Automated crypto trading in Python.
This is my attempt to write a robust python3 framework to implement different automated trading strategies.
This project works with CCXT and is therefor compatible with many exchanges.
This project is compatible with python3 and there's no reason why I should spend more time to make it compatible with python2.
pip install ccxt
pip install numpy
pip install pandas
git clone https://github.com/Insider-Pr/Crypto-bot-in-python.git
cd python-crypto-bot
Rename .env.sample to .env and edit it to your preferences.
API_KEY= YourApiKey
API_SECRET= YourApiSecret
ASSET=BTC or any asset available on the exchance
MARKET=USDT or any base asset available on the exchange
TIMEFRAME=1m or any timeframce available
COINS_ASSET=1 used for backtest, how much assets to start with
COINS_MARKET=100 used for backtest, how much base assets to start with
EXCHANGE=poloniex your choice of exchange available in CCXT
FEES=0.125 used for backtest, emulate fees in %
SPREAD=0.00 used for backtest, emulate spread in %
ALLOCATION=1 how much of your assets do you want to play at each order (1==100%)
INTERVAL=10 used for forward test and live, interval between each call to the API in seconds
START_DATE=2021-01-01 00:00:00 date at which backtest should start, if not specified, bot will run in forward test mode python bot.py
This will launch the trading strategy on the pair ASSET/MARKET, with a candlestick period of TIMEFRAME, starting on START_DATE.
You can see the result in the command line AND the output/index.html file in the project
Leave START_DATE empty to run forward test
A new call is made every INTERVAL seconds. You can follow the trades almost live be reloading output/index.html
python bot.py --live
### Important files
`shared.py` contains a bunch of variable shared across the different modules
`bot.py` is where everything start
`botapi.py` is where the connections are made between the bot and the registered APIs.
`botstrategy.py` is where the magic happens. The default strategy is a simple Moving Average Crossover strategy. IT WILL NOT WORK LIVE! Feel free to experiment and write your own strategy
`botindicators.py` contains all the indicator available in bostrategy.py
`botchart.py` generates the candlesticks data in backtest mode, as well as the data for the final graph viewable in `output/output.html`. It is based on [googlecharts](https://developers.google.com/chart/) and can be overwelming work with at first. If you change the strategy, there is a 99% that you need to modify output.html and botchart.py as well.
If you want rendering of your trades, you gonna have to dig into this. Sorry.
### Last notes
What is this spreadPercentage thingy in shared.py?
I implemented this to emulate the difference between ask and bid price. How many time did I think I was gonna get rich in a matter of days just because I forgot about the spread. Going live is full of bad surprises.
Kraken's api has been quite a turbulent child recently, often returning a time out. There is a [pull request](https://github.com/veox/python3-krakenex/pull/100) on krakenex to attempt to fix that but is not merge to master yet... so be patient or try and fix it by yourself ;)
Once again I do not recommend the use of Kraken API.
Also pairs on kraken are a bit weird, if you intend to trade on the ETHXBT market you should use XXBT_XETH as the currency_pair argument. I'll probably do some more work on that in the future, but for now... that's the way.
I know this is not the best readme ever but hey... at least there is one.