# Library imports
import datetime
import requests_cache
import matplotlib.pyplot as plt
from pandas_datareader import data as wb
import yfinance as yf

class Ticker:
    """Class for fetcing data from yahoo finance."""
    
    @staticmethod
    def get_historical_data(ticker, start_date = None, end_date = None, cache_data = True, cache_days = 1):
        """
        Fetches stock data from yahoo finance. Request is by default cashed in sqlite db for 1 day.
        
        Params:
        ticker: ticker symbol
        start_date: start date for getting historical data
        end_date: end date for getting historical data
        cache_date: flag for caching fetched data into sqlite db
        cache_days: number of days data will stay in cache 
        """
        try:
            # initializing sqlite for caching yahoo finance requests
            expire_after = datetime.timedelta(days = 1)
            session = requests_cache.CachedSession(cache_name = 'cache', backend = 'sqlite', expire_after = expire_after)

            # Adding headers to session
            session.headers = {'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:89.0) Gecko/20100101 Firefox/89.0', 
                               'Accept': 'application/json;charset=utf-8'
                              }
            
            if(start_date is not None and end_date is not None):
                data = yf.download(ticker, start = start_date, end = end_date)
            else:
                data = yf.download(ticker)

            if data is None:
                return None
            return data
        
        except Exception as e:
            print(e)
            return None

    @staticmethod
    def get_columns(data):
        """
        Gets dataframe columns from previously fetched stock data.
        
        Params:
        data: dataframe representing fetched data
        """
        if data is None:
            return None
        return [column for column in data.columns]

    @staticmethod
    def get_last_price(data, column_name):
        """
        Returns last available price for specified column from already fetched data.
        
        Params:
        data: dataframe representing fetched data
        column_name: name of the column in dataframe
        """
        if data is None or column_name is None:
            return None
        if column_name not in Ticker.get_columns(data):
            return None
        return data[column_name].iloc[len(data) - 1]


    @staticmethod
    def plot_data(data, ticker, column_name):
        """
        Plots specified column values from dataframe.
        
        Params:
        data: dataframe representing fetched data
        column_name: name of the column in dataframe
        """
        try:
            if data is None:
                return
            data[column_name].plot()
            plt.ylabel(f'{column_name}')
            plt.xlabel('Date')
            plt.title(f'Historical data for {ticker} - {column_name}')
            plt.legend(loc = 'best')
            plt.show()

        except Exception as e:
            print(e)
            return