A fast and lightweight logging library for Python
Project description
picologging
Warning This project is in beta. There are some incomplete features (see Limitations).
Picologging is a high-performance logging library for Python. picologging is 4-10x faster than the logging
module in the standard library.
Picologging is designed to be used as a drop-in replacement for applications which already use logging, and supports the same API as the logging
module.
Check out the Documentation for more.
Installation
Picologging can be installed from PyPi using pip:
pip install picologging
Or from conda forge using conda:
conda install -c conda-forge picologging
Usage
Import picologging as logging
to use picologging instead of the standard library logging module.
This patches all the loggers registered to use picologging loggers and formatters.
import picologging as logging
logging.basicConfig()
logger = logging.getLogger()
logger.info("A log message!")
logger.warning("A log message with %s", "arguments")
Benchmarks
Run richbench benchmarks/ --markdown
with the richbench CLI to see the benchmarks, here is a sample on macOS 11:
Benchmark | Min | Max | Mean | Min (+) | Max (+) | Mean (+) |
---|---|---|---|---|---|---|
FileHandler() | 0.138 | 0.151 | 0.143 | 0.055 (2.5x) | 0.063 (2.4x) | 0.058 (2.5x) |
WatchedFileHandler() | 0.189 | 0.197 | 0.193 | 0.097 (1.9x) | 0.101 (1.9x) | 0.099 (1.9x) |
RotatingFileHandler() | 0.287 | 0.304 | 0.296 | 0.174 (1.6x) | 0.178 (1.7x) | 0.176 (1.7x) |
QueueHandler() | 1.109 | 1.195 | 1.130 | 0.142 (7.8x) | 0.151 (7.9x) | 0.147 (7.7x) |
QueueListener() + QueueHandler() | 0.157 | 0.167 | 0.162 | 0.034 (4.6x) | 0.039 (4.3x) | 0.037 (4.3x) |
MemoryHandler() | 0.126 | 0.144 | 0.133 | 0.051 (2.5x) | 0.059 (2.5x) | 0.054 (2.5x) |
LogRecord() | 0.225 | 0.248 | 0.233 | 0.026 (8.7x) | 0.029 (8.5x) | 0.028 (8.4x) |
Formatter().format() | 0.076 | 0.086 | 0.081 | 0.004 (18.7x) | 0.005 (18.9x) | 0.004 (19.1x) |
Formatter().format() with date | 0.298 | 0.311 | 0.304 | 0.081 (3.7x) | 0.087 (3.6x) | 0.084 (3.6x) |
Logger(level=DEBUG).debug() | 0.726 | 0.743 | 0.734 | 0.059 (12.3x) | 0.061 (12.3x) | 0.060 (12.3x) |
Logger(level=DEBUG).debug() with args | 0.761 | 0.809 | 0.777 | 0.081 (9.4x) | 0.087 (9.3x) | 0.084 (9.2x) |
Logger(level=INFO).debug() | 0.016 | 0.018 | 0.017 | 0.004 (4.3x) | 0.005 (3.8x) | 0.004 (4.1x) |
Logger(level=INFO).debug() with args | 0.018 | 0.019 | 0.018 | 0.005 (3.8x) | 0.005 (3.8x) | 0.005 (3.7x) |
Limitations
See Limitations
Contributing
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
Local development
This project comes bundled with a dev container which sets up an appropriate environment. If you install the Dev Containers extension for VS Code, then opening this project in VS Code should prompt it to open it in the dev container.
Once opened in the dev container, run:
pip install -e ".[dev]"
pre-commit install
python setup.py build_ext --inplace --build-type Debug
Run the build command whenever you make changes to the files.
It's also helpful to create a .vscode/launch.json
file like this one:
{
"version": "0.2.0",
"configurations": [
{
"name": "(gdb) Launch pytest",
"type": "cppdbg",
"request": "launch",
"program": "/usr/local/bin/python",
"args": ["-m", "pytest", "tests"],
"stopAtEntry": false,
"cwd": "${workspaceFolder}",
"environment": [],
"externalConsole": false,
"MIMode": "gdb",
"setupCommands": [
{
"description": "Enable pretty-printing for gdb",
"text": "-enable-pretty-printing",
"ignoreFailures": true
},
{
"description": "Set Disassembly Flavor to Intel",
"text": "-gdb-set disassembly-flavor intel",
"ignoreFailures": true
},
]
}
}
Now you can press the "Run and debug" button to run pytest
from the gdb
debugger
and use breakpoint debugging in the C code.
If you would like to be able to dive into the CPython code while debugging, then:
-
Do a git checkout of the tagged branch for the devcontainer's Python version into the devcontainer's
/workspaces/
directory. You may need tosudo
. -
Follow the instructions in the CPython README to compile the code.
-
Add the following key to the the configuration in
launch.json
:"sourceFileMap": { "/usr/src/python": "/workspaces/cpython" },
-
Add the following command to the
setupCommands
inlaunch.json
:{ "description": "Find CPython source code", "text": "-gdb-set auto-load safe-path /workspaces/cpython" },
Trademarks
Some components of this Python package are from CPython 3.11 logging library for compatibility reasons.
CPython 3.11 is licensed under the PSF license. The logging module is Copyright (C) 2001-2019 Vinay Sajip. All Rights Reserved.
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.
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Details for the file picologging-0.9.3-cp37-cp37m-macosx_10_15_x86_64.whl
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- Upload date:
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- Tags: CPython 3.7m, macOS 10.15+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/2.7.15
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