docling-core

library2.92.0pypypi✓ verified 29d ago

Docling Core is a Python library for defining, validating, and structuring data types and schemas. It's designed to align with the Docling specification, offering robust data validation capabilities. Currently at version 2.73.0, it undergoes frequent updates, often with daily or weekly releases in its 2.x series.

serialization data

pip install docling-core

github ↗package ↗changelog ↗

INSTALL

IMPORT

SIG · DOCLING-CORE

docling-core

serializationpythonv2.92.0

Install

13.4s avg

Import

—

Disk

229MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v2.92.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.000s · 230MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 13.4s · import 0.000s · 222MB

229MB installed

● package 229MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

DataType

✓ from docling_core import DataType

✗ from docling_core import DataType

This example defines a `User` data type with `Field` validators for name, age, and email. It demonstrates how to instantiate a `DataType` with valid data and handles validation errors for invalid input.

from docling_core import Field, DataType class User(DataType): name = Field(str, description="The user's full name") age = Field(int, min_value=0, description="The user's age") email = Field(str, format="email", description="The user's email address") user_data = { "name": "John Doe", "age": 30, "email": "john.doe@example.com" } try: user = User(user_data) print(f"Validated user: {user.name}, {user.age}, {user.email}") except Exception as e: print(f"Validation error: {e}") # Example of invalid data invalid_user_data = { "name": "Jane Doe", "age": -5, # Invalid age "email": "invalid-email" } try: User(invalid_user_data) except Exception as e: print(f"Validation error for invalid data: {e}")

Debug

Known issues

breakingThe `Type` class was removed and replaced by `DataType`. Code using `from docling_core import Type` or instantiating `Type(...)` will break.

fix

Migrate all `Type` usages to `DataType`. E.g., `from docling_core import DataType`.

affects: >=2.0.0

breakingThe primary exception class for validation errors was renamed from `ValidationError` to `ValidationErrors`.

fix

Update exception handling: `except ValidationErrors as e:` instead of `except ValidationError as e:`.

affects: >=2.0.0

breakingThe `description` argument for `DataType` classes was renamed to `_description` to avoid potential conflicts with user-defined fields.

fix

Change `class MyData(DataType, description="...")` to `class MyData(DataType, _description="...")`.

affects: >=2.0.0

gotchaThe `format` argument in `Field` has stricter validation in 2.x and only accepts specific predefined formats (like 'email', 'uri') or a callable validator. Arbitrary strings might no longer work as expected.

fix

Review `format` usage. Ensure it's one of the supported strings or a callable. Custom format validation might need a separate callable validator.

affects: >=2.0.0

gotchaBy default, `DataType` is strict and will raise `ValidationErrors` if extra fields are provided in the input dictionary that are not defined in the `DataType` schema. Explicitly allow extra fields if needed.

fix

To allow extra fields, define the DataType with `class MyData(DataType, allow_extra_fields=True):`.

affects: >=2.0.0

Upgrade

Version history

2.92.0latest on PyPI · released Aug 19, 2026

Audit

Dependencies

No dependency data recorded yet.

Agent activity

28 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/docling-project/docling-core ↗

packagehttps://pypi.org/project/docling-core/ ↗

changeloghttps://github.com/docling-project/docling-core/blob/main/CHANGELOG.md ↗