5a0dfafb898acda83a80dc303b6d6d56e30e7cab | 4ba36c89003fca6797025319e81fd9863fbd05b1 | refs/heads/master | 2022-10-15T03:29:38.709720 | 2022-09-24T12:56:41 | 2022-09-24T12:56:41 | 133,602,172 | 0 | 0 | null | false | 2022-09-24T12:57:23 | 2018-05-16T02:57:01 | 2022-09-24T12:56:46 | 2022-09-24T12:57:22 | 47,933 | 0 | 0 | 19 | Python | false | false | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@author = 'wyx'
@time = 2018/5/16 15:21
@annotation = ''
"""
import numpy as np
from sklearn.datasets import make_swiss_roll
np.random.seed(4)
m = 60
w1, w2 = 0.1, 0.3
noise = 0.1
angles = np.random.rand(m) * 3 * np.pi / 2 - 0.5
X = np.empty((m, 3))
X[:, 0] = np.cos(angles) + np.sin(angles) / 2 + noise * np.random.randn(m) / 2
X[:, 1] = np.sin(angles) * 0.7 + noise * np.random.randn(m) / 2
X[:, 2] = X[:, 0] * w1 + X[:, 1] * w2 + noise * np.random.randn(m)
from sklearn.decomposition import PCA
if False:
pca = PCA(n_components=2)
X2D = pca.fit_transform(X)
# 特征空间中的主轴
print(pca.components_)
# 轴的差异比率
print(pca.explained_variance_ratio_)
print(1 - pca.explained_variance_.sum())
# 解压缩 有损
pca.inverse_transform(X2D)
"""
find good Dimensions
"""
if False:
pca = PCA()
pca.fit(X)
cumsum = np.cumsum(pca.explained_variance_ratio_)
d = np.argmax(cumsum >= 0.95) + 1
print(d)
pca = PCA(n_components=0.95)
X_reduced = pca.fit_transform(X)
print(pca.n_components_)
"""
增量pca 节省内存 慢
"""
if False:
from sklearn.decomposition import IncrementalPCA
n_batches = 5
inc_pca = IncrementalPCA(n_components=2)
for X_batch in np.array_split(X, n_batches):
inc_pca.partial_fit(X_batch)
X_reduced = inc_pca.transform(X)
filename = 'x.data'
X_mm = np.memmap(filename, dtype='float32', mode='write', shape=X.shape)
X_mm[:] = X
del X_mm
X_mm = np.memmap(filename, dtype="float32", mode="readonly", shape=X.shape)
batch_size = m // n_batches
inc_pca = IncrementalPCA(n_components=2, batch_size=batch_size)
inc_pca.fit(X_mm)
X_reduced2 = inc_pca.transform(X)
if False:
X, t = make_swiss_roll(n_samples=1000, noise=0.2, random_state=42)
y = t > 6.9
from sklearn.decomposition import KernelPCA
rbf_pca = KernelPCA(n_components=2, kernel="rbf", gamma=0.04)
X_reduced = rbf_pca.fit_transform(X)
from sklearn.model_selection import GridSearchCV
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline import Pipeline
clf = Pipeline([
("kpca", KernelPCA(n_components=2)),
("log_reg", LogisticRegression())
])
param_grid = [{
"kpca__gamma": np.linspace(0.03, 0.05, 10),
"kpca__kernel": ["rbf", "sigmoid"]
}]
grid_search = GridSearchCV(clf, param_grid, cv=3)
grid_search.fit(X, y)
print(grid_search.best_estimator_)
print(grid_search.best_params_)
if False:
from sklearn.manifold import LocallyLinearEmbedding
from matplotlib import pyplot as plt
X, t = make_swiss_roll(n_samples=1000, noise=0.2, random_state=41)
lle = LocallyLinearEmbedding(n_components=2, n_neighbors=10, random_state=42)
X_reduced = lle.fit_transform(X)
plt.title("Unrolled swiss roll using LLE", fontsize=14)
plt.scatter(X_reduced[:, 0], X_reduced[:, 1], c=t, cmap=plt.cm.hot)
plt.xlabel("$z_1$", fontsize=18)
plt.ylabel("$z_2$", fontsize=18)
plt.axis([-0.065, 0.055, -0.1, 0.12])
plt.grid(True)
plt.show()
| UTF-8 | Python | false | false | 3,160 | py | 39 | dr.py | 35 | 0.629344 | 0.591055 | 0 | 110 | 27.254545 | 81 |
markman123/CourseCake | 13,022,340,849,896 | c9f292fb003ebc6562b6c4033ce53fda7847601a | 96ddf1d2e299ee4da92ed21c915853856064b75a | /coursecake/fastapi_app/api_v1/admin/routes.py | d7db9d2b0bf88063acecc67a0d0629963ac939a6 | [
"MIT"
]
| permissive | https://github.com/markman123/CourseCake | 586927c8ea4e894b6dff2e7a34dddb631165717a | 4ef40cb2bd5f42177c8596fd18ead66b4a9d2379 | refs/heads/master | 2022-12-24T21:44:39.508228 | 2020-10-06T22:13:15 | 2020-10-06T22:13:15 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # contains all routes for the courses endpoint
from typing import List, Optional
from fastapi import (
Depends,
APIRouter,
BackgroundTasks,
status,
HTTPException,
Query,
Request,
)
from sqlalchemy.orm import Session
from ....database import crud, models, sql, uploads
from ...limiter import limiter
from .. import schemas
from . import utils
router = APIRouter()
# dependency
def get_db():
db = sql.SessionLocal()
try:
yield db
finally:
db.close()
@router.post("/update/all")
@limiter.limit("2/minute")
async def update_all(
request: Request,
token: str,
background_tasks: BackgroundTasks,
db: Session = Depends(get_db),
term_id: str = Query("2020-fall"),
testing: bool = Query(False),
):
if not utils.verifyAdminToken(token):
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED, detail="Incorrect token"
)
background_tasks.add_task(uploads.update_all, db, term_id, testing)
return {
"message": "initiated updates for all database information via scrapers. this will take a few minutes."
}
| UTF-8 | Python | false | false | 1,141 | py | 53 | routes.py | 41 | 0.665206 | 0.658195 | 0 | 51 | 21.372549 | 111 |
open222333/PythonCode | 6,047,313,983,368 | 241ee35358a1188e5256bf76bae7de9b6f4ffcc5 | 3ff6b318db4d0fdda60c763f475b7dafa4f0c9ba | /Kingreturn_Ex/ch7/ch7-41.py | 1fba259b3358f7e90ec6e62141fc208913a94eab | []
| no_license | https://github.com/open222333/PythonCode | 493124dcbbb4d4ab18be3090bc35224e20959780 | b9baffd2598b2b1e131fdd6bb38536c685b633e5 | refs/heads/master | 2023-08-28T14:51:52.004948 | 2023-06-20T15:45:05 | 2023-06-20T15:45:05 | 356,302,028 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # pass 與無限迴圈
schools = ['明志科大', '台灣科大', '台北科大']
for school in schools:
pass
| UTF-8 | Python | false | false | 114 | py | 1,002 | ch7-41.py | 926 | 0.625 | 0.625 | 0 | 4 | 19 | 34 |
cowhi/HFO | 10,436,770,574,949 | f6dcf09af016fa9ae9d5bc9af5ef3e776893eb99 | d3d5539549f43fc7c228fd2a264ab137a808096c | /experiments/agents/sarsa.py | 77ddb243020a40a0ad733fce8ae7d65309867703 | [
"MIT"
]
| permissive | https://github.com/cowhi/HFO | d8c24b77440beb0c8d878f068b2a78e127ab5102 | 119d0233424bad64d92ff835dd335775fe66dd77 | refs/heads/master | 2021-01-22T01:42:32.179275 | 2016-11-13T13:38:40 | 2016-11-13T13:38:40 | 65,380,530 | 0 | 1 | null | true | 2016-08-10T12:26:07 | 2016-08-10T12:26:07 | 2016-08-07T21:55:15 | 2016-07-25T21:24:34 | 2,692 | 0 | 0 | 0 | null | null | null | import sys
import random
from .agent import Agent
from cmac import CMAC
class SARSA(Agent):
def __str__(self):
""" Overwrites the object.__str__ method.
Returns:
string (str): Important parameters of the object.
"""
return "Agent: " + str(self.unum) + ", " + \
"Type: " + str(self.name) + ", " + \
"Training steps: " + str(self.training_steps_total) + ", " + \
"Q-Table size: " + str(len(self.qTable))
def __init__(self, epsilon=0.1, alpha=0.1, gamma=0.9, decayRate=0.9, seed=12345,
cmac_level=20, cmac_quantization=0.3, cmac_beta=0.1, port=12345,serverPath = "/home/leno/HFO/bin/"):
super(SARSA, self).__init__(seed, port,serverPath=serverPath)
self.name = "SARSA"
self.qTable = {}
self.stateActionTrace = {}
self.epsilon = epsilon
self.alpha = alpha
self.gamma = gamma
self.decayRate = decayRate
self.cmac = CMAC(cmac_level,cmac_quantization,cmac_beta)
#print('***** %s: Agent uses CMAC(%s,%s,%s)' % (str(self.unum),str(cmac_level), str(cmac_quantization), str(cmac_beta)))
def quantize_features(self, features):
""" CMAC utilities for all agent """
quantVar = self.cmac.quantize(features)
data = []
#len(quantVar[0]) is the number of variables
for i in range(0,len(quantVar[0])):
#Transforms n tuples into a single array
for var in quantVar:
#copy each tuple value to the output
data.append(var[i])
#returns the output as a tuple
return tuple(data)
def advise_action(self,uNum,state):
"""Verifies if the agent can advice a friend, and return the action if possible"""
return None #No advising
def get_Q(self, state, action):
return self.qTable.get((state, action), 0.0)
def observe_reward(self,state,action,reward,statePrime):
""" After executing an action, the agent is informed about the state-reward-state tuple """
pass
'''
def observe_reward(self,state,action,reward,statePrime):
""" After executing an action, the agent is informed about the state-action-reward-state tuple """
if self.exploring:
#Selects the action for the next state without exploration
lastState = self.lastState
self.exploring = False
nextAction = self.select_action(statePrime)
#Hereafter the self.lastState refers to statePrime
#Executes Q-update
self.learn(lastState,action,reward,self.lastState,nextAction)
#turns on the exploration again
'''
def select_action(self, stateFeatures, state, noAdvice=False):
"""Executes the epsilon-greedy exploration strategy"""
#stores last CMAC result
#self.lastState = state
# select applicable actions
if stateFeatures[5] == 1: # State[5] is 1 when the player can kick the ball
actions = [self.SHOOT, self.DRIBBLE, self.PASSfar, self.PASSnear]
else:
return self.MOVE
# epsilon greedy action selection
if self.exploring and random.random() < self.epsilon and not noAdvice:
actionsRandom = [ self.SHOOT,self.DRIBBLE, self.DRIBBLE, self.SHOOT, self.PASSfar, self.PASSnear]
return random.choice(actionsRandom)
else:
cmacState = self.quantize_features(state)
qValues = [self.get_Q(cmacState, action) for action in actions]
maxQ = max(qValues)
count = qValues.count(maxQ)
if count > 1: #and self.exploring:
best = [i for i in range(len(actions)) if qValues[i] == maxQ]
if not self.exploring:
return actions[best[0]]
return actions[random.choice(best)]
else:
return actions[qValues.index(maxQ)]
def learn(self, state1, action1, reward, state2, action2):
qnext = self.get_Q(state2, action2)
self.learn_Q(state1, action1, reward, reward + self.gamma * qnext)
def learn_Q(self, state, action, reward, value):
oldv = self.qTable.get((state, action), None)
if oldv is None:
self.qTable[(state, action)] = reward
else:
self.qTable[(state, action)] = oldv + self.alpha * (value - oldv)
def step(self, state, action):
""" Perform a complete training step """
# perform action and observe reward & statePrime
self.execute_action(action)
status = self.hfo.step()
stateFeatures = self.hfo.getState()
statePrime = self.get_transformed_features(stateFeatures)
stateQuantized = self.quantize_features(state)
statePrimeQuantized = self.quantize_features(statePrime)
reward = self.get_reward(status)
# select actionPrime
if self.exploring:
actionPrime = self.select_action(stateFeatures, statePrime,False)
else:
actionPrime = self.select_action(stateFeatures, statePrime,True)
if self.exploring:
# calculate TDError
TDError = reward + self.gamma * self.get_Q(statePrimeQuantized, actionPrime) - self.get_Q(stateQuantized, action)
# update trace value
self.stateActionTrace[(stateQuantized, action)] = self.stateActionTrace.get((stateQuantized, action), 0) + 1
for stateAction in self.stateActionTrace:
# update update ALL Q values and eligibility trace values
self.qTable[stateAction] = self.qTable.get(stateAction, 0) + TDError * self.alpha * self.stateActionTrace.get(stateAction, 0)
# update eligibility trace Function for state and action
self.stateActionTrace[stateAction] = self.gamma * self.decayRate * self.stateActionTrace.get(stateAction, 0)
#self.learn(stateQuantized, action, reward,
# statePrimeQuantized, actionPrime)
self.training_steps_total += 1
if status != self.IN_GAME:
self.stateActionTrace = {}
return status, statePrime, actionPrime
def setupAdvising(self,agentIndex,allAgents):
""" This method is called in preparation for advising """
pass
| UTF-8 | Python | false | false | 6,374 | py | 58 | sarsa.py | 49 | 0.609978 | 0.602291 | 0 | 143 | 43.573427 | 141 |
Zengyi-Qin/LMSC | 4,552,665,349,722 | 5ab4677a7aff913bf7b38d636be7662a9da4f9bb | 211962cfdc43dd0d232cf1aff4f1b0733aea0663 | /render/ol_dynamics.py | f87fb8085bfa4b76a389998f59517a847b52eeba | []
| no_license | https://github.com/Zengyi-Qin/LMSC | 332abfd276ec29862312a9920cd1f3b97512b8cf | 37ae3055556049f2f7e4d4a82b27799df3965f3f | refs/heads/main | 2023-05-06T13:43:54.974794 | 2022-02-05T13:44:10 | 2022-02-05T13:44:10 | 368,742,015 | 4 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import numpy as np
# quadrotor physical constants
g = 9.81
# non-linear dynamics
def f(x, u):
x, y, z, vx, vy, vz, theta_x, theta_y = x.reshape(-1).tolist()
az, omega_x, omega_y = u.reshape(-1).tolist()
dot_x = np.array([
vx,
vy,
vz,
np.tan(theta_x),
np.tan(theta_y),
az,
omega_x,
omega_y])
return dot_x
def f_batch_azlast(x, u):
x, y, z, vx, vy, vz, theta_x, theta_y = [x[:,i] for i in range(x.shape[1])]
omega_x, omega_y, az = [u[:,i] for i in range(u.shape[1])]
dot_x = np.array([
vx,
vy,
vz,
np.tan(theta_x),
np.tan(theta_y),
az,
omega_x,
omega_y]).T
return dot_x
# linearization
# The state variables are x, y, z, vx, vy, vz, theta_x, theta_y
A = np.zeros([8,8])
A[0, 3] = 1.
A[1, 4] = 1.
A[2, 5] = 1.
A[3, 6] = 1.
A[4, 7] = 1.
B = np.zeros([8, 3])
B[5, 0] = 1.
B[6, 1] = 1.
B[7, 2] = 1.
| UTF-8 | Python | false | false | 909 | py | 43 | ol_dynamics.py | 34 | 0.50385 | 0.465347 | 0 | 46 | 18.76087 | 79 |
Sanyam-malik/Python-Auribasis-v2 | 8,830,452,795,231 | f4b6ec2b9fc7e060c353bd22b802487a223562cc | ffec74b0214621cb570fa1fdfa036bc6f1b3c78b | /Session6C.py | b4bc6dd3ec84bdf177de379c7b8d38f457e9987a | []
| no_license | https://github.com/Sanyam-malik/Python-Auribasis-v2 | 3d5d523521eebeab59ac2dd912b08b3b890dfcfd | 268d632d0e7b4ac14e058b6a92b7c17933812f48 | refs/heads/master | 2022-04-10T03:56:47.192364 | 2020-02-26T20:45:02 | 2020-02-26T20:45:02 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | class Employee:
def __init__(self, name, designation, salary, projects):
self.name = name
self.designation = designation
self.salary = salary
self.projects = projects # HAS-A Relation with 1 to Many
def showEmployee(self):
print("{} works as {} and withdraws {} INR".format(self.name,self.designation,self.salary))
#Iterate in the projects
for p in self.projects:
p.showProject()
class Project:
def __init__(self, title, technology, duration):
self.title = title
self.technology = technology
self.duration = duration
def showProject(self):
print("{} is developed in {} technology in a timeline of {} months".format(self.title,self.technology,self.duration))
# Collection : List or Projects
projectList = []
projectList.append(Project("Elzo","Firebase",2))
projectList.append(Project("YankTow","AWS",3))
emp = Employee("John Watson", "Software Engr", 30000, projectList)
emp.showEmployee() | UTF-8 | Python | false | false | 1,013 | py | 66 | Session6C.py | 64 | 0.657453 | 0.649556 | 0 | 33 | 29.727273 | 125 |
maria-noaptes/retele | 4,071,628,999,215 | 6491dfe5f7a398bb8dfe9b6cdba7078b03abefc0 | 3c44a78ad286302c484082c8cb181532da7be533 | /packets.py | 2b0597c00f0bed67f55aa996f1f4791dc134a475 | []
| no_license | https://github.com/maria-noaptes/retele | 84f1d5971a140e0424e1f236fe375eaf2531d2d0 | 2c14eafa57ada844a607beba5f510cfb8f7c2af5 | refs/heads/master | 2020-08-12T06:32:24.478162 | 2019-11-03T16:35:06 | 2019-11-03T16:35:06 | 214,707,114 | 0 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | class CONNECT:
def __init__(self,id,username,parola):
self.id=id
self.username=username
self.parola=parola
class CONNACK:
def __init__(self,flag_confirmare):
self.flag_confirmare=flag_confirmare
class SUBSCRIBE:
def __init__(self,packetID,subscriptii):
self.subscriptii=subscriptii
self.packetID=packetID
class PINGREQ:
pass
class SUBPACK:
def __init__(self,packetID,returnCode):
self.packetID=packetID
self.returnCode=returnCode
class PUBLISH:
def __init__(self,topic,payload):
self.topic=topic
self.payload=payload | UTF-8 | Python | false | false | 620 | py | 4 | packets.py | 2 | 0.66129 | 0.66129 | 0 | 22 | 27.227273 | 44 |
himanshu272/Digital_Fortress_Backend | 17,325,898,104,932 | 72853b58743ad210f662e911c0ba0de1bd8bdccc | 6fed9b70ab0f13889036c4c5e8336c6ae91bbd0e | /Quiz/migrations/0005_player_first_name.py | b41ec599d99d72bf316e6bf3fcfb70648fbfb979 | []
| no_license | https://github.com/himanshu272/Digital_Fortress_Backend | aaa9208e593d70f3b981936aefaba71a579a7714 | c8ed942f9ddcfa67bafbc32b80357e8f39e310c1 | refs/heads/master | 2020-08-04T21:46:49.416356 | 2020-01-24T14:19:50 | 2020-01-24T14:19:50 | 212,288,900 | 0 | 4 | null | null | null | null | null | null | null | null | null | null | null | null | null | # Generated by Django 2.2.4 on 2020-01-24 11:58
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('Quiz', '0004_duration'),
]
operations = [
migrations.AddField(
model_name='player',
name='first_name',
field=models.CharField(blank=True, max_length=200),
),
]
| UTF-8 | Python | false | false | 388 | py | 13 | 0005_player_first_name.py | 11 | 0.582474 | 0.525773 | 0 | 18 | 20.555556 | 63 |
SirLeonardoFerreira/Atividades-ifpi | 15,144,054,709,949 | a9f2671bf21bad8d1bc1324a4b5cd027b99bfa93 | fb00b570251ba52df467e4cc030a30e778f8a970 | /Atividade 02 - semana 04/questão5_semana4_atividade02.py | 7c26d99823df070af681aa1431f42e93357c3492 | []
| no_license | https://github.com/SirLeonardoFerreira/Atividades-ifpi | 7379f9df4640fd1ee3623d80e4341f495e855895 | e366ee3f801dc9a1876c7399a2eefd37a03d0a55 | refs/heads/master | 2023-01-05T04:03:30.774277 | 2020-11-02T00:56:10 | 2020-11-02T00:56:10 | 287,967,575 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | def ordem(um, dois, tres):
if um < dois < tres:
return um, dois, tres
elif um < tres < dois:
return um, dois, tres
elif dois < um < tres:
return dois, um, tres
elif dois < tres < um:
return dois, tres, um
elif tres < um < dois:
return tres, um, dois
elif tres < dois < um:
return tres, dois, um
def main():
numero_um = int(input("Digite o primeiro número: "))
numero_dois = int(input("Digite o segundo número: "))
numero_tres = int(input("Digite o terceiro número: "))
um, dois, tres = ordem(numero_um, numero_dois, numero_tres)
print(f'{um}')
print(f'{dois}')
print(f'{tres}')
if __name__ == '__main__':
main()
| UTF-8 | Python | false | false | 722 | py | 130 | questão5_semana4_atividade02.py | 130 | 0.55911 | 0.55911 | 0 | 26 | 26.653846 | 63 |
skk2106/NLP_PRACTICE | 12,953,621,405,085 | b9e5fa986ac22109bdcde942b5096229865311f6 | 80f4445fa0d1eb07fe1cb976b858e2c78d0a666c | /TD-IDF.py | e4dd7aef156d6cea6303df20da5f2979a687654c | []
| no_license | https://github.com/skk2106/NLP_PRACTICE | 8f17200cbb30c3ab830f1fcfec3aede3ce85ab79 | 69fe484465310308a86d5f218d6f3c6d09f843f5 | refs/heads/master | 2023-05-08T04:59:59.881918 | 2021-05-14T07:05:34 | 2021-05-14T07:05:34 | 366,959,234 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Thu May 13 11:32:34 2021
@author: SOHAM KULKARNI
"""
# -*- coding: utf-8 -*-
"""
Created on Thu May 13 11:32:34 2021
@author: SOHAM KULKARNI
"""
import nltk
from nltk.corpus import stopwords
paragraph = """I have three visions for India. In 3000 years of our history people from all over the world have come and invaded us, captured our lands, conquered our minds.
From Alexander onwards the Greeks, the Turks, the Moguls, the Portuguese, the British, the French, the Dutch, all of them came and looted us, took over what was ours.
Yet we have not done this to any other nation. We have not conquered anyone. We have not grabbed their land, their culture and their history and tried to enforce our way of life on them.
Why? Because we respect the freedom of others. That is why my FIRST VISION is that of FREEDOM.
I believe that India got its first vision of this in 1857, when we started the war of Independence.
It is this freedom that we must protect and nurture and build on. If we are not free, no one will respect us.
We have 10 percent growth rate in most areas. Our poverty levels are falling. Our achievements are being globally recognised today.
Yet we lack the self-confidence to see ourselves as a developed nation, self-reliant and self-assured.
Isn’t this incorrect? MY SECOND VISION for India is DEVELOPMENT. For fifty years we have been a developing nation.
It is time we see ourselves as a developed nation. We are among top five nations in the world in terms of GDP."""
#Cleaning the text
import re
from nltk.stem import PorterStemmer
from nltk.stem import WordNetLemmatizer
ps = PorterStemmer()
wordnet = WordNetLemmatizer()
sentences = nltk.sent_tokenize(paragraph)
corpus = []
for i in range(len(sentences)):
review = re.sub('[^a-zA-Z]', ' ',sentences[i])
review = review.lower()
review = review.split()
review = [wordnet.lemmatize(word) for word in review if not word in set(stopwords.words('english'))]
review = ' '.join(review)
corpus.append(review)
#TFIDF
from sklearn.feature_extraction.text import TfidfVectorizer
cv = TfidfVectorizer()
X = cv.fit_transform(corpus).toarray()
| UTF-8 | Python | false | false | 2,299 | py | 6 | TD-IDF.py | 4 | 0.710057 | 0.694384 | 0 | 46 | 48.717391 | 198 |
Ahmedsebit/doKonect | 3,143,916,099,381 | 03b60084cf86eb73bb3ec903948c7a6f1d62bf4f | bf5202eb2bae5c2f40660e1226d8269f1058d199 | /project/doctor_referral/tests.py | 0a0f7639f9a79ea1f1acac87ecb84880897a95f5 | []
| no_license | https://github.com/Ahmedsebit/doKonect | e7562a3e13bb227243dfb477011a8d70aec24708 | adfc3b5bc0d570bb5dda853fd3ec44c52a631b53 | refs/heads/master | 2021-01-22T02:57:58.736093 | 2017-10-16T08:09:46 | 2017-10-16T08:09:46 | 102,257,735 | 1 | 2 | null | false | 2017-10-16T08:09:47 | 2017-09-03T10:46:29 | 2017-09-03T11:01:30 | 2017-10-16T08:09:47 | 1,224 | 0 | 2 | 0 | Python | null | null | from django.contrib.auth import get_user_model
from django.test import TestCase
# Create your tests here.
from .models import Doctor_Referral
User = get_user_model()
class Doctor_ReferralTestCase(TestCase):
def setUp(self):
random_user = User.objects.create(username='testadmin')
def test_refferal_creation(self):
obj = Doctor_Referral.objects.create(
user = User.objects.first(),
patient_id = "patient_id",
doctor_id = "doctor_id",
booked_date = "booked_date",
group = "group"
)
self.assertTrue(obj.patient_id == "patient_id")
self.assertTrue(obj.id == 1)
| UTF-8 | Python | false | false | 673 | py | 67 | tests.py | 36 | 0.622585 | 0.6211 | 0 | 24 | 27.041667 | 63 |
weturner/hello-world | 12,300,786,356,068 | 1b454497f8b28125a07fc54ad76f473f210cad55 | a20c1ac4fac59d827313343e1e25d570b3e3f5a3 | /oldschool/selection.py | 3302e1087b6ed0fcda198d14fb0c739e40c67a9b | []
| no_license | https://github.com/weturner/hello-world | dd5e41be403921329eb9af4af8708c23ee789add | 99e4a3a2cb5431ad45fb43ef3de89fa47e510bee | refs/heads/master | 2017-09-07T22:12:38.625594 | 2016-05-06T01:23:39 | 2016-05-06T01:23:39 | 54,249,733 | 0 | 0 | null | false | 2016-03-19T05:54:58 | 2016-03-19T05:46:46 | 2016-03-19T05:46:46 | 2016-03-19T05:54:57 | 0 | 0 | 0 | 0 | null | null | null | #wes turner
#A2
#cs 301
def select(x):
n = len(x)
for i in range(n-1):
min = i
for j in range (i+1, n):
if x[min] > x[j]:
min = j
temp = x[min]
x[min] = x[i]
x[i] = temp
print "step ", i+1, x
z = [ 692, 1, 32, 14, 15, 123, 2431]
#print "SELECTION SORT\n"
#print "unsorted: ", z
select(z)
print "sorted: ", z
| UTF-8 | Python | false | false | 422 | py | 11 | selection.py | 11 | 0.417062 | 0.36019 | 0 | 22 | 17.181818 | 36 |
d1n0sva1d0/PISBD | 11,587,821,771,004 | af3f3dfca52bcd45505ad907b5f67577f0494ea9 | a1f3d6820711b7493b6e60fcacda797ec46ceab0 | /modulo/interfaz/showProducto.py | fd2ac68761a7b469e939e8f180221cb2492d7f6f | []
| no_license | https://github.com/d1n0sva1d0/PISBD | da77ebfca8cad28ae9b32ac4937dd6434cbb4df4 | b7ca7cb40dd1de17d63e87a8f834c79707643a62 | refs/heads/master | 2016-09-13T05:54:04.822525 | 2016-05-19T17:56:36 | 2016-05-19T17:56:36 | 59,073,259 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'showProducto.ui'
#
# Created: Wed May 4 15:43:06 2016
# by: PyQt4 UI code generator 4.11.2
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore, QtGui
try:
_fromUtf8 = QtCore.QString.fromUtf8
except AttributeError:
def _fromUtf8(s):
return s
try:
_encoding = QtGui.QApplication.UnicodeUTF8
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig, _encoding)
except AttributeError:
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig)
class Ui_showProducto(object):
def setupUi(self, showProducto):
showProducto.setObjectName(_fromUtf8("showProducto"))
showProducto.setWindowModality(QtCore.Qt.ApplicationModal)
showProducto.resize(800, 600)
icon = QtGui.QIcon()
icon.addPixmap(QtGui.QPixmap(_fromUtf8("Images/producto.png")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
showProducto.setWindowIcon(icon)
self.tableViewProductos = QtGui.QTableView(showProducto)
self.tableViewProductos.setGeometry(QtCore.QRect(10, 60, 781, 531))
self.tableViewProductos.setObjectName(_fromUtf8("tableViewProductos"))
self.lineBuscar = QtGui.QLineEdit(showProducto)
self.lineBuscar.setGeometry(QtCore.QRect(30, 20, 361, 22))
self.lineBuscar.setObjectName(_fromUtf8("lineBuscar"))
self.comboBoxOrdenar = QtGui.QComboBox(showProducto)
self.comboBoxOrdenar.setGeometry(QtCore.QRect(550, 20, 78, 23))
self.comboBoxOrdenar.setObjectName(_fromUtf8("comboBoxOrdenar"))
self.comboBoxOrdenar.addItem(_fromUtf8(""))
self.comboBoxOrdenar.addItem(_fromUtf8(""))
self.comboBoxOrdenar.addItem(_fromUtf8(""))
self.comboBoxOrdenar.addItem(_fromUtf8(""))
self.comboBoxOrdenar.addItem(_fromUtf8(""))
self.pushButtonFiltrar = QtGui.QPushButton(showProducto)
self.pushButtonFiltrar.setGeometry(QtCore.QRect(650, 20, 99, 23))
icon1 = QtGui.QIcon()
icon1.addPixmap(QtGui.QPixmap(_fromUtf8("Images/filtrar.png")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
self.pushButtonFiltrar.setIcon(icon1)
self.pushButtonFiltrar.setAutoDefault(True)
self.pushButtonFiltrar.setObjectName(_fromUtf8("pushButtonFiltrar"))
self.labelOrdenar = QtGui.QLabel(showProducto)
self.labelOrdenar.setGeometry(QtCore.QRect(440, 20, 101, 21))
self.labelOrdenar.setObjectName(_fromUtf8("labelOrdenar"))
self.retranslateUi(showProducto)
QtCore.QMetaObject.connectSlotsByName(showProducto)
showProducto.setTabOrder(self.lineBuscar, self.comboBoxOrdenar)
showProducto.setTabOrder(self.comboBoxOrdenar, self.pushButtonFiltrar)
showProducto.setTabOrder(self.pushButtonFiltrar, self.tableViewProductos)
def retranslateUi(self, showProducto):
showProducto.setWindowTitle(_translate("showProducto", "Mostrar Productos", None))
self.comboBoxOrdenar.setItemText(0, _translate("showProducto", "Defecto", None))
self.comboBoxOrdenar.setItemText(1, _translate("showProducto", "Nombre", None))
self.comboBoxOrdenar.setItemText(2, _translate("showProducto", "Marca", None))
self.comboBoxOrdenar.setItemText(3, _translate("showProducto", "Existencia", None))
self.comboBoxOrdenar.setItemText(4, _translate("showProducto", "Precio", None))
self.pushButtonFiltrar.setText(_translate("showProducto", "Filtrar", None))
self.labelOrdenar.setText(_translate("showProducto", "Ordenar por:", None))
| UTF-8 | Python | false | false | 3,704 | py | 49 | showProducto.py | 39 | 0.715443 | 0.689525 | 0 | 73 | 49.726027 | 108 |
Rafael-Jose/django_anuncios | 14,044,543,096,428 | eb973e679e372e1f02b89dd51c60ac916881e9fd | 3727560eddb053a983c32ece7392fb33b25f4663 | /usuarios/urls.py | b7d568c3a4e7452195bf8471424791024edc51d9 | []
| no_license | https://github.com/Rafael-Jose/django_anuncios | fb36a403c760a670373a5047dafeadb3dc298591 | 0df051df74538097a44bffc10c82d555df3307fe | refs/heads/master | 2023-07-19T16:01:53.600144 | 2021-09-28T16:58:36 | 2021-09-28T16:58:36 | 352,221,375 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.urls import path
from usuarios import views
urlpatterns = [
path('login/', views.Login.as_view(), name="login"),
path('logout', views.Logout.as_view(), name="logout"),
path('registrar', views.UsuarioCreate.as_view(), name="registrar"),
path('atualizar-dados/', views.PerfilUpdate.as_view(), name="atualizar-dados"),
]
| UTF-8 | Python | false | false | 349 | py | 20 | urls.py | 11 | 0.681948 | 0.681948 | 0 | 11 | 30.727273 | 83 |
natesilverman/cambia | 4,715,874,122,888 | dcfc62e9debfc6f5ccb257306b741cf00d7dfece | 3f5545f48dda891d92963f856acfc99923044420 | /ecs/execute_ecs_task.py | 1151667d1ee72a020c8b6968d7d77844cc0cdaca | []
| no_license | https://github.com/natesilverman/cambia | 36f4e0f9b8dbd227d8944c40771d777eec1e99ed | 21f2877a4a59a1a46a24d1dca5a576057517fba1 | refs/heads/master | 2020-03-18T04:32:14.196283 | 2018-05-21T16:19:03 | 2018-05-21T16:19:03 | 134,292,567 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from __future__ import unicode_literals
from copy import deepcopy
import boto3
import json
from moto.ec2 import utils as ec2_utils
from uuid import UUID
from moto import mock_cloudformation
from moto import mock_ecs
from moto import mock_ec2
from moto import mock_s3
from boto3 import client
@mock_ec2
@mock_ecs
@mock_s3
def run_task():
client = boto3.client('ecs', region_name='us-east-1')
ec2 = boto3.resource('ec2', region_name='us-east-1')
conn = boto3.resource('s3', region_name='us-east-1')
s3 = boto3.client('s3', region_name='us-east-1')
conn.create_bucket(Bucket='mybucket')
test_cluster_name = 'test_ecs_cluster'
_ = client.create_cluster(
clusterName=test_cluster_name
)
test_instance = ec2.create_instances(
ImageId="ami-1234abcd",
MinCount=1,
MaxCount=1,
)[0]
instance_id_document = json.dumps(
ec2_utils.generate_instance_identity_document(test_instance)
)
response = client.register_container_instance(
cluster=test_cluster_name,
instanceIdentityDocument=instance_id_document
)
_ = client.register_task_definition(
family='test_ecs_task',
containerDefinitions=[
{
'name': 'hello_world',
'image': 'docker/hello-world:latest',
'cpu': 1024,
'memory': 400,
'essential': True,
'environment': [{
'name': 'AWS_ACCESS_KEY_ID',
'value': 'SOME_ACCESS_KEY'
}],
'logConfiguration': {'logDriver': 'json-file'}
}
]
)
response = client.run_task(
cluster='test_ecs_cluster',
overrides={},
taskDefinition='test_ecs_task',
count=1,
startedBy='moto'
)
# Put Task Arn in S3 Bucket
s3.put_object(Bucket='mybucket', Key='taskArn', Body=response['tasks'][0]['taskArn'])
taskArn = conn.Object('mybucket', 'taskArn').get()['Body'].read().decode()
print("The S3 taskArn was: " + taskArn)
# Print out response attributes of ECS Task
print("Number of tasks: " + str(len(response['tasks'])))
print("Task ARN: " + response['tasks'][0]['taskArn'])
print("Cluster ARN: " + response['tasks'][0]['clusterArn'])
print("TaskDefinition ARN: " + response['tasks'][0]['taskDefinitionArn'])
print("Container Instance ARN: " + response['tasks'][0]['containerInstanceArn'])
print("Last Status: " + response['tasks'][0]['lastStatus'])
print("Desired Status: " + response['tasks'][0]['desiredStatus'])
print("Started By: " + response['tasks'][0]['startedBy'])
run_task()
| UTF-8 | Python | false | false | 2,771 | py | 11 | execute_ecs_task.py | 2 | 0.5821 | 0.564417 | 0 | 92 | 29.119565 | 89 |
suziexi/2020GSoC_FrameBlends | 7,962,869,382,703 | 59370bce67a9acfee9c38007f3596e83259f2403 | be6224a65608139f06b0077b3b9b943aac569bfb | /detect_metaphor.py | 3dca06f2857055af2a77d288894b0bc1444edf1d | []
| no_license | https://github.com/suziexi/2020GSoC_FrameBlends | deb547cc1a4b75457ccf195728e3d39b9f3b2157 | c7f61b6789ace34e1dbd5caa00e619351735af62 | refs/heads/master | 2022-12-14T10:07:57.880395 | 2020-08-29T03:06:37 | 2020-08-29T03:06:37 | 262,644,011 | 1 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | from pprint import pprint
from nltk.corpus import framenet as fn
import nltk
import xml.dom.minidom as DM
import xml.etree.ElementTree as ET
from xml.etree import ElementTree
from xml.etree.ElementTree import tostring
import os
import zipfile2
import lxml.etree as etree
path = ('/Users/mac/Desktop/fndata-1.7/fulltext')
def metapFilter(path):
metap_list = [None] * 1
item = ET.Element("FBL")
ET.SubElement(item, 'Source').text = 'Metaphor_label'
for filename in os.listdir(path):
if not filename.endswith('.xml'):
continue
fullname = os.path.join(path, filename)
tree_0 = ET.parse(fullname)
tree_1 = tree_0.getroot()
t = tostring(tree_1)
t = t.lower()
tree_2 = ET.fromstring(t)
for sentence in tree_2:
for annot in sentence.iter(): # text, annotationSet
for x, y in annot.attrib.items():
if y == 'metaphor':
print('Metaphor filter:')
print(sentence[0].text)
metap_list.append(sentence[0].text)
metap_list.append('--------------')
annot.append(item)
print(filename)
filename = open('/Users/mac/Desktop/metaphor_label/'+filename, "w")
filename.write(ET.tostring(tree_2, encoding="unicode"))
def main():
metapFilter(path)
if __name__ == "__main__":
main()
| UTF-8 | Python | false | false | 1,474 | py | 16 | detect_metaphor.py | 13 | 0.569199 | 0.56038 | 0 | 51 | 27.901961 | 75 |
javassj2019/fxol | 13,039,520,748,871 | a5a13b0f420ab28a97420565457bb7c5e553826b | 070df2e62355dbb4a68b46f89bfd90358ca5fa71 | /考试.py | ffe1a99f5accf4f6bc6eacfcacc6423e46a51dbc | []
| no_license | https://github.com/javassj2019/fxol | 8b3c3f3bb1c7760cb159b428db70210ed864d43d | c69c2fc91a8bc0c33a104144f04cae7acfd4caaf | refs/heads/master | 2023-07-05T16:27:32.446084 | 2021-08-26T13:22:56 | 2021-08-26T13:22:56 | 314,174,734 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import requests
import json
import pymysql
import re
import datetime
import urllib
# -*- coding:utf-8 -*-
# 连接数据库并获取账户密码信息
conn = pymysql.connect(host='cdb-kce5k8kq.bj.tencentcdb.com', user='root', passwd='a159753A!', port=10264,
charset='utf8', db='fxol')
cur = conn.cursor(pymysql.cursors.DictCursor) # 生成游标
# # 录入新用户
# def Typeuserid():
# print('请输入用户名：')
# userAccount = input()
# print('请输入密码：')
# userPassword = input()
# # 用户查重
# checkuid = cur.execute('select UserID from User where UserID = (%s)', userAccount)
# print(checkuid)
# if checkuid == 0:
# cur.execute('insert into User(UserID,UserPassword,TDpoint) VALUES (%s,%s,%s)', (userAccount, userPassword, 10))
# conn.commit()
# print('用户添加完成')
# else:
# print('用户已存在，无需再次添加')
#
#
# print('需要添加新用户吗？Yes')
# checktype = input()
# if checktype == 'Y':
# i = 0
# while i <= 100:
# Typeuserid()
# i = i + 1
###基础数据
http = 'http://'
host = 'mobile.faxuan.net'
loginurl = '/bss/service/userService!doUserLogin.do?'
getdetailurl = '/useris/service/getdetail?userAccount='
studyurl = '/sss/service/coursewareService!commitStudy.do?domainCode='
code = '&code=2f56fe3477f774c4ece2b926070b6d0a'
headers = {}
headers['If-Modified-Since'] = 'Tue, 1 Jul 2021 01:33:10 GMT+00:00'
headers['User-Agent'] = 'Dalvik/2.1.0 (Linux; U; Android 7.1.1; OPPO R9s Build/NMF26F)'
headers['Host'] = 'mobile.faxuan.net'
headers['Accept-Encoding'] = 'gizp,deflate'
headers['Connection'] = 'keep-alive'
headers['Content-Type'] = 'application/x-www-form-urlencoded; charset=UTF-8'
answerjson = '\[(.*)\]'
####比较最后更新时间并写数据库
today = str(datetime.date.today())
###开始登陆过程
s = 0
l = cur.execute('select UserID,UserPassword from User where Mark = (%s)', (3))
while s <= l:
cur.execute('select UserID,UserPassword from User where Mark = (%s)', (3))
tt1 = cur.fetchone()
print(tt1)
userAccount = tt1['UserID']
userPassword = tt1['UserPassword']
# 登陆并获取参数
tt = requests.get(http + host + loginurl + 'userAccount=' + userAccount + '&userPassword=' + userPassword + code,
headers=headers)
dd = json.loads(tt.text)
sid = dd['data']['sid']
# username = dd['data']['userName']
# 获取学员基础信息
t2 = requests.get(http + host + getdetailurl + userAccount + '&ssid=' + sid, headers=headers)
t2.encoding = 'utf8'
d2 = json.loads(t2.text)
lenth = len(d2)
dict1 = {}
i = 0
while i <= lenth-1:
dict1[d2[i]] = d2[i + 1]
i = i + 2
TDpoint = dict1['todaytpoint']
domainCode = dict1['domainCode']
Tpoint = dict1['tpoint']
username = dict1['userName']
print(username)
# 开始考试
examid = str(2440)
paperid = str(4932)
series = str(430)
t4 = requests.get(
http + host + '/ess/service/getpaper?paperId='+paperid+'&series='+series+'_answer&version=2.5.5&userAccount' + userAccount,
headers=headers)
# print(t4.text)
t4answer = re.findall(answerjson, str(t4.content))[0] # 此处返回text会因为返回有非json的数据不能读取
t4answer = t4answer.replace(',"score":"1.0",', ',')
t4answer = t4answer.replace(',"score":"2.0",', ',')
t4answer = t4answer.replace(',"score":"3.0",', ',')
t4answer = t4answer.replace('questionId":"', 'questionId":')
t4answer = t4answer.replace('","answerNo', ',"answerNo')
t4answer = t4answer.replace('},{', '}{')
t4answer = t4answer.replace('ABCD', 'A,B,C,D')
t4answer = t4answer.replace('ABC', 'A,B,C')
t4answer = t4answer.replace('ABD', 'A,B,D')
t4answer = t4answer.replace('ACD', 'A,C,D')
t4answer = t4answer.replace('BCD', 'B,C,D')
t4answer = t4answer.replace('AC', 'A,C')
t4answer = t4answer.replace('AD', 'A,D')
t4answer = t4answer.replace('BC', 'B,C')
t4answer = t4answer.replace('BD', 'B,D')
t4answer = t4answer.replace('CD', 'C,D')
answer = t4answer
data = {
'series': series,
'examId': examid,
'paperId': paperid,
'userAccount': userAccount,
'domainCode': domainCode,
'myExamAnswer': '[' + answer + ']'
}
t6 = requests.post(
http + host + '/ess/service/myexam/myExamAo!doCommitExam.do',
headers=headers,
data=data
)
# print(t6.text)
cur.execute('UPDATE User SET Mark = (%s) WHERE UserID = (%s)', (4, userAccount))
conn.commit()
print("学习过程结束")
##########这里还差学习执行过程
| UTF-8 | Python | false | false | 4,726 | py | 4 | 考试.py | 4 | 0.607207 | 0.572523 | 0 | 133 | 32.383459 | 131 |
Aasthaengg/IBMdataset | 16,527,034,199,193 | c13c2bb8ce64502d47684fa049ec9fb42dd3e062 | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p04020/s106001075.py | 1e4884768684ea5f5415973b24f44bab1b71f1fb | []
| no_license | https://github.com/Aasthaengg/IBMdataset | 7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901 | f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8 | refs/heads/main | 2023-04-22T10:22:44.763102 | 2021-05-13T17:27:22 | 2021-05-13T17:27:22 | 367,112,348 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | N = int(input())
A = [int(input()) for _ in range(N)]
res = 0
n = 0
for a in A:
if a == 0:
res += n // 2
n = 0
n += a
res += n // 2
print(res)
| UTF-8 | Python | false | false | 170 | py | 202,060 | s106001075.py | 202,055 | 0.4 | 0.364706 | 0 | 14 | 11.142857 | 36 |
sunny-aria/py_mysite | 19,499,151,541,632 | ea9b1f1eeabf697815469287b6b65521f71acb51 | 74c78a270a6a54d76f3aa707b2a5b5a207d85080 | /polls/admin.py | 4584739edbf2517032f7dce63cef9464068c6439 | []
| no_license | https://github.com/sunny-aria/py_mysite | 463856e70c85ad86faf7389206022885649a2264 | bf7df6355c6200ae98aa5d413b6e7cb5ec29f9a0 | refs/heads/master | 2020-03-28T15:33:41.120002 | 2018-10-09T03:37:12 | 2018-10-09T03:37:12 | 148,606,137 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.contrib import admin
# Register your models here.
from . import models
# 将models 注册到后台管理上面
admin.site.register(models.Poll)
admin.site.register(models.Choice) | UTF-8 | Python | false | false | 193 | py | 6 | admin.py | 4 | 0.797688 | 0.797688 | 0 | 9 | 18.333333 | 34 |
ronekko/study_reinforcement_learning | 3,358,664,449,177 | f1306ff3242601b96710e947c2fed3ab69052347 | 3e6091b1fede2f6333f96a323bb6f1267f78597f | /gym_usage.py | 5277c4a7f4b4fcfa37bdad4c3e80d77a3b05bd91 | [
"MIT"
]
| permissive | https://github.com/ronekko/study_reinforcement_learning | 411dcf31921f2fe705448f2121553a7732e703f0 | ef5201e3eae69c20f29b7f176b5a6de7ecdb856a | refs/heads/main | 2023-04-19T02:24:19.512943 | 2021-04-25T09:25:32 | 2021-04-25T09:25:32 | 346,573,950 | 0 | 0 | MIT | false | 2021-04-25T09:25:33 | 2021-03-11T04:09:19 | 2021-03-11T04:16:44 | 2021-04-25T09:25:32 | 39 | 0 | 0 | 0 | Python | false | false | # -*- coding: utf-8 -*-
"""
Created on Sat Feb 13 16:52:17 2021
@author: ryuhei
"""
import gym
if __name__ == '__main__':
# Gallery of environments: https://gym.openai.com/envs/#classic_control
env = gym.make('CartPole-v1') # state(pos, vel, angle, angular vel)
# env = gym.make('Pendulum-v0')
# env = gym.make('MsPacman-v0')
# env = gym.make('Pong-v0')
env.reset()
for _ in range(10):
env.reset()
states = []
rewards = []
for _ in range(200):
env.render()
# Choose an action from {0, 1}, where
# 0 or 1 are left or right acceleration respectively.
action = env.action_space.sample()
# Do the action and receive an outcome.
# An outcome consists of
# - observation (float np.array of length 4):
# [cart pos, cart vel, pole angle, pole angular vel]
# - reward (float): constant 1.
# - done (bool): True if the pole angle has exceeded the limits.
# - info (dict): Additional information.
outcome = env.step(action)
obs, reward, done, info = outcome
states.append(obs)
rewards.append(reward)
if done:
break
env.close()
| UTF-8 | Python | false | false | 1,317 | py | 6 | gym_usage.py | 5 | 0.525437 | 0.504176 | 0 | 46 | 27.630435 | 78 |
jcugat/django-custom-user | 9,345,848,888,466 | fd0ecff7ff765c442567d36ee033fa85ff21ab2e | 15aae55c7261460a4261223b991720ff8f9efbd9 | /src/custom_user/apps.py | 8a7f85ca1130363da95327f5af0043b93bd3fdb2 | [
"BSD-2-Clause"
]
| permissive | https://github.com/jcugat/django-custom-user | 242b08b5ae1187789df1797c6b0559c59959bb89 | 309d36c681d622bcdbc4648368cb13faab9cce95 | refs/heads/main | 2023-02-25T00:08:05.997146 | 2022-12-09T23:59:04 | 2022-12-09T23:59:04 | 9,319,295 | 281 | 77 | BSD-3-Clause | false | 2023-02-15T19:27:53 | 2013-04-09T11:08:02 | 2023-02-15T08:39:53 | 2023-02-15T19:27:50 | 281 | 310 | 65 | 4 | Python | false | false | """App configuration for custom_user."""
from django.apps import AppConfig
class CustomUserConfig(AppConfig):
"""
Default configuration for custom_user.
"""
name = "custom_user"
verbose_name = "Custom User"
# https://docs.djangoproject.com/en/3.2/releases/3.2/#customizing-type-of-auto-created-primary-keys
default_auto_field = "django.db.models.AutoField"
| UTF-8 | Python | false | false | 389 | py | 18 | apps.py | 10 | 0.701799 | 0.691517 | 0 | 14 | 26.785714 | 103 |
datvithanh/liveness | 9,620,726,751,440 | 9941d82c52524530de21999020a24d119f54c608 | f24e205b70666ac0b773a4d3a4828442f07c24a9 | /main.py | 0ea0be54b0801a4104e7dbdfefd12cbf74b73d20 | []
| no_license | https://github.com/datvithanh/liveness | 819a831d69452677b0b8788cda28891ca6c9cd84 | 1727d5830093c140b2d52fb021ffcd50a37bb59f | refs/heads/master | 2020-08-05T12:31:44.346370 | 2019-09-19T09:16:08 | 2019-09-19T09:16:08 | 212,506,306 | 3 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import argparse
import yaml
from src.estimator import Estimator
parser = argparse.ArgumentParser(description='Liveness estimator')
parser.add_argument('--config', type=str, help='Path to config of liveness')
parser.add_argument('--cuda', action='store_true', help='Use cuda for training/finetuning or not')
parser.add_argument('--epoch', default=0, type=int, help='Epoch to continue training/finetuning')
parser.add_argument('--model_path', default='', type=str, help='Path to pretrained model')
parser.add_argument('--mode', default='training', type=str, help='Mode: either training or finetuning')
params = parser.parse_args()
config = yaml.load(open(params.config, 'r'))
est = Estimator(params, config)
est.exec()
| UTF-8 | Python | false | false | 723 | py | 12 | main.py | 9 | 0.745505 | 0.744122 | 0 | 19 | 37.052632 | 103 |
mn3711698/markets_monitor | 7,481,833,079,478 | 2e83912ec0e757ca4f8e27cd7be239f08f086879 | 69aeac8061bfbf4f692163f97dc9bec095bfaf4e | /monitor_crawl/investing.py | 97683c72855b6a449bca1c517b86bbaaf75b7069 | []
| no_license | https://github.com/mn3711698/markets_monitor | 0939c8b6bd33a2a50f404f89b42bbd29e98ae666 | d00a649c46dc21f52a9e4e213797390bb7088c9b | refs/heads/master | 2021-04-06T00:00:56.322346 | 2015-02-11T08:34:10 | 2015-02-11T08:34:10 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Created on 2015/2/6
# !/usr/bin/env python
# -*- coding: utf-8 -*-
# Created on 2015/1/14
from base import *
import time
cur.execute("select * from ax_config WHERE status='active' and diff_url like '%investing%' ")
data = cur.fetchall()
start_time = time.time()
# while 1:
for i in xrange(1):
for item in data:
diff_url = item['diff_url']
# pow_format=item['pow_format']
diff_allow = item['diff_allow']
site_url = 'http://api.markets.wallstreetcn.com/v1/price.json?symbol=%s' % item['symbol']
try:
diff_price = get_data(diff_url)
ctime = int(time.time())
site_price, site_ctime = get_wallstreetcn(site_url)
if diff_price and site_price:
# print item['symbol'],diff_price,site_price,pow_format,diff_allow
# print u'允许误差',diff_allow*1.0/math.pow(10,pow_format)
if abs(diff_price - site_price) > diff_allow:
print diff_url, diff_allow
cur.execute("insert into log set symbol=%s,diff_price=%s,site_price=%s,ctime=%s,site_ctime=%s", (item['symbol'], diff_price, site_price, ctime, site_ctime))
cur.execute("update ax_config set diff_price=%s,site_price=%s,ctime=%s,site_ctime=%s,diff_status=1 WHERE id=%s", (diff_price, site_price, ctime, site_ctime, item['id']))
else:
cur.execute("update ax_config set diff_price=%s,site_price=%s,ctime=%s,site_ctime=%s,diff_status=0 WHERE id=%s", (diff_price, site_price, ctime, site_ctime, item['id']))
except Exception as e:
app_log.error(str(e))
end_time = time.time()
print end_time - start_time | UTF-8 | Python | false | false | 1,752 | py | 15 | investing.py | 8 | 0.593463 | 0.579702 | 0 | 43 | 39.581395 | 189 |
samuelbaltanas/face-pose-dataset | 11,733,850,664,415 | faa903bebc93532bc2a40c9f6e009f118e3deedb | 7b7062f9e07c9a655d0d91186d16eca7f435980b | /face_pose_dataset/__main__.py | df403ba2e6d9447a325163cbe9872eeccb13a184 | [
"MIT"
]
| permissive | https://github.com/samuelbaltanas/face-pose-dataset | 0fbc8df61f369f00629ecd3db3791d1268b3a530 | 84c864c155ac7c0b231032d403c0e2b2bc10b871 | refs/heads/master | 2022-08-28T10:46:08.005149 | 2020-05-26T08:11:28 | 2020-05-26T08:11:28 | 257,634,482 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import argparse
import logging
import os
import sys
import platform
logging.getLogger().setLevel(logging.INFO)
import PySide2
if platform.system() == "Windows":
dirname = os.path.dirname(PySide2.__file__)
plugin_path = os.path.join(dirname, 'plugins', 'platforms')
logging.info("%s is a dir : %s", plugin_path, os.path.isdir(plugin_path))
os.environ['QT_QPA_PLATFORM_PLUGIN_PATH'] = plugin_path
from PySide2 import QtCore, QtWidgets
class MainWindow(QtWidgets.QMainWindow):
def __init__(self, *args, **kwargs):
QtWidgets.QMainWindow.__init__(self, *args, **kwargs)
self.setWindowTitle("Dataset")
self.layouts = {}
self.kill_callback = None
# self.setGeometry(300, 200, 500, 400)
def register_layout(self, key, layout, resolution=(600, 360)):
self.layouts[key] = layout, resolution
@QtCore.Slot(str)
def change_layout(self, key: str):
lay = self.layouts[key]
self.setCentralWidget(lay[0])
self.resize(*lay[1])
self.show()
def closeEvent(self, event):
if self.kill_callback is not None:
self.kill_callback(event)
else:
quit_msg = "Are you sure you want to exit the program?"
reply = QtWidgets.QMessageBox.question(
self,
"Message",
quit_msg,
QtWidgets.QMessageBox.Yes,
QtWidgets.QMessageBox.No,
)
if reply == QtWidgets.QMessageBox.Yes:
event.accept()
else:
event.ignore()
def main(args):
try:
if args.quiet:
logging.getLogger().setLevel(logging.ERROR)
elif args.verbose:
logging.getLogger().setLevel(logging.DEBUG)
else:
logging.getLogger().setLevel(logging.INFO)
app = QtWidgets.QApplication(sys.argv)
logging.info(args)
logging.info("Platform: %s", platform.platform())
if args.force_cpu:
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
else:
os.environ['TF_FORCE_GPU_ALLOW_GROWTH'] = 'true'
from face_pose_dataset.controller import estimation, logging_controller, storage_control
from face_pose_dataset.model import score, storage
from face_pose_dataset.view import login, main_view
# PARAMS
dims = 7, 7
yaw_range = -65.0, 65.0
pitch_range = -35.0, 35.0
# MODELS
scores = score.ScoreModel(dims, pitch_range=pitch_range, yaw_range=yaw_range)
store = storage.DatasetModel(shape=dims)
# VIEW
window = MainWindow()
window.resize(600, 360)
# Login
login_widget = login.Login()
window.register_layout("login", login_widget)
window.change_layout("login")
# Main widget
widget = main_view.MainWidget(scores)
window.register_layout("main", widget, (1200, 720))
# CONTROLLERS
store_controller = storage_control.StorageController(scores, store)
store_controller.change_pos.connect(widget.plot.update_pointer)
logger = logging_controller.LoggingController(login_widget, store)
logger.change_layout.connect(window.change_layout)
if args.force_cpu:
gpu = -1
else:
gpu = 0
th = estimation.EstimationThread(gpu=gpu)
th.video_feed.connect(widget.video.set_image)
th.worker.result_signal.connect(store_controller.process)
# th.setTerminationEnabled(True)
login_widget.switch_window.connect(logger.access)
logger.set_camera.connect(th.init_camera)
store_controller.flag_pause.connect(th.set_pause)
widget.controls.buttons[0].clicked.connect(th.toggle_pause)
widget.controls.buttons[1].clicked.connect(store_controller.terminateApp)
store_controller.flag_end.connect(th.set_stop)
scores.change_score.connect(widget.plot.update_plot)
window.kill_callback = lambda x: store_controller.terminateApp()
# Execute application
logging.info("[MAIN] Running main loop.")
_excepthook = sys.excepthook
def exception_hook(exctype, value, traceback):
print(exctype, value, traceback)
_excepthook(exctype, value, traceback)
sys.exit(-1)
sys.excepthook = exception_hook
# th.start()
res = app.exec_()
finally:
logging.info("[MAIN] Waiting for thread to terminate.")
# th.wait(2000)
logging.info("[MAIN] Terminated.")
sys.exit(res)
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--force-cpu",
action="store_true",
help="Forces the estimator to use a CPU. When not set, it searches for any available GPU.",
)
group = parser.add_mutually_exclusive_group()
group.add_argument("-v", "--verbose", action="store_true")
group.add_argument("-q", "--quiet", action="store_true")
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
main(args)
| UTF-8 | Python | false | false | 5,209 | py | 39 | __main__.py | 33 | 0.60933 | 0.597811 | 0 | 170 | 29.641176 | 99 |
karthikpappu/pyc_source | 4,028,679,342,572 | 2dc18446213f5f1022dabebd56cf3ea9cedc8f62 | 91fa095f423a3bf47eba7178a355aab3ca22cf7f | /pycfiles/boo_box-0.3.7-py2.4/teste.py | 45ac43a15758474c67d1be4bfcd32bc7734e00d5 | []
| no_license | https://github.com/karthikpappu/pyc_source | 0ff4d03e6d7f88c1aca7263cc294d3fa17145c9f | 739e7e73180f2c3da5fd25bd1304a3fecfff8d6e | refs/heads/master | 2023-02-04T11:27:19.098827 | 2020-12-27T04:51:17 | 2020-12-27T04:51:17 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # uncompyle6 version 3.7.4
# Python bytecode 2.4 (62061)
# Decompiled from: Python 3.6.9 (default, Apr 18 2020, 01:56:04)
# [GCC 8.4.0]
# Embedded file name: build/bdist.linux-i686/egg/boo_box/teste.py
# Compiled at: 2008-05-02 09:14:26
import boo_box, simplejson
boo = boo_box.Box('submarinoid', '248960').getJSON('livros javascript').replace('jsonBooboxApi(', '')
json = simplejson.loads(boo[:-1])
for item in json['item']:
print item | UTF-8 | Python | false | false | 441 | py | 114,545 | teste.py | 111,506 | 0.702948 | 0.582766 | 0 | 11 | 39.181818 | 101 |
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