fast-reading 0.1.2

A fast reading file library for Python

Fast Reading

A fast reading file library for Python

Description

Fast Reading is a high-performance file reading library for Python, written in Rust using pyo3. It provides an efficient mechanism for reading files by loading them in batches and yielding file content one at a time. This makes it ideal for processing large volumes of data with minimal overhead.

Features

• High Performance: Built with Rust for speedy file operations.
• Seamless Python Integration: Uses pyo3 for a natural Python interface.
• Batch File Reading: Reads files in batches to optimize I/O, then iterates over individual file data.
• Flexible Iterators: Provides different iterator types for various use cases.
• Cross-Platform Compatibility: Works with Python 3.9 and above.

Installation

Ensure you have maturin installed:

pip install fast-reading

Tests

> 100_000 files of 1024 bytes each

$ Python reading time: 0.777500 seconds
$ FilesBatchIterator reading time (batch_size=5): 0.449203 seconds
$ FlattenFilesBatchIterator reading time (batch_size=5): 0.448566 seconds

> 100_000 files of 32768 bytes each

$ Python reading time: 1.138894 seconds
$ FilesBatchIterator reading time (batch_size=5): 0.847089 seconds
$ FlattenFilesBatchIterator reading time (batch_size=5): 0.835050 seconds

> 1_000_000 files of 4096 bytes each

$ Python reading time: 14.950660 seconds
$ FilesBatchIterator reading time (batch_size=5): 5.086445 seconds
$ FlattenFilesBatchIterator reading time (batch_size=5): 5.068229 seconds

Usage

FilesBatchIterator Example

This iterator reads files in batches and returns a list of file contents for each batch.

from fast_reading import FilesBatchIterator

# Initialize the iterator for reading files from a directory with a batch size of 100
for file_bytes in FilesBatchIterator("/path/to/directory", batch_size=100):
    # file_bytes is a list of bytes read from one or more files
    print(file_bytes)

FlattenFilesBatchIterator Example

This iterator loads a batch of files but yields file content one by one.

from fast_reading import FlattenFilesBatchIterator

# Initialize the iterator to read files in batches of 5,
# but return one file's content at a time.
for file_content in FlattenFilesBatchIterator("/path/to/directory", batch_size=5):
    # file_content is the bytes content of a single file
    print(file_content)

License

This project is licensed under the MIT License.

Contact

Author: @vffuunnyy