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Tool to convert 'typed docstrings' (i.e. Sphinx 'Napoleon' format) to PEP-484 Py2 type comments.

Project description



Build Status Latest PyPI version

Python 3.7 Python 3.8
(...but primarily for running on Python 2.7 code)

A cli tool to convert type annotations found in 'Google-style' docstrings (as understood and documented by the Sphinx Napoleon plugin) into PEP-484 type comments which can be checked statically using mypy --py2.

For an example of the format see


Waterloo itself requires Python 3.7 or later, but is primarily designed for projects having Python 2.7 source files.
(It can be run on Python 3 source files too, but since we add type-comments you will want to run the comm2ann tool afterwards to migrate those to Py3 annotations).

For this reason it is best installed using pipx:

$ pipx install waterloo
  installed package waterloo 0.7.10, Python 3.7.7
  These apps are now globally available
    - waterloo
done! ✨ 🌟 ✨

(NOTE: we currently have to install from GitHub due to using a forked version Bowler, PyPI installation will be available once our changes are upstreamed)

Basic Usage

After we parse the docstrings and prepare the type comments (and imports of mentioned types), the resulting modifications to the files are performed by Bowler. This tool provides a few nice features such as an optional interactive "diff" interface (or just preview diffs without writing changes yet as a "dry run").

In short you can...

waterloo annotate my-project-dir/ --write

...and it will derive type comments from all of your typed docstrings and add them to the files.

To preview the changes without committing them:

waterloo annotate my-project-dir/ --show-diff

Waterloo will remove the type info from the docstrings, since it is now redundant. We assume you'll be using a type-checker like mypy to validate the annotations, so you don't want type info in the docstrings that can go outo of sync.

If you are using Sphinx to generate documentation from your docstrings you can use the sphinx-autodoc-typehints plugin to ensure the type info is still present in your docs.

CLI options

usage: waterloo annotate [-h] [-p PYTHON_VERSION] [-aa] [-rr]
                         [-ic {IMPORT,NO_IMPORT,FAIL}] [-up {IGNORE,WARN,FAIL}]
                         [-w] [-s] [-i]
                         F [F ...]

positional arguments:
  F                     List of file or directory paths to process.

Annotation options:

arg description
-p --python-version We can refactor either Python 2 or Python 3 source files but the underlying bowler+fissix libraries need to know which grammar to use (to know if print is a statement or a function). In Py2 mode, print will be auto-detected based on whether a from __future__ import print_function is found. For Py3 files print can only be a function. We also use parso library which can benefit from knowing <major>.<minor> version of your sources. (default: 2.7)
-aa, --allow-untyped-args If any args or return types are found in docstring we can attempt to output a type annotation. If arg types are missing or incomplete, default behaviour is to raise an error. If this flag is set we will instead output an annotation like (...) -> returnT which mypy will treat as if all args are Any. (default: False)
-rr, --require-return-type If any args or return types are found in docstring we can attempt to output a type annotation. If the return type is missing our default behaviour is to assume function should be annotated as returning -> None. If this flag is set we will instead raise an error. (default: False)
-ic --import-collision-policy {IMPORT,NO_IMPORT,FAIL} There are some cases where it is ambiguous whether we need to add an import for your documented type. This can occur if you gave a dotted package path but there is already a matching from package import *, or a relative import of same type name. In both cases it is safest for us to add a new specific import for your type, but it may be redundant. The default option IMPORT will add imports. The NO_IMPORT option will annotate without adding imports, and will also show a warning message. FAIL will print an error and won't add any annotation. (default: IMPORT)
-ut --unpathed-type-policy {IGNORE,WARN,FAIL} There are some cases where we cannot determine an appropriate import to add - when your types do not have a dotted path and we can't find a matching type in builtins, typing package or locals. When policy is IGNORE we will annotate as documented, you will need to resolve any errors raised by mypy manually. WARNoption will annotate as documented but also display a warning. FAIL will print an error and won't add any annotation. (default: FAIL)

Apply options:

arg description
-w, --write Whether to apply the changes to target files. Without this flag set waterloo will just perform a 'dry run'. (default: False)
-s, --show-diff Whether to print the hunk diffs to be applied. (default: False)
-i, --interactive Whether to prompt about applying each diff hunk. (default: False)

Logging options:

arg description
-l, --enable-logging Enable structured logging to stderr. (default: False)
-ll {DEBUG,INFO,WARNING,ERROR}, --log-level {DEBUG,INFO,WARNING,ERROR} Set the log level for stderr logging. (default: INFO)
-q, --quiet 'quiet' mode for minimal details on stdout (filenames, summary stats only). (default: False)
-v, --verbose 'verbose' mode for informative details on stdout (inc. warnings with suggested remedies). (default: True)


You can also define a waterloo.toml file in the root of your project to provide your own defaults to some of these options:

python_version = 3

allow_untyped_args = false
require_return_type = true
unpathed_type_policy = "IGNORE"
import_collision_policy = "FAIL"

Environment vars

You can also provide config defaults via environment variables, e.g.:



Notes on 'Napoleon' docstring format

The format is defined here

For now we only support the "Google-style" option. Open an issue if you need the alternative "Numpy-style" format.

In addition to the official list of Section headings we also allow Kwargs: (since I'd used that one myself in many places).

If you run waterloo with --show-diff option you will notice that we automatically add imports for the annotated types:

--- tests/fixtures/
+++ tests/fixtures/
@@ -2,6 +2,8 @@
 Boring docstring for the module itself
 import logging
+from engine.models import Product
+from typing import Any, Callable, Dict, Iterable, List, Optional, Union

 logger = logging.getLogger(__name__)

Built-in types and those from typing module are recognised. For other types we can still generate the import as long as you use dotted-path syntax in the docstring, for example:

        products (Union[Iterable[Dict], Iterable[engine.models.Product]])
        getter (Callable[[str], Callable])

In this docstring, waterloo is able to add the from engine.models import Product import.

If your docstrings don't have dotted paths you will see warnings like:

⚠️  line 231: Ambiguous Type: MysteryType in docstring for def myfunc does not match any builtins, 
typing.<Type>, imported names or class def in the file, and does not provide a dotted-path we can
use to add an import statement. However there are some forms we cannot auto-detect which may mean
no import is needed.
   ➤ annotation added: will assume no import needed

Waterloo will still add the annotation to the function, but when you try to run mypy on this file it will complain that MysteryType is not imported (if MysteryType is not already imported or defined in the file). You will then have to resolve that manually.

You may want to run a formatter such as isort on your code after applying annotations with waterloo, since it will just append the imports to the bottom of your existing import block.

Upgrading your project to Python 3

Adding type comments with waterloo can be an intermediate step. You can start type checking with mypy while you're still on Python 2.7.

Later when you're ready to upgrade you can then run this other tool and it will convert the py2 type-comments into proper py3 type annotations.

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