What is the use case for `pip install -e`?
Question:
When I need to work on one of my pet projects, I simply clone the repository as usual (git clone <url>), edit what I need, run the tests, update the setup.py version, commit, push, build the packages and upload them to PyPI.
What is the advantage of using pip install -e? Should I be using it? How would it improve my workflow?
Answers:
pip install -e is how setuptools dependencies are handled via pip.
What you typically do is to install the dependencies:
git clone URLcd project- run
pip install -e . or pip install -e .[dev]*
And now all the dependencies should be installed.
*[dev] is the name of the requirements group from setup.py
Other than setuptools (egg) there is also a wheel system of python installation.
Both these systems are based on promise that no building and compilation is performed.
I find pip install -e extremely useful when simultaneously developing a product and a dependency, which I do a lot.
Example:
You build websites using Django for numerous clients, and have also developed an in-house Django app called locations which you reuse across many projects, so you make it available on pip and version it.
When you work on a project, you install the requirements as usual, which installs locations into site packages.
But you soon discover that locations could do with some improvements.
So you grab a copy of the locations repository and start making changes. Of course, you need to test these changes in the context of a Django project.
Simply go into your project and type:
pip install -e /path/to/locations/repo
This will overwrite the directory in site-packages with a symbolic link to the locations repository, meaning any changes to code in there will automatically be reflected – just reload the page (so long as you’re using the development server).
The symbolic link looks at the current files in the directory, meaning you can switch branches to see changes or try different things etc…
The alternative would be to create a new version, push it to pip, and hope you’ve not forgotten anything. If you have many such in-house apps, this quickly becomes untenable.
For those who don’t have time:
If you install your project with an -e flag (e.g. pip install -e mynumpy) and use it in your code (e.g. from mynumpy import some_function), when you make any change to some_function, you should be able to use the updated function without reinstalling it.
When I need to work on one of my pet projects, I simply clone the repository as usual (git clone <url>), edit what I need, run the tests, update the setup.py version, commit, push, build the packages and upload them to PyPI.
What is the advantage of using pip install -e? Should I be using it? How would it improve my workflow?
pip install -e is how setuptools dependencies are handled via pip.
What you typically do is to install the dependencies:
git clone URLcd project- run
pip install -e .orpip install -e .[dev]*
And now all the dependencies should be installed.
*[dev] is the name of the requirements group from setup.py
Other than setuptools (egg) there is also a wheel system of python installation.
Both these systems are based on promise that no building and compilation is performed.
I find pip install -e extremely useful when simultaneously developing a product and a dependency, which I do a lot.
Example:
You build websites using Django for numerous clients, and have also developed an in-house Django app called locations which you reuse across many projects, so you make it available on pip and version it.
When you work on a project, you install the requirements as usual, which installs locations into site packages.
But you soon discover that locations could do with some improvements.
So you grab a copy of the locations repository and start making changes. Of course, you need to test these changes in the context of a Django project.
Simply go into your project and type:
pip install -e /path/to/locations/repo
This will overwrite the directory in site-packages with a symbolic link to the locations repository, meaning any changes to code in there will automatically be reflected – just reload the page (so long as you’re using the development server).
The symbolic link looks at the current files in the directory, meaning you can switch branches to see changes or try different things etc…
The alternative would be to create a new version, push it to pip, and hope you’ve not forgotten anything. If you have many such in-house apps, this quickly becomes untenable.
For those who don’t have time:
If you install your project with an -e flag (e.g. pip install -e mynumpy) and use it in your code (e.g. from mynumpy import some_function), when you make any change to some_function, you should be able to use the updated function without reinstalling it.