https://img.shields.io/pypi/pyversions/code-data-share https://img.shields.io/pypi/implementation/code-data-share https://img.shields.io/badge/platform-linux--64%20%7C%20osx--64-lightgrey

Introduction

The main goal of code-data-share-for-python is to improve the efficiency of importing python module, including time and memory footprint, by persistence of code object of imported modules with a memory-mapped file.

For more information not included in this README, e.g. detailed user and developer guide, performance results, please refer to our wiki page.

Basic Usage

code-data-share-for-python provides mechanism to determine imported packages, dump a memory mapped file from the list of packages and import packages directly from the memory mapped file.

Install

pip install code-data-share

Determine the imported packages

# tracer: list imported packages to mod.lst
PYCDSMODE=TRACE PYCDSLIST=mod.lst python -c 'import json'

Create the memory-mapped file

# dumper: create archive named mod.img from mod.lst
python -c 'import cds.dump; cds.dump.run_dump("mod.lst", "mod.img")'

Import packages from archive

# replayer
PYCDSMODE=SHARE PYCDSARCHIVE=mod.img python -c 'import json'

AppCDS in Java

The design is inspired by the Application Class-Data Sharing (AppCDS) feature, introduced in OpenJDK. AppCDS allows a set of application classes to be pre-processed into a shared archive file, which can then be memory-mapped at runtime to reduce startup time and memory footprint.

Key dates

PyPI data
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  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for oraluben from gravatar.com oraluben

Requires

Python >=3.8

Classifiers

Report project as malware

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This release

0.1.0 This release

35 files

0.0.5

26 files

0.0.4

26 files

0.0.3

26 files

0.0.2

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0.0.1

19 files

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