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Python containers with persistency

Project description


Python containers with persistency

|landscape| |travis| |codecov|

`pysistency` provides clones of standard containers backed by persistent data
storage. These containers allow to wrk with data too large for memory, and to
seamlessly keep data across program executions.

.. |landscape| image::
:alt: Code Health

.. |travis| image::
:alt: Test Health

.. |codecov| image::
:alt: Code Coverage

.. contents:: **Table of Contents**
:depth: 2


Efficiently implementing each container requires code tailored to its data
structure and usage. Each implementation is developed separately from others.

================ =========================================== ==============
Python Pysistency Status
================ =========================================== ==============
`dict` `pysistency.pdict.PersistentDict` Stable
`list` `pysistency.plist.PersistentList` Experimental
================ =========================================== ==============

The following `Status` categories are used:

Public interfaces and data storage may change at any time. Functionality
is lacking.

Core functionality fully implemented, data storage will remain stable.
Some functionality still missing.

All functionality available. Internal implementation details may change.

All functionality available, internal implementation stable, passes all
applicable, official tests.

Where's X?

Priority for new/existing types depends mostly on ease of implementation and
need. If you require a specific type or interface, let me know.


The containers of `pysistency` rely on backends to store data. This allows
switching the storage backend for each container. Currently, there is only
one backend: a file-based backend using `pickle`.

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