{ "info": { "author": "Vladimir Shapranov", "author_email": "equidamoid@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Operating System :: MacOS :: MacOS X", "Operating System :: POSIX :: Linux", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7" ], "description": "### dltpy - library and utilities for DLT logging\n\n#### Installing\n##### Requirements\ndltpy uses native extension to parse and filter messages. This is done purely for performance reasons.\nIn my usecases which involve filtering out ~95% of the logs it speeds up the processing ~20 times.\nAs a funny fact, due to stricter filtering `dltpy-dump` is even faster than `dlt-convert -a` for me.\n\n - `boost::python`. Sorry for the pain. If it complains about it, make sure that you have the `-dev`\n package installed. Also keep in mind that is has to be built/installed for every minor version of python. So if you\n built python 3.7 for your ubuntu 16.04, `apt-get` won't help you, you have to built boost yourself. Sorry again.\n\n - `fmtlib` for native logging and formatting exceptions\n\n##### Installation\n```\ngit clone git+https://github.com/Equidamoid/dltpy\n(cd dltpy; git checkout native-dltreader)\npip install --user ./dltpy\n```\n\n#### Using\n\nThere are 3 commandline utilities that demonstrate usage of the library:\n - `dltpy-print` prints specified .dlt file as plain text. \"text-like\" payloads are decoded and printed as text, others are `repr()`ed\n - `dltpy-filter` filters out unneeded boring messages. Run it with `-f IDS:OF YOUR:APPS` and enjoy tiny logs that take seconds to load.\n - `dltpy-receive` demonstrates integration with asyncio and direct use of the native module, like `dlt-receive`. 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