py-hpl-logger 0.1.6

A high-performance, buffered, non-blocking logger for Python, implemented in Rust.

High-Performance Python Logger (in Rust)

A high-performance, buffered, non-blocking logger for Python, with the core logic implemented in Rust for maximum speed and efficiency.

This logger is designed for high-throughput applications where standard Python logging would become a bottleneck. It sends logs on a dedicated background thread, ensuring your application's main threads are never blocked by I/O.

Features

• Non-Blocking: Log calls return instantly.
• Batching: Logs are sent to destinations in efficient batches (Elastic bulk API).
• Resilient: In-memory buffer with retries for when destinations are temporarily unavailable.
• Multiple Outputs: Configure logging to stdout, files, and Elasticsearch simultaneously.
• Python logging Integration: Includes a logging.Handler to seamlessly integrate with the standard library.

Requirements

• Python 3.9+
• pip version 21 or newer.

This package uses modern Python packaging standards (PEP 517). Older versions of pip may not be able to install it correctly. You can upgrade pip with the following command:

pip install --upgrade pip

Pre-compiled wheels for officially Supported Platforms

• Linux: x86_64 (manylinux compatible)
• macOS: arm64 (Apple Silicon)

Installation

pip install py-hpl-logger

Quick Start

1(Optional). Configure your logger with ElasticConfig if needed:

ELASTIC_HOST=localhost
ELASTIC_PORT=9200
ELASTIC_USERNAME=elastic
ELASTIC_PASSWORD=changeme
ELASTIC_INDEX=my-python-logs

Configure using code:

elastic_config = ElasticConfig(
    host="localhost",
    port=9200,
    index="my-app",
    username="elastic",
    password="changeme"
)

Configure using .env. You can choose .env search depth using local_only argument:

elastic_config = ElasticConfig.from_env(local_only=False)

2. Use the logger in your Python application:

   import logging
   from py_hpl_logger import LoggerBuilder, ElasticConfig, RustLogHandler
   
   # 1. Build the Rust logger backend once
   elastic_config = ElasticConfig(
       host="localhost",
       port=9200,
       index="my-app",
       username="elastic",
       password="changeme"
   )
   # default buffer params:
   # channel_size: 4096
   # batch_size: 256
   # `channel_size` sets maximum inner buffer size. If log amount exceeds this argument, over limiting logs are dropped to avoid memory leaks
   # `batch_size` is an argument used to bulk push amount of logs specified
   rust_backend = (
       LoggerBuilder()
       .with_stdout(True) # whether to use stdout or not
       .with_file_output("my_app_session")
       .with_elastic_output(elastic_config)
       .with_batch_size(1000) # how many log rows to wait before forced flush
       .with_flush_interval(1.0) # # how many seconds to wait before forced flush
       .build()
   )
   
   # 2. Integrate with Python's standard logging
   handler = RustLogHandler(rust_logger=rust_backend)
   formatter = logging.Formatter("%(threadName)s - %(message)s")
   handler.setFormatter(formatter)
   logger.addHandler(handler)
   
   # 3. Use the standard logging API anywhere!
   log = logging.getLogger(__name__)
   log.info("This log is being handled by Rust!")
   log.error("This is a high-performance error log.")
   
   # 4. For graceful shutdown, flush the logger before exiting
   # (The logger also attempts to flush automatically on exit)
   rust_backend.flush()
   

Benchmark

Measurements completed under python3.11 on Apple M2 Max using remote Elastic Search instance with 2 Gb memory limit. The logger version used is py-hpl-logger==0.1.5.

20.000 messages were successfully written in a total time of 1.9494 seconds

    --- Running Benchmark for: High-Performance Rust Logger ---
    Logging 20,000 messages across 10 threads...
    Time taken for High-Performance Rust Logger: 0.1023 seconds

    Flushing Rust logger buffer...
    Flush took an additional 1.8471 seconds.

    --- Benchmark Results ---
    The application code was blocked for 0.1023 seconds with the Rust logger.
    Throughput: 195,474.04 logs/second
    Logs written: 20,000
    Time taken for flush: 1.8471 seconds
    Total time: 1.9494 seconds

Changelog

[0.1.5] - 2025-11-04

• Added 'with_channel_size' constructor to LoggerBuilder

[0.1.6] - 2025-11-04

• Added benchmark results

License

This project is licensed under the MIT License.