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Static Python models parser that extracts ORM, Pydantic, and dataclass models into a unified structure (no code execution).

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xnuinside/py-models-parser

Py-Models-Parser

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It's a second parser that I've created. The first is simple-ddl-parser for SQL DDL with different dialects.

Py-Models-Parser can parse & extract information from models & table definitions:

Number of supported models will be increased. Check the 'TODO' section. If you want support for different model types, please open an issue.

Py-Models-Parser is written with PEG parser and its Python implementation - parsimonious. It's pretty new and I did not cover all possible test cases, so if you have an issue - please just open an issue with an example, I will fix it as soon as possible.

NOTE: This is a text parser, so it doesn't import or load your code. The parser works with source code as text, not objects in Python. So to run the parser you DO NOT NEED to install dependencies for models that you're trying to parse - only the models themselves.

Output Format

Py-Models-Parser takes different Python code with Models as input and provides output in a standard form:

[
    {
        'name': 'ModelName',
        'parents': ['BaseModel'],  # class parents defined in ()
        'attrs': [
            {
                'name': 'attr_name',
                'type': 'integer',
                'default': 'default_value',
                'properties': {
                    # additional info like foreign_key, server_default, etc.
                }
            }
        ],
        'properties': {
            'table_name': '...'  # model-level properties
        }
    }
]

For ORM models, 'attrs' contains columns. Three keys - 'type', 'name', 'default' - exist in all parsed model attrs. The 'properties' key contains additional information depending on Model type.

Installation

pip install py-models-parser

Usage

Parse from string

from py_models_parser import parse

models_str = """
from gino import Gino

db = Gino()

class OrderItems(db.Model):
    __tablename__ = 'order_items'

    product_no = db.Column(db.Integer(), db.ForeignKey('products.product_no'), ondelete="RESTRICT", primary_key=True)
    order_id = db.Column(db.Integer(), db.ForeignKey('orders.order_id'), ondelete="CASCADE", primary_key=True)
"""

result = parse(models_str)

Parse from file

from py_models_parser import parse_from_file

result = parse_from_file("path/to/your/models.py")

Parse OpenAPI/Swagger specifications

from py_models_parser import parse_openapi, parse_openapi_file

# Parse from string
openapi_spec = """
openapi: "3.0.0"
components:
  schemas:
    User:
      type: object
      properties:
        id:
          type: integer
        name:
          type: string
"""
result = parse_openapi(openapi_spec)

# Or parse from file (supports both YAML and JSON)
result = parse_openapi_file("path/to/openapi.yaml")

CLI

pmp path_to_models.py

# Dump output to JSON file
pmp path_to_models.py -d target_file.json

Output Example

For the GinoORM model above, the library produces:

[
    {
        "name": "OrderItems",
        "parents": ["db.Model"],
        "attrs": [
            {
                "name": "product_no",
                "type": "db.Integer()",
                "default": None,
                "properties": {
                    "foreign_key": "'products.product_no'",
                    "ondelete": '"RESTRICT"',
                    "primary_key": "True",
                },
            },
            {
                "name": "order_id",
                "type": "db.Integer()",
                "default": None,
                "properties": {
                    "foreign_key": "'orders.order_id'",
                    "ondelete": '"CASCADE"',
                    "primary_key": "True",
                },
            },
        ],
        "properties": {"table_name": "'order_items'"},
    }
]

You can find more output examples in tests.

TODO

  1. Add more tests for supported models
  2. Add support for SQLAlchemy Core Tables

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Static Python models parser that extracts ORM, Pydantic, and dataclass models into a unified structure (no code execution).

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