import pandas as pd
from datetime import datetime
from dateutil.parser import parse


# ----------------------------
#  USER CONFIGURATION
#   all answers should be in double quotes
#   avoid spaces and special characters
#   intraday should be True or False with no quotes
#
input_file_name = "C:/users/Dave/Documents/cK.csv"
output_file_name = "C:/users/Dave/Documents/CLforBA.csv"
symbol = "CL"
direction = "Long"
strategy_name = "CLkase"
intraday = True



# --------------------------------
#   read in TradeStation report
#
df = pd.read_csv(input_file_name,delimiter=',',index_col=2,parse_dates=True,header=None)
if df.index[-1] == "Open":
	df = df[:-1]
if intraday:
	df.index = [parse(d) for d in df.index]
	df.index = [pd.to_datetime(d) for d in df.index]
else:
        df.index = [pd.to_datetime(d) for d in df.index]
df['Time'] = [str(d.hour * 10000 + d.minute * 100 + d.second) if intraday else "170000" for d in df.index]
df['Results'] = [float(x.replace('(','-').replace('$','').replace(')','').replace(',','')) for x in df[6]]




# ---------------------------
#  Create File
#
fh = open(output_file_name,'w')
fh.write("#%s,%s,%s\n" % (symbol,strategy_name,direction))



# ----------------------------
#  Grab trades
#
for i,d in enumerate(df.index):
	if df[1][i] == "Sell" or df[1][i] == "Buy to Cover":
		fh.write("%s,%s,%s,%s,%.2f\n" % (df.index[i-1].strftime("%Y%m%d"),df['Time'][i-1],df.index[i].strftime("%Y%m%d"),df['Time'][i],df['Results'][i]))


fh.close()