Free, open source crypto trading bot
3473fd3c90
This commit includes: * Reducing complexity of modules * Remove unneeded wrapper classes * Implement init() for each module which initializes everything based on the config * Implement some basic tests |
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rpc | ||
test | ||
.gitignore | ||
.pylintrc | ||
analyze.py | ||
config.json.example | ||
Dockerfile | ||
exchange.py | ||
LICENSE | ||
main.py | ||
misc.py | ||
persistence.py | ||
README.md | ||
requirements.txt |
freqtrade
Simple High frequency trading bot for crypto currencies. Currently supported exchanges: bittrex, poloniex (partly implemented)
This software is for educational purposes only. Don't risk money which you are afraid to lose.
The command interface is accessible via Telegram (not required).
Just register a new bot on https://telegram.me/BotFather
and enter the telegram token
and your chat_id
in config.json
Persistence is achieved through sqlite.
Telegram RPC commands:
- /start: Starts the trader
- /stop: Stops the trader
- /status: Lists all open trades
- /profit: Lists cumulative profit from all finished trades
- /forcesell <trade_id>: Instantly sells the given trade (Ignoring
minimum_roi
). - /performance: Show performance of each finished trade grouped by pair
Config
minimal_roi
is a JSON object where the key is a duration
in minutes and the value is the minimum ROI in percent.
See the example below:
"minimal_roi": {
"2880": 0.005, # Sell after 48 hours if there is at least 0.5% profit
"1440": 0.01, # Sell after 24 hours if there is at least 1% profit
"720": 0.02, # Sell after 12 hours if there is at least 2% profit
"360": 0.02, # Sell after 6 hours if there is at least 2% profit
"0": 0.025 # Sell immediately if there is at least 2.5% profit
},
The other values should be self-explanatory, if not feel free to raise a github issue.
Prerequisites
- python3.6
- sqlite
- TA-lib binaries
Install
$ cd freqtrade/
# copy example config. Dont forget to insert your api keys
$ cp config.json.example config.json
$ python -m venv .env
$ source .env/bin/activate
$ pip install -r requirements.txt
$ ./main.py
Docker
$ cd freqtrade
$ docker build -t freqtrade .
$ docker run --rm -it freqtrade