__init__.py

"""

![xkcd.com/1570](https://imgs.xkcd.com/comics/engineer_syllogism.png){: height=263}

## Manuals

* [**Quick Start User Guide**](../examples/Quick Start User Guide.html)

## Tutorials

The tutorials encompass most framework features, so it's important
and advisable to go through all of them. They are short.

* [Library of Utilities and Composable Base Strategies](../examples/Strategies Library.html)
* [Multiple Time Frames](../examples/Multiple Time Frames.html)
* [**Parameter Heatmap & Optimization**](../examples/Parameter Heatmap & Optimization.html)
* [Trading with Machine Learning](../examples/Trading with Machine Learning.html)

These tutorials are also available as live Jupyter notebooks:
[![Binder](https://mybinder.org/badge_logo.svg)][binder]
[![Google Colab](https://colab.research.google.com/assets/colab-badge.png)][colab]
<br>In Colab, you might have to `!pip install backtesting`.

[binder]: \
    https://mybinder.org/v2/gh/kernc/backtesting.py/master?\
urlpath=lab%2Ftree%2Fdoc%2Fexamples%2FQuick%20Start%20User%20Guide.ipynb
[colab]: https://colab.research.google.com/github/kernc/backtesting.py/

## Video Tutorials

* Some [**coverage on YouTube**](https://github.com/kernc/backtesting.py/discussions/677).
* [YouTube search](https://www.youtube.com/results?q=%22backtesting.py%22)

## Example Strategies

* (contributions welcome)


.. tip::
    For an overview of recent changes, see
    [What's New, i.e. the **Change Log**](https://github.com/kernc/backtesting.py/blob/master/CHANGELOG.md).


## FAQ

Some answers to frequent and popular questions can be found on the
[issue tracker](https://github.com/kernc/backtesting.py/issues?q=label%3Aquestion+-label%3Ainvalid)
or on the [discussion forum](https://github.com/kernc/backtesting.py/discussions) on GitHub.
Please use the search!

## License

This software is licensed under the terms of [AGPL 3.0]{: rel=license},
meaning you can use it for any reasonable purpose and remain in
complete ownership of all the excellent trading strategies you produce,
but you are also encouraged to make sure any upgrades to _Backtesting.py_
itself find their way back to the community.

[AGPL 3.0]: https://www.gnu.org/licenses/agpl-3.0.html

# API Reference Documentation
"""
try:
    from ._version import version as __version__
except ImportError:
    __version__ = '?.?.?'  # Package not installed

from . import lib  # noqa: F401
from ._plotting import set_bokeh_output  # noqa: F401
from .backtesting import Backtest, Strategy  # noqa: F401


# Add overridable backtesting.Pool used for parallel optimization
def Pool(processes=None, initializer=None, initargs=()):
    import multiprocessing as mp
    if mp.get_start_method() == 'spawn':
        import warnings
        warnings.warn(
            "If you want to use multi-process optimization with "
            "`multiprocessing.get_start_method() == 'spawn'` (e.g. on Windows),"
            "set `backtesting.Pool = multiprocessing.Pool` (or of the desired context) "
            "and hide `bt.optimize()` call behind a `if __name__ == '__main__'` guard. "
            "Currently using thread-based paralellism, "
            "which might be slightly slower for non-numpy / non-GIL-releasing code. "
            "See https://github.com/kernc/backtesting.py/issues/1256",
            category=RuntimeWarning, stacklevel=3)
        from multiprocessing.dummy import Pool
        return Pool(processes, initializer, initargs)
    else:
        return mp.Pool(processes, initializer, initargs)