{
    "info": {
        "author": "Lasse Hyyrynen",
        "author_email": "leh@protonmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3",
            "Topic :: Utilities"
        ],
        "description": "|Build Status| |Coverage| |PyPI|\n\nJF\n==\n\nJF, aka \"jndex fingers\" or more commonly \"json filter pipeline\", is a\njq-clone written in python. It supports evaluation of python oneliners,\nmaking it especially appealing for data scientists who are used to\nworking with python.\n\nInstalling\n==========\n\n::\n\n    pip install jf\n\nHow does it work\n================\n\nJF works by converting json or yaml data structure through a\nmap/filter-pipeline. The pipeline is compiled from a string representing\na comma-separated list filters and mappers. The query parser assumes\nthat each function of the pipeline reads items from a generator. The\ngenerator is given as the last non-keyword parameter to the function, so\n\"map(conversion)\" is interpreted as \"map(conversion, inputgenerator)\".\nThe result from a previous function is given as the input generator for\nthe next function in the pipeline. The pipeline conversion is shown\nbelow as pseudocode:\n\n::\n\n    def build_pipeline(input, conversions):\n        pipeline = input\n        for convert in conversions:\n            pipeline = convert(pipeline)\n        return pipeline\n\nThe pipeline generated by the previous function is then iterated and\nprinted to the user. The basic building blocks of a pipeline are\n\n-  map(val) = map item to new object\n-  filter(cond) = filter to show only items matching condition\n-  update(val) = update item values\n-  hide(dict\\_keys) = hide dict\\_keys from output\n\nSome built-in functions headers have been remodeled to be more intuitive\nwith the framework. Most noticeable is the sorted-function, which\nnormally has the key defined as a keyword argument. This was done since\nit seems more logical to sort items by id by writing \"sorted(x.id)\" than\n\"sorted(key=lambda x: x.id)\". Similar changes are done for some other\nuseful functions:\n\n-  islice(stop) => islice(arr, start=0, stop, step=1)\n-  islice(start, stop, step=1) => islice(arr, start, stop, step)\n-  first(N=1) => islice(arr, N)\n-  last(N=1) => iter(deque(arr, maxlen=N))\n-  I = arr (== identity operation)\n-  yield\\_from(x) => yield items from x\n-  group\\_by(key) => group items by data key value\n-  chain() => chain(\\*arr) - combine items into a list\n\nFor datetime processing, two useful helper functions are imported by\ndefault:\n\n-  date(string) for parsing string into a python datetime-object\n-  age(string) for calculating timedelta between now() and date(string)\n\nThese are useful for sorting or filtering items in based on timestamps.\nSome of these functions have aliases predefined, such as head(), tail(),\nyield\\_all(), group() and reduce\\_list().\n\nFor shortened syntax, '{...}' is interpreted as 'map({...})' and (...)\nis interpreted as filter(...).\n\nBasic usage\n===========\n\nFilter selected fields\n\n::\n\n    $ cat samples.jsonl | jf 'map({id: x.id, subject: x.fields.subject})'\n    {\"id\": \"87086895\", \"subject\": \"Swedish children stories\"}\n    {\"id\": \"87114792\", \"subject\": \"New Finnish storybooks\"}\n\nFilter selected items\n\n::\n\n    $ cat samples.jsonl | jf 'map({id: x.id, subject: x.fields.subject}),\n            filter(x.id == \"87114792\")'\n    {\"id\": \"87114792\", \"subject\": \"New Finnish storybooks\"}\n\nFilter selected items with shortened syntax\n\n::\n\n    $ cat samples.jsonl | jf '{id: x.id, subject: x.fields.subject},\n            (x.id == \"87114792\")'\n    {\"id\": \"87114792\", \"subject\": \"New Finnish storybooks\"}\n\nFilter selected values\n\n::\n\n    $ cat samples.jsonl | jf 'map(x.id)'\n    \"87086895\"\n    \"87114792\"\n\nFilter items by age (and output yaml)\n\n::\n\n    $ cat samples.jsonl | jf 'map({id: x.id, datetime: x[\"content-datetime\"]}),\n            filter(age(x.datetime) > age(\"456 days\")),\n            update({age: age(x.datetime)})' --indent=5 --yaml\n    age: 457 days, 4:07:54.932587\n    datetime: '2016-10-29 10:55:42+03:00'\n    id: '87086895'\n\nSort items by age and print their id, length and age\n\n::\n\n    $ cat samples.jsonl|jf 'update({age: age(x[\"content-datetime\"])}),\n            sorted(x.age),\n            map(.id, \"length: %d\" % len(.content), .age)' --indent=3 --yaml\n    - '14941692'\n    - 'length: 63'\n    - 184 days, 0:02:20.421829\n    - '90332110'\n    - 'length: 191'\n    - 215 days, 22:15:46.403613\n    - '88773908'\n    - 'length: 80'\n    - 350 days, 3:11:06.412088\n    - '14558799'\n    - 'length: 1228'\n    - 450 days, 6:30:54.419461\n\nFilter items after a given datetime (test.json is a git commit history):\n\n::\n\n    $ jf 'update({age: age(.commit.author.date)}),\n            filter(date(.commit.author.date) > date(\"2018-01-30T17:00:00Z\")),\n            sorted(x.age, reverse=True), map(.sha, .age, .commit.author.date)' test.json \n    [\n      \"68fe662966c57443ae7bf6939017f8ffa4b182c2\",\n      \"2 days, 9:40:12.137919\",\n      \"2018-01-30T18:35:27Z\"\n    ]\n    [\n      \"d3211e1141d8b2bf480cbbebd376b57bae9d8bdf\",\n      \"2 days, 9:18:07.134418\",\n      \"2018-01-30T18:57:32Z\"\n    ]\n    [\n      \"f8ba0ba559e39611bc0b63f236a3e67085fe8b40\",\n      \"2 days, 8:50:09.129790\",\n      \"2018-01-30T19:25:30Z\"\n    ]\n\nImport your own modules and hide fields:\n\n::\n\n    $ cat test.json|jf --import_from modules/ --import demomodule --yaml 'update({id: x.sha}),\n            demomodule.timestamppipe(),\n            hide(\"sha\", \"committer\", \"parents\", \"html_url\", \"author\", \"commit\",\n                 \"comments_url\"), islice(3,5)'\n    - Pipemod: was here at 2018-01-31 09:26:12.366465\n      id: f5f879dd7303c35fa3712586af1e7df884a5b98b\n      url: https://api.github.com/repos/alhoo/jf/commits/f5f879dd7303c35fa3712586af1e7df884a5b98b\n    - Pipemod: was here at 2018-01-31 09:26:12.368438\n      id: b393d09215efc4fc0382dd82ec3f38ae59a287e5\n      url: https://api.github.com/repos/alhoo/jf/commits/b393d09215efc4fc0382dd82ec3f38ae59a287e5\n\nRead yaml:\n\n::\n\n    $ cat test.yaml | jf --yamli 'update({id: x.sha, age: age(x.commit.author.date)}),\n            filter(x.age < age(\"1 days\"))' --indent=2 --yaml\n    - age: 0 days, 22:45:56.388477\n      author:\n        avatar_url: https://avatars1.githubusercontent.com/u/8501204?v=4\n        events_url: https://api.github.com/users/hyyry/events{/privacy}\n        followers_url: https://api.github.com/users/hyyry/followers\n        ...\n\nGroup duplicates (age is within the same hour):\n\n::\n\n    $ cat test.json|jf --import_from modules/ --import demomodule 'update({id: x.sha}),\n            sorted(.commit.author.date, reverse=True),\n            demomodule.DuplicateRemover(int(age(.commit.author.date).total_seconds()/3600),\n            group=1).process(lambda x: {\"duplicate\": x.id}),\n            map(list(map(lambda y: {age: age(y.commit.author.date), id: y.id, \n                         date: y.commit.author.date, duplicate_of: y[\"duplicate\"],\n                         comment: y.commit.message}, x))),\n            first(2)'\n    [\n      {\n        \"comment\": \"Add support for hiding fields\",\n        \"duplicate_of\": null,\n        \"id\": \"f8ba0ba559e39611bc0b63f236a3e67085fe8b40\",\n        \"age\": \"16:19:00.102299\",\n        \"date\": \"2018-01-30 19:25:30+00:00\"\n      },\n      {\n        \"comment\": \"Enhance error handling\",\n        \"duplicate_of\": \"f8ba0ba559e39611bc0b63f236a3e67085fe8b40\",\n        \"id\": \"d3211e1141d8b2bf480cbbebd376b57bae9d8bdf\",\n        \"age\": \"16:46:58.104188\",\n        \"date\": \"2018-01-30 18:57:32+00:00\"\n      }\n    ]\n    [\n      {\n        \"comment\": \"Reduce verbosity when debugging\",\n        \"duplicate_of\": null,\n        \"id\": \"f5f879dd7303c35fa3712586af1e7df884a5b98b\",\n        \"age\": \"19:26:00.106777\",\n        \"date\": \"2018-01-30 16:18:30+00:00\"\n      },\n      {\n        \"comment\": \"Print help if no input is given\",\n        \"duplicate_of\": \"f5f879dd7303c35fa3712586af1e7df884a5b98b\",\n        \"id\": \"b393d09215efc4fc0382dd82ec3f38ae59a287e5\",\n        \"age\": \"19:35:16.108654\",\n        \"date\": \"2018-01-30 16:09:14+00:00\"\n      }\n    ]\n\nUse pythonic conditional operation, string.split() and complex string\nand date formatting with built-in python syntax. Also you can combine\nthe power of regular expressions by including the re-library.\n\n::\n\n    $ jf --import_from modules/ --import re --import demomodule --input skype.json 'yield_from(x.messages),\n            update({from: x.from.split(\":\")[-1], mid: x.skypeeditedid if x.skypeeditedid else x.clientmessageid}),\n            sorted(age(x.composetime), reverse=True),\n            demomodule.DuplicateRemover(x.mid, group=1).process(),\n            map(last(x)),\n            yield_from(x),\n            sorted(age(.composetime), reverse=True),\n            map(\"%s %s: %s\" % (date(x.composetime).strftime(\"%d.%m.%Y %H:%M\"), x.from, re.sub(r\"(<[^>]+>)+\", \" \", x.content)))' --raw\n    27.01.2018 11:02 2296ead9324b68aef4bc105c8e90200c@thread.skype:  1518001760666 8:live:matti_3426 8:live:matti_6656 8:hyyrynen.london 8:live:suvi_56 8:jukka.mattinen \n    27.01.2018 11:12 matti_7626: Required competence: PHP programmer (Mika D, Markus H, Heidi), some JavaScript (e.g. for GUI)\n    27.01.2018 11:12 matti_7626: Matti: parameters part\n    27.01.2018 11:15 matti_7626: 1.) Clarify customer requirements - AP: Suvi/Joseph\n    27.01.2018 11:22 matti_7626: This week - initial installation and setup\n    27.01.2018 11:22 matti_7626: Next week (pending customer requirements) - system configuration\n    27.01.2018 11:25 matti_7626: configuration = parameters, configuration files (audio files, from customer, ask Suvi to request today?), add audio files to system (via GUI)\n    27.01.2018 11:26 matti_7626: Testing = specify how we do testing, for example written test cases by the customer.\n    27.01.2018 11:28 matti_7626: Need test group (testgroup 1 prob easiest to recognise says Lasse)\n\nFeatures\n========\n\n-  json, jsonl and yaml files for input and output\n-  bz2 and gzip compressed input for json, jsonl and yaml\n-  csv and xlsx support if pandas and xlrd is installed\n-  markdown table output support\n-  construct generator pipeline with map, hide, filter\n-  access json dict as classes with dot-notation for attributes\n-  datetime and timedelta comparison\n-  age() for timedelta between datetime and current time\n-  first(N), last(N), islice(start, stop, step)\n-  head and tail alias for last and first\n-  firstnlast(N) (or headntail(N))\n-  import your own modules for more complex filtering\n-  Support stateful classes for complex interactions between items\n-  drop your filtered data to IPython for manual data exploration\n-  pandas profiling support for quick data exploration\n-  user --ordered\\_dict to keep items in order\n\nKnown bugs\n==========\n\n-  IPython doesn't launch perfectly with piped data\n\n.. |Build Status| image:: https://travis-ci.org/alhoo/jf.svg?branch=master\n   :target: https://travis-ci.org/alhoo/jf\n.. |Coverage| image:: https://codecov.io/github/alhoo/jf/coverage.svg?branch=master\n   :target: https://codecov.io/github/alhoo/jf\n.. |PyPI| image:: https://img.shields.io/pypi/v/jf.svg\n   :target: https://pypi.python.org/pypi/jf\n",
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