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Tools for generating Python models from JSON Schema documents.

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Statham Schema

statham is a Python DSL for JSON Schema. Read the documentation.

This project includes tools for writing and generating extensible Python classes based on JSON Schema documents.

Example DSL Definition

The DSL can be used to write JSON Schema documents and their corresponding application-level models in one go:

from typing import List

from statham.dsl.elements import Array, Integer, Object, String
from statham.dsl.property import Property


class Choice(Object):
    choice_text: str = Property(String(maxLength=200), required=True)
    votes: int = Property(Integer(default=0))


class Poll(Object):
    question: str = Property(String(), required=True)
    choices: List[Choice] = Property(Array(Choice), required=True)

Generating python classes

Alternatively, DSL models may be generated automatically from an existing schema:

statham --input http://example.com/schema.json

Command-line arguments

Required arguments:
  --input INPUT    Specify the path to the JSON Schema to be generated.

                   If the target schema is not at the root of a document, specify the
                   JSON Pointer in the same format as a JSON Schema `$ref`, e.g.
                   `--input path/to/document.json#/definitions/schema`


Optional arguments:
  --output OUTPUT  Output directory or file in which to write the output.

                   If the provided path is a directory, the command will derive the name
                   from the input argument. If not passed, the command will write to
                   stdout.

  -h, --help       Display this help message and exit.

Installation

This project requires Python 3.6 and may be installed using pip:

pip install statham-schema

Development

  1. Clone the repository: git clone git@github.com:jacksmith15/statham-schema.git && cd statham-schema
  2. Install the requirements: pip install -r requirements.txt -r requirements-test.txt
  3. Run pre-commit install
  4. Run the tests: bash run_test.sh -c -a

This project uses the following QA tools:

  • PyTest - for running unit tests.
  • PyLint - for enforcing code style.
  • MyPy - for static type checking.
  • Travis CI - for continuous integration.
  • Black - for uniform code formatting.

Documentation is written using Sphinx.

License

This project is distributed under the MIT license.

statham

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