A high performance python technical analysis library written in Rust and the Numpy C API.

Related tags

Machine learning python rust finance wrapper performance fintech stock-market indicator stocks financial-analysis indicators
Overview

Rust

Panther

A efficient, high-performance python technical analysis library written in Rust using PyO3 and rust-numpy.

Indicators

  • ATR
  • CMF
  • SMA
  • EMA
  • RSI
  • MACD
  • ROC

How to build (Windows)

  • Run cargo build --release from the main directory.
  • Get the generated dll from the target/release directory.
  • Rename extension from .dll to .pyd.
  • Place .pyd file in the same folder as script.
  • Put from panther import * in python script.

Speed

On average, I found the Panther calculations of these indicators to be about 9x or 900% faster than the industry standard way of calculating these indicators using Pandas. Don't believe me? Install the library and run the tests in the speed_tests directory to see it for yourself :)

License

MIT License

Copyright (c) 2022 Greg James

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Comments
  • How to rename the compiled code released on MAC with M1 chip?

    How to rename the compiled code released on MAC with M1 chip?

    Hi,

    I run the cargo build --release script from the main directory, and libpanther.d and libpanther.dylib are created in the release folder along with many *.d and *.dylib files in the build and deps folder. How do I rename those files such that they can work with my python script?

    Any suggestions?

    opened by jeffrey82221 6
  • Technical analysis is cringe and a scam

    Technical analysis is cringe and a scam

    Firstly, this is a really cool library and some of it (SMA and EMA) is useful for things that aren't technical analysis.

    Secondly, you're clearly a smart guy and I can see you're interested in other quant trading and quant finance stuff. I would encourage you to focus on those things instead, because they are actually useful and won't be embarrassing like TA is. And also because the existence of a high-performance TA library like this serves to legitimize TA.

    opened by kevinheavey 6
  • Build and publish wheels on GitHub Actions using maturin-action

    Build and publish wheels on GitHub Actions using maturin-action

    Unfortunately the panther package name is already taken on PyPI: https://pypi.org/project/panther/ , so you need to rename the Python package.

    Fixes #3

    opened by messense 2
  • Weird initial values from ema function

    Weird initial values from ema function

    Something seems to be wrong in the init of the ema function. Just compare these two calculations from the speed_tests examples:

    # first 20 values of the panther ema function
ema(data['Close'], 4)[:20]

    # first 20 values of the pandas implementation
data['Close'].ewm(span=4, adjust=False).mean().head(20)

    Later on the values seems to be closer, but still not the same...

    bug 
    opened by Franky1 0
  • Process Pandas Dataframe instead of list?

    Process Pandas Dataframe instead of list?

    Usually Pandas Dataframes are used in all Python financial frameworks/workflows.

    Is it possible to rewrite the Rust functions so that they can directly process a Pandas dataframe? Currently everything has to be converted: DataFrame > List > Panther > List > DataFrame

    In addition, the speed_tests are not fully meaningful in this context, because the conversions to and from lists have to be counted.

    Add: I tried this out briefly. If you want to get it back into a pandas dataframe, all speed advantages are gone. Can you show a real workflow example with a pandas dataframe?

    enhancement 
    opened by Franky1 4
  • I get the error

    I get the error "linking with `cc` failed"

    warning: function is never used: sma_helper --> src/lib.rs:6:4 | 6 | fn sma_helper(price_ndarray: &Array1, period: usize) -> Array1{ | ^^^^^^^^^^ | = note: #[warn(dead_code)] on by default

    error: linking with cc failed: exit status: 1

    opened by cryp2one 3
Owner
Greg
Computer Science Major with a passion for FinTech, Blockchain, and Social media analysis.
Greg
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