PyAnnotate: Auto-generate PEP-484 annotations

Insert annotations into your source code based on call arguments and return types observed at runtime.

For license and copyright see the end of this file.

Blog post: http://mypy-lang.blogspot.com/2017/11/dropbox-releases-pyannotate-auto.html

How to use

See also the example directory.

Phase 1: Collecting types at runtime

Install the usual way (see "red tape" section below)
Add from pyannotate_runtime import collect_types to your test
Early in your test setup, call collect_types.init_types_collection()
Bracket your test execution between calls to collect_types.start() and collect_types.stop() (or use the context manager below)
When done, call collect_types.dump_stats(filename)

All calls between the start() and stop() calls will be analyzed and the observed types will be written (in JSON form) to the filename you pass to dump_stats(). You can have multiple start/stop pairs per dump call.

If you'd like to automatically collect types when you run pytest, see example/example_conftest.py and example/README.md.

Instead of using start() and stop() you can also use a context manager:

collect_types.init_types_collection()
with collect_types.collect():
    <your code here>
collect_types.dump_stats(<filename>)

Phase 2: Inserting types into your source code

The command-line tool pyannotate can add annotations into your source code based on the annotations collected in phase 1. The key arguments are:

Use --type-info FILE to tell it the file you passed to dump_stats()
Positional arguments are source files you want to annotate
With no other flags the tool will print a diff indicating what it proposes to do but won't do anything. Review the output.
Add -w to make the tool actually update your files. (Use git or some other way to keep a backup.)

At this point you should probably run mypy and iterate. You probably will have to tweak the changes to make mypy completely happy.

Notes and tips

It's best to do one file at a time, at least until you're comfortable with the tool.
The tool doesn't touch functions that already have an annotation.
The tool can generate either of:
- type comments, i.e. Python 2 style annotations
- inline type annotations, i.e. Python 3 style annotations, using --py3 in v1.0.7+

Red tape

Installation

This should work for Python 2.7 as well as for Python 3.4 and higher.

pip install pyannotate

This installs several items:

A runtime module, pyannotate_runtime/collect_types.py, which collects and dumps types observed at runtime using a profiling hook.
A library package, pyannotate_tools, containing code that can read the data dumped by the runtime module and insert annotations into your source code.
An entry point, pyannotate, which runs the library package on your files.

For dependencies, see setup.py and requirements.txt.

Testing etc.

To run the unit tests, use pytest:

pytest

TO DO

We'd love your help with some of these issues:

Better documentation.
Python 3 code generation.
Refactor the tool modules (currently its legacy architecture shines through).

Acknowledgments

The following people contributed significantly to this tool:

Tony Grue
Sergei Vorobev
Jukka Lehtosalo
Guido van Rossum

Licence etc.

License: Apache 2.0.
Copyright attribution: Copyright (c) 2017 Dropbox, Inc.
External contributions to the project should be subject to Dropbox's Contributor License Agreement (CLA): https://opensource.dropbox.com/cla/