Python Compression Library to Work with Large ZIP-Archives
A Powerful Open source Python fast Compression Library that allows to Seamlessly Integrate Zstandard Compression and Decompression Capabilities in Python apps.
Data compression is a crucial technique in the world of computing, enabling efficient storage and transmission of large volumes of information. The python-zstandard compression library has gained recognition for its balance between compression ratios and speed. Compression libraries play a pivotal role in reducing the size of data for storage and transmission. They work by using various algorithms to eliminate redundancies in the data, resulting in smaller representations. The Python library is one such tool that brings the power of data compression to Python developers.
Python-zstandard is a Python binding for the Zstandard compression library, which is known for its high compression and decompression speeds. There are some notable features that make the library stand out, such as high compression ratios, rapid decompression speeds, effectively reducing the size of data without sacrificing quality, predefined dictionaries support, progressive decompression, multi-threading support, designed to be memory efficient, and many more.
The Python-Zstandard library provides a straightforward and intuitive interface, making it easy for software developers to integrate compression and decompression functionalities into their Python applications. It brings the power of the Zstandard compression algorithm to the Python programming world. With its blend of high compression ratios and rapid decompression speeds, it's a versatile tool for various data compression tasks. Whether you're dealing with large datasets, network communication optimization, or storage constraints, Python-Zstandard has the potential to be a valuable addition to your coding arsenal.
At A Glance
An overview of Python-Zstandard features.
- Create Large Archives
- Edit ZIP-archives
- Low Memory Footprint
- Multithreading support
- Data Archiving Support
- Fast Data Compression
- Extract zip
- AES encryption
- BZIP2 compression
- ZIP64 extensions
- Format Compatibility
Python-Zstandard only requires Python 3.6+
- Python 3.6 and Above.
Getting Started with Python-Zstandard
The recommend way to install Python-zstandard is using pypi.org. Please use the following command for a smooth installation.
Install Python-Zstandard via .NET via pypi
It is also possible to install it manually; download the latest release files directly from GitHub repository.
pip install python-zstandard
High Compression Ratio
The open source Python-zstandard library has provided powerful functionality for handling data compression with high ration inside Python applications. Zstandard's compression algorithm is known for its ability to achieve high compression ratios, effectively reducing the size of data without sacrificing quality. The library allows to compress and decompress data using a simple and consistent API. Here's a basic example of how to use the library for compression and decompression different types of data using Python commands.
How to Compress and Decompress data using Python API?
import zstandard as zstd # Create a compression context cctx = zstd.ZstdCompressor() # Compress data compressed_data = cctx.compress(b"Hello, this is some sample data.") # Create a decompression context dctx = zstd.ZstdDecompressor() # Decompress data decompressed_data = dctx.decompress(compressed_data)
Adaptive Strategies & Multi-threading Support
The Python-zstandard library employs adaptive strategies that automatically adjust compression parameters based on the input data. This dynamic approach ensures optimal compression performance for various types of data. Moreover, the library supports multi-threading, allowing compression and decompression to take advantage of multi-core processors. This feature contributes to faster data processing, especially for large datasets.
Simple Interface & Dictionary Support
The open source Python-zstandard library provides a straightforward and intuitive interface, making it easy for software developers to integrate compression and decompression functionalities into their Python applications. This simplicity is especially valuable for projects with tight deadlines or limited resources. The library also supports the use of predefined dictionaries, which can significantly improve compression ratios for specific types of data.