Python service that collects crypto-currencies symbols pairs data & allows setup of notifications & automatic trading
Project description
XTCryptoSignals
XTCryptoSignals is a Python service that collects crypto-currencies symbols pairs data such as BTC/USDT, ETH/BTC or any other pair that a Crypto-currency Exchange API supports and allows the user to setup signals based on rules to send real-time notifications through e-mail or Push Notifications to the browser or mobile app. It will allow as well automatic trading.
Roadmap
- Add crypto-currencies exchanges (Dec 2018)
- Setup notification rules (Dec 2018 / Jan 2019)
- Implement e-mail and web browser push notifications signals (Jan 2019)
- Start building Unit, functional and end-to-end testing (From Jan 2019)
- Implement automatic trading (Feb/Mar 2019)
- Build iOS app (Mar 2019)
Getting Started
Pre-requisites
Installation
Install from source
Clone project repository
hg clone ssh://hg@bitbucket.org/pantunes/xtcryptosignals
cd xtcryptosignals
Setup Python virtual environment:
virtualenv venv -p python3
source venv/bin/activate
Install package
pip install -e .
(Dependencies will be installed automatically from requirements.txt)
Install from PyPi
Create folder project:
mkdir <project directory>
cd <project directory>
Setup Python virtual environment:
virtualenv venv -p python3
source venv/bin/activate
Install package
pip install xtcryptosignals
pip install -e .
(Dependencies will be installed automatically from requirements.txt)
Start service
xt-crypto-signals
Starts standalone script without Celery (for testing purposes)
xt-crypto-signals-test
Setup
There is already an initial setup with some crypto-currencies (coins and tokens) that can be changed in settings_exchanges.py.
BIBOX: {
'pairs': [
('ONT', 'USDT'),
('ONT', 'BTC'),
('ONT', 'ETH'),
('NEO', 'USDT'),
('NEO', 'BTC'),
('NEO', 'ETH'),
('LTC', 'USDT'),
('LTC', 'BTC'),
('CARD', 'ETH'),
]
}
UPHOLD: {
'pairs': [
('BTC', 'USD'),
('ETH', 'USD'),
('LTC', 'USD'),
('XRP', 'USD'),
]
}
Initial setup to create dynamic MongoDB collections for data segmentation categorized by Exchanges pooling frequency in settings.py.
HISTORY_FREQUENCY = (
'10s', '30s', '1m', '10m', '30m', '1h', '3h', '6h', '12h', '24h'
)
Results
This service is fast as it uses threading. It takes around 6 seconds to collect data of 70 crypto-currencies symbols pairs from 7 exchanges and save it in 11 collections in MongoDB. (Depending on external Exchange APIs availability and Internet connection/latency)
Disclaimer
This project is work in progress and when it comes to trading use it at your own risk.
License
Project details
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