path: root/python-zipline-reloaded.spec

%global _empty_manifest_terminate_build 0
Name:		python-zipline-reloaded
Version:	2.4
Release:	1
Summary:	A Pythonic backtester for trading algorithms
License:	 Apache License Version 2.0, January 2004 http://www.apache.org/licenses/  TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION  1. Definitions.  "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document.  "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License.  "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity.  "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License.  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While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability.  END OF TERMS AND CONDITIONS  APPENDIX: How to apply the Apache License to your work.  To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!)  The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives.  Copyright 2018 Quantopian, Inc.  Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at  http://www.apache.org/licenses/LICENSE-2.0  Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. 
URL:		https://pypi.org/project/zipline-reloaded/
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/65/a8/acbb91218decd68b4c8016579ed59c80666f165cb889b15846e296b52bc3/zipline-reloaded-2.4.tar.gz

Requires:	python3-alembic
Requires:	python3-bcolz-zipline
Requires:	python3-bottleneck
Requires:	python3-click
Requires:	python3-empyrical-reloaded
Requires:	python3-h5py
Requires:	python3-intervaltree
Requires:	python3-iso3166
Requires:	python3-iso4217
Requires:	python3-lru-dict
Requires:	python3-multipledispatch
Requires:	python3-networkx
Requires:	python3-numexpr
Requires:	python3-numpy
Requires:	python3-pandas
Requires:	python3-patsy
Requires:	python3-dateutil
Requires:	python3-interface
Requires:	python3-pytz
Requires:	python3-requests
Requires:	python3-scipy
Requires:	python3-six
Requires:	python3-sqlalchemy
Requires:	python3-statsmodels
Requires:	python3-ta-lib
Requires:	python3-tables
Requires:	python3-toolz
Requires:	python3-exchange-calendars
Requires:	python3-flake8
Requires:	python3-black
Requires:	python3-pre-commit
Requires:	python3-Cython
Requires:	python3-Cython
Requires:	python3-Sphinx
Requires:	python3-numpydoc
Requires:	python3-sphinx-autobuild
Requires:	python3-pydata-sphinx-theme
Requires:	python3-sphinx-markdown-tables
Requires:	python3-m2r2
Requires:	python3-tox
Requires:	python3-pytest
Requires:	python3-pytest-cov
Requires:	python3-pytest-xdist
Requires:	python3-pytest-timeout
Requires:	python3-parameterized
Requires:	python3-testfixtures
Requires:	python3-flake8
Requires:	python3-matplotlib
Requires:	python3-responses
Requires:	python3-pandas-datareader
Requires:	python3-click
Requires:	python3-coverage
Requires:	python3-pytest-rerunfailures

%description
<p align="center">
<a href="https://zipline.ml4trading.io">
<img src="https://i.imgur.com/DDetr8I.png" width="25%">
</a>
</p>

# Backtest your Trading Strategies

| Version Info        | [![Python](https://img.shields.io/pypi/pyversions/zipline-reloaded.svg?cacheSeconds=2592000)](https://pypi.python.org/pypi/zipline-reloaded) [![Anaconda-Server Badge](https://anaconda.org/ml4t/zipline-reloaded/badges/platforms.svg)](https://anaconda.org/ml4t/zipline-reloaded) [![Release](https://img.shields.io/pypi/v/zipline-reloaded.svg?cacheSeconds=2592000)](https://pypi.org/project/zipline-reloaded/) [![Anaconda-Server Badge](https://anaconda.org/ml4t/zipline-reloaded/badges/version.svg)](https://anaconda.org/ml4t/zipline-reloaded)                                                                                                                                                                                                 |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **Test** **Status** | [![CI Tests](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/ci_tests_full.yml/badge.svg)](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/unit_tests.yml) [![PyPI](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/build_wheels.yml/badge.svg)](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/build_wheels.yml) [![Anaconda](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/conda_package.yml/badge.svg)](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/conda_package.yml) [![codecov](https://codecov.io/gh/stefan-jansen/zipline-reloaded/branch/main/graph/badge.svg)](https://codecov.io/gh/stefan-jansen/zipline-reloaded) |
| **Community**       | [![Discourse](https://img.shields.io/discourse/topics?server=https%3A%2F%2Fexchange.ml4trading.io%2F)](https://exchange.ml4trading.io) [![ML4T](https://img.shields.io/badge/Powered%20by-ML4Trading-blue)](https://ml4trading.io) [![Twitter](https://img.shields.io/twitter/follow/ml4trading.svg?style=social)](https://twitter.com/ml4trading)                                                                                                                                                                                                                                                                                                                                                                                                           |

Zipline is a Pythonic event-driven system for backtesting, developed and used as the backtesting and live-trading engine by [crowd-sourced investment fund Quantopian](https://www.bizjournals.com/boston/news/2020/11/10/quantopian-shuts-down-cofounders-head-elsewhere.html). Since it closed late 2020, the domain that had hosted these docs expired. The library is used extensively in the book [Machine Larning for Algorithmic Trading](https://ml4trading.io)
by [Stefan Jansen](https://www.linkedin.com/in/applied-ai/) who is trying to keep the library up to date and available to his readers and the wider Python algotrading community.

- [Join our Community!](https://exchange.ml4trading.io)
- [Documentation](https://zipline.ml4trading.io)

## Features

- **Ease of Use:** Zipline tries to get out of your way so that you can focus on algorithm development. See below for a code example.
- **Batteries Included:** many common statistics like moving average and linear regression can be readily accessed from within a user-written algorithm.
- **PyData Integration:** Input of historical data and output of performance statistics are based on Pandas DataFrames to integrate nicely into the existing PyData ecosystem.
- **Statistics and Machine Learning Libraries:** You can use libraries like matplotlib, scipy, statsmodels, and scikit-klearn to support development, analysis, and visualization of state-of-the-art trading systems.

> **Note:** Release 2.4 updates Zipline to use [exchange_calendars](https://github.com/gerrymanoim/exchange_calendars) >= 4.2. This is a major version update and may break existing code (which we have tried to avoid but cannot guarantee). Please review the changes [here](https://github.com/gerrymanoim/exchange_calendars/issues/61).

## Installation

Zipline supports Python >= 3.8 and is compatible with current versions of the relevant [NumFOCUS](https://numfocus.org/sponsored-projects?_sft_project_category=python-interface) libraries, including [pandas](https://pandas.pydata.org/) and [scikit-learn](https://scikit-learn.org/stable/index.html).

If your system meets the pre-requisites described in the [installation instructions](https://zipline.ml4trading.io/install.html), you can install Zipline using `pip` by running:

```bash
pip install zipline-reloaded
```

> **Note:** Installation under Python 3.11 requires building `h5py` [from source](https://docs.h5py.org/en/stable/build.html#source-installation) until [wheels become available](https://github.com/h5py/h5py/issues/2146).

Alternatively, if you are using the [Anaconda](https://www.anaconda.com/products/individual) or [miniconda](https://docs.conda.io/en/latest/miniconda.html) distributions, you can use

> **Note:** We are currently working to transition the conda package to [conda-forge](https://conda-forge.org/docs/index.html).

```bash
conda install -c conda-forge zipline-reloaded
```

You can also [enable](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-channels.html) `conda-forge` by listing it in your `.condarc`.

In case you are installing `zipline-reloaded` alongside other packages and encounter [conflict errors](https://github.com/conda/conda/issues/9707), consider using [mamba](https://github.com/mamba-org/mamba) instead.

See the [installation](https://zipline.ml4trading.io/install.html) section of the docs for more detailed instructions.

## Quickstart

See our [getting started tutorial](https://zipline.ml4trading.io/beginner-tutorial).

The following code implements a simple dual moving average algorithm.

```python
from zipline.api import order_target, record, symbol


def initialize(context):
    context.i = 0
    context.asset = symbol('AAPL')


def handle_data(context, data):
    # Skip first 300 days to get full windows
    context.i += 1
    if context.i < 300:
        return

    # Compute averages
    # data.history() has to be called with the same params
    # from above and returns a pandas dataframe.
    short_mavg = data.history(context.asset, 'price', bar_count=100, frequency="1d").mean()
    long_mavg = data.history(context.asset, 'price', bar_count=300, frequency="1d").mean()

    # Trading logic
    if short_mavg > long_mavg:
        # order_target orders as many shares as needed to
        # achieve the desired number of shares.
        order_target(context.asset, 100)
    elif short_mavg < long_mavg:
        order_target(context.asset, 0)

    # Save values for later inspection
    record(AAPL=data.current(context.asset, 'price'),
           short_mavg=short_mavg,
           long_mavg=long_mavg)
```

You can then run this algorithm using the Zipline CLI. But first, you need to download some market data with historical prices and trading volumes:

```bash
$ zipline ingest -b quandl
$ zipline run -f dual_moving_average.py --start 2014-1-1 --end 2018-1-1 -o dma.pickle --no-benchmark
```

This will download asset pricing data sourced from [Quandl](https://www.quandl.com/databases/WIKIP/documentation?anchor=companies) (since [acquisition](https://www.nasdaq.com/about/press-center/nasdaq-acquires-quandl-advance-use-alternative-data) hosted by NASDAQ), and stream it through the algorithm over the specified time range. Then, the resulting performance DataFrame is saved as `dma.pickle`, which you can load and analyze from Python.

You can find other examples in the [zipline/examples](https://github.com/stefan-jansen/zipline-reloaded/tree/main/src/zipline/examples) directory.

## Questions, suggestions, bugs?

If you find a bug or have other questions about the library, feel free to [open an issue](https://github.com/stefan-jansen/zipline/issues/new) and fill out the template.


%package -n python3-zipline-reloaded
Summary:	A Pythonic backtester for trading algorithms
Provides:	python-zipline-reloaded
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
BuildRequires:	python3-cffi
BuildRequires:	gcc
BuildRequires:	gdb
%description -n python3-zipline-reloaded
<p align="center">
<a href="https://zipline.ml4trading.io">
<img src="https://i.imgur.com/DDetr8I.png" width="25%">
</a>
</p>

# Backtest your Trading Strategies

| Version Info        | [![Python](https://img.shields.io/pypi/pyversions/zipline-reloaded.svg?cacheSeconds=2592000)](https://pypi.python.org/pypi/zipline-reloaded) [![Anaconda-Server Badge](https://anaconda.org/ml4t/zipline-reloaded/badges/platforms.svg)](https://anaconda.org/ml4t/zipline-reloaded) [![Release](https://img.shields.io/pypi/v/zipline-reloaded.svg?cacheSeconds=2592000)](https://pypi.org/project/zipline-reloaded/) [![Anaconda-Server Badge](https://anaconda.org/ml4t/zipline-reloaded/badges/version.svg)](https://anaconda.org/ml4t/zipline-reloaded)                                                                                                                                                                                                 |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **Test** **Status** | [![CI Tests](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/ci_tests_full.yml/badge.svg)](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/unit_tests.yml) [![PyPI](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/build_wheels.yml/badge.svg)](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/build_wheels.yml) [![Anaconda](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/conda_package.yml/badge.svg)](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/conda_package.yml) [![codecov](https://codecov.io/gh/stefan-jansen/zipline-reloaded/branch/main/graph/badge.svg)](https://codecov.io/gh/stefan-jansen/zipline-reloaded) |
| **Community**       | [![Discourse](https://img.shields.io/discourse/topics?server=https%3A%2F%2Fexchange.ml4trading.io%2F)](https://exchange.ml4trading.io) [![ML4T](https://img.shields.io/badge/Powered%20by-ML4Trading-blue)](https://ml4trading.io) [![Twitter](https://img.shields.io/twitter/follow/ml4trading.svg?style=social)](https://twitter.com/ml4trading)                                                                                                                                                                                                                                                                                                                                                                                                           |

Zipline is a Pythonic event-driven system for backtesting, developed and used as the backtesting and live-trading engine by [crowd-sourced investment fund Quantopian](https://www.bizjournals.com/boston/news/2020/11/10/quantopian-shuts-down-cofounders-head-elsewhere.html). Since it closed late 2020, the domain that had hosted these docs expired. The library is used extensively in the book [Machine Larning for Algorithmic Trading](https://ml4trading.io)
by [Stefan Jansen](https://www.linkedin.com/in/applied-ai/) who is trying to keep the library up to date and available to his readers and the wider Python algotrading community.

- [Join our Community!](https://exchange.ml4trading.io)
- [Documentation](https://zipline.ml4trading.io)

## Features

- **Ease of Use:** Zipline tries to get out of your way so that you can focus on algorithm development. See below for a code example.
- **Batteries Included:** many common statistics like moving average and linear regression can be readily accessed from within a user-written algorithm.
- **PyData Integration:** Input of historical data and output of performance statistics are based on Pandas DataFrames to integrate nicely into the existing PyData ecosystem.
- **Statistics and Machine Learning Libraries:** You can use libraries like matplotlib, scipy, statsmodels, and scikit-klearn to support development, analysis, and visualization of state-of-the-art trading systems.

> **Note:** Release 2.4 updates Zipline to use [exchange_calendars](https://github.com/gerrymanoim/exchange_calendars) >= 4.2. This is a major version update and may break existing code (which we have tried to avoid but cannot guarantee). Please review the changes [here](https://github.com/gerrymanoim/exchange_calendars/issues/61).

## Installation

Zipline supports Python >= 3.8 and is compatible with current versions of the relevant [NumFOCUS](https://numfocus.org/sponsored-projects?_sft_project_category=python-interface) libraries, including [pandas](https://pandas.pydata.org/) and [scikit-learn](https://scikit-learn.org/stable/index.html).

If your system meets the pre-requisites described in the [installation instructions](https://zipline.ml4trading.io/install.html), you can install Zipline using `pip` by running:

```bash
pip install zipline-reloaded
```

> **Note:** Installation under Python 3.11 requires building `h5py` [from source](https://docs.h5py.org/en/stable/build.html#source-installation) until [wheels become available](https://github.com/h5py/h5py/issues/2146).

Alternatively, if you are using the [Anaconda](https://www.anaconda.com/products/individual) or [miniconda](https://docs.conda.io/en/latest/miniconda.html) distributions, you can use

> **Note:** We are currently working to transition the conda package to [conda-forge](https://conda-forge.org/docs/index.html).

```bash
conda install -c conda-forge zipline-reloaded
```

You can also [enable](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-channels.html) `conda-forge` by listing it in your `.condarc`.

In case you are installing `zipline-reloaded` alongside other packages and encounter [conflict errors](https://github.com/conda/conda/issues/9707), consider using [mamba](https://github.com/mamba-org/mamba) instead.

See the [installation](https://zipline.ml4trading.io/install.html) section of the docs for more detailed instructions.

## Quickstart

See our [getting started tutorial](https://zipline.ml4trading.io/beginner-tutorial).

The following code implements a simple dual moving average algorithm.

```python
from zipline.api import order_target, record, symbol


def initialize(context):
    context.i = 0
    context.asset = symbol('AAPL')


def handle_data(context, data):
    # Skip first 300 days to get full windows
    context.i += 1
    if context.i < 300:
        return

    # Compute averages
    # data.history() has to be called with the same params
    # from above and returns a pandas dataframe.
    short_mavg = data.history(context.asset, 'price', bar_count=100, frequency="1d").mean()
    long_mavg = data.history(context.asset, 'price', bar_count=300, frequency="1d").mean()

    # Trading logic
    if short_mavg > long_mavg:
        # order_target orders as many shares as needed to
        # achieve the desired number of shares.
        order_target(context.asset, 100)
    elif short_mavg < long_mavg:
        order_target(context.asset, 0)

    # Save values for later inspection
    record(AAPL=data.current(context.asset, 'price'),
           short_mavg=short_mavg,
           long_mavg=long_mavg)
```

You can then run this algorithm using the Zipline CLI. But first, you need to download some market data with historical prices and trading volumes:

```bash
$ zipline ingest -b quandl
$ zipline run -f dual_moving_average.py --start 2014-1-1 --end 2018-1-1 -o dma.pickle --no-benchmark
```

This will download asset pricing data sourced from [Quandl](https://www.quandl.com/databases/WIKIP/documentation?anchor=companies) (since [acquisition](https://www.nasdaq.com/about/press-center/nasdaq-acquires-quandl-advance-use-alternative-data) hosted by NASDAQ), and stream it through the algorithm over the specified time range. Then, the resulting performance DataFrame is saved as `dma.pickle`, which you can load and analyze from Python.

You can find other examples in the [zipline/examples](https://github.com/stefan-jansen/zipline-reloaded/tree/main/src/zipline/examples) directory.

## Questions, suggestions, bugs?

If you find a bug or have other questions about the library, feel free to [open an issue](https://github.com/stefan-jansen/zipline/issues/new) and fill out the template.


%package help
Summary:	Development documents and examples for zipline-reloaded
Provides:	python3-zipline-reloaded-doc
%description help
<p align="center">
<a href="https://zipline.ml4trading.io">
<img src="https://i.imgur.com/DDetr8I.png" width="25%">
</a>
</p>

# Backtest your Trading Strategies

| Version Info        | [![Python](https://img.shields.io/pypi/pyversions/zipline-reloaded.svg?cacheSeconds=2592000)](https://pypi.python.org/pypi/zipline-reloaded) [![Anaconda-Server Badge](https://anaconda.org/ml4t/zipline-reloaded/badges/platforms.svg)](https://anaconda.org/ml4t/zipline-reloaded) [![Release](https://img.shields.io/pypi/v/zipline-reloaded.svg?cacheSeconds=2592000)](https://pypi.org/project/zipline-reloaded/) [![Anaconda-Server Badge](https://anaconda.org/ml4t/zipline-reloaded/badges/version.svg)](https://anaconda.org/ml4t/zipline-reloaded)                                                                                                                                                                                                 |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **Test** **Status** | [![CI Tests](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/ci_tests_full.yml/badge.svg)](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/unit_tests.yml) [![PyPI](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/build_wheels.yml/badge.svg)](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/build_wheels.yml) [![Anaconda](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/conda_package.yml/badge.svg)](https://github.com/stefan-jansen/zipline-reloaded/actions/workflows/conda_package.yml) [![codecov](https://codecov.io/gh/stefan-jansen/zipline-reloaded/branch/main/graph/badge.svg)](https://codecov.io/gh/stefan-jansen/zipline-reloaded) |
| **Community**       | [![Discourse](https://img.shields.io/discourse/topics?server=https%3A%2F%2Fexchange.ml4trading.io%2F)](https://exchange.ml4trading.io) [![ML4T](https://img.shields.io/badge/Powered%20by-ML4Trading-blue)](https://ml4trading.io) [![Twitter](https://img.shields.io/twitter/follow/ml4trading.svg?style=social)](https://twitter.com/ml4trading)                                                                                                                                                                                                                                                                                                                                                                                                           |

Zipline is a Pythonic event-driven system for backtesting, developed and used as the backtesting and live-trading engine by [crowd-sourced investment fund Quantopian](https://www.bizjournals.com/boston/news/2020/11/10/quantopian-shuts-down-cofounders-head-elsewhere.html). Since it closed late 2020, the domain that had hosted these docs expired. The library is used extensively in the book [Machine Larning for Algorithmic Trading](https://ml4trading.io)
by [Stefan Jansen](https://www.linkedin.com/in/applied-ai/) who is trying to keep the library up to date and available to his readers and the wider Python algotrading community.

- [Join our Community!](https://exchange.ml4trading.io)
- [Documentation](https://zipline.ml4trading.io)

## Features

- **Ease of Use:** Zipline tries to get out of your way so that you can focus on algorithm development. See below for a code example.
- **Batteries Included:** many common statistics like moving average and linear regression can be readily accessed from within a user-written algorithm.
- **PyData Integration:** Input of historical data and output of performance statistics are based on Pandas DataFrames to integrate nicely into the existing PyData ecosystem.
- **Statistics and Machine Learning Libraries:** You can use libraries like matplotlib, scipy, statsmodels, and scikit-klearn to support development, analysis, and visualization of state-of-the-art trading systems.

> **Note:** Release 2.4 updates Zipline to use [exchange_calendars](https://github.com/gerrymanoim/exchange_calendars) >= 4.2. This is a major version update and may break existing code (which we have tried to avoid but cannot guarantee). Please review the changes [here](https://github.com/gerrymanoim/exchange_calendars/issues/61).

## Installation

Zipline supports Python >= 3.8 and is compatible with current versions of the relevant [NumFOCUS](https://numfocus.org/sponsored-projects?_sft_project_category=python-interface) libraries, including [pandas](https://pandas.pydata.org/) and [scikit-learn](https://scikit-learn.org/stable/index.html).

If your system meets the pre-requisites described in the [installation instructions](https://zipline.ml4trading.io/install.html), you can install Zipline using `pip` by running:

```bash
pip install zipline-reloaded
```

> **Note:** Installation under Python 3.11 requires building `h5py` [from source](https://docs.h5py.org/en/stable/build.html#source-installation) until [wheels become available](https://github.com/h5py/h5py/issues/2146).

Alternatively, if you are using the [Anaconda](https://www.anaconda.com/products/individual) or [miniconda](https://docs.conda.io/en/latest/miniconda.html) distributions, you can use

> **Note:** We are currently working to transition the conda package to [conda-forge](https://conda-forge.org/docs/index.html).

```bash
conda install -c conda-forge zipline-reloaded
```

You can also [enable](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-channels.html) `conda-forge` by listing it in your `.condarc`.

In case you are installing `zipline-reloaded` alongside other packages and encounter [conflict errors](https://github.com/conda/conda/issues/9707), consider using [mamba](https://github.com/mamba-org/mamba) instead.

See the [installation](https://zipline.ml4trading.io/install.html) section of the docs for more detailed instructions.

## Quickstart

See our [getting started tutorial](https://zipline.ml4trading.io/beginner-tutorial).

The following code implements a simple dual moving average algorithm.

```python
from zipline.api import order_target, record, symbol


def initialize(context):
    context.i = 0
    context.asset = symbol('AAPL')


def handle_data(context, data):
    # Skip first 300 days to get full windows
    context.i += 1
    if context.i < 300:
        return

    # Compute averages
    # data.history() has to be called with the same params
    # from above and returns a pandas dataframe.
    short_mavg = data.history(context.asset, 'price', bar_count=100, frequency="1d").mean()
    long_mavg = data.history(context.asset, 'price', bar_count=300, frequency="1d").mean()

    # Trading logic
    if short_mavg > long_mavg:
        # order_target orders as many shares as needed to
        # achieve the desired number of shares.
        order_target(context.asset, 100)
    elif short_mavg < long_mavg:
        order_target(context.asset, 0)

    # Save values for later inspection
    record(AAPL=data.current(context.asset, 'price'),
           short_mavg=short_mavg,
           long_mavg=long_mavg)
```

You can then run this algorithm using the Zipline CLI. But first, you need to download some market data with historical prices and trading volumes:

```bash
$ zipline ingest -b quandl
$ zipline run -f dual_moving_average.py --start 2014-1-1 --end 2018-1-1 -o dma.pickle --no-benchmark
```

This will download asset pricing data sourced from [Quandl](https://www.quandl.com/databases/WIKIP/documentation?anchor=companies) (since [acquisition](https://www.nasdaq.com/about/press-center/nasdaq-acquires-quandl-advance-use-alternative-data) hosted by NASDAQ), and stream it through the algorithm over the specified time range. Then, the resulting performance DataFrame is saved as `dma.pickle`, which you can load and analyze from Python.

You can find other examples in the [zipline/examples](https://github.com/stefan-jansen/zipline-reloaded/tree/main/src/zipline/examples) directory.

## Questions, suggestions, bugs?

If you find a bug or have other questions about the library, feel free to [open an issue](https://github.com/stefan-jansen/zipline/issues/new) and fill out the template.


%prep
%autosetup -n zipline-reloaded-2.4

%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-zipline-reloaded -f filelist.lst
%dir %{python3_sitearch}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 2.4-1
- Package Spec generated