import pandas as pd
import numpy as np
import plotly.express as px
import plotly.graph_objects as go
import streamlit as st
from typing import Dict, List, Any


class DataProcessor:
    def __init__(self):
        self.data = None
        self.numeric_columns = []
        self.categorical_columns = []
        self.date_columns = []
    
    def load_data(self, file) -> bool:
        try:
            self.data = pd.read_csv(file)
            self._classify_columns()
            return True
        except Exception as e:
            st.error(f"Error loading data: {str(e)}")
            return False
    
    def _classify_columns(self):
        for col in self.data.columns:
            if pd.api.types.is_numeric_dtype(self.data[col]):
                self.numeric_columns.append(col)
            elif pd.api.types.is_datetime64_any_dtype(self.data[col]):
                self.date_columns.append(col)
            else:
                try:
                    pd.to_datetime(self.data[col])
                    self.date_columns.append(col)
                except:
                    self.categorical_columns.append(col)

    def get_basic_stats(self) -> Dict[str, Any]:
        if self.data is None:
            return {}
        
        stats = {
            'summary': self.data[self.numeric_columns].describe(),
            'missing_values': self.data.isnull().sum(),
            'row_count': len(self.data),
            'column_count': len(self.data.columns)
        }
        return stats

    def create_visualization(self, chart_type: str, x_col: str, y_col: str, color_col: str = None) -> go.Figure:
        if chart_type == "Line Plot":
            fig = px.line(self.data, x=x_col, y=y_col, color=color_col)
        elif chart_type == "Bar Plot":
            fig = px.bar(self.data, x=x_col, y=y_col, color=color_col)
        elif chart_type == "Scatter Plot":
            fig = px.scatter(self.data, x=x_col, y=y_col, color=color_col)
        elif chart_type == "Box Plot":
            fig = px.box(self.data, x=x_col, y=y_col, color=color_col)
        else:
            fig = px.histogram(self.data, x=x_col, color=color_col)
        
        return fig