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

This version

0.26.0

0.25.0

0.24.1

0.24.0

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-0.26.0.tar.gz (278.2 kB view details)

Uploaded Source

Built Distributions

pydantic_core-0.26.0-pp39-pypy39_pp73-win_amd64.whl (1.4 MB view details)

Uploaded PyPy Windows x86-64

pydantic_core-0.26.0-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded PyPy musllinux: musl 1.1+ x86-64

pydantic_core-0.26.0-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded PyPy musllinux: musl 1.1+ ARM64

pydantic_core-0.26.0-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-0.26.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pydantic_core-0.26.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.5+ i686

pydantic_core-0.26.0-pp39-pypy39_pp73-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded PyPy macOS 10.7+ x86-64

pydantic_core-0.26.0-pp38-pypy38_pp73-win_amd64.whl (1.4 MB view details)

Uploaded PyPy Windows x86-64

pydantic_core-0.26.0-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded PyPy musllinux: musl 1.1+ x86-64

pydantic_core-0.26.0-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded PyPy musllinux: musl 1.1+ ARM64

pydantic_core-0.26.0-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-0.26.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pydantic_core-0.26.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.5+ i686

pydantic_core-0.26.0-pp38-pypy38_pp73-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded PyPy macOS 10.7+ x86-64

pydantic_core-0.26.0-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl (1.6 MB view details)

Uploaded PyPy musllinux: musl 1.1+ x86-64

pydantic_core-0.26.0-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded PyPy musllinux: musl 1.1+ ARM64

pydantic_core-0.26.0-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-0.26.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pydantic_core-0.26.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.5+ i686

pydantic_core-0.26.0-pp37-pypy37_pp73-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded PyPy macOS 10.7+ x86-64

pydantic_core-0.26.0-cp311-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.11 Windows x86-64

pydantic_core-0.26.0-cp311-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.11 Windows x86

pydantic_core-0.26.0-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-0.26.0-cp311-cp311-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ARM64

pydantic_core-0.26.0-cp311-cp311-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.24+ s390x

pydantic_core-0.26.0-cp311-cp311-manylinux_2_24_ppc64le.whl (1.4 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.24+ ppc64le

pydantic_core-0.26.0-cp311-cp311-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.26.0-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-0.26.0-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-0.26.0-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-0.26.0-cp311-cp311-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pydantic_core-0.26.0-cp311-cp311-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.11 macOS 10.7+ x86-64

pydantic_core-0.26.0-cp310-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.10 Windows x86-64

pydantic_core-0.26.0-cp310-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.10 Windows x86

pydantic_core-0.26.0-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-0.26.0-cp310-cp310-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ARM64

pydantic_core-0.26.0-cp310-cp310-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.24+ s390x

pydantic_core-0.26.0-cp310-cp310-manylinux_2_24_ppc64le.whl (1.4 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.24+ ppc64le

pydantic_core-0.26.0-cp310-cp310-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.26.0-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-0.26.0-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-0.26.0-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-0.26.0-cp310-cp310-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pydantic_core-0.26.0-cp310-cp310-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.10 macOS 10.7+ x86-64

pydantic_core-0.26.0-cp39-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.9 Windows x86-64

pydantic_core-0.26.0-cp39-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.9 Windows x86

pydantic_core-0.26.0-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-0.26.0-cp39-cp39-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ARM64

pydantic_core-0.26.0-cp39-cp39-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.24+ s390x

pydantic_core-0.26.0-cp39-cp39-manylinux_2_24_ppc64le.whl (1.4 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.24+ ppc64le

pydantic_core-0.26.0-cp39-cp39-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.26.0-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-0.26.0-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-0.26.0-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-0.26.0-cp39-cp39-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pydantic_core-0.26.0-cp39-cp39-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.9 macOS 10.7+ x86-64

pydantic_core-0.26.0-cp38-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.8 Windows x86-64

pydantic_core-0.26.0-cp38-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.8 Windows x86

pydantic_core-0.26.0-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-0.26.0-cp38-cp38-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ARM64

pydantic_core-0.26.0-cp38-cp38-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.24+ s390x

pydantic_core-0.26.0-cp38-cp38-manylinux_2_24_ppc64le.whl (1.5 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.24+ ppc64le

pydantic_core-0.26.0-cp38-cp38-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.26.0-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-0.26.0-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-0.26.0-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-0.26.0-cp38-cp38-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pydantic_core-0.26.0-cp38-cp38-macosx_10_7_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.8 macOS 10.7+ x86-64

pydantic_core-0.26.0-cp37-none-win_amd64.whl (1.4 MB view details)

Uploaded CPython 3.7 Windows x86-64

pydantic_core-0.26.0-cp37-none-win32.whl (1.3 MB view details)

Uploaded CPython 3.7 Windows x86

pydantic_core-0.26.0-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-0.26.0-cp37-cp37m-musllinux_1_1_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ ARM64

pydantic_core-0.26.0-cp37-cp37m-manylinux_2_24_s390x.whl (2.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.24+ s390x

pydantic_core-0.26.0-cp37-cp37m-manylinux_2_24_ppc64le.whl (1.5 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.24+ ppc64le

pydantic_core-0.26.0-cp37-cp37m-manylinux_2_24_armv7l.whl (1.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.24+ ARMv7l

pydantic_core-0.26.0-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-0.26.0-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-0.26.0-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-0.26.0-cp37-cp37m-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.7m macOS 11.0+ ARM64

pydantic_core-0.26.0-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-0.26.0.tar.gz.

File metadata

  • Download URL: pydantic_core-0.26.0.tar.gz
  • Upload date:
  • Size: 278.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.11

File hashes

Hashes for pydantic_core-0.26.0.tar.gz
Algorithm Hash digest
SHA256 0e07597a69bd8ee95f0e124f513ef1571a021b6ef1f7e0fbdcf36ed3fdf85c10
MD5 1ef6b7bd06f9ff5125fef0c28d3d230d
BLAKE2b-256 61b4009e6dc9757a9eaf75448ce70b98b46d87249fb2f2d5a31939af09baa7d7

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 1a61085efbaad78e6a1767f6b31ffc1755d0fb063ad027c4864cd7d15ba695fa
MD5 c4c46781460d730df13ec8d1440b9b11
BLAKE2b-256 0cb5a2e1a5760ef10424120c3a3e9690505eedc1063faaa574a96bc2f561e168

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 629c56abd7985eaad2cdfb6d007575321b1d9ddd507bc837628efffc6ced5d21
MD5 7e6f2eaee231c10c20c9496b0ad5b237
BLAKE2b-256 de519117c3ecf8fe6d574cbeea0ce1fed44c88d4b66052445c2fc3a566ee3760

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 9fe8a2c01e68a528b810dad649a82ae0f262918ad1b31517d4cdc477aa5b2e39
MD5 bc18ec3d6a6d41ca03b692066988a662
BLAKE2b-256 7d41fd1e29d10a556dea653cc56e10b5a0564a3cd9a471184ea00d22f3e6f06e

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7520e8309e0abc0c983fb4dacfa60f506609d9af28c6491cfc1cd3273f345b0e
MD5 ac85b2728f43d2939240af020222ef36
BLAKE2b-256 f03d39035c8f46ecd54ce3e8c32d5246900b0428afe425e2b742b7abd35a59b2

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 61c7a4391e9c67439ad42a44d6e8774c39e430f31c8c585d52abff16f80a1b11
MD5 79470a55317e9e1f0c0743c5bd381db3
BLAKE2b-256 a12fa7eb7c53f0cd82628040cbb52cea286760603b564322b5997cfa77747046

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 1dd472ef0b8c4bd2b14949c320b01c2fc7490ee5772fb999a00cabe421429f1c
MD5 15098051d41cbb85f04d52dbe7fb430e
BLAKE2b-256 fbcd23ffd3664beb157990bc2400c5fee3704b8cb319b1ad801a6401645e2ca4

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp39-pypy39_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp39-pypy39_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 0c736df46f1fbe50709505d6bdaf6b6f6cc34de1295dce7bdaf0293b8da28206
MD5 94ae200e5c3f567b2c073c7d5a2b9b89
BLAKE2b-256 ae8a524aaa84fb4b89df9909b429f30f9cfff8ff6040ef8c6cb40a8c9760e1c6

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 5a98f9a72fb084d211ee13a8077d43def5c7f53e40641bc1d2ee91ff8385a2ed
MD5 f6e3b6ff17efed01a870b42823228781
BLAKE2b-256 1e1d3aee620d07eb57ec499a4cdf4caa7a33405ef7a5e7b1b105fdb25186e9b8

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 10f470ffe676e547d07184bf3dd2286f1d9cd3626e4c20bd89432179c1da629b
MD5 fcc99ec28baa78d9d1fcdf69cb300949
BLAKE2b-256 51824f0ace4288a61b718c2f77dc6e997aa48fd5bec0fac91a8eed4094005944

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 914b385c8cb942a47979428906fedb31e07adad871ce78d1335c1e0aafdc4799
MD5 8a1b1c10ff378febaa3edd8f283d1c0a
BLAKE2b-256 5685df97337a367967c7acadb811ec8e65812f737ef0890bf7e39a80e8e9885e

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a4fe67d0b2346b3dd19440880d4d3f9afdc2bab81b8483558f4772e307ab3111
MD5 2b382c7e84b384be7b81ebe5abbd7506
BLAKE2b-256 d001019ccea87552722825f7b547bd125c8b5b2e53ae34f65fc2688802be4233

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 35cccc8160e591db669d908e619e6be92695be58736e5f0a926596c834f48931
MD5 87b2d90915b9c336fa903022da25b886
BLAKE2b-256 f8acbca4580e48cb72abdf1616d001822f80682d333853564327cc76f3396a1e

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 a7f30bf25490858f1a1406f5161b3702b74fd76b5671044fa2ee3e91f39120b5
MD5 6a58fb4064b1a48ab50b43d10c8359e1
BLAKE2b-256 e3c97c572fb90dbb6b9e0fe1c581ea2a6962f5c922b6b79901b7b64accc70126

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp38-pypy38_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp38-pypy38_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 709f2cb38b824a7c8e0d8bda6b8fe1537bb03b3c5f5aa170964bb56c2b8cdefe
MD5 d5192cdea0a85c069346fd5ea8512cca
BLAKE2b-256 823fe4fbf1a178a14585fafec7fc3fede21803954323afc8e9f67bb3c90a9d66

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 6200df9c30ac124ea657916e203feaf73760986e52b0f04d24e95f6dc5e05896
MD5 9b37d494137f41b121cf4258ff4afb84
BLAKE2b-256 b8deaae9d71cff0e46238b33b4831b12a352d541a7333864cad0f22aa6a1b404

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 0ac2c1a1f3c03ee1e484097a340ad06b7c0acbd5b672db53a1eb3bdaeb3e5025
MD5 569154c104ca97a00943fff26467760a
BLAKE2b-256 7558e3d6d53def5fac49ec4e2e868aef80510476114b306322f3050b966ab6ba

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0800d03825f9050f04d0219c042ba61ab7d8c32c0d6cb1366d14d8367839ec52
MD5 cea49081b2d7eabe696c4935c4e0e150
BLAKE2b-256 4aef2dcfcaf10d285abb5180f468d6a30864be8ddb72ada7d021f87aefff7916

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 8e22f2269c68ba6db738c30de3dbd2280eaadf9243ad29b67cc3cd88e873e4a5
MD5 790023889305aced3ab7b3714f509813
BLAKE2b-256 7642d643d0346f5d34e65b57be3593fc24b7db9953dcb606ae787912253be3e5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 6db4b5a4871e6c86edba63da362e19919a126b3a79e7698ac911abbaa5e522d0
MD5 ffe93378fe3916c0c53abf332b136869
BLAKE2b-256 547559f55a3c7684e61504bbc6fe75a789387b5876b337258f673bdf15b03659

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-pp37-pypy37_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-pp37-pypy37_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 c22afa5438a41092da60ec8a37091acbb796cba96c91795fd0e530c2e7262c6b
MD5 c82558107630be3978c08b0836b5452f
BLAKE2b-256 5a6914a32d4ebf3586d1ef6733af21cdd102823b3c960560ad23bad99e28fb07

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-none-win_amd64.whl
Algorithm Hash digest
SHA256 c2c72d1c655605e1ecd4fa217011635ce7fdfdb093cf2400e440ff6d31190290
MD5 65694b2ca0df4ee2385ed5d5cc09ef1a
BLAKE2b-256 4b663eae12c04b6e883d26b805a462c8266cf2293e1cfc87826dfdadf0a4ed96

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-none-win32.whl
Algorithm Hash digest
SHA256 4e5182e0bcf3fa5199baaf1731b4e7338082d1020ae4a2e96e815b2ce86aeb9a
MD5 ba1e48596d1f971ffd658a5cb1afa93c
BLAKE2b-256 eec1f27b6376953d5a7531eb9767880987282c5164de04604c5ef7d41cf9d0fd

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 0205f39726bf03e4b690c23542f197c9b1fbda1296ea716c46d02e4cc3ecbdc7
MD5 a1547f763c69070058b597403159ee6e
BLAKE2b-256 23252e2243a9cbb52124cca156df7d128230f3bca4e5c72261689f573409299c

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 49eca1466c3ba7441dfa07583431506a18ff0d804c38410ba19af668dde791b2
MD5 09afe6e4de633e327e2ce821d947a5d1
BLAKE2b-256 623746878fc663d21e1385be1710e08d2e2406c60ac8d17ea2b5fc92e033fca2

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 ff5976357ef8280ac08fd09adbc20bae9e6c5f96bce54b62d43e5091e82809bb
MD5 7e03c993d3bade48a2b2d5f48f78543b
BLAKE2b-256 68ab2829535911b867d9bd248fd35ce3bc4eb79d851fa57558d29be93f0222e7

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 43a5242c4c7ba807c9ad6a706f225e4792c7968bcb57a21612fb42e383138363
MD5 d84f20ed92cce40f5eb99b878eb6dd21
BLAKE2b-256 1de628c2ea7b485c0b052e2083165c4fa77430da57fb5efa11e23524a2906af8

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 b5e4dc138be26b542fc399a8b37967dcc4531fa1b6393695fd2ef96fac0ab341
MD5 8859a6c087ab66e5c5189859572c014e
BLAKE2b-256 3acd5f86f28bc451f782d694b94ff8011675a575e8e79f0ceb1fdaac69ba0002

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7699de8c20acec25c83927afb2ca58101d5c2d3d2f89f07acd73985d16a9c8aa
MD5 adbc94975d337147889fa110ecbadf59
BLAKE2b-256 5a4afbe816f22572a0861af809826173d250251225d613e84d0c328a342692f6

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 ef43158076d21cd0f261da8e177ea6606353765785682b0152c21e40df8f1dce
MD5 ce73d9cd675376be33550013b24e7cc3
BLAKE2b-256 6da88ec522160113479901c0c7631b23581e7c404dc19ab6fd80e317e9269554

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 b93f62b366f7bb8763c3d1857f911a76ada706d20422a35b6ea3505874ad05be
MD5 56b5492b29f7c5314993b30c335e01cb
BLAKE2b-256 a09f6e84458b76caa1e2ebd30dbab9e4e08554571ba44bf03219766450147a56

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 73b0515fdc124859ef449f9e278f9d9ab13266e6da35357b99bd955a76c4b3b7
MD5 dc6a44e4302ce5f02a109cfb0104707c
BLAKE2b-256 889da38d0572cb277bed1fe854e538955954a8eeedd73cc2e6aba01d595b27fb

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp311-cp311-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp311-cp311-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 45deb2633c1960bda49457154d428a7d5d163b79ea8bd99e2d5f1ea77ef460da
MD5 16b4ab4d07a4c81ff3cc68cc84cc5ddb
BLAKE2b-256 4d8383b9e846de8a99fd600c4a839d01d74ecd6762442373b94965ab6e7748e9

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-none-win_amd64.whl
Algorithm Hash digest
SHA256 b0e19497124535420f4ae7edffce6e63db68ffebd10ff3f7e21e36a61b1b09e9
MD5 f4c82c741945cdbdc5e20558997859fc
BLAKE2b-256 9c68eafd8458badde9c9661238d926baddc789cdcc7536ad28223859c100b833

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-none-win32.whl
Algorithm Hash digest
SHA256 131362299b308df9adec8be1894b99b103904c12e5126c851e33f74e184d00bb
MD5 f5eb4d5b8c80c483aab42bb4272abb0f
BLAKE2b-256 cc4049eeb7a9511ea9498f2b16a6d19b8406a9393d9f70fe433c590afb2bd3d7

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 d76bcdfc2faa57eb443a0060fe9fc663575de2df4d1f6e5d0c3c1d97e0a16221
MD5 fa900e8f5b05903c190f8a3c9cb99cf8
BLAKE2b-256 c44f8c6f745c0873e11bd932d9d5b8a3eb194a22c6a21616c2eada28dce9e155

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 9c57dc91947cd605d7a7ecf8fb40a89a7da4f185da797f6f3995c80bf0f7d62b
MD5 1f899eb1b21551689df5451087875ffe
BLAKE2b-256 099d2eaf32f23b33998ad3e6c6cd74b8d7890514c37ffc0b9f100e776e9e4b95

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 2b7c087cca5c8a97fbca99d9b39b94d67a7c0e3a0188aace624ff28659bec7bf
MD5 85f3a620a91c8220754d1c27a5e83707
BLAKE2b-256 50391ade6d76ad7d27d009a1587a23bc670040e5c4bc8726631cbfb6f0646fb8

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 a4ee13fac4f1d94af2d20b345a98e6dab4391d75ba3c5b93b2bb696e24304244
MD5 5df9f7c6ca95437001ecf184d32bc283
BLAKE2b-256 3a0f46d63e0df984e1401ff35046108a70804806c8eff6ae88d8200c6b56c789

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 b6036ef01920f4bce223211d2d41afec8129cd875e5684b53526214cda054d0b
MD5 5e85bc900664a0b70413efaffd3b9e06
BLAKE2b-256 ac6bcf8f9291e4d9c92e4de56fc0129888a0e0ef8fe59c7f1ec9b0fc83c09871

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6a3087a127348c80a3415234106110be7bfca994b7e5eaab5d38076bc8b6c6d4
MD5 c4de4956262411b0c6ad71f7b5aca3f6
BLAKE2b-256 961297ef8a93521b023159872713a350f99028833cbb5aae33b1a6b1b5e366f2

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 cd7879b8121ccd178c62628bbdbb003d68aa26243ffbc9fef124cca974aeb2ee
MD5 a248ba3021ebb7f4dc28ad12b49f1e2a
BLAKE2b-256 7308acd00a8b7022c38d685e5ea0bdea38576dcb91d1d0bccd8c2ca54c81fcd2

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 d40c454058c5fef7c391765dc0e63c77f4d56af6a5b8bb8bd87852a561ed9bfb
MD5 a8399557b46158df295b93a62c8d0791
BLAKE2b-256 970dcd3b20f4dafe49b84833d8171fdaeb7c35d5ddb81fc11637e7fd62f80da5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6591cb52424321765cd1cb1ef5561c586a614afd850beb550e55271bbb930496
MD5 680f469d745bec310e10a22558b53d3c
BLAKE2b-256 018d98b9b2d0845e1e6b50914005729ce302353277ab64b7d2a7f2ebacf19f9e

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp310-cp310-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp310-cp310-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 86192ab688292ec67a69b0f5e3ff9698780ce017854b59d056bcfca235101178
MD5 577723e0d48b1a3baf74f490f94ea897
BLAKE2b-256 e6e1003bc7e481c282980505bc0ef3cc837f402ee3aebdd143d2295baf487832

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-none-win_amd64.whl
Algorithm Hash digest
SHA256 5a5297b4b345b7ed4895b66c104d82de15edf2496b684cc080f4893c6cd954dd
MD5 f4fe9ac09cc6dbdf32db9f1f9a813009
BLAKE2b-256 6a2af1c7ee7f76acd4db0a9db4fc3444a6a9ba33f5fb12caebf1564e7235f0ab

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-none-win32.whl
Algorithm Hash digest
SHA256 6ced89348d9cf11760b1c2d27204103fb6f8edaadc2a68993b4264d967f5c2fd
MD5 afb8dc909c8ea17cd611875093e2a2ee
BLAKE2b-256 790880c6a459e21ef5aa11ed92bfb16e8b6aadef1ca7e87bea1ac67d73961ff2

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 db0449282b85fcfa1291b1233c9ba08f99442129d8a59fbbd54ba6930cc7a648
MD5 1edd4d26a739c48cafff63ce00d7dceb
BLAKE2b-256 4a6c2d72250921c6c2e5e0de94050fed9d7e1169c53579bd921bbf82b214fe8e

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 1dbdc98579df8e08d1603e5834266d49518440200eb4c13efc03ddaa14537e98
MD5 96473f9c89ae534d826f3c6da5c78b44
BLAKE2b-256 8678e84146b0aeeb7efce92cb828bde25035a254d01773e9e01d619c50e763e9

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 1fd9e74cb85cb7289e243807b6f4d50d854dfd0f8b77c2b773d9189c25a1da24
MD5 2bb4bd2f0e93fe94918220abaf79b9d5
BLAKE2b-256 0c7155f21596ead82145797ed08918826f3a73faed06a968bb96cfb1aab17239

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 25aeb3ac4c28dc0ad1f39090735d8ffb1d4e31e99e55b68124c8309a2a3041f7
MD5 ee7278842c83ef89f2d265c499f55821
BLAKE2b-256 c700e926ff0d255790befbf6b2757bd59732280cd788bdf00172634aef035ba5

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 72f68400a3768e745340b639f714d62655cc238c4f44f700ed292fd705648d1f
MD5 6e166f2436ada7b4c05533af6f65fa77
BLAKE2b-256 6e149b3b404d8938b66dea41000dfb9963dc0941cbd5053790b8abd8c05b21ed

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6b8fdbcb23b2d6e95befbebf99bf2ea82b20f601db5c9c25ccdce1d9eb8857f0
MD5 e552d7c83dce55cedeb15b6090afb1a4
BLAKE2b-256 50939a364b0a9caf0aedde294af749136019c034ee4dcf71d27d138699747390

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 825c3928bf08b8517644cfcb7e4aa09a4f88fa2167153d841c8dcd85ca8a456b
MD5 65aca2195d7c9525b2add58f10e05f23
BLAKE2b-256 56cf8b8b5e93e2f06fcfce869ef15bd48068907806ed2fc47c360f35b659c063

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 8fcc59b76a04e374622676a16cf32418fc09703eb79714d82b5d48679332f2fd
MD5 6459f6a6a0bd76e8e27f72eedeb0ee8b
BLAKE2b-256 f22079ff2386c1544eb5fecb58e397bf997248d539214a4fbbb86bb8cf389575

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ca3bdb60ba9dc37d71d981e872fdd74819ab0ae2242156083d5115b1410bd480
MD5 796c6f5c96ab83ba7f1a8ec9db378c69
BLAKE2b-256 6c516a9f7a8efe35ed1e7e1ae903ffb6e6a7be75795085e7c6f4c3e5953f6c55

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp39-cp39-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp39-cp39-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 7b4e65d70919d11d7400cbe1ca4bdb95ffa3396276dbfbd76fc1f31edd526a26
MD5 98fc6cf95b22f399e87ceb6c7d708ac8
BLAKE2b-256 acf1248657ce65fef70123eff824ff59b623658752a7d1833e5f49be7532d038

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-none-win_amd64.whl
Algorithm Hash digest
SHA256 70dfbdc3770897682cd856fbe0d995301aea70597467e17ae85bc71999aed77b
MD5 759dd2898e316e3d78f5d7be41e9cc02
BLAKE2b-256 97453ab864e76bc43d73a7ff67be21549c5acfb6b00c7e5782b455a76679ad5c

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-none-win32.whl
Algorithm Hash digest
SHA256 fa3fd1cdc744c2e3fba6c9006b3bfcf47026b2e3deec05b655cc0e8d4bd4c8d3
MD5 7894552edafa1ef850545b331618b344
BLAKE2b-256 7940e3d2a7b8d318bede8bc1d640db2622fd9190e6ad957da7815706cfd6ae3a

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 9173cedd82c1879bfeb4162ac001fbe0d50b7e6754af6b4d6278d882ef5901d9
MD5 1f34fa1e18b0d6199499c471699c9896
BLAKE2b-256 daa39178a642d8bc024ba72f16ba956ff403395a2eb895078f6a6f598d4fa555

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 bcd4c0bb634d171d21686185a290057661edadc0b9a42ba1de8e4af83cb050d8
MD5 4dadb6285546414673b3fc8b60857dce
BLAKE2b-256 007c0b51f990d1e6c4d7ba63dc03f2ba871bf830fd7e073e8475ab88ffe47a9c

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 36bfa0bcd1fc2906180da100b9c3c811f1a4bce633242a1163eab1b0c6c96f9f
MD5 9b3cdb0a143e0f250ea831c9bbbfd12f
BLAKE2b-256 77b0b725611fee9c07e5347cff896128cdf2393502cd987f5d7900fb29e4e7d8

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 b9193ba929ec3e82f9f9f9990a0403fe41777b22d0efb7b19df52229e2fc2985
MD5 6aa95be1e67a7b33793c6d8df85acd6e
BLAKE2b-256 0fa9a30cf3d80beef1554773e2b0cdf2521298f4044f5c9c933807f1dbc90b43

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 53bc99e85a2e4085171e4f68c237b12e1284ecd3588accc4239747cb703496fd
MD5 17560712c989cd8a8a09ba04dd87010c
BLAKE2b-256 8ddd6ad7394457fe705c9848efb7ee03af1117aaeec05da61cd52b005771c53b

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ce93454008ac22eb7b06372ddfd96e7ab7dcbd8067844ce5787aa4001116f399
MD5 8b4ca9d7fb405d55992c3e66629fffce
BLAKE2b-256 0d2d05b4ee147dccdc0c9c26bfdbc309366e2f145d10c18491a80746da8ec119

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7b6057cf9a52b24111b0c41ac7cc02622872d1ecd2ce61493b9396db67346df9
MD5 d521862d0143afba7fa456dcff517631
BLAKE2b-256 9aa2f74148b4212449d0621d4f4b702ed2c9fc0c45264de570c12c1120363944

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 4a847d2754b30f163468e0a4bb9630e72ca27d88380d5767c199f92f6224ca0a
MD5 ecdefb455e3c7635daca81293702b016
BLAKE2b-256 bc50d76a54f4e72072520e2503d62f35de868480d0fe084c6b1631ab08ca487a

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 62931fbfd0b685980b51d905ef98a7ec025f126f9079a70c2401534842a40641
MD5 3a5bf51182f29d6dd8b561c089325205
BLAKE2b-256 3d0b5e7b103efac0a860b62b928465337768d17b69085adb38892c55dabba5dd

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp38-cp38-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp38-cp38-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 bf6d335107e8e26ab9e2685735b9ea7ba28a66d84e79f89bc0f346850e7f1870
MD5 351aed5db813d2a1976393ba0b137708
BLAKE2b-256 15be08952478a0a356a00a03e64c82690cfac66974a8e605ccfda4cf94f633a9

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-none-win_amd64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-none-win_amd64.whl
Algorithm Hash digest
SHA256 c9625b9f7110208ceecd7fc2ad3b64b4b60889b0a7f7dcf5f2f67262f53a14f6
MD5 dafefaca40651fe0c91e15818f0a237d
BLAKE2b-256 7290f56b9c29ff86853b06ef1d273ae85d55f042a8362d9ef35f2edb807894a3

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-none-win32.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-none-win32.whl
Algorithm Hash digest
SHA256 fb4d0e13c06e3fba531c61fa67dea02d8652bb1a8f9386bf939157f20a442e33
MD5 baf096ab9ef5a8d8b51dc0a1bd7b8108
BLAKE2b-256 5c85b4356084d2e23a2942e290acbe7ecadf938ce9401a738248d5ac9893f625

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 5b5b876d54f8540e9b56c72cb3ae9e558c93c3f8f5be0e62dfde5395055bedd8
MD5 93d4b5ca64c4c99cac0428cbe46db457
BLAKE2b-256 9b191dfb1572deb58661f97def1d3ef505afd4a1a0e1e1b4db8929df782c6093

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 41e374f933a33dc95930a1282250bb902149628e979796150ca2cd07f5403778
MD5 89e9bfabf41bf759a3b6a9e6f165e098
BLAKE2b-256 df55abc192e86064a4472f5829cfda79be7f07bab50e8f9264955dc7a4b9c0fa

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-manylinux_2_24_s390x.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-manylinux_2_24_s390x.whl
Algorithm Hash digest
SHA256 c1a0bf676e91502996ad051dc60c310ffd09b4b606982da4f2295a264f4ed19c
MD5 0bb3c82b6a5dffa3f770700b13b1a08c
BLAKE2b-256 1605c717497bbeebad7f3e4fe5e9e34956222653356c46e34bb81954549f6c82

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-manylinux_2_24_ppc64le.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-manylinux_2_24_ppc64le.whl
Algorithm Hash digest
SHA256 64a959fb25002d98cddeecc1e8fb0696b39eb07567af7e9499a05868236e30d3
MD5 4ebb3b589a1315598f58a6b3c62eee47
BLAKE2b-256 df0f74fc0c0514db69c8536fe0bc8977e96535f27fad9e5ba99c501266be2501

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-manylinux_2_24_armv7l.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-manylinux_2_24_armv7l.whl
Algorithm Hash digest
SHA256 8dfc5225ed096c846a3483f1f80cadbc70a1e935665e35ea54d29c5923ef9ad3
MD5 6ad1344a8c4fb94e9bea371c7ba3a196
BLAKE2b-256 9fddd208e7e65fc6dfec10f47488461520dc1e2f2281503083e1861b0c6df257

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0cf257ae8111dd6da8ba3414dcecd65aa149f7e9066295583f3381bd0ba7acfc
MD5 25ec3c829f5c686d430b82a82a0c335c
BLAKE2b-256 d1a27d45949892aef5d5b757123691ca66d1b3363d6e16c576dfc9e01d5e154a

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 0ea54a613d60fe675b9ac9fc8185856106adf8f51026cec7b6393339f8168afb
MD5 aa6f46e6804c66670d8a2ce7bd49fb93
BLAKE2b-256 83740ee7b8aa3d3e23e17105de21a2748bfe9aedad9a80d0a800a75ebca76a00

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 3ad55c77738c56c8154208c6118090204893180d4f99a55c416014ef41c5731e
MD5 aa96f91fb4a62c06ced28508635e8c94
BLAKE2b-256 d50e141bcdb47711f5fa844327835fa17720ef8e097b2804cf2a1ae52effb3af

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4027fb2cfdfc282744b5667acb5368e992b2b7ffac4c052687a807febb343d12
MD5 7f4110ccf699131090b36322683e45b2
BLAKE2b-256 14046590be84da824915897a2c6f55e07cebf7791622b94380c46d63562f1bea

See more details on using hashes here.

Provenance

File details

Details for the file pydantic_core-0.26.0-cp37-cp37m-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pydantic_core-0.26.0-cp37-cp37m-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 47a4aef7f2087b7b11390ec173d59aebb3ceeabdfa9a4e853610cd885f253301
MD5 956b2563fa3adbcda0483c823d4a6c7e
BLAKE2b-256 3a797d20a7e28d4a96b7dac962dac51658a74262f973fa64ca09114a0bd3d234

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