Pydantic models covering Python AST types.
pip install pydantic-ast
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
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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 runsblack
,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 usevirtualenv
environment instead of conda, skip that. Runpdm 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.