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Optimized, opinionated structured logging for Python

Project description

containerlog

A lightweight, optimized, and opinionated structured logging library for Python, intended for containerized applications.

containerlog was born out of a desire to have high-quality structured logging for containerized applications (e.g. microservices) without having to compromise detailed logging for application/request latency.

structlog is a great general-purpose structured logging library for Python, but being general-purpose means that there is additional overhead when logging messages.

When we updated a microservice to use structured logging, we found that request latency went up, seemingly due to the transition to use structlog.

containerlog is not for everyone. It is highly opinionated, minimally configurable, and intentionally feature-sparse so that it can achieve better performance than the Python standard logger

Not every application needs optimized logging, but where latency and performance matters, containerlog could work for you.

timestamp='2020-07-23T13:11:28.009804Z' logger='my-logger' level='debug' event='loading configuration' path='./config.yaml'
timestamp='2020-07-23T13:11:28.010137Z' logger='my-logger' level='info' event='starting application'
timestamp='2020-07-23T13:11:28.010158Z' logger='my-logger' level='warn' event='having too much fun' countdown=[3, 2, 1]

Installation

containerlog can be installed with pip:

pip install containerlog

It is only intended to work for Python 3.6+.

Usage

See the documentation at https://containerlog.readthedocs.io/en/latest/

Optimizations

There are numerous sources discussion micro-optimizations in Python. This project probably does not implement them all, so there is room for improvement. Current optimization work has leveraged:

  • dis: to disassemble python bytecode for analysis
  • timeit: to measure execution time of code snippets

If you wish to contribute optimizations and use other libraries, tools, or sources, open a PR to add them to this list.

Benchmarks

Benchmarking scripts can be found in the benchmarks directory. To run,

$ cd benchmarks
$ ./run.sh

This will run benchmarks the Python standard logger and for containerlog. The latest results can be found below.

Results

Benchmarks were measured using Python 3.8.0 on macOS 10.15.1 with a 2.9 GHz 6-Core Intel Core i9 processor and 16 GB 2400 MHz DDR4 memory.

containerlog 0.3.0

Benchmark std logger (ns) std proxy (ns) containerlog (ns)
baseline 0.68 +/- 0.02 0.69 +/- 0.01 0.7 +/- 0.02
silent 108.0 +/- 6.0 1140.0 +/- 50.0 51.7 +/- 1.7
basic 4750.0 +/- 160.0 1140.0 +/- 60.0 1070.0 +/- 50.0
short-simple 5370.0 +/- 160.0 1280.0 +/- 60.0 1330.0 +/- 60.0
long-simple 5280.0 +/- 180.0 1480.0 +/- 70.0 2120.0 +/- 60.0
short-complex 5630.0 +/- 170.0 1500.0 +/- 150.0 1480.0 +/- 80.0
long-complex 6900.0 +/- 190.0 2870.0 +/- 80.0 3260.0 +/- 80.0
exception 10400.0 +/- 300.0 4440.0 +/- 150.0 4370.0 +/- 500.0

Contribute

While containerlog is intentionally feature-sparse, feature requests are welcome. Additionally, if you can find any other ways to micro-optimize the codebase, pull requests are very much appreciated.

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