Metadata-Version: 2.1
Name: jello
Version: 1.2.6
Summary: Filter JSON and JSON Lines data with Python syntax.
Home-page: https://github.com/kellyjonbrazil/jello
Author: Kelly Brazil
Author-email: kellyjonbrazil@gmail.com
License: MIT
Description: ![Tests](https://github.com/kellyjonbrazil/jello/workflows/Tests/badge.svg?branch=master)
        ![Pypi](https://img.shields.io/pypi/v/jello.svg)
        
        # jello
        Filter JSON and JSON Lines data with Python syntax
        
        `jello` is similar to `jq` in that it processes JSON and JSON Lines data except `jello` uses standard python dict and list syntax.
        
        JSON or JSON Lines can be piped into `jello` (JSON Lines are automatically slurped into a list of dictionaries) and are available as the variable `_`. Processed data can be output as JSON, JSON Lines, bash array lines, or a grep-able schema.
        
        For more information on the motivations for this project, see my [blog post](https://blog.kellybrazil.com/2020/03/25/jello-the-jq-alternative-for-pythonistas/).
        
        ## Install
        ```
        pip3 install --upgrade jello
        ```
        
        ### Usage
        ```
        <JSON Data> | jello [OPTIONS] [QUERY]
        ``` 
        `QUERY` is optional and can be most any valid python code. `_` is the sanitized JSON from STDIN presented as a python dict or list of dicts. If `QUERY` is omitted then the original JSON input will simply be pretty printed.
        
        A simple query:
        ```
        $ cat data.json | jello '_["foo"]'
        ```
        
        #### Options
        - `-c` compact print JSON output instead of pretty printing
        - `-i` initialize environment with a custom config file
        - `-l` lines output (suitable for bash array assignment)
        - `-m` monochrome output
        - `-n` print selected `null` values
        - `-r` raw output of selected strings (no quotes)
        - `-s` print the JSON schema in grep-able format
        - `-h` help
        - `-v` version info
        
        #### Assigning Results to a Bash Array
        
        Use the `-l` option to print JSON array output in a manner suitable to be assigned to a bash array. The `-r` option can be used to remove quotation marks around strings. If you want `null` values to be printed as `null`, use the `-n` option, otherwise they are skipped.
        ```
        variable=($(cat data.json | jello -rl '_["foo"]'))
        ```
        
        #### Custom Configuration File
        
        You can use the `-i` option to initialize the `jello` environment with your own configuration file. The configuration file accepts valid python code where you can set the `jello` options you would like enabled or disabled, customize your colors, add `import` statements for your favorite modules, and define your own functions.
        
        The file must be named `.jelloconf.py` and must be located in the proper directory based on the OS platform:
        - Linux, unix, macOS: `~/`
        - Windows: `%appdata%/`
        
        ##### Setting Options
        To set `jello` options in the `.jelloconf.py` file, add any of the following and set to `True` or `False`:
        ```
        mono = True            # -m option
        compact = True         # -c option
        lines = True           # -l option
        raw = True             # -r option
        nulls = True           # -n option
        schema = True          # -s option
        ```
        ##### Setting Colors
        You can customize the colors by setting the following variables to one of the following string values: `'black'`, `'red'`, `'green'`, `'yellow'`, `'blue'`, `'magenta'`, `'cyan'`, `'gray'`, `'brightblack'`, `'brightred'`, `'brightgreen'`, `'brightyellow'`, `'brightblue'`, `'brightmagenta'`, `'brightcyan'`, or `'white'`.
        ```
        keyname_color = 'blue'            # Key names
        keyword_color = 'brightblack'     # true, false, null
        number_color = 'magenta'          # integers, floats
        string_color = 'green'            # strings
        arrayid_color = 'red'             # array IDs in Schema view
        arraybracket_color = 'magenta'    # array brackets in Schema view
        ```
        > Note: Any colors set via the `JELLO_COLORS` environment variable will take precedence over any color values set in the `.jelloconf.py` configuration file
        
        ##### Importing Modules
        To import a module (e.g. `glom`) during initialization, just add the `import` statement to your `.jelloconf.py` file:
        ```
        from glom import *
        ```
        Then you can use `glom` in your `jello` filters without importing:
        ```
        $ jc -a | jello -i 'glom(_, "parsers.25.name")'
        
        "lsblk"
        ```
        
        ##### Adding Functions
        You can also add functions to your initialization file.  For example, you could simplify `glom` use by adding the following function to `.jelloconf.py`:
        ```
        def g(q, data=_):
            import glom
            return glom.glom(data, q)
        ```
        Then you can use the following syntax to filter the JSON data:
        ```
        $ jc -a | jello -i 'g("parsers.6.compatible")'
        
        [
          "linux",
          "darwin",
          "cygwin",
          "win32",
          "aix",
          "freebsd"
        ]
        ```
        ## Setting Custom Colors via Environment Variable
        In addition to setting custom colors in the `.jelloconf.py` intialization file, you can also set them via the `JELLO_COLORS` environment variable. Any colors set in the environment variable will take precedence over any colors set in the initialization file.
        
        The `JELLO_COLORS` environment variable takes six comma separated string values in the following format:
        ```
        JELLO_COLORS=<keyname_color>,<keyword_color>,<number_color>,<string_color>,<arrayid_color>,<arraybracket_color>
        ```
        Where colors are: `black`, `red`, `green`, `yellow`, `blue`, `magenta`, `cyan`, `gray`, `brightblack`, `brightred`, `brightgreen`, `brightyellow`, `brightblue`, `brightmagenta`, `brightcyan`, `white`, or  `default`
        
        For example, to set to the default colors:
        ```
        JELLO_COLORS=blue,brightblack,magenta,green,red,magenta
        ```
        or
        ```
        JELLO_COLORS=default,default,default,default,default,default
        ```
        
        ## Examples:
        ### Printing the Grep-able Schema
        ```
        $ jc -a | jello -s
        
        .name = "jc";
        .version = "1.10.2";
        .description = "jc cli output JSON conversion tool";
        .author = "Kelly Brazil";
        .author_email = "kellyjonbrazil@gmail.com";
        .parser_count = 50;
        .parsers[0].name = "airport";
        .parsers[0].argument = "--airport";
        .parsers[0].version = "1.0";
        .parsers[0].description = "airport -I command parser";
        .parsers[0].author = "Kelly Brazil";
        .parsers[0].author_email = "kellyjonbrazil@gmail.com";
        .parsers[0].compatible[0] = "darwin";
        .parsers[0].magic_commands[0] = "airport -I";
        .parsers[1].name = "airport_s";
        .parsers[1].argument = "--airport-s";
        .parsers[1].version = "1.0";
        ...
        ```
        ### Lambda Functions and Math
        ```
        $ echo '{"t1":-30, "t2":-20, "t3":-10, "t4":0}' | jello '\
        keys = _.keys()
        vals = _.values()
        cel = list(map(lambda x: (float(5)/9)*(x-32), vals))
        dict(zip(keys, cel))'
        
        {
          "t1": -34.44444444444444,
          "t2": -28.88888888888889,
          "t3": -23.333333333333336,
          "t4": -17.77777777777778
        }
        
        ```
        ```
        $ jc -a | jello 'len([entry for entry in _["parsers"] if "darwin" in entry["compatible"]])'
        
        32
        ```
        ### For Loops
        Output as JSON array
        ```
        $ jc -a | jello '\
        result = []
        for entry in _["parsers"]:
          if "darwin" in entry["compatible"]:
            result.append(entry["name"])
        result'
        
        [
          "airport",
          "airport_s",
          "arp",
          "crontab",
          "crontab_u",
          ...
        ]
        ```
        Output as bash array
        ```
        $ jc -a | jello -rl '\
        result = []
        for entry in _["parsers"]:
          if "darwin" in entry["compatible"]:
            result.append(entry["name"])
        result'
        
        airport
        airport_s
        arp
        crontab
        crontab_u
        ...
        ```
        ### List and Dictionary Comprehension
        Output as JSON array
        ```
        $ jc -a | jello '[entry["name"] for entry in _["parsers"] if "darwin" in entry["compatible"]]'
        
        [
          "airport",
          "airport_s",
          "arp",
          "crontab",
          "crontab_u",
          ...
        ]
        ```
        Output as bash array
        ```
        $ jc -a | jello -rl '[entry["name"] for entry in _["parsers"] if "darwin" in entry["compatible"]]'
        
        airport
        airport_s
        arp
        crontab
        crontab_u
        ...
        ```
        ### Environment Variables
        ```
        $ echo '{"login_name": "joeuser"}' | jello '\
        True if os.getenv("LOGNAME") == _["login_name"] else False'
        
        true
        ```
        ### Using 3rd Party Modules
        You can import and use your favorite modules to manipulate the data.  For example, using `glom`:
        ```
        $ jc -a | jello '\
        from glom import *
        glom(_, ("parsers", ["name"]))'
        
        [
          "airport",
          "airport_s",
          "arp",
          "blkid",
          "crontab",
          "crontab_u",
          "csv",
          ...
        ]
        ```
        ### Advanced JSON Manipulation
        The data from this example comes from https://programminghistorian.org/assets/jq_twitter.json
        
        Under **Grouping and Counting**, Matthew describes an advanced `jq` filter against a sample Twitter dataset that includes JSON Lines data. There he describes the following query:
        
        *“We can now create a table of users. Let’s create a table with columns for the user id, user name, followers count, and a column of their tweet ids separated by a semicolon.”*
        
        https://programminghistorian.org/en/lessons/json-and-jq
        
        Here is a simple solution using `jello`:
        ```
        $ cat jq_twitter.json | jello -l '\
        user_ids = set()
        for tweet in _:
            user_ids.add(tweet["user"]["id"])
        result = []
        for user in user_ids:
            user_profile = {}
            tweet_ids = []
            for tweet in _:
                if tweet["user"]["id"] == user:
                    user_profile.update({
                        "user_id": user,
                        "user_name": tweet["user"]["screen_name"],
                        "user_followers": tweet["user"]["followers_count"]})
                    tweet_ids.append(str(tweet["id"]))
            user_profile["tweet_ids"] = ";".join(tweet_ids)
            result.append(user_profile)
        result'
        
        ...
        {"user_id": 2696111005, "user_name": "EGEVER142", "user_followers": 1433, "tweet_ids": "619172303654518784"}
        {"user_id": 42226593, "user_name": "shirleycolleen", "user_followers": 2114, "tweet_ids": "619172281294655488;619172179960328192"}
        {"user_id": 106948003, "user_name": "MrKneeGrow", "user_followers": 172, "tweet_ids": "501064228627705857"}
        {"user_id": 18270633, "user_name": "ahhthatswhy", "user_followers": 559, "tweet_ids": "501064204661850113"}
        {"user_id": 14331818, "user_name": "edsu", "user_followers": 4220, "tweet_ids": "615973042443956225;618602288781860864"}
        {"user_id": 2569107372, "user_name": "SlavinOleg", "user_followers": 35, "tweet_ids": "501064198973960192;501064202794971136;501064214467731457;501064215759568897;501064220121632768"}
        {"user_id": 22668719, "user_name": "nodehyena", "user_followers": 294, "tweet_ids": "501064222772445187"}
        ...
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Utilities
Requires-Python: >=3.6
Description-Content-Type: text/markdown
