import glob
import pandas as pd

from plotting import BacktestChart, plot

DATE = 'Period'
PROFIT = 'Cum. net profit'
TOTAL_PROFIT = 'Total Cum. net profit'

backtest_results_path = ''
backtest_result_plot_title = ''

all_start_dates = []
all_end_dates = []

# Find the earliest start date and the latest end date among all backtests.
for file in glob.glob(backtest_results_path):
    backtest = pd.read_csv(file, sep = ',', usecols = [DATE])
    backtest[DATE] = pd.to_datetime(backtest[DATE])
    all_start_dates.append(backtest[DATE].min())
    all_end_dates.append(backtest[DATE].max())

start_date = min(all_start_dates)
end_date = max(all_end_dates)
all_dates = pd.date_range(start = start_date, end = end_date, freq = 'D')

backtests = []

def parse_profit(profit):
    profit = profit.replace('$', '').replace(',', '').strip()
    # Negative values are enclosed in parentheses.
    if profit.startswith('(') and profit.endswith(')'):
        profit = profit.strip('()')
        return -float(profit)
    else:
        return float(profit)

for file in glob.glob(backtest_results_path):
    backtest = pd.read_csv(file, sep = ',')

    backtest[DATE] = pd.to_datetime(backtest[DATE])
    backtest.set_index(DATE, inplace = True)
    
    backtest[PROFIT] = backtest[PROFIT].apply(parse_profit)
    backtest = backtest[[PROFIT]]

    backtest = backtest.reindex(all_dates)
    backtests.append(backtest)

combined_backtests = pd.concat(backtests, axis = 1)

combined_backtests.dropna(axis = 0, how = 'all', inplace = True)
combined_backtests.ffill(inplace=True)
combined_backtests.fillna(0, inplace = True)

combined_backtests[TOTAL_PROFIT] = combined_backtests.sum(axis = 1)

combined_backtests = combined_backtests[[TOTAL_PROFIT]]
combined_backtests.reset_index(inplace = True)
combined_backtests.rename(columns={'index': 'Date'}, inplace = True)

plot(BacktestChart(
    dates = combined_backtests['Date'],
    profit = combined_backtests[TOTAL_PROFIT],
    title = backtest_result_plot_title
))