Google Cloud Functions - How to set up a function (trading bot) - google-cloud-functions

Question

I would like to set up a trading bot via Google Cloud to run around the clock.
In Google Cloud Functions I use the Inline editor with runtime Python 3.7.
I have two questions:
1) Main.py section: Here I copied the full code of my Python script (Trading Bot) - see code below for reference (which works well when run as a script in my IDE Spyder).
However, below Google asks to provide a function to execute. However, my code is just a script with no main function. Can I just put at the top of the code e.g.: "def trading_bot(self):" and indent the remaining part below?
While the code as a script copied below works well, if I add the "def trading_bot(self):" at the top in my IDE (Spyder), the code doesnt seem to work properly...How can I make sure the code within the function runs properly, when I call the function from Google Cloud (or from my IDE).
2) Requirements.txt section: Can you provide guidance what exactly I need to put there, i.e. can I look up the dependencies used in my code somewhere? I use Anaconda for distribution, the classes imported for the script are at the top of the script provided below.
Thanks for any help. Glad also for your advice if you think Google Cloud Functions is not the best approach to run a trading bot but it seemed to me to be the simplest solution.
import bitmex
import json
from time import sleep
from bitmex_websocket import BitMEXWebsocket
import logging, time, requests
import numpy as np
import pandas as pd
import matplotlib.dates as mdates
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings("ignore")
from datetime import datetime
import math
from statistics import mean
#-------------------------
#variable
symbol = "XBTUSD"
#standard API connection
api_key = "XXX"
api_secret = "XXX"
#True for testnet
client = bitmex.bitmex(test=False, api_key=api_key, api_secret=api_secret)
#------------------
# Trading algorithm
symbol = "XBTUSD"
ordType = 'Stop'
#starting order quantity
orderQty = 1
leftBars = 6
rightBars = 2
#round to 0.5
def round_to_BTC(n):
result = round(n*2)/2
return result
t=1
while t < 1000000:
time_now = (time.strftime('%H:%M:%S', time.localtime(int(time.time()))))
t_now = time_now[6:8]
t1 = "00"
t2 = "59"
FMT = '%S'
def days_hours_minutes_seconds(td):
return td.days, td.seconds//3600, (td.seconds//60)%60, td.seconds
if t_now == str('00'):
#give 1 second to candlestick to properly close
sleep(1)
elif t_now > str('00') and t_now <= str('59'):
s1 = datetime.strptime(t2, FMT) - datetime.strptime(t_now, FMT)
s1_seconds = days_hours_minutes_seconds(s1)[3]+2
sleep(s1_seconds)
else:
pass
time_now = (time.strftime('%H:%M:%S', time.localtime(int(time.time()))))
print("The time is now: " + time_now)
#most recent swing candles, get highs and lows / #binsizes = {"1m": 1, "5m": 5, "1h": 60, "1d": 1440}
#+1 is the middle bar
totalBars = leftBars + rightBars + 1
swing_candles = client.Trade.Trade_getBucketed(symbol=symbol, binSize="1m", count=totalBars, reverse=True).result()[0]
last_highs = []
last_lows = []
i=0
while i <= (len(swing_candles)-1):
last_highs.append(swing_candles[i]["high"])
last_lows.append(swing_candles[i]["low"])
i += 1
#get the highest high and the lowest low
highest_high = max(last_highs)
lowest_low = min(last_lows)
#check if there are existing positions & orders
if client.Position.Position_get().result()[0] != []:
positions_quantity = client.Position.Position_get().result()[0][0]["currentQty"]
else:
positions_quantity = 0
#check existing orders
buy_orders_quantity = []
sell_orders_quantity = []
orders_quantity = client.Order.Order_getOrders(filter=json.dumps({"open": True})).result()[0]
h=0
while h <= len(orders_quantity)-1:
if orders_quantity[h]["side"] == "Sell":
sell_orders_quantity.append(orders_quantity[h])
elif orders_quantity[h]["side"] == "Buy":
buy_orders_quantity.append(orders_quantity[h])
h += 1
if highest_high == last_highs[rightBars] and positions_quantity == 0:
if buy_orders_quantity == []:
client.Order.Order_new(symbol = symbol, orderQty = orderQty*1, side = "Buy", ordType = 'Stop', stopPx = (highest_high+0.5), execInst ='LastPrice' ).result()
elif buy_orders_quantity != []:
orderID = buy_orders_quantity[0]["orderID"]
client.Order.Order_amend(orderID=orderID, orderQty=orderQty*1, stopPx = (highest_high+0.5)).result()
else:
pass
elif highest_high == last_highs[rightBars] and positions_quantity > 0:
#dont place any additional long
pass
elif highest_high == last_highs[rightBars] and positions_quantity < 0:
if buy_orders_quantity != []:
orderID = buy_orders_quantity[0]["orderID"]
client.Order.Order_amend(orderID=orderID, orderQty=orderQty*2, stopPx = (highest_high+0.5)).result()
else:
client.Order.Order_new(symbol = symbol, orderQty = (orderQty)*2, side = "Buy", ordType = 'Stop', stopPx = (highest_high+0.5), execInst ='LastPrice' ).result()
elif lowest_low == last_lows[rightBars] and positions_quantity == 0:
if sell_orders_quantity == []:
client.Order.Order_new(symbol = symbol, orderQty = (orderQty)*-1, side = "Sell", ordType = 'Stop', stopPx = (lowest_low-0.5), execInst ='LastPrice' ).result()
elif sell_orders_quantity != []:
orderID = sell_orders_quantity[0]["orderID"]
client.Order.Order_amend(orderID=orderID, orderQty=orderQty*-1, stopPx = (lowest_low-0.5)).result()
else:
pass
elif lowest_low == last_lows[rightBars] and positions_quantity < 0:
#dont place any additional shorts
pass
elif lowest_low == last_lows[rightBars] and positions_quantity > 0:
if sell_orders_quantity != []:
orderID = sell_orders_quantity[0]["orderID"]
client.Order.Order_amend(orderID=orderID, orderQty=orderQty*-2, stopPx = (lowest_low-0.5)).result()
else:
client.Order.Order_new(symbol = symbol, orderQty = (orderQty)*-2, side = "Sell", ordType = 'Stop', stopPx = (lowest_low-0.5), execInst ='LastPrice' ).result()
positions_quantity = client.Position.Position_get().result()[0][0]["currentQty"]
buy_orders_quantity = []
sell_orders_quantity = []
orders_quantity = client.Order.Order_getOrders(filter=json.dumps({"open": True})).result()[0]
h=0
while h <= len(orders_quantity)-1:
if orders_quantity[h]["side"] == "Sell":
sell_orders_quantity.append(orders_quantity[h])
elif orders_quantity[h]["side"] == "Buy":
buy_orders_quantity.append(orders_quantity[h])
h += 1
if positions_quantity > 0:
if sell_orders_quantity != []:
orderID = sell_orders_quantity[0]["orderID"]
client.Order.Order_amend(orderID=orderID, orderQty=orderQty*-2).result()
elif positions_quantity < 0:
if buy_orders_quantity != []:
orderID = buy_orders_quantity[0]["orderID"]
client.Order.Order_amend(orderID=orderID, orderQty=orderQty*2).result()
print("Your current position is " + str(positions_quantity))
print("This is iteration: " + str(t))
t += 1

Answer 1

As concerns my second question, I solved it in the following way:
In the command terminal, type: pip freeze > requirements.txt
The file contains all dependencies.
As concerns question 1 I still dont understand what code exactly needs to be put in the section main.py.
Thanks!

Answer 2

Cloud Functions is not an adequate product for your use case. They are mostly used for lightweight calculations or not high resource consuming methods.
The magic of CF consists in that they execute your code whenever you hit the URL that belongs to it. This is important to understand for your question number 1. If you want your function to work, you need to always create a method that accepts the "request" parameter. As it is the information from the HTTP request made when the URL is hit.
You can take a look at this document for reference.
You function should always start like this
from flask #import your dependencies
def my_awesome_function(request):
#Your logic
In this case you should write "my_awesome_function" on the Function to Execute textbox.
You also have to be careful with your resources, as CF have 5 presentations. They differ in CPU and Memory you can read more about this here.
This, among many reasons, you should not use Cloud Functions for your bot. I could recommend you to use a virtual machine, but activities related to use of the Services for cryptocurrency mining without Google's prior written approval are frowned upon and may result in the deactivation of your product as stated in the terms of service.