trading-strategy


Nametrading-strategy JSON
Version 0.24.4 PyPI version JSON
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home_pagehttps://tradingstrategy.ai
SummaryAlgorithmic trading data for cryptocurrencies and DEXes like Uniswap, Aave and PancakeSwap
upload_time2024-10-25 16:54:51
maintainerNone
docs_urlNone
authorMikko Ohtamaa
requires_python<3.13,>=3.10
licenseAGPL
keywords algorithmic trading ethereum polygon avalanche aave arbitrum cryptocurrency uniswap quantitative finance binance blockchain pancakeswap polygon web3
VCS
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# 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](https://tradingstrategy.ai/trading-view/backtesting) and [real-time price feeds](https://tradingstrategy.ai/trading-view)
from [Trading Strategy Protocol](https://tradingstrategy.ai/). 

# Use cases

* Analyse cryptocurrency investment opportunities on [decentralised exchanges (DEXes)](https://tradingstrategy.ai/trading-view/exchanges)

* Creating trading algorithms and trading bots that trade on DEXes

* Deploy trading strategies as on-chain smart contracts where users can invest and withdraw with their wallets

# Features

* Supports multiple blockchains like [Ethereum mainnet](https://tradingstrategy.ai/trading-view/ethereum), 
  [Binance Smart Chain](https://tradingstrategy.ai/trading-view/binance) and 
  [Polygon](https://tradingstrategy.ai/trading-view/polygon)

* Access trading data from on-chain decentralised exchanges like
  [SushiSwap](https://tradingstrategy.ai/trading-view/ethereum/sushi), [QuickSwap](https://tradingstrategy.ai/trading-view/polygon/quickswap) and [PancakeSwap](https://tradingstrategy.ai/trading-view/binance/pancakeswap-v2)

* Integration with Jupyter Notebook for easy manipulation of data.
  See [example notebooks](https://tradingstrategy.ai/docs/programming/code-examples/index.html).

* Write [algorithmic trading strategies](https://tradingstrategy.ai/docs/programming/strategy-examples/index.html) for  decentralised exchange 

# Getting started 

See [the Getting Started repository](https://github.com/tradingstrategy-ai/getting-started) and the rest of the [Trading Strategy documentation](https://tradingstrategy.ai/docs/).

# Prerequisites

* Python 3.10

* [Understanding Python package management and installation](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/)
  (unless using Dev Container from teh above)

# Installing the package

You can install this package with 

[Poetry](https://python-poetry.org/) as a dependency:

```shell
poetry add trading-strategy -E direct-feed
```

Poetry, local development:

```shell
poetry install -E direct-feed
```

Pip:

```shell
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](https://github.com/tradingstrategy-ai/trade-executor/).

# Documentation

- [Documentation](https://tradingstrategy.ai/docs/).

- [Getting started](https://tradingstrategy.ai/docs/getting-started.html).

Community
---------

* [Trading Strategy website](https://tradingstrategy.ai)

* [Blog](https://tradingstrategy.ai/blog)

* [Twitter](https://twitter.com/TradingProtocol)

* [Discord](https://tradingstrategy.ai/community#discord) 

* [Telegram channel](https://t.me/trading_protocol)

* [Changelog and version history](https://github.com/tradingstrategy-ai/trading-strategy/blob/master/CHANGELOG.md)

[Read more documentation how to develop this package](https://tradingstrategy.ai/docs/programming/development.html).

# License

GNU AGPL 3.0. 

            

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