pydantic-gen 0.2.1

Python wrapper for Coda.io API

Pydantic Schemas Generator

What is Pydantic

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

Here's an official example from the docs

Why generate schemas?

Normally you just program the schemas within your program, but there are several user 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

pip install 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 now to 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 example_output.py

2. Import the code directly witout saving

generated.to_sys(module_name='generated_schemas')

After running .to_sys() module 'generated_schemas' will be added to sys.modules and become importable like a normal module:

from generated_schemas import GeneratedSchema1

schema = 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.