Skip to main content

A modern dataclass & data conversion library, focused on speed and expressiveness.

Project description

pane

pane is a modern Python library for dataclasses and data conversion, aiming for speed and expressiveness.

pane draws heavy inspiration from Pydantic (among others), but its goals are quite different. For example, pane has first-class conversion to and from all JSON datatypes, not just mappings (and no 'root' hacks necessary). In this sense pane is a library for general data conversion & validation, while Pydantic is a dataclass-first library. In addition, pane is stricter than Pydantic in several cases. For instance, pane will not attempt to coerce 3.14 or "3" to an integer.

pane is designed to be used to create complex declarative configuration languages in formats like JSON, TOML, and YAML. This requires full support for complex, nested types like t.Union[int, t.Tuple[int, str], list[int]]. It also requires useful error messages:

>>> pane.convert('fail', t.Union[int, t.Tuple[int, str], list[int]])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "pane/convert.py", line 489, in convert
    return from_data(data, ty)
           ^^^^^^^^^^^^^^^^^^^
  File "pane/convert.py", line 484, in from_data
    return converter.convert(val)
           ^^^^^^^^^^^^^^^^^^^^^^
  File "pane/convert.py", line 128, in convert
    raise ConvertError(node)
pane.convert.ConvertError: Expected one of:
- an int
- tuple of length 2
- sequence
Instead got `fail` of type `str`

Features

pane is a work in progress. The following is a roadmap of features:

Feature State
Basic type conversions Done
Numeric array types (numpy) Done
Sum & product type support Done
Tagged unions Partial
'Flattened' fields Planned
Basic dataclasses Done
Dataclass helpers Partial
Generic & inherited dataclasses Done
Parameter aliases & renaming Done
Arbitrary validation logic Done
Schema import/export Not planned

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

py_pane-0.11.5.tar.gz (47.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

py_pane-0.11.5-py3-none-any.whl (41.5 kB view details)

Uploaded Python 3

File details

Details for the file py_pane-0.11.5.tar.gz.

File metadata

  • Download URL: py_pane-0.11.5.tar.gz
  • Upload date:
  • Size: 47.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for py_pane-0.11.5.tar.gz
Algorithm Hash digest
SHA256 715400f7d13224cf2250b5a301aac74a7b442dc3efe40b9cd12c93ef8cb1a920
MD5 7c2eab98cabc8705b6e05fcd54dc130a
BLAKE2b-256 24f3bb13b3344de2371a2414ce529503438856115069769986a9f732d4eb116b

See more details on using hashes here.

File details

Details for the file py_pane-0.11.5-py3-none-any.whl.

File metadata

  • Download URL: py_pane-0.11.5-py3-none-any.whl
  • Upload date:
  • Size: 41.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for py_pane-0.11.5-py3-none-any.whl
Algorithm Hash digest
SHA256 82a5b4cbf29ed6ad66f08b6b3665594ce308a3e65c7422ec9d743db1f28737e2
MD5 69ff9db13ef9538567403b0f92466387
BLAKE2b-256 656dacfdd0a9b6af8387c95c97077c82e18186b55a09761ad83dd02514453c07

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page