[](https://github.com/kellyjonbrazil/jello/actions)
[](https://pypi.org/project/jello/)
>Built on `jello`:
>- [Jello Explorer](https://github.com/kellyjonbrazil/jellex) (aka `jellex`) interactive TUI
>- `jello` [web demo](https://jello-web.onrender.com)
# 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` via STDIN or can be loaded from a JSON file or JSON Lines files (JSON Lines are automatically slurped into a list of dictionaries). Once loaded, the data is available as a python list or dictionary object named '`_`'. 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
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](https://pypi.org/project/jello/):
[](https://pypi.org/project/jello/)
```bash
pip3 install jello
```
### Packages and Binaries
| OS | Command |
|-----------------------|--------------------------|
| Debian/Ubuntu linux | `apt-get install jello` |
| Fedora linux | `dnf install jello` |
| Arch linux | `pacman -S jello` |
| macOS | `brew install jello` |
> For more OS packages, see https://repology.org/project/jello/versions.
See [Releases](https://github.com/kellyjonbrazil/jello/releases) on Github for MSI packages and binaries.
### Usage
```
cat data.json | jello [OPTIONS] [QUERY | -q <query_file>]
jello [OPTIONS] [QUERY | -q <query_file>] [-f <input_files>]
```
`QUERY` is optional and can be most any valid python code. Alternatively, a
query file can be specified with `-q` to load the query from a file. Within the query, `_` 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:
```bash
cat data.json | jello _.foo
```
or
```bash
jello _.foo -f data.json
```
or
```bash
jello '_["foo"]' -f data.json
```
#### Options
- `-c` compact print JSON output instead of pretty printing
- `-C` force color output even when using pipes (overrides `-m` and the `NO_COLOR` env variable)
- `-e` empty data (don't process data from STDIN or file)
- `-f` load input data from JSON file or JSON Lines files (must be the final option, if used)
- `-i` initialize environment with a custom config file
- `-l` lines output (suitable for bash array assignment)
- `-m` monochrome output
- `-n` print selected `null` values
- `-q` load query from a file
- `-r` raw output of selected strings (no quotes)
- `-s` print the JSON schema in grep-able format
- `-t` print type annotations in schema view
- `-h` help
- `-v` version info
#### Simple Examples
`jello` simply pretty prints the JSON if there are no options or query passed:
```bash
echo '{"foo":"bar","baz":[1,2,3]}' | jello
{
"foo": "bar",
"baz": [
1,
2,
3
]
}
```
If you prefer compact output, use the `-c` option:
```bash
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:
```bash
echo '{"foo":"bar","baz":[1,2,3]}' | jello -l _.baz
1
2
3
```
The `-l` option also allows you to create [JSON Lines](https://jsonlines.org/):
```bash
echo '[{"foo":"bar","baz":[1,2,3]},{"fiz":"boo","buz":[4,5,6]}]' | jello -l
{"foo":"bar","baz":[1,2,3]}
{"fiz":"boo","buz":[4,5,6]}
```
You can print a grep-able schema by using the `-s` option:
```bash
echo '{"foo":"bar","baz":[1,2,3]}' | jello -s
_ = {};
_.foo = "bar";
_.baz = [];
_.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 printed as blank lines.
Bash variable:
```
variable=($(cat data.json | jello -rl _.foo))
```
Bash array variable (Bash 4+):
```
mapfile -t variable < <(cat data.json | jello -rl _.foo)
```
Bash array variable (older versions of Bash):
```
variable=()
while read -r value; do
variable+=("$value")
done < <(cat data.json | jello -rl _.foo)
```
### Setting Custom Colors via Environment Variable
Custom colors can be set via the `JELLO_COLORS` environment variable. Any colors set in the environment variable will take precedence over any colors set in the initialization file. (see [Advanced Usage](https://github.com/kellyjonbrazil/jello/blob/master/ADVANCED_USAGE.md))
The `JELLO_COLORS` environment variable takes four comma separated string values in the following format:
```
JELLO_COLORS=<keyname_color>,<keyword_color>,<number_color>,<string_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
```
or
```
JELLO_COLORS=default,default,default,default
```
### Disable Colors via Environment Variable
You can set the [`NO_COLOR`](http://no-color.org/) environment variable to any value to disable color output in `jello`. Note that using the `-C` option to force color output will override both the `NO_COLOR` environment variable and the `-m` option.
### Advanced Usage
Here is more [Advanced Usage](https://github.com/kellyjonbrazil/jello/blob/master/ADVANCED_USAGE.md) information.
> To accelerate filter development and testing, try [`jellex`](https://github.com/kellyjonbrazil/jellex). `jellex` is an interactive front-end TUI built on `jello` that allows you to see your filter results in real-time along with any errors.
## Examples:
### Printing the Grep-able Schema
```bash
$ jc -a | jello -s
_ = {};
_.name = "jc";
_.version = "1.17.2";
_.description = "JSON CLI output utility";
_.author = "Kelly Brazil";
_.author_email = "kellyjonbrazil@gmail.com";
_.website = "https://github.com/kellyjonbrazil/jc";
_.copyright = "© 2019-2021 Kelly Brazil";
_.license = "MIT License";
_.parser_count = 80;
_.parsers = [];
_.parsers[0] = {};
_.parsers[0].name = "acpi";
_.parsers[0].argument = "--acpi";
_.parsers[0].version = "1.2";
_.parsers[0].description = "`acpi` command parser";
_.parsers[0].author = "Kelly Brazil";
_.parsers[0].author_email = "kellyjonbrazil@gmail.com";
_.parsers[0].compatible = [];
_.parsers[0].compatible[0] = "linux";
_.parsers[0].magic_commands = [];
_.parsers[0].magic_commands[0] = "acpi";
_.parsers[1] = {};
_.parsers[1].name = "airport";
_.parsers[1].argument = "--airport";
_.parsers[1].version = "1.3";
...
```
### Printing the Grep-able Schema with type annotations (useful for grepping types)
```bash
jc dig example.com | jello -st
_ = []; // (array)
_[0] = {}; // (object)
_[0].id = 23819; // (number)
_[0].opcode = "QUERY"; // (string)
_[0].status = "NOERROR"; // (string)
_[0].flags = []; // (array)
_[0].flags[0] = "qr"; // (string)
_[0].flags[1] = "rd"; // (string)
_[0].flags[2] = "ra"; // (string)
_[0].query_num = 1; // (number)
_[0].answer_num = 1; // (number)
_[0].authority_num = 0; // (number)
_[0].additional_num = 1; // (number)
_[0].opt_pseudosection = {}; // (object)
_[0].opt_pseudosection.edns = {}; // (object)
_[0].opt_pseudosection.edns.version = 0; // (number)
_[0].opt_pseudosection.edns.flags = []; // (array)
_[0].opt_pseudosection.edns.udp = 4096; // (number)
_[0].question = {}; // (object)
_[0].question.name = "example.com."; // (string)
_[0].question.class = "IN"; // (string)
_[0].question.type = "A"; // (string)
_[0].answer = []; // (array)
_[0].answer[0] = {}; // (object)
_[0].answer[0].name = "example.com."; // (string)
_[0].answer[0].class = "IN"; // (string)
_[0].answer[0].type = "A"; // (string)
_[0].answer[0].ttl = 48358; // (number)
_[0].answer[0].data = "93.184.216.34"; // (string)
_[0].query_time = 46; // (number)
_[0].server = "2600:1700:bab0:d40::1#53(2600:1700:bab0:d40::1)"; // (string)
_[0].when = "Mon Nov 29 09:41:11 PST 2021"; // (string)
_[0].rcvd = 56; // (number)
_[0].when_epoch = 1638207671; // (number)
_[0].when_epoch_utc = null; // (null)
```
### Printing the Structure of the JSON
```bash
jc dig example.com | jello -st | grep '(object)\|(array)'
_ = []; // (array)
_[0] = {}; // (object)
_[0].flags = []; // (array)
_[0].opt_pseudosection = {}; // (object)
_[0].opt_pseudosection.edns = {}; // (object)
_[0].opt_pseudosection.edns.flags = []; // (array)
_[0].question = {}; // (object)
_[0].answer = []; // (array)
_[0].answer[0] = {}; // (object)
```
### Lambda Functions and Math
```bash
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
}
```
```bash
jc -a | jello 'len([entry for entry in _.parsers if "darwin" in entry.compatible])'
45
```
### For Loops
Output as JSON array
```bash
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
```bash
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
```bash
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
```bash
jc -a | jello -rl '[entry.name for entry in _.parsers if "darwin" in entry.compatible]'
airport
airport_s
arp
crontab
crontab_u
...
```
### Expressions and Environment Variables
```bash
echo '{"login_name": "joeuser"}' | jello 'os.getenv("LOGNAME") == _.login_name'
true
```
### Using 3rd Party Modules
You can import and use your favorite modules to manipulate the data. For example, using `glom`:
```bash
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`:
```bash
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"}
...
```
Raw data
{
"_id": null,
"home_page": "https://github.com/kellyjonbrazil/jello",
"name": "jello",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.6",
"maintainer_email": "",
"keywords": "",
"author": "Kelly Brazil",
"author_email": "kellyjonbrazil@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/8a/1d/25e13e337f0c5c8076a4fc42db02b726529b611a69d816b71f8d591cf0f5/jello-1.6.0.tar.gz",
"platform": null,
"description": "[](https://github.com/kellyjonbrazil/jello/actions)\n[](https://pypi.org/project/jello/)\n\n>Built on `jello`:\n>- [Jello Explorer](https://github.com/kellyjonbrazil/jellex) (aka `jellex`) interactive TUI\n>- `jello` [web demo](https://jello-web.onrender.com)\n\n# jello\nFilter JSON and JSON Lines data with Python syntax\n\n`jello` is similar to `jq` in that it processes JSON and JSON Lines data except `jello` uses standard python dict and list syntax.\n\nJSON or JSON Lines can be piped into `jello` via STDIN or can be loaded from a JSON file or JSON Lines files (JSON Lines are automatically slurped into a list of dictionaries). Once loaded, the data is available as a python list or dictionary object named '`_`'. Processed data can be output as JSON, JSON Lines, bash array lines, or a grep-able schema.\n\nFor 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/).\n\n## Install\nYou 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.\n\n### Pip (macOS, linux, unix, Windows)\nFor the most up-to-date version and the most cross-platform option, use `pip` or `pip3` to download and install `jello` directly from [PyPi](https://pypi.org/project/jello/):\n\n[](https://pypi.org/project/jello/)\n\n```bash\npip3 install jello\n```\n\n### Packages and Binaries\n\n| OS | Command |\n|-----------------------|--------------------------|\n| Debian/Ubuntu linux | `apt-get install jello` |\n| Fedora linux | `dnf install jello` |\n| Arch linux | `pacman -S jello` |\n| macOS | `brew install jello` |\n\n> For more OS packages, see https://repology.org/project/jello/versions.\n\nSee [Releases](https://github.com/kellyjonbrazil/jello/releases) on Github for MSI packages and binaries.\n\n### Usage\n```\ncat data.json | jello [OPTIONS] [QUERY | -q <query_file>]\n\njello [OPTIONS] [QUERY | -q <query_file>] [-f <input_files>]\n```\n`QUERY` is optional and can be most any valid python code. Alternatively, a\nquery file can be specified with `-q` to load the query from a file. Within the query, `_` 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.\n\n> 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`)\n\nA simple query:\n```bash\ncat data.json | jello _.foo\n```\nor\n```bash\njello _.foo -f data.json\n```\nor\n```bash\njello '_[\"foo\"]' -f data.json\n```\n\n#### Options\n- `-c` compact print JSON output instead of pretty printing\n- `-C` force color output even when using pipes (overrides `-m` and the `NO_COLOR` env variable)\n- `-e` empty data (don't process data from STDIN or file)\n- `-f` load input data from JSON file or JSON Lines files (must be the final option, if used)\n- `-i` initialize environment with a custom config file\n- `-l` lines output (suitable for bash array assignment)\n- `-m` monochrome output\n- `-n` print selected `null` values\n- `-q` load query from a file\n- `-r` raw output of selected strings (no quotes)\n- `-s` print the JSON schema in grep-able format\n- `-t` print type annotations in schema view\n- `-h` help\n- `-v` version info\n\n#### Simple Examples\n`jello` simply pretty prints the JSON if there are no options or query passed:\n```bash\necho '{\"foo\":\"bar\",\"baz\":[1,2,3]}' | jello\n\n{\n \"foo\": \"bar\",\n \"baz\": [\n 1,\n 2,\n 3\n ]\n}\n```\n\nIf you prefer compact output, use the `-c` option:\n```bash\necho '{\"foo\":\"bar\",\"baz\":[1,2,3]}' | jello -c\n\n{\"foo\":\"bar\",\"baz\":[1,2,3]}\n```\n\nUse the `-l` option to convert lists/arrays into lines:\n```bash\necho '{\"foo\":\"bar\",\"baz\":[1,2,3]}' | jello -l _.baz\n\n1\n2\n3\n```\n\nThe `-l` option also allows you to create [JSON Lines](https://jsonlines.org/):\n```bash\necho '[{\"foo\":\"bar\",\"baz\":[1,2,3]},{\"fiz\":\"boo\",\"buz\":[4,5,6]}]' | jello -l\n\n{\"foo\":\"bar\",\"baz\":[1,2,3]}\n{\"fiz\":\"boo\",\"buz\":[4,5,6]}\n```\n\nYou can print a grep-able schema by using the `-s` option:\n```bash\necho '{\"foo\":\"bar\",\"baz\":[1,2,3]}' | jello -s\n\n_ = {};\n_.foo = \"bar\";\n_.baz = [];\n_.baz[0] = 1;\n_.baz[1] = 2;\n_.baz[2] = 3;\n```\n\n#### Assigning Results to a Bash Array\n\nUse 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 printed as blank lines.\n\nBash variable:\n```\nvariable=($(cat data.json | jello -rl _.foo))\n```\n\nBash array variable (Bash 4+):\n```\nmapfile -t variable < <(cat data.json | jello -rl _.foo)\n```\n\nBash array variable (older versions of Bash):\n```\nvariable=()\nwhile read -r value; do\n variable+=(\"$value\")\ndone < <(cat data.json | jello -rl _.foo)\n```\n\n### Setting Custom Colors via Environment Variable\nCustom colors can be set via the `JELLO_COLORS` environment variable. Any colors set in the environment variable will take precedence over any colors set in the initialization file. (see [Advanced Usage](https://github.com/kellyjonbrazil/jello/blob/master/ADVANCED_USAGE.md))\n\nThe `JELLO_COLORS` environment variable takes four comma separated string values in the following format:\n```\nJELLO_COLORS=<keyname_color>,<keyword_color>,<number_color>,<string_color>\n```\nWhere colors are: `black`, `red`, `green`, `yellow`, `blue`, `magenta`, `cyan`, `gray`, `brightblack`, `brightred`, `brightgreen`, `brightyellow`, `brightblue`, `brightmagenta`, `brightcyan`, `white`, or `default`\n\nFor example, to set to the default colors:\n```\nJELLO_COLORS=blue,brightblack,magenta,green\n```\nor\n```\nJELLO_COLORS=default,default,default,default\n```\n\n### Disable Colors via Environment Variable\nYou can set the [`NO_COLOR`](http://no-color.org/) environment variable to any value to disable color output in `jello`. Note that using the `-C` option to force color output will override both the `NO_COLOR` environment variable and the `-m` option.\n\n### Advanced Usage\nHere is more [Advanced Usage](https://github.com/kellyjonbrazil/jello/blob/master/ADVANCED_USAGE.md) information.\n\n> To accelerate filter development and testing, try [`jellex`](https://github.com/kellyjonbrazil/jellex). `jellex` is an interactive front-end TUI built on `jello` that allows you to see your filter results in real-time along with any errors.\n\n## Examples:\n### Printing the Grep-able Schema\n```bash\n$ jc -a | jello -s\n\n_ = {};\n_.name = \"jc\";\n_.version = \"1.17.2\";\n_.description = \"JSON CLI output utility\";\n_.author = \"Kelly Brazil\";\n_.author_email = \"kellyjonbrazil@gmail.com\";\n_.website = \"https://github.com/kellyjonbrazil/jc\";\n_.copyright = \"\u00a9 2019-2021 Kelly Brazil\";\n_.license = \"MIT License\";\n_.parser_count = 80;\n_.parsers = [];\n_.parsers[0] = {};\n_.parsers[0].name = \"acpi\";\n_.parsers[0].argument = \"--acpi\";\n_.parsers[0].version = \"1.2\";\n_.parsers[0].description = \"`acpi` command parser\";\n_.parsers[0].author = \"Kelly Brazil\";\n_.parsers[0].author_email = \"kellyjonbrazil@gmail.com\";\n_.parsers[0].compatible = [];\n_.parsers[0].compatible[0] = \"linux\";\n_.parsers[0].magic_commands = [];\n_.parsers[0].magic_commands[0] = \"acpi\";\n_.parsers[1] = {};\n_.parsers[1].name = \"airport\";\n_.parsers[1].argument = \"--airport\";\n_.parsers[1].version = \"1.3\";\n...\n```\n### Printing the Grep-able Schema with type annotations (useful for grepping types)\n```bash\njc dig example.com | jello -st\n\n_ = []; // (array)\n_[0] = {}; // (object)\n_[0].id = 23819; // (number)\n_[0].opcode = \"QUERY\"; // (string)\n_[0].status = \"NOERROR\"; // (string)\n_[0].flags = []; // (array)\n_[0].flags[0] = \"qr\"; // (string)\n_[0].flags[1] = \"rd\"; // (string)\n_[0].flags[2] = \"ra\"; // (string)\n_[0].query_num = 1; // (number)\n_[0].answer_num = 1; // (number)\n_[0].authority_num = 0; // (number)\n_[0].additional_num = 1; // (number)\n_[0].opt_pseudosection = {}; // (object)\n_[0].opt_pseudosection.edns = {}; // (object)\n_[0].opt_pseudosection.edns.version = 0; // (number)\n_[0].opt_pseudosection.edns.flags = []; // (array)\n_[0].opt_pseudosection.edns.udp = 4096; // (number)\n_[0].question = {}; // (object)\n_[0].question.name = \"example.com.\"; // (string)\n_[0].question.class = \"IN\"; // (string)\n_[0].question.type = \"A\"; // (string)\n_[0].answer = []; // (array)\n_[0].answer[0] = {}; // (object)\n_[0].answer[0].name = \"example.com.\"; // (string)\n_[0].answer[0].class = \"IN\"; // (string)\n_[0].answer[0].type = \"A\"; // (string)\n_[0].answer[0].ttl = 48358; // (number)\n_[0].answer[0].data = \"93.184.216.34\"; // (string)\n_[0].query_time = 46; // (number)\n_[0].server = \"2600:1700:bab0:d40::1#53(2600:1700:bab0:d40::1)\"; // (string)\n_[0].when = \"Mon Nov 29 09:41:11 PST 2021\"; // (string)\n_[0].rcvd = 56; // (number)\n_[0].when_epoch = 1638207671; // (number)\n_[0].when_epoch_utc = null; // (null)\n```\n### Printing the Structure of the JSON\n```bash\njc dig example.com | jello -st | grep '(object)\\|(array)'\n\n_ = []; // (array)\n_[0] = {}; // (object)\n_[0].flags = []; // (array)\n_[0].opt_pseudosection = {}; // (object)\n_[0].opt_pseudosection.edns = {}; // (object)\n_[0].opt_pseudosection.edns.flags = []; // (array)\n_[0].question = {}; // (object)\n_[0].answer = []; // (array)\n_[0].answer[0] = {}; // (object)\n```\n### Lambda Functions and Math\n```bash\necho '{\"t1\":-30, \"t2\":-20, \"t3\":-10, \"t4\":0}' | jello '\\\nkeys = _.keys()\nvals = _.values()\ncel = list(map(lambda x: (float(5)/9)*(x-32), vals))\ndict(zip(keys, cel))'\n\n{\n \"t1\": -34.44444444444444,\n \"t2\": -28.88888888888889,\n \"t3\": -23.333333333333336,\n \"t4\": -17.77777777777778\n}\n\n```\n\n```bash\njc -a | jello 'len([entry for entry in _.parsers if \"darwin\" in entry.compatible])'\n\n45\n```\n\n### For Loops\nOutput as JSON array\n```bash\njc -a | jello '\\\nresult = []\nfor entry in _.parsers:\n if \"darwin\" in entry.compatible:\n result.append(entry.name)\nresult'\n\n[\n \"airport\",\n \"airport_s\",\n \"arp\",\n \"crontab\",\n \"crontab_u\",\n ...\n]\n```\nOutput as bash array\n```bash\njc -a | jello -rl '\\\nresult = []\nfor entry in _.parsers:\n if \"darwin\" in entry.compatible:\n result.append(entry.name)\nresult'\n\nairport\nairport_s\narp\ncrontab\ncrontab_u\n...\n```\n### List and Dictionary Comprehension\nOutput as JSON array\n```bash\njc -a | jello '[entry.name for entry in _.parsers if \"darwin\" in entry.compatible]'\n\n[\n \"airport\",\n \"airport_s\",\n \"arp\",\n \"crontab\",\n \"crontab_u\",\n ...\n]\n```\n\nOutput as bash array\n```bash\njc -a | jello -rl '[entry.name for entry in _.parsers if \"darwin\" in entry.compatible]'\n\nairport\nairport_s\narp\ncrontab\ncrontab_u\n...\n```\n\n### Expressions and Environment Variables\n```bash\necho '{\"login_name\": \"joeuser\"}' | jello 'os.getenv(\"LOGNAME\") == _.login_name'\n\ntrue\n```\n\n### Using 3rd Party Modules\nYou can import and use your favorite modules to manipulate the data. For example, using `glom`:\n```bash\njc -a | jello '\\\nfrom glom import *\nglom(_, (\"parsers\", [\"name\"]))'\n\n[\n \"airport\",\n \"airport_s\",\n \"arp\",\n \"blkid\",\n \"crontab\",\n \"crontab_u\",\n \"csv\",\n ...\n]\n```\n\n### Advanced JSON Manipulation\nThe data from this example comes from https://programminghistorian.org/assets/jq_twitter.json\n\nUnder **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:\n\n> \"We can now create a table of users. Let\u2019s create a table with columns for the user id, user name, followers count, and a column of their tweet ids separated by a semicolon.\"\n\nhttps://programminghistorian.org/en/lessons/json-and-jq\n\nHere is a simple solution using `jello`:\n```bash\ncat jq_twitter.json | jello -l '\\\nuser_ids = set()\nfor tweet in _:\n user_ids.add(tweet.user.id)\nresult = []\nfor user in user_ids:\n user_profile = {}\n tweet_ids = []\n for tweet in _:\n if tweet.user.id == user:\n user_profile.update({\n \"user_id\": user,\n \"user_name\": tweet.user.screen_name,\n \"user_followers\": tweet.user.followers_count})\n tweet_ids.append(str(tweet.id))\n user_profile[\"tweet_ids\"] = \";\".join(tweet_ids)\n result.append(user_profile)\nresult'\n\n...\n{\"user_id\": 2696111005, \"user_name\": \"EGEVER142\", \"user_followers\": 1433, \"tweet_ids\": \"619172303654518784\"}\n{\"user_id\": 42226593, \"user_name\": \"shirleycolleen\", \"user_followers\": 2114, \"tweet_ids\": \"619172281294655488;619172179960328192\"}\n{\"user_id\": 106948003, \"user_name\": \"MrKneeGrow\", \"user_followers\": 172, \"tweet_ids\": \"501064228627705857\"}\n{\"user_id\": 18270633, \"user_name\": \"ahhthatswhy\", \"user_followers\": 559, \"tweet_ids\": \"501064204661850113\"}\n{\"user_id\": 14331818, \"user_name\": \"edsu\", \"user_followers\": 4220, \"tweet_ids\": \"615973042443956225;618602288781860864\"}\n{\"user_id\": 2569107372, \"user_name\": \"SlavinOleg\", \"user_followers\": 35, \"tweet_ids\": \"501064198973960192;501064202794971136;501064214467731457;501064215759568897;501064220121632768\"}\n{\"user_id\": 22668719, \"user_name\": \"nodehyena\", \"user_followers\": 294, \"tweet_ids\": \"501064222772445187\"}\n...\n```\n",
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