- Generating requirements.txt for Python project.
- Handling the difference between different Python versions.
- Jupyter notebook (
*.ipynb
) support. - Including the import statements from
exec
/eval
, doctest of docstring, etc.
- Searching packages by import name.
- Checking the latest versions for Python project.
NOTE: Pipenv or other tools is recommended for improving your development flow.
pigar
can run on Python 2.7.+ and 3.2+.
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@[master or other branch] --upgrade
-
pigar
can consider all kinds of complicated situations. For example, this project has py2_requirements.txt and py3_requirements.txt for different Python versions(see the above GIF).# Generate requirements.txt for current directory. $ pigar # Generating requirements.txt for given directory in given file. $ pigar -p ../dev-requirements.txt -P ../
pigar
can list all files which referenced the package(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. -
If you do not know the import name that belongs to a specific package (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 -s bs4 MySQLdb
-
Checking for the latest version:
# Specify a requirements file. $ pigar -c ./requirements.txt # Or, you can let pigar searching all *requirements.txt in the current directory # level by itself. If not found, pigar will generate a new requirements.txt # for the current project, then check for the latest versions. $ pigar -c
-
More:
pigar --help
(1) Why `pigar` generates multiple packages for same import name?
(2) Why pigar
generates different packages for same import name in different environment?
pigar
generates different packages for same import name in different environment?pigar
can not handle it gracefully, you may need to remove the duplicate packages in requirements.txt manually.
Install the required package(remove others) in local environment should fix it as well.
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
, doctest of docstring, etc.
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!