glom

Restructuring data, the Python way

Real applications have real data, and real data nests. Objects inside of objects inside of lists of objects.

glom is a new and powerful way to handle real-world data, featuring:

• Path-based access for nested data structures


• Readable, meaningful error messages


• Declarative data transformation, using lightweight, Pythonic specifications


• Built-in data exploration and debugging features

All of that and more, available as a fully-documented, pure-Python package, tested on Python 2.7-3.7, as well as PyPy. Installation is as easy as:

  pip install glom

And when you install glom, you also get the glom command-line interface, letting you experiment at the console, but never limiting you to shell scripts:

Usage: glom [FLAGS] [spec [target]]



Command-line interface to the glom library, providing nested data access and data

restructuring with the power of Python.



Flags:



  --help / -h                     show this help message and exit

  --target-file TARGET_FILE       path to target data source (optional)

  --target-format TARGET_FORMAT   format of the source data (json or python) (defaults

                                  to 'json')

  --spec-file SPEC_FILE           path to glom spec definition (optional)

  --spec-format SPEC_FORMAT       format of the glom spec definition (json, python,

                                  python-full) (defaults to 'python')

  --indent INDENT                 number of spaces to indent the result, 0 to disable

                                  pretty-printing (defaults to 2)

  --debug                         interactively debug any errors that come up

  --inspect                       interactively explore the data

Anything you can do at the command line readily translates to Python code, so you've always got a path forward when complexity starts to ramp up.

Examples

Without glom

>>> data = {'a': {'b': {'c': 'd'}}}

>>> data['a']['b']['c']

'd'

>>> data2 = {'a': {'b': None}}

>>> data2['a']['b']['c']

Traceback (most recent call last):

...

TypeError: 'NoneType' object is not subscriptable

With glom

>>> glom(data, 'a.b.c')

'd'

>>> glom(data2, 'a.b.c')

Traceback (most recent call last):

...

PathAccessError: could not access 'c', index 2 in path Path('a', 'b', 'c'), got error: ...

Learn more

If all this seems interesting, continue exploring glom below:

• glom Tutorial


• Full API documentation at Read the Docs


• Original announcement blog post (2018-05-09)


• Frequently Asked Questions


• PyCon 2018 Lightning Talk (2018-05-11)

All of the links above are overflowing with examples, but should you find anything about the docs, or glom itself, lacking, please submit an issue!

In the meantime, just remember: When you've got nested data, glom it!
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