Code generator for pydantic schemas
Project description
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:
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
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:
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