A virtualenv first approach to Python projects

I have until the last few months (of my ~4 years of working with Python) always worked without virtualenv for all my Python projects. Why? I think I found the whole idea of having to do the following two steps before I work on something cumbersome:

  • Remember the exact virtualenv name, and then
  • Activate it

That said, I was very much aware that it was certainly a good thing to do and would cause me less headaches someday. That someday finally came, and I ran into conflicting package requirements for applications which needed to run simultaneously. This forced me to start using virtualenvs. I think I also found the tool which will make me keep using them even when I don't need to. The tool is pew.

Installation and Basics

The home page lists various options of installing pew. The most straightforward is of course to just use pip install pew. Once you have it installed, typing pew lists the various sub-commands, such as new, workon, ls and others. Eac of the sub-commands is accompanied by a summary of they will do.

So far, I have been mostly working with the above sub-commands. Here is how we can create a new virtualenv:

$ pew new flask-graphql-demo
New python executable in flask-graphql-demo/bin/python2
Also creating executable in flask-graphql-demo/bin/python
Installing setuptools, pip...done.
Launching subshell in virtual environment. Type 'exit' or 'Ctrl+D' to return.
flask-graphql-demo $

Our virtualenv flask-graphql-demo is created and we are in it, which we can check:

$ which pip
~/.local/share/virtualenvs/flask-graphql-demo/bin/pip

We can do all our usual work now (installing other packages, running our applications) and once done, we can simply exit and we will be out of the virtualenv.

Now, if I want to resume work on this particular project, I can first use pew ls to list the currently created virtualenvs:

$ pew ls
flask-graphql-demo

and then use pew workon flask-graphql-demo to start working on it again. On Linux, pew workon also gives me all the available virtualenvs as suggestions automatically.

Conclusion

As you may have already seen, pew has a number of other features which should make working with virtualenvs really easy. It has definitely made me change my approach to working on Python projects.

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