jello 1.3.3

Filter JSON and JSON Lines data with Python syntax.

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jello now supports dot notation!

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.

Install

You can install jello via pip, via OS Package Repository, MSI installer for Windows, or by downloading the correct binary for your architecture and running it anywhere on your filesystem.

Pip (macOS, linux, unix, Windows)

For the most up-to-date version and the most cross-platform option, use pip or pip3 to download and install jello directly from PyPi:

pip3 install jello

OS Packages

MSI Installer (Windows 2016+)

The MSI Installer packages for Windows are built from PyPi and can be installed on modern versions of Windows. These installers may not always be on the very latest jello version, but are regularly updated.

Version	File	SHA256 Hash
1.3.2	jello-1.3.2.msi	3cbdbb36adf33c7090e9f2d7aac577e4286edae1544c9582c1377eaccc08ef49
1.2.11	jello-1.2.11.msi	08da1c91e5d1930542529473350dc10ffc3d4adf5c06cc365c333663ac82a8fc

Binaries (x86_64)

Linux and macOS x86_64 binaries are built from PyPi and can be copied to any location in your path and run. These binaries may not always be on the very latest jello version, but are regularly updated.

Linux (Fedora, RHEL, CentOS, Debian, Ubuntu)

Version	File	SHA256 Hash (binary file)
1.3.2	jello-1.3.2-linux.tar.gz	4fea973ab37b2def713240757a18304ba7399f026afe3bf211d775b0d9db083c
1.2.9	jello-1.2.9-linux.tar.gz	ffe8dfe2cc1dc446aeade32078db654de604176976be5dee89f83f0049551c45

macOS (Mojave and higher)

Version	File	SHA256 Hash (binary file)
1.3.2	jello-1.3.2-darwin.tar.gz	a21ad322e8d4a279f3b2c8ba9b60835c1c6ba5809994f965ae529369520ec113
1.2.9	jello-1.2.9-darwin.tar.gz	9355bf19212cce60f5f592a1a778fdf26984f4b86968ceca2a3e99792c258037

Usage

cat data.json | 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. You can use dot notation or traditional python bracket notation to access key names.

Note: Reserved key names that cannot be accessed using dot notation can be accessed via standard python dictionary notation. (e.g. _.foo["get"] instead of _.foo.get)

A simple query:

cat data.json | jello _.foo

or

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

Simple Examples

jello simply pretty prints the JSON if there are no options passed:

echo '{"foo":"bar","baz":[1,2,3]}' | jello

{
  "foo": "bar",
  "baz": [
    1,
    2,
    3
  ]
}

If you prefer compact output, use the -c option:

echo '{"foo":"bar","baz":[1,2,3]}' | jello -c

{"foo":"bar","baz":[1,2,3]}

Use the -l option to convert lists/arrays into lines:

echo '{"foo":"bar","baz":[1,2,3]}' | jello -l _.baz

1
2
3

You can also create JSON Lines with the -l option:

echo '[{"foo":"bar","baz":[1,2,3]},{"foo":"bar","baz":[1,2,3]}]' | jello -l

{"foo":"bar","baz":[1,2,3]}
{"foo":"bar","baz":[1,2,3]}

You can also print a grep-able schema by using the -s option:

echo '{"foo":"bar","baz":[1,2,3]}' | jello -s

.foo = "bar";
.baz[0] = 1;
.baz[1] = 2;
.baz[2] = 3;

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.

Bash variable:

variable=($(cat data.json | jello -rl _.foo))

Bash array variable:

variable=()
while read -r value; do
    variable+=("$value")
done < <(cat data.json | jello -rl _.foo)

Here is more advanced usage information.

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 = "[e-mail]";
.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 = "[e-mail]";
.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])'

45

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"}
...