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PyAnnotate: Auto-generate PEP-484 annotations

Project description

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:

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 code between calls to `collect_types.resume()` and
`collect_types.pause()` (or use the context manager below)
- When done, call `collect_types.dump_stats(filename)`

All calls between the `pause()` and `resume()` 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 pause/resume pairs
per dump call.

If you'd like to automatically collect types when you run `pytest`,
see `example/` and `example/`.

Instead of using `resume()` and `pause()` you can also use a context
with collect_types.collect():
<your code here>

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 currently always generates type comments, i.e. Python 2
style annotations. (Python 3 style are a TO DO item.)

Red tape


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/, 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 and requirements.txt.

Testing etc.

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

Licence etc.

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):

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