pydantic-ast 0.2.1

Pydantic models covering Python AST types

Pydantic AST

Pydantic models covering Python AST types.

Installation

pip install pydantic-ast

Usage

Use it as a drop-in replacement to ast.parse with a more readable representation.

>>> import ast
>>> import pydantic_ast
>>> source = "x = 1"
>>> ast.parse(source)
<ast.Module object at 0x7fef82567610>
>>> pydantic_ast.parse(source)
body=[Assign(targets=[Name(id='x', ctx=Store())], value=Constant(value=1), type_comment=None)] type_ignores=[]

Use it on the command line to quickly get an AST of a Python program or a section of one

echo '"Hello world"' | pydantic-ast

⇣

body=[Expr(value=Constant(value='Hello world'))] type_ignores=[]

Use it on ASTs you got from elsewhere to make them readable, or to inspect parts of them more easily. The AST_to_pydantic class is a ast.NodeTransformer that converts nodes in the AST to pydantic_ast model types when the tree nodes are visited.

>>> from pydantic_ast import AST_to_pydantic
>>> source = "123 + 345 == expected"
>>> my_mystery_ast = ast.parse(source)
>>> ast_model = AST_to_pydantic().visit(my_mystery_ast)
>>> ast_model
body=[Expr(value=Compare(left=BinOp(left=Constant(value=123), op=Add(), right=Constant(value=345)), ops=[Eq()], comparators=[Name(id='expected', ctx=Load())]))] type_ignores=[]
>>> ast_model.body
[Expr(value=Compare(left=BinOp(left=Constant(value=123), op=Add(), right=Constant(value=345)), ops=[Eq()], comparators=[Name(id='expected', ctx=Load())]))]

It's simply much easier to drill down into a tree when you can see the fields in a repr.

>>> ast_model.body[0].value
Compare(left=BinOp(left=Constant(value=123), op=Add(), right=Constant(value=345)), ops=[Eq()],
comparators=[Name(id='expected', ctx=Load())])
>>> ast_model.body[0].value.left
BinOp(left=Constant(value=123), op=Add(), right=Constant(value=345))
>>> ast_model.body[0].value.left.left
Constant(value=123)
>>> ast_model.body[0].value.left.left.value
123

Development

• To set up pre-commit hooks (to keep the CI bot happy) run pre-commit install-hooks so all git commits trigger the pre-commit checks. I use Conventional Commits. This runs black, flake8, autopep8, pyupgrade, etc.

• To set up a dev env, I first create a new conda environment and use it in PDM with which python > .pdm-python. To use virtualenv environment instead of conda, skip that. Run pdm install and a .venv will be created if no Python binary path is found in .pdm-python.

• To run tests, run pdm run python -m pytest and the PDM environment will be used to run the test suite.