def update_output(n_intervals, value, chart_type):
#stock = redis_conn.get('stock')
stock = value
hash_key = stock + str(current_user.id)
pdebug1("In update output: {}".format(stock))
try:
fh = open('log/freedom_trade.log', 'r')
logMsg = fh.read()
fh.close()
#logMsg = redis_conn.get('logMsg'+cache_type)
except:
logMsg = "Something went wrong !!"
fig = ''
trade_summary = 'Ongoing ...'
if stock == '':
return fig, 'logMsg', 'No option selected', ''
summary_stat = datetime.fromtimestamp(
float(backtest_cache.hget(hash_key + cache_type, 'last_processed')))
if backtest_cache.get('done' + str(current_user.id) +
cache_type) == "1": ## to reduce load on processor
#pinfo(hash_key)
fig = freedom_chart(hash_key, cache_type, chart_type)
trade_df = backtest_cache.getTrades(hash_key)
try:
(total_profit, max_loss, max_profit, total_win, total_loss,
max_winning_streak, max_loosing_streak,
trade_log_df) = trade_analysis_raw(trade_df)
summary_stat = 'Total Profit: {:.02f}, Max Drawdown: {:.02f}, Max Profit {:.02f}'.format(
total_profit, max_loss, max_profit)
#summary_stat = summary_stat + html.Br()
summary_stat = summary_stat + '\n Win: {}, Loss: {}, Longest Streak => Win: {}, Loss: {}'.format(
total_win, total_loss, max_winning_streak, max_loosing_streak)
trade_log_df['profit'] = trade_log_df['profit'].map(
"{:,.02f}".format)
trade_log_df['CumProfit'] = trade_log_df['CumProfit'].map(
"{:,.02f}".format)
trade_log_df['date'] = trade_log_df.index
#trade_log_df = trade_log_df.map("{:,.0f}".format) backtest_cache
if 'mode' in trade_log_df.columns:
trade_summary = df_to_table(
trade_log_df[[
'date', 'mode', 'buy', 'sell', 'profit', 'CumProfit'
]], 'trade_summary_table', False)
else:
trade_summary = df_to_table(
trade_log_df[[
'date', 'mode', 'buy', 'sell', 'profit', 'CumProfit'
]], 'trade_summary_table', False)
except:
trade_summary = 'not enough data'
return fig, logMsg, trade_summary, summary_stat
def update_intervals(n_intervals, clicks):
pdebug1("Update Intervals: {}: {}".format(n_intervals, backtest_cache.get('done')))
# if done is set to 1 then backtest is complete -> Time to disable interval and enable backtest button
if backtest_cache.get('done'+cache_type) == "1": # Backtest complete
pdebug("Returning True: Disable Interval")
return True, False, 'Go'
else: # Backtest is in progress
pdebug1("Returning False: Enable Interval")
return False, True, 'Wait'
def update_intervals(n_intervals, clicks):
hash_key = 'done' + str(current_user.id) + cache_type
if clicks == 0:
backtest_cache.set(hash_key, 1)
pdebug1("Update Intervals: {}: {}".format(n_intervals,
backtest_cache.get(hash_key)))
# if done is set to 1 then backtest is complete -> Time to disable interval and enable backtest button
if backtest_cache.get(hash_key) == "1": # Backtest complete
pdebug("Returning True: Disable Interval")
return True, False, 'Go'
else: # Backtest is in progress
pdebug1("Returning False: Enable Interval")
return False, True, 'Wait'
def start_backtest(n_clicks, stocks, qty, sl, target, start_date, end_date, algo, freq, algo_name, mode ):
toDate = end_date
fromDate = start_date
try:
pinfo("==========: {} :========".format(session["access_token"]))
except:
perror("Access Token Not found")
#return 0
if n_clicks == 0:
return 0
if len(mode) > 0:
backtest = 'quick'
else:
backtest = 'full'
if not isinstance(stocks,list):
stocks = [stocks]
pdebug1(stocks)
# Step 1: Create the msg for initiating backtest
#pinfo(freq)
backtest_msg={'stock':stocks,'sl':sl,'target':target,'qty':qty,'algo':algo_name,'fromDate':fromDate,'toDate':toDate,'freq':freq, 'mode':backtest}
try:
store_algo(algo, algo_name)
except:
perror('Something went wrong while saving algo')
pdebug1(backtest_msg)
# Step 2: Store the stock name under backtest in the redis cache
for stock in stocks:
backtest_cache.set('stock',stock) #TODO: replace
# Step 4: Done is set to 0: Backtest is in progress, will be resetted by backtest job
backtest_cache.set('done'+cache_type,0)
# Step 5: Send the msg to backtest thread to initiate the back test
pdebug(json.dumps(backtest_msg))
backtest_cache.publish('kite_simulator'+cache_type,json.dumps(backtest_msg))
# Step 6: Return 0 to reset n_intervals count
return 0