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Backport/clone of ChainMap for py26, py32, and pypy3.

Project description

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This module is a polyfill, implementing ChainMap for reasonably-recent versions of Python that do not have collections.ChainMap–namely, Python 2.6, Python 3.2, and PyPy3 releases based on Python 3.2. (It will also work as expected on Python 2.7, PyPy, and Python 3.3+, but it is not strictly needed there since those verions’ collections modules contains good ChainMap implementations.)

The code for this package is closely derived from the Python 3.5 source code, (especially the collections and reprlib modules). Several changes have been made to ensure Python 2.6 compatibility, and tests and packaging have been added.

Typical usage:

from chainmap import ChainMap

If you prefer to preferentially import from the Python standard library when ChainMap is available there:

try:
    from collections import ChainMap
except ImportError:
    from chainmap import ChainMap

Please see the standard documentation for details on how to use ChainMap.

If you’re not sure why someone would use a ChainMap, they are useful for managing “nested” contexts and “overlays.” See e.g. my options, quoter, and say packages, which use them extensively for flexible option handling. You can find similar uses in the Context class of Django’s template engine.

Notes

  • Automated multi-version testing managed with pytest, pytest-cov, coverage, and tox. Packaging linting with pyroma.

  • Thanks to Travis CI, successfully packaged for, and tested against, all reasonably late-model versions of Python: 2.6, 2.7, 3.2, 3.3, 3.4, 3.5, 3.6, and 3.7, as well as PyPy 5.8.0 (essentially Python 2.7.13) and PyPy3 5.10.1 (corresponding to Python 3.5.3).

  • The author, Jonathan Eunice or @jeunice on Twitter welcomes your comments and suggestions.

Installation

To install or upgrade to the latest version:

pip install -U chainmap

To easy_install under a specific Python version (3.3 in this example):

python3.3 -m easy_install --upgrade chainmap

(You may need to prefix these with sudo to authorize installation. In environments without super-user privileges, you may want to use pip’s --user option, to install only for a single user, rather than system-wide.)

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