Pip and venv have done a lot to improve the accessibility and ease of installing python packages, but I believe there is still a lot of room for improvement.  I only realised how cumbersome I find working with python packages when I recently spent a lot of time on a javascript project using npm.  A bit of googling and I found several articles discussing pip, venv and npm, and all of them seemed to say the same thing, i.e. pip/venv could learn a lot from npm.

My proposal revolves around two issues:

1. Setting up and working with virtual environments can be onerous.  Creating one is easy enough, but using them means remembering to run `source activate` every time, which also means remembering which venv is used for which project.  Not a major issue, but still and annoyance.
   
2. Managing lists of required packages is not nearly as easy as in npm since these is no equivalent to `npm install --save ...`.  The best that pip offers is `pip freeze`.  Howevere, using that is a) an extra step to remember and b) includes all implied dependencies which is not ideal.

My proposal is to use a similar model to npm, where each project has a `venvrc` file which lets python-related tools know which environment to use.  In order to showcase the sort of funcionality I'm proposing, I've created a basic example on github (https://github.com/aquavitae/pyle).  This is currently py3.4 on linux only and very pre-alpha.  Once I've added a few more features that I have in mind (e.g. multiple venvs) I'll add it to pypi and if there is sufficient interest I'd be happy to write up a PEP for getting it into the stdlib.

Does this seem like the sort of tool that would be useful in the stdlib?

Regards

David

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