No project description provided

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dmontagu from gravatar.com dmontagu Avatar for samuelcolvin from gravatar.com samuelcolvin

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Samuel Colvin
  • Requires: Python >=3.7
Classifiers

Project description

pydantic-core

CI Coverage pypi versions license

This package provides the core functionality for pydantic.

The package is currently a work in progress and subject to significant change.

There is, as yet, no integration with pydantic, so schemas can only be defined via dictionaries.

The plan is for pydantic to adopt pydantic-core in v2 and to generate the schema definition from type hints in pydantic, then create a SchemaValidator upon model creation.

pydantic-core will be a separate package, required by pydantic.

The public interface to pydantic shouldn't change too much as a result of this switch (though I intend to clean up quite a lot in the public API in v2 as well).

Example of usage:

from pydantic_core import SchemaValidator, ValidationError


v = SchemaValidator(
    {
        'type': 'typed-dict',
        'fields': {
            'name': {
                'type': 'typed-dict-field',
                'schema': {
                    'type': 'str',
                },
            },
            'age': {
                'type': 'typed-dict-field',
                'schema': {
                    'type': 'int',
                    'ge': 18,
                },
            },
            'is_developer': {
                'type': 'typed-dict-field',
                'schema': {
                    'type': 'default',
                    'schema': {'type': 'bool'},
                    'default': True,
                },
            },
        },
    }
)

r1 = v.validate_python({'name': 'Samuel', 'age': 35})
assert r1 == {'name': 'Samuel', 'age': 35, 'is_developer': True}

# pydantic-core can also validate JSON directly
r2 = v.validate_json('{"name": "Samuel", "age": 35}')
assert r1 == r2

try:
    v.validate_python({'name': 'Samuel', 'age': 11})
except ValidationError as e:
    print(e)
    """
    1 validation error for model
    age
      Input should be greater than or equal to 18
      [type=greater_than_equal, context={ge: 18}, input_value=11, input_type=int]
    """

Pydantic-core is currently around 17x faster than pydantic standard. See tests/benchmarks/ for details.

This relative performance will be less impressive for small models but could be significantly move impressive for deeply nested models.

The improvement will decrease slightly when we have to create a class instance after validation, but shouldn't change more.

The aim is to remain 10x faster than current pydantic for common use cases.

Getting Started

While pydantic-core is not yet released and not designed for direct use, you can still try it.

You'll need rust stable installed, or rust nightly if you want to generate accurate coverage.

With rust and python 3.7+ installed, compiling pydantic-core should be possible with roughly the following:

# clone this repo or your fork
git clone git@github.com:pydantic/pydantic-core.git
cd pydantic-core
# create a new virtual env
python3 -m venv env
source env/bin/activate
# install dependencies and install pydantic-core
make install

That should be it, the example shown above should now run.

You might find it useful to look at pydantic_core/_pydantic_core.pyi and pydantic_core/core_schema.py for more information on the python API, beyond that, tests/ provide a large number of examples of usage.

If you want to contribute to pydantic-core, you'll want to use some other make commands:

  • make build-dev to build the package during development
  • make build-prod to perform an optimised build for benchmarking
  • make test to run the tests
  • make testcov to run the tests and generate a coverage report
  • make lint to run the linter
  • make format to format python and rust code
  • make to run format build-dev lint test

Why not JSONSchema?

Looking at the above schema passed to SchemaValidator it would seem reasonable to ask "why not use JSONSchema?".

And if we could use JSONSchema, why not use an existing rust library to do validation?

In fact, in the very early commits to pydantic-core, I did try to use JSONSchema, however I quickly realized it wouldn't work.

JSONSchema does not match the schema for pydantic that closely:

  • there are lots of extra checks which pydantic wants to do and aren't covered by JSONSchema
  • there are configurations which are possible in JSONSchema but are hard or impossible to imagine in pydantic
  • pydantic has the concept of parsing or coercion at it's core, JSONSchema doesn't - it assumes you either accept or reject the input, never change it
  • There are whole classes of problem pydantic has to deal with (like python class instance validation) which JSONSchema has no idea about since it's dedicated to JSON

Even if we could use JSONSchema, it wouldn't help much since rust JSONSchema validators expect to know the schema at compile time, pydantic-core has no knowledge of the schema until SchemaValidator is initialised.

Still, it wouldn't be that hard to implement a conversion layer (either in python or rust) to convert JSONSchema to "pydantic schema" and thereby achieve partial JSONSchema validation.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dmontagu from gravatar.com dmontagu Avatar for samuelcolvin from gravatar.com samuelcolvin

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Samuel Colvin
  • Requires: Python >=3.7
Classifiers

Release history Release notifications | RSS feed

2.27.0

2.26.0

2.25.1

2.25.0

2.24.2

2.24.1

2.24.0

2.23.4

2.23.3

2.23.2

2.23.1

2.23.0

2.22.0

2.21.0

2.20.1

2.20.0

2.19.0

2.18.4

2.18.3

2.18.2

2.18.1

2.18.0

2.17.0

2.16.3

2.16.2

2.16.1

2.16.0

2.15.0

2.14.6

2.14.5

2.14.4

2.14.3

2.14.1

2.14.0

2.13.0

2.12.0

2.11.0

2.10.1

2.10.0

2.9.0

2.8.0

2.7.0

2.6.3

2.6.2

2.6.1

2.6.0

2.5.0

2.4.0

2.3.1

2.3.0

2.2.0

2.1.3

2.1.2

2.0.2

2.0.1

2.0.0

0.42.0

0.41.0

0.40.1

0.40.0

0.39.0

0.38.0

0.37.0

0.36.0

0.35.0

0.34.0

0.33.0

0.32.0

0.31.0

0.30.0

0.29.0

0.28.1

0.28.0

0.27.1

0.27.0

0.26.0

0.25.0

0.24.1

0.24.0

This version

0.23.1

0.23.0

0.22.0

0.21.0

0.20.0

0.19.0

0.18.1

0.18.0

0.17.1

0.16.1

0.16.0

0.15.2

0.15.1

0.15.0

0.14.1

0.14.0

0.13.0

0.12.1

0.12.0

0.11.1

0.11.0

0.10.0

0.9.0

0.8.2

0.8.1

0.7.1

0.7.0

0.6.0

0.5.3

0.5.2

0.5.1

0.5.0

0.4.0

0.3.1

0.3.0

0.1.0

0.0.1

Download files

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

Source Distribution

pydantic_core-0.23.1.tar.gz (269.7 kB view details)

Uploaded Source

Built Distributions

pydantic_core-0.23.1-pp39-pypy39_pp73-win_amd64.whl (1.4 MB view details)

Uploaded PyPy Windows x86-64

pydantic_core-0.23.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded PyPy musllinux: musl 1.1+ x86-64

pydantic_core-0.23.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded PyPy musllinux: musl 1.1+ ARM64

pydantic_core-0.23.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pydantic_core-0.23.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pydantic_core-0.23.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.5+ i686

pydantic_core-0.23.1-pp39-pypy39_pp73-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded PyPy macOS 10.7+ x86-64

pydantic_core-0.23.1-pp38-pypy38_pp73-win_amd64.whl (1.4 MB view details)

Uploaded PyPy Windows x86-64

pydantic_core-0.23.1-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded PyPy musllinux: musl 1.1+ x86-64

pydantic_core-0.23.1-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded PyPy musllinux: musl 1.1+ ARM64

pydantic_core-0.23.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pydantic_core-0.23.1-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pydantic_core-0.23.1-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.5+ i686

pydantic_core-0.23.1-pp38-pypy38_pp73-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded PyPy macOS 10.7+ x86-64

pydantic_core-0.23.1-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded PyPy musllinux: musl 1.1+ x86-64

pydantic_core-0.23.1-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded PyPy musllinux: musl 1.1+ ARM64

pydantic_core-0.23.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pydantic_core-0.23.1-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pydantic_core-0.23.1-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.5+ i686

pydantic_core-0.23.1-pp37-pypy37_pp73-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded PyPy macOS 10.7+ x86-64

pydantic_core-0.23.1-cp311-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.11 Windows x86-64

pydantic_core-0.23.1-cp311-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.11 Windows x86

pydantic_core-0.23.1-cp311-cp311-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

pydantic_core-0.23.1-cp311-cp311-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ARM64

pydantic_core-0.23.1-cp311-cp311-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.24+ s390x

pydantic_core-0.23.1-cp311-cp311-manylinux_2_24_ppc64le.whl (1.4 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.24+ ppc64le

pydantic_core-0.23.1-cp311-cp311-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.23.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pydantic_core-0.23.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

pydantic_core-0.23.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.5+ i686

pydantic_core-0.23.1-cp311-cp311-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pydantic_core-0.23.1-cp311-cp311-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.11 macOS 10.7+ x86-64

pydantic_core-0.23.1-cp310-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.10 Windows x86-64

pydantic_core-0.23.1-cp310-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.10 Windows x86

pydantic_core-0.23.1-cp310-cp310-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

pydantic_core-0.23.1-cp310-cp310-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ARM64

pydantic_core-0.23.1-cp310-cp310-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.24+ s390x

pydantic_core-0.23.1-cp310-cp310-manylinux_2_24_ppc64le.whl (1.4 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.24+ ppc64le

pydantic_core-0.23.1-cp310-cp310-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.23.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pydantic_core-0.23.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

pydantic_core-0.23.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.5+ i686

pydantic_core-0.23.1-cp310-cp310-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pydantic_core-0.23.1-cp310-cp310-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.10 macOS 10.7+ x86-64

pydantic_core-0.23.1-cp39-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.9 Windows x86-64

pydantic_core-0.23.1-cp39-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.9 Windows x86

pydantic_core-0.23.1-cp39-cp39-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

pydantic_core-0.23.1-cp39-cp39-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ARM64

pydantic_core-0.23.1-cp39-cp39-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.24+ s390x

pydantic_core-0.23.1-cp39-cp39-manylinux_2_24_ppc64le.whl (1.4 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.24+ ppc64le

pydantic_core-0.23.1-cp39-cp39-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.23.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pydantic_core-0.23.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

pydantic_core-0.23.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.5+ i686

pydantic_core-0.23.1-cp39-cp39-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pydantic_core-0.23.1-cp39-cp39-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.9 macOS 10.7+ x86-64

pydantic_core-0.23.1-cp38-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.8 Windows x86-64

pydantic_core-0.23.1-cp38-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.8 Windows x86

pydantic_core-0.23.1-cp38-cp38-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

pydantic_core-0.23.1-cp38-cp38-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ARM64

pydantic_core-0.23.1-cp38-cp38-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.24+ s390x

pydantic_core-0.23.1-cp38-cp38-manylinux_2_24_ppc64le.whl (1.4 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.24+ ppc64le

pydantic_core-0.23.1-cp38-cp38-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.23.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pydantic_core-0.23.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

pydantic_core-0.23.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.5+ i686

pydantic_core-0.23.1-cp38-cp38-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pydantic_core-0.23.1-cp38-cp38-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.8 macOS 10.7+ x86-64

pydantic_core-0.23.1-cp37-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.7 Windows x86-64

pydantic_core-0.23.1-cp37-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.7 Windows x86

pydantic_core-0.23.1-cp37-cp37m-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ x86-64

pydantic_core-0.23.1-cp37-cp37m-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ ARM64

pydantic_core-0.23.1-cp37-cp37m-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.24+ s390x

pydantic_core-0.23.1-cp37-cp37m-manylinux_2_24_ppc64le.whl (1.4 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.24+ ppc64le

pydantic_core-0.23.1-cp37-cp37m-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.23.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

pydantic_core-0.23.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

pydantic_core-0.23.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.5+ i686

pydantic_core-0.23.1-cp37-cp37m-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.7m macOS 11.0+ ARM64

pydantic_core-0.23.1-cp37-cp37m-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.7m macOS 10.7+ x86-64

File details

Details for the file pydantic_core-0.23.1.tar.gz.

File metadata

  • Download URL: pydantic_core-0.23.1.tar.gz
  • Upload date:
  • Size: 269.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.10

File hashes

Hashes for pydantic_core-0.23.1.tar.gz
Algorithm Hash digest
SHA256 5aec2b7b8244b2e4eb9ab8f57436ff1ec2d3b9f443a5f99d5a67ed5e47e9a6fb
MD5 37466257fb6cbe8f355126d243284f11
BLAKE2b-256 23b579c60a57d392993d433ab6329903eb4cf3469d87b5d8c40fc52751229628

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 6603a1cc5bd4f0fd54bd496040478f5391270e7e79308d1b162f4c6644c2c56a
MD5 24647ae886a2c9b78a43521c000120da
BLAKE2b-256 6f299836befd674b4e6d0a5fdd6f4bc1d334c3db803a607c1b2b4699f91aeeef

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 a9492f8c80520835875b1d5df786915135a6492d165bd7fc6d30f1b4abc35e0e
MD5 238ecc47e99a4b06265615849160861d
BLAKE2b-256 46af2a1f837e6b54d71ad2a2fda254ab807d58dba3fe8c88d343b315260e7ba5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 a5131b838d2fe3dd6c53453cfbb809660049bc580bc9f564a8c12ae019bba0dd
MD5 a5920da611f8029ab1494b45fd73ccc8
BLAKE2b-256 9a46678ca2b28c0396c0cab03336c804551fec62425181e82c0ec54b214e13e2

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 11d375d3ca125894a346a5a3ca26daadd352b619b791eee9344f5045fa1f983f
MD5 d019be1b9f37331a7b7aaf93b525b766
BLAKE2b-256 f2d08799b210011a0cb135f27965a497d0037c2e689c9e1318f6349214c5683c

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 d4204947bdc5f71770b0a42acfb000a79e5e82ba107704a37212865d95d05ddf
MD5 f536b8aad5b1026afd6c0e51b5b34a6e
BLAKE2b-256 a5dee3a518a0cb39f59335f6cf780d5f671877d6f63ded94c0bb9fcf5b0b9bf6

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 c4c056d6d27a5e75c36af141fee80dc03b4b5212ffb14c47b2a29bf5f04c1623
MD5 6457886e196b16c854505b4b06aabe0d
BLAKE2b-256 ce4364f936eb28614a6cd8128f4a801d880cc85aa495e74042b2d522efaf1c97

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp39-pypy39_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp39-pypy39_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 31faca184fa19f94879f7fefd498aa5524c160e7739ca19e64ebd31b765b825f
MD5 4678ef21ae26f4dfbc377ec81a6550cf
BLAKE2b-256 a8cad557004cde6bb06fc66a3968f60f6a45e768ee0827b1df5406dfee3c19bb

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 1dce4b872b877324db665c09b920351390c29c40ef5f77a59b2e4ff837a31798
MD5 4e53a46b25591b38e6a397ca507d56dd
BLAKE2b-256 fa5fed8cc57f3b5844a2c2c01d2e61a1327f5cc007223e084d327a626dc53f34

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 7e58e83e1daa5b36c609467559b93d7604ee09293a9e56277bcfdb5b43a8ce50
MD5 0d94de2fbc7a1d4aac987a9dc946e643
BLAKE2b-256 5e5c3292b1c0b046d0622955059bbca0c6f6064f22c61edbd79fd69b8edde870

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 f09c00318f39c6c80a9b4057d31b83db07944be8bfac230545d368d292c2605b
MD5 a7e48d438448c51922802828051b1d75
BLAKE2b-256 305b2200d35295fe7a40e62ffab1d55dfca6b4e162e257e39d6b072c3ead6805

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7896d16f27dcb246829ef6244fbaf85fad2173e53b1b08aea616857e229c1015
MD5 399002290635bbb46fb33d52940a772a
BLAKE2b-256 c4346f12a0829d70bc050005ca14b4667ccd19aff65b1717905587d09bd2eb2a

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 245f7dbc34ba84ceabdf277c6698c716c3f02db8564bbbc6f84138452cb8412b
MD5 e7c564bb8962f4b3ca39039fb76827b5
BLAKE2b-256 7cf3793b0ed5b5614f5bedbabb609c9efc8853f2641c700f05bba704333877ba

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 9f01f7f1e9a7ecae35810f1ca6128eeb88245c26b7319a47e0fa16cf33a3bc09
MD5 7e81677e38525e173383486220717baa
BLAKE2b-256 e660ef1c0bd2c5ffbcd2125c88e9cea6edaf8ae0413b45d42f750745dfddbbc9

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp38-pypy38_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp38-pypy38_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 a1cc8ccb29b88a6b636e90559f8b6d87c638e77464ae43ee2cdaebde3e62bbd7
MD5 196ddc3f2fbf372694db4fb5c39625b4
BLAKE2b-256 b103be43d8414c3b8c59a5afab46cbff9ff2bff50d95279087fc9c82a203a4aa

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 6d366baba9d1bab8f430e45ba20e578e0dfbf4af93cbe5a9e5193c92057c652c
MD5 3d836c10b7b37dc42c02f3616a0d7c05
BLAKE2b-256 a3a87ccc776da56d529ab0a2800ded93b9f46b139f61d8a5cc1d1986661170ba

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 4405f8670377ca5496ba94c68a563cdd00356d7e612a0868f8d30b828f57b1f8
MD5 416622f5089c5ee17c02f4c4087a059b
BLAKE2b-256 76c245c85b79723c7cd04f29c76484cf38618794d5d5354275ffe4d6662f54de

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3798175638e02cee53914b8474ab0e0bd97e6d4841e110f53653446bf500ba8c
MD5 160dcb8410a60c3f1808dbed6ec114fc
BLAKE2b-256 d596be6cdea73661daa9013058f99a0bb3e44b8ed5669101ab2ee76ea0bf2941

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 660dbce02e24c82c141724e02823abf8e04e1253d09bf03ce36507eccd4ed51c
MD5 882ccad45ac7394577cfd477f6cc6a1d
BLAKE2b-256 567b8a58f7dae7ede57c7d34fd5774bccf6009e256e543552578d493e0d20ee8

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 cb1e7e6438c6148c161dfd1426311fa504e1e160c10ae070a77874fc4e5d094e
MD5 d6f22c7fa5fdc7edc9d044b82fff35b6
BLAKE2b-256 3d7d224017ea6b5f906c133ca91ca9e84f264d7f6190b28979b0e2f514a25858

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-pp37-pypy37_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-pp37-pypy37_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 8a9881636c13b9dd5e67f5955dc0ddaadd25e8f91328361bff4227f712ab72b9
MD5 d57ef7fd3c86428d4e65427c9e8f241e
BLAKE2b-256 b73ae1c6f94d343409eb83c58e30fe69681e68f7aea4a88c735dc4e47f9ea38c

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-none-win_amd64.whl
Algorithm Hash digest
SHA256 789edd3b49bf7f59181943196b644fa14c34825945a8811c78ea502203b64b8e
MD5 66d83374dd49afd4cdc545c98e26774a
BLAKE2b-256 165902129609110e7a207f2d0209ae8b2a3903857e4e696ba939561b47253c17

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-none-win32.whl
Algorithm Hash digest
SHA256 2b12cb72176d7a17a2d8039eba7cef1a7d20a359e5b970ae8b37ceedcc557f18
MD5 f7fe9d1e54cc4e7a966474a111a40668
BLAKE2b-256 e9861c2b6ffd0a2941ace30fab2e5d0aadeb8690c65e13dd36f0f88d2ccb96a5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 1bdd246f8ce3abf68ee91b75007b866968dc4cc1dc834a16d4c3ae1852207cfd
MD5 d0406730827bfc0ea2773983e237466f
BLAKE2b-256 2d01b183528153ded644a954bd09d7a01afb288bffbab63f967e9f3196e11880

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 d9e9eb4109aa8339cc3e2c04fe744c09428d819925ff4662f452d2caff9fcd8c
MD5 16b33c0c36f67ea2f3b2a1c207023a4a
BLAKE2b-256 7d7adf54e7153b58d9f3febeb59ae1bac9e9f2c51b98aa33f252859e577e559d

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 2de1a6cd19c18692dadb75d4ad7728b5c1aee7e7f7adc55073499c5863bf1b38
MD5 d8884c170635b6e7cdf585375b648d3c
BLAKE2b-256 7cfe681a510f042d98cf9a675db4051c93788696d62eb8cb446f4a71c1fc59c9

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 832e7c9fffd367429b8cb0c0b58db114535ca1becd51a2a49faf146762720652
MD5 f0d20a8c64ff979e1d7e19f0a0f143a1
BLAKE2b-256 d6744f97ccd9637f4b2af91609c6eccdb96ff0ce82f42b2fc67d6eecc597dcb9

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 0acd0ff5ced407c2afbd691008c1876114bb48d4435c1492709f9f50cd56c5d8
MD5 9290838ab13ef73fa100edac260763de
BLAKE2b-256 36458cbd9fba3d7e794956c01cf3e9f3448e54352690a5b7b7be9f2db307aa61

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 be0edd4df529bf500bddac92c128de5fd33b22ccc3a2d24da38c72f3c07fa774
MD5 8f8d8c5d26d656fa64ce3c23a3cc2b37
BLAKE2b-256 3702ab81b93d990d536378213f5e3217832d104acbb65c78c21f96e9829f0459

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c86d22371dbe0992553b5ac954a43a83f1eec6f6f496f5f491fc1bb7bb187f88
MD5 f8f8df13395e8d1500a74401a9d0df72
BLAKE2b-256 9ab5bdbe04c81c099b095ca688b515fe579cb8a2662d7ea0036b5b33cac0f27c

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 7706e76e7a49908ba3a94bcdd82797366552989827ce2464488edbc5e17910b7
MD5 5c8d5c3f44dfd61d34a6bcc6d0d98c41
BLAKE2b-256 dbe89d25dc671a67f2325a9ef9078e452913ef5fd9725d2334e9a745bba78b7e

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 0410c690341a4b708047cc72f9ebd23e4ba9d20f196f9289bbd980f1ee8f8450
MD5 f8ced20dd7e55dbd90266b5135fcfc13
BLAKE2b-256 47ce182dfc34874160d460f793b8aa2e3a1d2bb4bfb1774ecd7dfe95fb09934f

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp311-cp311-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp311-cp311-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 736d0dcbe7cd0a3d25eb44300ebde2d7c9c567bfdff0f44510f04ed8bbbb32ea
MD5 bbeaac2cfbb935693ba43838884c4ab5
BLAKE2b-256 27869bb77e7ecd7f82f066c4947a38368664f0524b55c457b9ab252b62c8ce4c

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-none-win_amd64.whl
Algorithm Hash digest
SHA256 4ffa0f72f6963ed61fcacd473d59a1e110dfc44df8796bbc1c031b98e98b7362
MD5 3b25cab94349a2e3e037cea059ad8e6e
BLAKE2b-256 c7b7920cb70aaadd08124598b445d2aa1b23c7134191b3aeafe829471e8493a1

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-none-win32.whl
Algorithm Hash digest
SHA256 6d521cddf70dc92a7d2ab44705576439aee1dc2b35055571592c78088ea51632
MD5 3691cdd7ce9b37645d3a0d560566d054
BLAKE2b-256 ac1e2b7e4fd090d052d6b567c5a5152d28308dc381873495d4612ddf30ac07a5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 c5a9add173825540e5d2f4154e324fadb2eefc4c75d494fb8f843aad20f83247
MD5 9aaea3253ec519a11d383e346ac99815
BLAKE2b-256 c2215dfba25d30977a00121faaec44f27fc044ee0790e0a4849e5554eae96fd5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 e109c909c1dec49b8ec2e6caadd3c3686d56a0c209f312c5f6c696fd25f91b70
MD5 60d8de73ace6feb17c053b84d22b40a5
BLAKE2b-256 dde1977841c1e60cf2848a6db5c4e7b0564a60ab0cd6b0be71a65272d188d940

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 fccc8e7d20041ec2793f1acf8a7ea0560c0b7cb28ea7b62137626bfe13c7b630
MD5 c4a6fb0caaa43532ec5dfc96eff8c2c0
BLAKE2b-256 b8d179c45705930d3842d62899c4a0454515ac6953e285d2ead0d8708e7ae1d5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 258915b2447d54d95f864922d3f5e978c713bb313729bb3541071475348c37f2
MD5 c2c886c0459303ad8dd62806c865715e
BLAKE2b-256 a485863c5ee2dc83c9871e53d08bd9ee3228367694face93e0c3e0bbdf11c57b

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 c81b68bb5c647a62ff6f4849ca24be0f218105fdccbed99e07f7fd3d089c9d75
MD5 453829ae285b029e7690abd3754f61fe
BLAKE2b-256 8738fadcbc24c4cd38602b2da007213bfad046e03841d7fdd78b908fc46f9fdc

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 966074e340bd896f0ea73b40b0265d50aa8c46026f800fe341a980002368cf5d
MD5 566483e49ad2207fedec1a6fe14d4644
BLAKE2b-256 8674c422e12b08727ff4b6b54e71c85cc4a3cbb1ae895beeb6d9ecfd218c2a03

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 9845d90b6f3d983534838240fed9fc98301f180540704caea2bfbcb24ef030a7
MD5 febff1c8253e476c85f9127499c32ba3
BLAKE2b-256 1e4a6a80dcdffd3a642d87ec1ae3fe35b546f54fed4ebb83a1d3c28820154758

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 244634aa97971076042004f27b41fcb3fc8ab2142f2ac4f28a95d193b1610046
MD5 036c8f40282a6fa2fdcb0ad881152868
BLAKE2b-256 d4bf0a0688b0ceb0943fde98fa6db9e043385a2b4bfbf0d48deba9cfd3278122

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f3a3631843abe9adbbe1d280757d5a5d883505a8ff5645d9a0859b166fa4de03
MD5 dfa44cebd26e0a8c4c7cb02c0bbe0943
BLAKE2b-256 566383612e8a3a4c32260e4ee067edf5c5ab4e47a12f717f39f55b9819b1116c

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp310-cp310-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp310-cp310-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 807d1f2aa738b0f629c4fb23f88ccd95f083f5776c4c2b2ae774ae90076f02b3
MD5 25801e9da9e473d14bb471592103f488
BLAKE2b-256 7625729b3fde981c5e01e7d726492f6fab9b06fb50d0153aed3c105648ec2a37

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-none-win_amd64.whl
Algorithm Hash digest
SHA256 362bcb4e8b17786ce25007c941783d0cd62d6b585116ca7e172a09a4456dc820
MD5 8a6b99673f1b9f62b64763da75ae4b02
BLAKE2b-256 cc08d052218a18010670042c641e3ab6007dc49fed9e98eb26358d2822813b7a

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-none-win32.whl
Algorithm Hash digest
SHA256 dabfa5670c5ca19459d040348162bab7c43f7b4988ccc3649597c05d3e3cb7a0
MD5 d38abbd9dbffb8bcadc5d2d283b0e780
BLAKE2b-256 f81f1d894f69759c74318a773d16d27860f958d8f821d6dab4b78a6030624dd8

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 bb0362c7cd8769c7b53ad4d71183b84ccab1996140fd1aedcc265ca6c2655236
MD5 11c65422436d686687e1ef6553b6c177
BLAKE2b-256 ef4b9e282ac84e0fe7ffc27c9eaa3f9cac032586df4b3c0fc8ceb959ddfccfe3

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 24f7035801de73d0c4f6cd2e6aed4debc72692d6a7711408382da729861341ca
MD5 022524c34836443afca9b2188ad34723
BLAKE2b-256 0fc62f9db159757678ecf27d5a0f23b1be8948451ebd9e730354de1892aefd99

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 d84068c07a16d37488fb2a7b2067bff8ccda17f382136080ebaf3b1e5f26135f
MD5 86d330512254792b76f347902e25f398
BLAKE2b-256 7991ea4b86b36d834bae3471268afbd5cc3ff0430dc916dd1a5769af9fe0cb52

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 5590b0f7846356ff9de766c6eeb4191da60519d87613739422d2ae35eafce1e6
MD5 50639d6b13cfc38c4d269c067d248418
BLAKE2b-256 81bdbe280358ac5b5ca36a798b335ca3bf7f1959653f57d1b1de3ab705ee9cdc

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 422411aa4ea7121475805ac7bf46270729d499b6a74b453e014cb7633cbc28a1
MD5 a218ccfbcc409f0c9218d6fba00f99a7
BLAKE2b-256 cd11c44c4ae322c095d39dafb018f893e4075fb2bab70b9ab996fabe20d49825

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c15027fc86db4f80e21b5d8127a6859d952fe4ef3027db6c55aba057c276d53b
MD5 06d2c29a95230cd743c3ad2bf3fae51f
BLAKE2b-256 6dde105090462ea0582650b58fd66842791aea2685689d2f85e082b28ceaf03f

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 a721cf4f6959c9083ace2c374040cc526d1d16cf5748b417f2b0a55ebc212e6d
MD5 6368eaa9c0762731f5eb46c69f17cd02
BLAKE2b-256 79ed21d84b8423205bc4ae367dd6673227480e0915113c59d3311c2b5b07429e

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 c6c64ce5bddd22e91c43dde4d41b5a89111015960b537f580b988756c84ae087
MD5 5454bf8a647782e1c7c53a4597990756
BLAKE2b-256 d2d15f68d16c1d4951ae8ddb5ab90bceb5e5b83389e7c28ee2c402696fbd58f9

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ee439eb33c3932d5ab6b999a1be379400a06c8e59420120a287d5c3b050d34de
MD5 f09b72ba08525371046d2d5aed39b474
BLAKE2b-256 98790c10e0ba06d6d94995a006517c81cc678060bb49f3ebc4d63d46d662fa2a

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp39-cp39-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp39-cp39-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 55dbd9ba78bbc6c7de33edbbef255c589ad3496cc3b0b211f1b9a2032b5b568d
MD5 7354f68f2234d5cd7e30b057fd95d7b8
BLAKE2b-256 fef64e5e5cd69ea5ef4d98bbf6ecc996905dc9b94a70d5d8241d29a2ea7ebc86

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-none-win_amd64.whl
Algorithm Hash digest
SHA256 c3ad0907132e28c7b381a237de74597018c07e5348c3508272e9b116b54e2e4e
MD5 8c40b195f4e3d8303077a7e78834d1e0
BLAKE2b-256 c7ea853482d1e5871c7173cabc25ae53bbe4bd459cec2e4a90c5331efc6d329b

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-none-win32.whl
Algorithm Hash digest
SHA256 69ae310c49eccf188b78af23021a5c31bb6cd3c31ddf089ffa52df4cf59db6b6
MD5 91663deddef3d8cc54cb766a6ec7f4c5
BLAKE2b-256 262d893bfb9631d43c81faf6fd4fb6cf6785da75b37536c9e0741359e8c14d88

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 1baafa4b688d814a091932b9d9e33fdc4a4265dde1d2b06074672da172f0d182
MD5 5974ba6a15469b6f633af99ced133d10
BLAKE2b-256 a65675db9173e390234b775bb9bb7e84122879dd34ae3189e9b11db0c4e35fd5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 f0df7f38c173126544297a5b42f4694b011db56b38b51af4d802a4a198879d8c
MD5 4c8a6da5899d5af2e73908a6fc098847
BLAKE2b-256 237068185d7de972f2ee2df6695feca9407cdb3c269bc22b8b33b331bd857352

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 4e6ffcbff6a55cf95d8fe32c3faf406fe5ce4db5fa388f54a86828311f2b8538
MD5 708b72cd3ba849ddbda18b7f92aeface
BLAKE2b-256 632996a74add67673316f2c6af8022d8b29cc48de2acfbc987a9f2786fe92f2b

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 b6642f908b97e75e8a2a50b7173fc454413d56728a8efd4e5088bb3329e787d0
MD5 4ee88fc2e099b195faaab78ef270cf2f
BLAKE2b-256 2f7008488de26f17d5a5f3e6dc6e190f22a2c7f1f65c7fa9c2d96cc5a5966b00

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 feeef0c48cd2bfbf4f13210a5730ba638db5db1eb72a8f9cd39224b3af223108
MD5 45a65b669f4349fa062ff0666985b019
BLAKE2b-256 fde3466dfc2874fa475174074a21e29f6a6975b0fda122f0c1842c24b49c2e23

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9389d3b3187a310fcc080e9709fe18855ddcbc8cb8c006be93d13fb847a7a1de
MD5 8028748b5b27873fa24e9fb99359c688
BLAKE2b-256 62f1812fa8ec5f585a2c40f4b27fb1a65099025238fff21aeae1d76d93b3ac75

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 42d653cd124193054cd7f9c85f0879fb08ab9479d9221fa405c18337f107627b
MD5 1868ae6a965aaef22410b4e65b7b94cb
BLAKE2b-256 ca9a31908b3fb165cdd8f9ad099c4965b14fb312d8e734b2c1dc0375d4b18b6a

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 2152a95ddb160a4e92ecf9532ceaa65b31c220c244a39c2d1cd970fdf6efbb11
MD5 de42572895d4a27fd126814b660df108
BLAKE2b-256 a896f725e80e2fe7c13e785ab26dfe567c3b1522130de74e4dd5afe184abfb0b

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d3116d663b4157844ca2e8b10fd41c1acd38f6c0d23c26ed6ece35ccdafc5aba
MD5 4df6db5d917aa966624732832cc7e893
BLAKE2b-256 11b388cab4eeadc3de6b1977f0e1af8d8c9bc69314df4a55d55ef150c1dd9bb0

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp38-cp38-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp38-cp38-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 55a004b51892f00e4c3f25ceae4235061caf7c4c495d8acc15a841bea115d009
MD5 c58d048ab1d2d7227c9df3d4315700ed
BLAKE2b-256 1e2a0e64fde09ebf80690153a6c55a106d35626f9ed31096c330fe5a1ae8d3fe

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-none-win_amd64.whl
Algorithm Hash digest
SHA256 2d857264277b71324dace10201a292b9da2ba57d2f85e5dc4676cb6eada7c09d
MD5 3d1db55ebb3bd31c5c67b6d462d78656
BLAKE2b-256 a4d19ce7afbd02b31ce754afd551186aed2cf297d305f7bbe7af7206cd1085bc

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-none-win32.whl
Algorithm Hash digest
SHA256 8ef075cf0000a3e65f3aa8bab29101a04eb21066f692495c9d51b0d496f92f5e
MD5 03c268552be1dec90ca714bad2c947a1
BLAKE2b-256 5918fdc429818ca4d88718b9f9291a483bfa93357455081bfba75ac72b64844f

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 fcd0b4fa69c72b027c916f228134181bcd15873dd7381956751c235058fbd3ff
MD5 3d6e1c8765724164c348ba236b3df432
BLAKE2b-256 4759aaddef777f04fd37e31f16b2777e6bb029bf0b9460d575b24c5bf72e7eb5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 c9c4a350286ed711c9dcb926d2a8aa08eb1f35da1770d0e608ff88f8379d2739
MD5 17038aa474fc3acc2f78ddafe1dbec7d
BLAKE2b-256 df191545f6c16fbb02ecc4a9505c34b0a672d4fb8e1fd40ac763606bc3755849

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 8344586c05119eaa1d22aa995dc5749f31625c798fea8504dcc3bca0ee939982
MD5 5e24fec1df984f31635f8c4a24a16fb7
BLAKE2b-256 3981125e1c5894f4d55d296faae5dfbfbb392e28bc77335c9a37159d78cac34c

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 f2a9fcd4aabc0837f3cc3edb5d410c022a66a6c1b94ca8382f1da46e8e41c091
MD5 b904e755e4c1735c9e54ec857cc36baa
BLAKE2b-256 e11e6e8fc5fed287841816c6769f92b66284854328eff0d78590f62723951611

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 8da93ebef2aca62493fe011f513b10d633d4a111140978115a82c4e3947ff0f4
MD5 4cc90f2055a9c0e11494c6f4ea31e698
BLAKE2b-256 b8b693b7a78b39fd6c6e5e36d9aaf5b02d56d8fd0094875751928df6be6bc2f1

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 38496f67b6e3be93de28fa326cb77804cc171894513a90a499b4d431aaa1e9bb
MD5 ada2c5db475915f62e329408bff06b5d
BLAKE2b-256 7fdda798cd4aab1bef6ff6013c2566c0ac827a4fcfa71f7ecc74d9cf716d9a8f

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 f079b842f017192500c90b33c70f1085e007ef03c5066d9339f2daf1d90a83b5
MD5 79762080660608121dc4ce193711e1e4
BLAKE2b-256 a531d2e4f35fa1c26deeecbcda698ed5c43c6b5ad4103af563a726fbda33df12

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 375bc3bc61847179989aa03d2dd2bfc158033cb988ed9740258663bb1434e5cb
MD5 b4d3bf137093574ad07800d9ee9ac167
BLAKE2b-256 41e6ab8c2bc7c7fbec4140e0913b0002350a431c4bda2d81cc9148e994b4bb85

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1bde5e4266f7e492d19e94824b9ecce75a5bbb4be19f773772f792204f72e65c
MD5 29b498b5d796656987ffb2c0cc01a1f2
BLAKE2b-256 6db9b73406fa023ce475140c5db0550b3b477bd992418247831cff306af8d27d

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.23.1-cp37-cp37m-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.23.1-cp37-cp37m-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 aab63d0a925f3f16e60c0980a805887770e663bc0a504ae8e4d0624a559bae8e
MD5 c454c466545dec2cac4a4a5118025697
BLAKE2b-256 12b959b3fb70c9d8a9220eee7cfa9dcc0c09ed8d2611051785aabf5ba1ad586b

See more details on using hashes here.

Provenance

Supported by

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