%global _empty_manifest_terminate_build 0 Name: python-margot Version: 1.13 Release: 1 Summary: An algorithmic trading framework for PyData. License: apache-2.0 URL: https://github.com/pymargot/margot Source0: https://mirrors.nju.edu.cn/pypi/web/packages/ea/16/d1db37c2b0d80eb1bd36f82dfd32abf1ba404f22d4554ef2d3f5fc8ea267/margot-1.13.tar.gz BuildArch: noarch Requires: python3-alpha-vantage Requires: python3-exchange-calendars Requires: python3-ftx Requires: python3-numpy Requires: python3-pandas Requires: python3-pyfolio Requires: python3-pytz Requires: python3-scipy Requires: python3-tables Requires: python3-versioneer %description [![](https://api.codacy.com/project/badge/Grade/1d42c486297a49158494e5f31b25793b)](https://app.codacy.com/manual/pymargot/margot?utm_source=github.com&utm_medium=referral&utm_content=pymargot/margot&utm_campaign=Badge_Grade_Dashboard) [![](https://travis-ci.org/pymargot/margot.svg?branch=master)](https://travis-ci.org/github/pymargot/margot) [![](https://readthedocs.org/projects/margot/badge/?version=latest)](https://margot.readthedocs.io/en/latest/?badge=latest) [![](https://codecov.io/gh/pymargot/margot/branch/master/graph/badge.svg)](https://codecov.io/gh/pymargot/margot) [![](https://img.shields.io/github/license/pymargot/margot)](https://github.com/pymargot/margot/blob/master/LICENSE) ![](https://img.shields.io/pypi/wheel/margot) ![](https://img.shields.io/pypi/pyversions/margot) [![](https://img.shields.io/pypi/v/margot)](https://pypi.org/project/margot/) # What is margot? Margot makes it super easy to backtest trading elgorithms. Firstly, Margot makes it super easy tocreate neat and tidy Pandas dataframes for time-series analysis. Margot manages data collection, caching, cleaning, feature generation, management and persistence using a clean, declarative API. If you've ever used Django you will find this approach similar to the Django ORM. Margot also provides a simple framework for writing and backtesting systematic trading algorithms. Results from margot's trading algorithms can be analysed using pyfolio. # Getting Started pip install margot Next you need to make sure you have a couple of important environment variables set:: export ALPHAVANTAGE_API_KEY=YOUR_API_KEY export DATA_CACHE=PATH_TO_FOLDER_TO_STORE_HDF5_FILES Once you've done that, try running the code in the [notebook](notebook.margot.data). # Status This is still an early stage software project, and should not be used for live trading just yet. # Documentation The documentation is at [readthedocs](https://margot.readthedocs.io/en/latest/). # Contributing Feel free to make a pull request or chat about your idea first using [issues](https://github.com/atkinson/margot/issues). Dependencies are kept to a minimum. Generally if there's a way to do something in the standard library (or numpy / Pandas), let's do it that way rather than add another library. # License Margot is licensed for use under Apache 2.0. For details see [the License](https://github.com/atkinson/margot/blob/master/LICENSE). %package -n python3-margot Summary: An algorithmic trading framework for PyData. Provides: python-margot BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-margot [![](https://api.codacy.com/project/badge/Grade/1d42c486297a49158494e5f31b25793b)](https://app.codacy.com/manual/pymargot/margot?utm_source=github.com&utm_medium=referral&utm_content=pymargot/margot&utm_campaign=Badge_Grade_Dashboard) [![](https://travis-ci.org/pymargot/margot.svg?branch=master)](https://travis-ci.org/github/pymargot/margot) [![](https://readthedocs.org/projects/margot/badge/?version=latest)](https://margot.readthedocs.io/en/latest/?badge=latest) [![](https://codecov.io/gh/pymargot/margot/branch/master/graph/badge.svg)](https://codecov.io/gh/pymargot/margot) [![](https://img.shields.io/github/license/pymargot/margot)](https://github.com/pymargot/margot/blob/master/LICENSE) ![](https://img.shields.io/pypi/wheel/margot) ![](https://img.shields.io/pypi/pyversions/margot) [![](https://img.shields.io/pypi/v/margot)](https://pypi.org/project/margot/) # What is margot? Margot makes it super easy to backtest trading elgorithms. Firstly, Margot makes it super easy tocreate neat and tidy Pandas dataframes for time-series analysis. Margot manages data collection, caching, cleaning, feature generation, management and persistence using a clean, declarative API. If you've ever used Django you will find this approach similar to the Django ORM. Margot also provides a simple framework for writing and backtesting systematic trading algorithms. Results from margot's trading algorithms can be analysed using pyfolio. # Getting Started pip install margot Next you need to make sure you have a couple of important environment variables set:: export ALPHAVANTAGE_API_KEY=YOUR_API_KEY export DATA_CACHE=PATH_TO_FOLDER_TO_STORE_HDF5_FILES Once you've done that, try running the code in the [notebook](notebook.margot.data). # Status This is still an early stage software project, and should not be used for live trading just yet. # Documentation The documentation is at [readthedocs](https://margot.readthedocs.io/en/latest/). # Contributing Feel free to make a pull request or chat about your idea first using [issues](https://github.com/atkinson/margot/issues). Dependencies are kept to a minimum. Generally if there's a way to do something in the standard library (or numpy / Pandas), let's do it that way rather than add another library. # License Margot is licensed for use under Apache 2.0. For details see [the License](https://github.com/atkinson/margot/blob/master/LICENSE). %package help Summary: Development documents and examples for margot Provides: python3-margot-doc %description help [![](https://api.codacy.com/project/badge/Grade/1d42c486297a49158494e5f31b25793b)](https://app.codacy.com/manual/pymargot/margot?utm_source=github.com&utm_medium=referral&utm_content=pymargot/margot&utm_campaign=Badge_Grade_Dashboard) [![](https://travis-ci.org/pymargot/margot.svg?branch=master)](https://travis-ci.org/github/pymargot/margot) [![](https://readthedocs.org/projects/margot/badge/?version=latest)](https://margot.readthedocs.io/en/latest/?badge=latest) [![](https://codecov.io/gh/pymargot/margot/branch/master/graph/badge.svg)](https://codecov.io/gh/pymargot/margot) [![](https://img.shields.io/github/license/pymargot/margot)](https://github.com/pymargot/margot/blob/master/LICENSE) ![](https://img.shields.io/pypi/wheel/margot) ![](https://img.shields.io/pypi/pyversions/margot) [![](https://img.shields.io/pypi/v/margot)](https://pypi.org/project/margot/) # What is margot? Margot makes it super easy to backtest trading elgorithms. Firstly, Margot makes it super easy tocreate neat and tidy Pandas dataframes for time-series analysis. Margot manages data collection, caching, cleaning, feature generation, management and persistence using a clean, declarative API. If you've ever used Django you will find this approach similar to the Django ORM. Margot also provides a simple framework for writing and backtesting systematic trading algorithms. Results from margot's trading algorithms can be analysed using pyfolio. # Getting Started pip install margot Next you need to make sure you have a couple of important environment variables set:: export ALPHAVANTAGE_API_KEY=YOUR_API_KEY export DATA_CACHE=PATH_TO_FOLDER_TO_STORE_HDF5_FILES Once you've done that, try running the code in the [notebook](notebook.margot.data). # Status This is still an early stage software project, and should not be used for live trading just yet. # Documentation The documentation is at [readthedocs](https://margot.readthedocs.io/en/latest/). # Contributing Feel free to make a pull request or chat about your idea first using [issues](https://github.com/atkinson/margot/issues). Dependencies are kept to a minimum. Generally if there's a way to do something in the standard library (or numpy / Pandas), let's do it that way rather than add another library. # License Margot is licensed for use under Apache 2.0. For details see [the License](https://github.com/atkinson/margot/blob/master/LICENSE). %prep %autosetup -n margot-1.13 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-margot -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Wed May 31 2023 Python_Bot - 1.13-1 - Package Spec generated