Package Health Score

97 / 100

security
No known security issues
popularity
Key ecosystem project
maintenance
Healthy
community
Active

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Popularity

Key ecosystem project

GitHub Stars: 21.72K
Forks: 1.94K
Contributors: 470

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package pydantic, we found that it has been starred 21,718 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Dec 18, 2024
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 465
Open PR: 18
Last Release: 6 days ago
Last Commit: 6 days ago

Further analysis of the maintenance status of pydantic based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that pydantic demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: No
Contributors: 470
Funding: Yes

A good and healthy external contribution signal for pydantic project, which invites more than one hundred open source maintainers to collaborate on the repository.

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Package

Python Versions Compatibility: >=3.8

Age: 8 years
Latest Release: 6 days ago
Dependencies: 0 Direct
Versions: 162
Maintainers: 2
Wheels: OS Independent

Not sure how to use pydantic?

To help you get started, we've collected the most common ways that pydantic is being used within popular public projects.

dry-python / stories / tests / helpers / examples / contract / pydantic / __init__.py View on Github

baz: int


class ChildWithNull(object):
    @story
    def x(I):
        I.one


class ChildWithShrink(object):
    @story
    def x(I):
        I.one

    @x.contract
    class Contract(BaseModel):
        baz: int


class ChildAlias(object):
    @story
    def x(I):
        I.one

    @x.contract
    class Contract(BaseModel):
        foo: Dict[str, str]
        bar: Dict[str, str]
        baz: Dict[str, int]


class ParamChild(object):

View more ways to use pydantic

Pydantic

Data validation using Python type hints.

Fast and extensible, Pydantic plays nicely with your linters/IDE/brain. Define how data should be in pure, canonical Python 3.8+; validate it with Pydantic.

Pydantic Logfire 🔥

We've recently launched Pydantic Logfire to help you monitor your applications. Learn more

Pydantic V1.10 vs. V2

Pydantic V2 is a ground-up rewrite that offers many new features, performance improvements, and some breaking changes compared to Pydantic V1.

If you're using Pydantic V1 you may want to look at the pydantic V1.10 Documentation or, 1.10.X-fixes git branch. Pydantic V2 also ships with the latest version of Pydantic V1 built in so that you can incrementally upgrade your code base and projects: from pydantic import v1 as pydantic_v1.

Help

See documentation for more details.

Installation

Install using pip install -U pydantic or conda install pydantic -c conda-forge. For more installation options to make Pydantic even faster, see the Install section in the documentation.

A Simple Example

from datetime import datetime
from typing import List, Optional
from pydantic import BaseModel

class User(BaseModel):
    id: int
    name: str = 'John Doe'
    signup_ts: Optional[datetime] = None
    friends: List[int] = []

external_data = {'id': '123', 'signup_ts': '2017-06-01 12:22', 'friends': [1, '2', b'3']}
user = User(**external_data)
print(user)
#> User id=123 name='John Doe' signup_ts=datetime.datetime(2017, 6, 1, 12, 22) friends=[1, 2, 3]
print(user.id)
#> 123

Contributing

For guidance on setting up a development environment and how to make a contribution to Pydantic, see Contributing to Pydantic.

Reporting a Security Vulnerability

See our security policy.

Changelog

v2.10.4 (2024-12-18)

GitHub release

What's Changed

Packaging

Bump pydantic-core to v2.27.2 by @davidhewitt in #11138

Fixes

Fix for comparison of AnyUrl objects by @alexprabhat99 in #11082
Properly fetch PEP 695 type params for functions, do not fetch annotations from signature by @Viicos in #11093
Include JSON Schema input core schema in function schemas by @Viicos in #11085
Add len to _BaseUrl to avoid TypeError by @Kharianne in #11111
Make sure the type reference is removed from the seen references by @Viicos in #11143

New Contributors

@alexprabhat99 made their first contribution in #11082
@Kharianne made their first contribution in #11111

v2.10.3 (2024-12-03)

GitHub release

What's Changed

Fixes

Set fields when defer_build is set on Pydantic dataclasses by @Viicos in #10984
Do not resolve the JSON Schema reference for dict core schema keys by @Viicos in #10989
Use the globals of the function when evaluating the return type for PlainSerializer and WrapSerializer functions by @Viicos in #11008
Fix host required enforcement for urls to be compatible with v2.9 behavior by @sydney-runkle in #11027
Add a default_factory_takes_validated_data property to FieldInfo by @Viicos in #11034
Fix url json schema in serialization mode by @sydney-runkle in #11035

v2.10.2 (2024-11-25)

GitHub release

What's Changed

Fixes

Only evaluate FieldInfo annotations if required during schema building by @Viicos in #10769
Do not evaluate annotations for private fields by @Viicos in #10962
Support serialization as any for Secret types and Url types by @sydney-runkle in #10947
Fix type hint of Field.default to be compatible with Python 3.8 and 3.9 by @Viicos in #10972
Add hashing support for URL types by @sydney-runkle in #10975
Hide BaseModel.__replace__ definition from type checkers by @Viicos in 10979

v2.10.1 (2024-11-21)

GitHub release

What's Changed

Packaging

Bump pydantic-core version to v2.27.1 by @sydney-runkle in #10938

Fixes

Use the correct frame when instantiating a parametrized TypeAdapter by @Viicos in #10893
Relax check for validated data in default_factory utils by @sydney-runkle in #10909
Fix type checking issue with model_fields and model_computed_fields by @sydney-runkle in #10911
Use the parent configuration during schema generation for stdlib dataclasses by @sydney-runkle in #10928
Use the globals of the function when evaluating the return type of serializers and computed_fields by @Viicos in #10929
Fix URL constraint application by @sydney-runkle in #10922
Fix URL equality with different validation methods by @sydney-runkle in #10934
Fix JSON schema title when specified as '' by @sydney-runkle in #10936
Fix python mode serialization for complex inference by @sydney-runkle in pydantic-core#1549

v2.10.0 (2024-11-20)

The code released in v2.10.0 is practically identical to that of v2.10.0b2.

GitHub release

See the v2.10 release blog post for the highlights!

What's Changed

Packaging

Bump pydantic-core to v2.27.0 by @sydney-runkle in #10825
Replaced pdm with uv by @frfahim in #10727

New Features

Support fractions.Fraction by @sydney-runkle in #10318
Support Hashable for json validation by @sydney-runkle in #10324
Add a SocketPath type for linux systems by @theunkn0wn1 in #10378
Allow arbitrary refs in JSON schema examples by @sydney-runkle in #10417
Support defer_build for Pydantic dataclasses by @Viicos in #10313
Adding v1 / v2 incompatibility warning for nested v1 model by @sydney-runkle in #10431
Add support for unpacked TypedDict to type hint variadic keyword arguments with @validate_call by @Viicos in #10416
Support compiled patterns in protected_namespaces by @sydney-runkle in #10522
Add support for propertyNames in JSON schema by @FlorianSW in #10478
Adding __replace__ protocol for Python 3.13+ support by @sydney-runkle in #10596
Expose public sort method for JSON schema generation by @sydney-runkle in #10595
Add runtime validation of @validate_call callable argument by @kc0506 in #10627
Add experimental_allow_partial support by @samuelcolvin in #10748
Support default factories taking validated data as an argument by @Viicos in #10678
Allow subclassing ValidationError and PydanticCustomError by @Youssefares in pydantic/pydantic-core#1413
Add trailing-strings support to experimental_allow_partial by @sydney-runkle in #10825
Add rebuild() method for TypeAdapter and simplify defer_build patterns by @sydney-runkle in #10537
Improve TypeAdapter instance repr by @sydney-runkle in #10872

Changes

Don't allow customization of SchemaGenerator until interface is more stable by @sydney-runkle in #10303
Cleanly defer_build on TypeAdapters, removing experimental flag by @sydney-runkle in #10329
Fix mro of generic subclass by @kc0506 in #10100
Strip whitespaces on JSON Schema title generation by @sydney-runkle in #10404
Use b64decode and b64encode for Base64Bytes type by @sydney-runkle in #10486
Relax protected namespace config default by @sydney-runkle in #10441
Revalidate parametrized generics if instance's origin is subclass of OG class by @sydney-runkle in #10666
Warn if configuration is specified on the @dataclass decorator and with the __pydantic_config__ attribute by @sydney-runkle in #10406
Recommend against using Ellipsis (...) with Field by @Viicos in #10661
Migrate to subclassing instead of annotated approach for pydantic url types by @sydney-runkle in #10662
Change JSON schema generation of Literals and Enums by @Viicos in #10692
Simplify unions involving Any or Never when replacing type variables by @Viicos in #10338
Do not require padding when decoding base64 bytes by @bschoenmaeckers in pydantic/pydantic-core#1448
Support dates all the way to 1BC by @changhc in pydantic/speedate#77

Performance

Schema cleaning: skip unnecessary copies during schema walking by @Viicos in #10286
Refactor namespace logic for annotations evaluation by @Viicos in #10530
Improve email regexp on edge cases by @AlekseyLobanov in #10601
CoreMetadata refactor with an emphasis on documentation, schema build time performance, and reducing complexity by @sydney-runkle in #10675

Fixes

Remove guarding check on computed_field with field_serializer by @nix010 in #10390
Fix Predicate issue in v2.9.0 by @sydney-runkle in #10321
Fixing annotated-types bound by @sydney-runkle in #10327
Turn tzdata install requirement into optional timezone dependency by @jakob-keller in #10331
Use correct types namespace when building namedtuple core schemas by @Viicos in #10337
Fix evaluation of stringified annotations during namespace inspection by @Viicos in #10347
Fix IncEx type alias definition by @Viicos in #10339
Do not error when trying to evaluate annotations of private attributes by @Viicos in #10358
Fix nested type statement by @kc0506 in #10369
Improve typing of ModelMetaclass.mro by @Viicos in #10372
Fix class access of deprecated computed_fields by @Viicos in #10391
Make sure inspect.iscoroutinefunction works on coroutines decorated with @validate_call by @MovisLi in #10374
Fix NameError when using validate_call with PEP 695 on a class by @kc0506 in #10380
Fix ZoneInfo with various invalid types by @sydney-runkle in #10408
Fix PydanticUserError on empty model_config with annotations by @cdwilson in #10412
Fix variance issue in _IncEx type alias, only allow True by @Viicos in #10414
Fix serialization schema generation when using PlainValidator by @Viicos in #10427
Fix schema generation error when serialization schema holds references by @Viicos in #10444
Inline references if possible when generating schema for json_schema_input_type by @Viicos in #10439
Fix recursive arguments in Representation by @Viicos in #10480
Fix representation for builtin function types by @kschwab in #10479
Add python validators for decimal constraints (max_digits and decimal_places) by @sydney-runkle in #10506
Only fetch __pydantic_core_schema__ from the current class during schema generation by @Viicos in #10518
Fix stacklevel on deprecation warnings for BaseModel by @sydney-runkle in #10520
Fix warning stacklevel in BaseModel.__init__ by @Viicos in #10526
Improve error handling for in-evaluable refs for discriminator application by @sydney-runkle in #10440
Change the signature of ConfigWrapper.core_config to take the title directly by @Viicos in #10562
Do not use the previous config from the stack for dataclasses without config by @Viicos in #10576
Fix serialization for IP types with mode='python' by @sydney-runkle in #10594
Support constraint application for Base64Etc types by @sydney-runkle in #10584
Fix validate_call ignoring Field in Annotated by @kc0506 in #10610
Raise an error when Self is invalid by @kc0506 in #10609
Using core_schema.InvalidSchema instead of metadata injection + checks by @sydney-runkle in #10523
Tweak type alias logic by @kc0506 in #10643
Support usage of type with typing.Self and type aliases by @kc0506 in #10621
Use overloads for Field and PrivateAttr functions by @Viicos in #10651
Clean up the mypy plugin implementation by @Viicos in #10669
Properly check for typing_extensions variant of TypeAliasType by @Daraan in #10713
Allow any mapping in BaseModel.model_copy() by @Viicos in #10751
Fix isinstance behavior for urls by @sydney-runkle in #10766
Ensure cached_property can be set on Pydantic models by @Viicos in #10774
Fix equality checks for primitives in literals by @sydney-runkle in pydantic/pydantic-core#1459
Properly enforce host_required for URLs by @Viicos in pydantic/pydantic-core#1488
Fix when coerce_numbers_to_str enabled and string has invalid Unicode character by @andrey-berenda in pydantic/pydantic-core#1515
Fix serializing complex values in Enums by @changhc in pydantic/pydantic-core#1524
Refactor _typing_extra module by @Viicos in #10725
Support intuitive equality for urls by @sydney-runkle in #10798
Add bytearray to TypeAdapter.validate_json signature by @samuelcolvin in #10802
Ensure class access of method descriptors is performed when used as a default with Field by @Viicos in #10816
Fix circular import with validate_call by @sydney-runkle in #10807
Fix error when using type aliases referencing other type aliases by @Viicos in #10809
Fix IncEx type alias to be compatible with mypy by @Viicos in #10813
Make __signature__ a lazy property, do not deepcopy defaults by @Viicos in #10818
Make __signature__ lazy for dataclasses, too by @sydney-runkle in #10832
Subclass all single host url classes from AnyUrl to preserve behavior from v2.9 by @sydney-runkle in #10856

New Contributors

@jakob-keller made their first contribution in #10331
@MovisLi made their first contribution in #10374
@joaopalmeiro made their first contribution in #10405
@theunkn0wn1 made their first contribution in #10378
@cdwilson made their first contribution in #10412
@dlax made their first contribution in #10421
@kschwab made their first contribution in #10479
@santibreo made their first contribution in #10453
@FlorianSW made their first contribution in #10478
@tkasuz made their first contribution in #10555
@AlekseyLobanov made their first contribution in #10601
@NiclasvanEyk made their first contribution in #10667
@mschoettle made their first contribution in #10677
@Daraan made their first contribution in #10713
@k4nar made their first contribution in #10736
@UriyaHarpeness made their first contribution in #10740
@frfahim made their first contribution in #10727

v2.10.0b2 (2024-11-13)

Pre-release, see the GitHub release for details.

v2.10.0b1 (2024-11-06)

Pre-release, see the GitHub release for details.

... see here for earlier changes.

FAQs

What is pydantic?

Data validation using Python type hints. Visit Snyk Advisor to see a full health score report for pydantic, including popularity, security, maintenance & community analysis.

Is pydantic popular?

The python package pydantic receives a total of 63,182,319 weekly downloads. As such, pydantic popularity was classified as a key ecosystem project. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is pydantic well maintained?

We found that pydantic demonstrated a healthy version release cadence and project activity. It has a community of 470 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is pydantic safe to use?

The python package pydantic was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 24 December-2024, at 16:58 (UTC).

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Pydantic

Pydantic Logfire 🔥

Pydantic V1.10 vs. V2

Help

Installation

A Simple Example

Contributing

Reporting a Security Vulnerability

Changelog

v2.10.4 (2024-12-18)

What's Changed

Packaging

Fixes

New Contributors

v2.10.3 (2024-12-03)

What's Changed

Fixes

v2.10.2 (2024-11-25)

What's Changed

Fixes

v2.10.1 (2024-11-21)

What's Changed

Packaging

Fixes

v2.10.0 (2024-11-20)

What's Changed

Packaging

New Features

Changes

Performance

Fixes

New Contributors

v2.10.0b2 (2024-11-13)

v2.10.0b1 (2024-11-06)

FAQs

What is pydantic?

Is pydantic popular?

Is pydantic well maintained?

Is pydantic safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

Monitor for new issues