- Generating requirements.txt for Python project.
- Handling the difference between different Python versions.
- Jupyter notebook (
*.ipynb
) support. - Including the import statements/magic from
exec
/eval
/importlib
, doctest of docstring, etc.
- Searching ditributions(packages) by the top level import/module names.
- Checking the latest versions of requirements.
NOTE: Pipenv or other tools is recommended for improving your development flow.
pigar
can run on Python 3.7+.
To install it with pip
, use:
[sudo] pip install pigar
To install it with conda
, use:
conda install -c conda-forge pigar
To get the newest code from GitHub:
pip install git+https://github.com/damnever/pigar.git@[main or other branch] --upgrade
-
pigar
can consider most kinds of complicated situations(see FAQ). For example,pigar v1
has py2_requirements.txt and py3_requirements.txt for different Python versions.# Generate requirements.txt for current directory. $ pigar generate # Generating requirements.txt for given directory in given file. $ pigar gen -f ../dev-requirements.txt ../
pigar gen --with-referenced-comments
can list all files which referenced the package/distribution(the line numbers for Jupyter notebook may be a bit confusing), for example:# project/foo.py: 2,3 # project/bar/baz.py: 2,7,8,9 foobar == 3.3.3
If the requirements.txt is overwritten,
pigar
will show the difference between the old and the new, use--dont-show-differences
to disable it.NOTE,
pigar
will search the packages/distributions in local environment first, then it will do further analysis and search missing packages/distributions on PyPI.See also: EXPERIMENTAL FEATURES.
-
If you do not know the import name that belongs to a specific distribution (more generally, does
Import Error: xxx
drive you crazy?), such asbs4
which may come frombeautifulsoup4
orMySQLdb
which could come frommysql-python
, try searching for it:$ pigar search bs4 MySQLdb
-
Checking for the latest version:
# Specify a requirements file. $ pigar check -f ./requirements.txt # Or, you can let pigar searching all *requirements.txt in the current directory # level by itself. $ pigar check
-
More:
TIP:
pigar
accepts a prefix for a command, such aspigar gen
,pigar c
.pigar --help
-
requirement-annotations
Some packages may require optional packages/distributions to be installed depending on your usage. To make
pigar
a little bit more useful, usepigar generate --enable-feature requirement-annotations
in conjunction with comments following the format below:import foo # pigar: required-imports=import_name_bar,import_name_baz import foo # pigar: required-packages=package-name-bar,package-name-baz # Extra comments are allowed. foo(features=['bar', 'baz']) # pigar: required-distributions=package-name-bar,package-name-baz
If you find the comment intrusive, you can extract those comments into a separate Python file and delete it as needed, for example, 'pigar_annotations.py'.
Is `pigar` a dependency management tool?
No. I've thought about this many times, but there is too much dirty work to be done to make pigar
's way reliable.
I like the way pigar
does the job, but sadly, pigar
does a bad job of managing dependencies, pigar
is more like a tool to assist an old project to migrate to a new development workflow.
(1) Why does `pigar` show multiple packages/distributions for the same import name?
(2) Why does pigar
generate different packages/distributions for the same import name in different environment?
pigar
generate different packages/distributions for the same import name in different environment?pigar
can not handle those situations gracefully, you may need to remove the duplicate packages in requirements.txt manually, or select one of them when pigar
asks you.
Install the required packages/distributions(remove others) in local environment should fix it as well.
Why can't `pigar` find the packages/distributions that have not been explicit import?
Some frameworks may use some magic to import the modules for users automatically, and pigar
can not handle it, you may need to fix it manually or use the EXPERIMENTAL FEATURES.
pigar
does not use regular expressions in such a violent way. Instead, it uses AST, which is a better method for extracting imported names from arguments of exec
/eval
/importlib
, doctest of docstring, etc. However, pigar
can not solve all the tricky problems, see FAQ.
Also, pigar
can detect the difference between different Python versions. For example, you can find concurrent.futures
from the Python 3.2 standard library, but you will need install futures
in earlier versions of Python to get concurrent.futures
, this is not a hardcode.
If you have any issues or suggestions, please submit an issue on GitHub. All contributions are appreciated!