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        "author": "Joel Smith",
        "author_email": "joel.pypi@gmail.com",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
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        "description": "# Simplog\n\nA simple, functional, opinionated logger for python\n\n## Motivation\n\nI generally only need to implement simple logging in my services. For the most part, I don't need anything especially fancy,\nbut I do need to stick to a consistent format, to help log analyzers do their job.\n\n## Requirements\n\nCurrently this requires python 3 to run (developed against 3.6, but should compile under most recent versions)\n\n## Usage\n\nThere are 3 main steps:\n\n1. Generate a loging function:\n   `log = logger.make_logger(print)`\n2. Provide some input into logging function:\n   `log(\"The program is exploding\", level='error', why='Value Error')`\n3. Observe the results:\n    `2018-12-02T22:44:17.269137 level=error why=\"Value Error\" msg=\"The program is exploding\"`\n\nNote that only level and message are requird. Level, in addition, has a default value of `info`. All other values\nto be logged can be provided as keyword arguments (see above), which will be logged in `key=value` format. The current\nsystem time is always provided as well, to help order the events.\nIn addition, there are some configuration possible that will make themselves useful in certain situations.\n\n### Basic\n\nTypically, all I need is a print that goes to standard out. You can accomplish this via this approach:\n\n```python\nfrom logger import make_logger, refine_logger\nfrom uuid import uuid4\n\n# Generate a logger function\nmain_logger = make_logger()\n\nmain_logger(\"This is happening on the mainline\")\n# prints to standard out: 'dt level=info msg=\"This is happening on the mainline\"'\n\nctx_logger = refine_logger(main_logger, context=uuid4())\nctx_logger(\"A configured logger\")\n# prints to standard out: 'dt level=info context=\"ff088e2c-b127-4d8a-ba1d-347de59d302e\" msg=\"A configured logger\"'\n```\n\n### Advanced\n\nIf you need something more robust, then there are some configuration opportunities.\n\n#### Preconfigre log values\n\nIf you want to ensure that consistent values are always provided with the logger, you can refine the logger via the\n`refine_logger` method. This will return a new logger that always have the supplied arugments when called. Note that\nunder the hood, this is just a call to functool's `partial`\n\n```python\nlog = make_logger()\nrlog = refine_logger(log, confidence_level=\"100%\")\nrlog(\"Things are going well\")\n# Outputs: 2018-12-02T23:23:43.524875 level=info confidence_level=100% msg=\"Things are going well\"\n\n# These values is overwritable as well:\nrlog(\"Things aren't looking so great\", confidence_level=\"25%\")\n# Outputs: 2018-12-02T23:24:07.786726 level=info confidence_level=25% msg=\"Things aren't looking so great\"\n```\n\n#### Output to somewhere else\n\nThis project is meant to log to the console, but will accept any function that accepts a string as input.\n\n```python\n# Completely untested, but in theory this would work\nimport os\n\ndef make_filewriter_function(output_path):\n    writer = open(output_path, 'a', 0)  # Writing in unhuffered mode\n    def write_fn(s):\n      writer.write(s)\n\n    def close_fn():\n      os.close(writer)\n\n    return write_fn, close_fn\n\nwrite_fn, close_fn = make_filewriter_function('/var/log/my-script-log.log')\nlog = logger.make_logger(write_fn)\n# ...\nclose_fn()\n```\n\n#### Change default labels\n\nIf you don't like `msg` and `level` you can easily switch these when making the logger\nIf you want to add a label for the time, you can do that too\n\n```python\ncustom_log = logger.make_logger(print, message_label='message', level_label='logLevel', time_label='app_time')\ncustom_log(\"Look at that!\")\n# outputs: app_time=2018-12-02T23:06:59.566174 logLevel=info message=\"Look at that!\"\n```\n\n#### Forcing quoting\n\nBy default, any value that does not have a space in it will be left unquoted, while any string that does have a space will be double-quoted\n(i.e. `\"Expect values like this\"`)\nIf you always make to make sure your values are quoted, you can do that by supplying `force_quote=True` in the make_logger constructor.\n\n#### Serialize non-standard values\n\nIf you have some class you want to log, you'll need to supply your own serializer. Once you have that, you can pass the serialize func\nusing the `to_string_func` parameter.\n\n## Development\n\nThis project uses pipenv to aid development. See https://pipenv.readthedocs.io/en/latest/ for usage.\n\n### Running tests\n\nThis project utilizes pytest for running unit tests. They can be run via:\n\n```sh\npipenv shell\ncd simplog\npython -m pytest\n```\n\n## TODOs\n\n1. Make a proper distributable\n2. Test & Optimize performance\n3. Suport custom character escapes?\n4. Add in support for mypy",
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