Trading Strategy framework for Python
Trading Strategy framework is a Python framework for algorithmic trading on decentralised exchanges.
- Download decentralised finance market data sets
- Develop and backtest trading strategies in Jupyter Notebook
- Live trade execution for onchain trading
- Smart contract vault support for turning your trading strategy to a third-party investable vault
The trading-strategy library provides data fetching for backtesting and live trading.
It is using backtesting data and real-time price feeds from Trading Strategy Protocol.
Use cases
-
Analyse cryptocurrency investment opportunities on decentralised exchanges (DEXes)
-
Creating trading algorithms and trading bots that trade on DEXes
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Deploy trading strategies as on-chain smart contracts where users can invest and withdraw with their wallets
Features
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Supports multiple blockchains like Ethereum mainnet, Binance Smart Chain and Polygon
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Access trading data from on-chain decentralised exchanges like SushiSwap, QuickSwap and PancakeSwap
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Integration with Jupyter Notebook for easy manipulation of data. See example notebooks.
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Write algorithmic trading strategies for decentralised exchange
Getting started
See the Getting Started repository and the rest of the Trading Strategy documentation.
Prerequisites
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Python 3.10
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Understanding Python package management and installation (unless using Dev Container from teh above)
Installing the package
You can install this package with
Poetry as a dependency:
poetry add trading-strategy -E direct-feed
Poetry, local development:
poetry install -E direct-feed
Pip:
pip install "trading-strategy[direct-feed]"
Note: trading-strategy package provides trading data
download and management functionality only. If you want to developed
automated trading strategies you need to install trade-executor package as well.
Documentation
Community
Read more documentation how to develop this package.
License
GNU AGPL 3.0.
Metadata
Release files for trading-strategy 0.28
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| trading_strategy-0.28.tar.gz | 57.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| trading_strategy-0.28-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 116.2 MB
Release files / trading_strategy-0.28.tar.gz
| Download URL | trading_strategy-0.28.tar.gz |
|---|---|
| Size | 57.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.4 CPython/3.11.10 Darwin/24.6.0
|
Release files / trading_strategy-0.28-py3-none-any.whl
| Download URL | trading_strategy-0.28-py3-none-any.whl |
|---|---|
| Size | 58.6 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.4 CPython/3.11.10 Darwin/24.6.0
|