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https://github.com/gristlabs/asttokens

Annotate Python AST trees with source text and token information
https://github.com/gristlabs/asttokens

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Annotate Python AST trees with source text and token information

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ASTTokens
=========

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.. Start of user-guide

The ``asttokens`` module annotates Python abstract syntax trees (ASTs) with the positions of tokens
and text in the source code that generated them.

It makes it possible for tools that work with logical AST nodes to find the particular text that
resulted in those nodes, for example for automated refactoring or highlighting.

Installation
------------
asttokens is available on PyPI: https://pypi.python.org/pypi/asttokens/::

pip install asttokens

The code is on GitHub: https://github.com/gristlabs/asttokens.

The API Reference is here: http://asttokens.readthedocs.io/en/latest/api-index.html.

Usage
-----

ASTTokens can annotate both trees built by `ast `_,
AND those built by `astroid `_.

Here's an example:

.. code-block:: python

import asttokens, ast
source = "Robot('blue').walk(steps=10*n)"
atok = asttokens.ASTTokens(source, parse=True)

Once the tree has been marked, nodes get ``.first_token``, ``.last_token`` attributes, and
the ``ASTTokens`` object offers helpful methods:

.. code-block:: python

attr_node = next(n for n in ast.walk(atok.tree) if isinstance(n, ast.Attribute))
print(atok.get_text(attr_node))
start, end = attr_node.last_token.startpos, attr_node.last_token.endpos
print(atok.text[:start] + 'RUN' + atok.text[end:])

Which produces this output:

.. code-block:: text

Robot('blue').walk
Robot('blue').RUN(steps=10*n)

The ``ASTTokens`` object also offers methods to walk and search the list of tokens that make up
the code (or a particular AST node), which is more useful and powerful than dealing with the text
directly.

Contribute
----------

To contribute:

1. Fork this repository, and clone your fork.
2. Install the package with test dependencies (ideally in a virtualenv) with::

pip install -e '.[test]'

3. Run tests in your current interpreter with the command ``pytest`` or ``python -m pytest``.
4. Run tests across all supported interpreters with the ``tox`` command. You will need to have the interpreters installed separately. We recommend ``pyenv`` for that. Use ``tox -p auto`` to run the tests in parallel.
5. By default certain tests which take a very long time to run are skipped, but they are run in CI.
These are marked using the ``pytest`` marker ``slow`` and can be run on their own with ``pytest -m slow`` or as part of the full suite with ``pytest -m ''``.