Skip to main content

Code generator for pydantic schemas

Project description

https://img.shields.io/pypi/pyversions/pydantic-gen https://img.shields.io/badge/code%20style-black-000000.svg https://img.shields.io/pypi/v/pydantic-gen https://img.shields.io/pypi/dw/pydantic-gen https://img.shields.io/endpoint.svg?url=https%3A%2F%2Factions-badge.atrox.dev%2Flicht1stein%2Fpydantic-gen%2Fbadge&style=flat https://img.shields.io/readthedocs/pydantic-gen:alt:ReadtheDocs https://img.shields.io/badge/Support-With_coffee!-Green

What this package does

This is a code generation package that converts YML definitions to Pydantic models (either python code or python objects).

What is Pydantic

Pydantic is a python library for data validation and settings management using python type annotations.

Take a look at the official example from the Pydantic docs.

Why generate schemas?

Normally you just program the schemas within your program, but there are several use cases when code generation makes a lot of sense:

  • You’re programming several apps that use the same schema (think an API server and client library for it)

  • You’re programming in more than one programming language

Getting started

Installation

Using pip:

pip install pydantic-gen

Using poetry:

poetry add pydantic-gen

Usage

First you need to create a YAML file with your desired class schema. See example.yml file.

from pydantic_gen import SchemaGen

generated = SchemaGen('example.yml')

The code is now generated and stored in generated.code attribute. There are two ways to use the code:

  1. Save it to a file, and use the file in your program:

generated.to_file('example_output.py')

You can inspect the resulting file in the example_output.py

  1. Or directly import the generated classed directly without saving:

generated.to_sys(module_name='generated_schemas')

After running generated.to_sys(module_name=’generated_schemas’ your generated code will be available for import:

import generated_schemas as gs

schema = gs.GeneratedSchema1(id=1)

Usage pattern

Recommended usage pattern is creating the yaml files needed for your projects and storing them in a separate repository, to achieve maximum consistency across all projects.

YAML-file structure

schemas - list of all schemas described

name - name of the generated class

props - list of properties of the class using python type annotation. Fields: name - field name, type - field type, optional - bool, if True the type will be wrapped in Optional, default - default value for the field.

config - list of config settings from Model Config of pydantic.

Testing

Project is fully covered by tests and uses pytest. To run:

pytest

Packaging Notice

This project uses the excellent poetry for packaging. Please read about it and let’s all start using pyproject.toml files as a standard. Read more:

Project details


Download files

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

Source Distribution

pydantic-gen-0.3.3.tar.gz (5.3 kB view details)

Uploaded Source

Built Distribution

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

pydantic_gen-0.3.3-py3-none-any.whl (5.4 kB view details)

Uploaded Python 3

File details

Details for the file pydantic-gen-0.3.3.tar.gz.

File metadata

  • Download URL: pydantic-gen-0.3.3.tar.gz
  • Upload date:
  • Size: 5.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.0.5 CPython/3.7.7 Linux/5.3.0-1022-azure

File hashes

Hashes for pydantic-gen-0.3.3.tar.gz
Algorithm Hash digest
SHA256 1ccd5d6d6b716977eb6ddf9d8a832890e18dbc6ee378b25ecb055967b94f901e
MD5 cb124ea94b2d5f038d295d09916d0b1d
BLAKE2b-256 600af38e2cbba22133713459cd859b7d481ead230cf07be58e5dc532c4748386

See more details on using hashes here.

File details

Details for the file pydantic_gen-0.3.3-py3-none-any.whl.

File metadata

  • Download URL: pydantic_gen-0.3.3-py3-none-any.whl
  • Upload date:
  • Size: 5.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.0.5 CPython/3.7.7 Linux/5.3.0-1022-azure

File hashes

Hashes for pydantic_gen-0.3.3-py3-none-any.whl
Algorithm Hash digest
SHA256 74b70740e827e0a80e5d121cfb841444a2d81914721c72aa13901c4e72e5ca44
MD5 1e25bca4f39b8d77672eac70bc853e55
BLAKE2b-256 527acb0059ee2605866cf375f0f0c2923b24ba9e98e297b38659476bb327cdd7

See more details on using hashes here.

Supported by

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