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GitHub - dropbox/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

See also the example directory.

• 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>)

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.

• 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+

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

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.

To run the unit tests, use pytest:

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).

The following people contributed significantly to this tool:

• Tony Grue
• Sergei Vorobev
• Jukka Lehtosalo
• Guido van Rossum

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

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