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: 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()
andcollect_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 todump_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
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/
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