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.
1 maintainer
Metadata
1 maintainer
Release files for code-data-share 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| code_data_share-0.1.0.tar.gz | 41.2 kB | Details |
Built distributions (wheels)
Total release size: 692.1 kB
