{"repo":"gregyjames/ZenithTA","free":true,"listed":false,"github":"https://github.com/gregyjames/ZenithTA","clone":"git clone https://github.com/gregyjames/ZenithTA.git","description":"A high performance python technical analysis library written in Rust and the Numpy C API.","language":"Rust","stars":220,"topics":["rust","python","stocks","stock-market","indicators","performance","wrapper","finance","financial-analysis","fintech"],"license":"MIT","category":"trading","readme_excerpt":"ZenithTA Formerly 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 install pip3 install zenithta 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","default_branch":null,"files":null,"tree":[],"storefront":"/r/gregyjames","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/gregyjames/ZenithTA/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}