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☄️ Python's nested data operator (and CLI), for all your declarative restructuring needs. Got data? Glom it! ☄️


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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 3.7+, as well as PyPy3. 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.


  --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, python, toml,
                                  or yaml) (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.


Without glom

>>> data = {'a': {'b': {'c': 'd'}}}
>>> data['a']['b']['c']
>>> 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')
>>> 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:

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! ☄️