Python alias commands that play nice with virtualenv

There are plenty of predefined Python executables, symlinks, and aliases that come bundled with your operating system. These commands come in very handy because it saves you from typing out long commands or chain of scripts. However the downfall of operating system aliases is that they don’t always play nice with virtualenv (or venv if you’re on Python 3). Most predefined aliases use the system’s default Python as the interpreter, which is next to useless when your application runs in a virtual environment. Over the years, I’ve come up with my own Python aliases that play nice with virtual environments. For this post, I tried to stay as generic as possible such that any alias here can be used by every Pythonista. In other words, there will be no aliases for specific frameworks such as running a Django server or starting a Scrappy spider. The following is one of my bash scripts I source:

.py-aliases

#----- Pip -----#
alias pip-list="pip freeze | less"
alias pip-search="pip freeze | grep -i"
alias pip-remove="pip uninstall"
alias pip-upgrade="pip install -U"
alias pip-upgrade-all="pip freeze --local | grep -v '^\-e' | cut -d = -f 1|xargs -n1 pip install -U"

#----- Debugging -----#
alias pdb="python -m pdb"
alias ppjson="python -m json.tool"
alias module-locate="python -c 'from imp import find_module;from sys import argv;print(find_module(argv[1])[1])'"

#----- Documentation -----#
alias pydoc="python -m pydoc"

Pip

This set of commands is the most convenient because pip can be a bit awkward when installing, uninstalling, and upgrading modules. Astute dev-ops folks might notice that I took heavy inspiration from tools like apt-get and yum. These commands also imitate conda, so for those who are using Anaconda, checkout conda out.

• pip-list: List all installed modules then pipe to a cursor so that it’s easy to scroll.
• pip-search: Search installed Python modules
• pip-remove: Uninstall Python module(s)
• pip-upgrade: Upgrade Python module(s)
• pip-upgrade-all: My favorite for development. Upgrades all the Python packages without the need to specifying them individually.

Debugging

• pdb: This is self explanatory for veterans. Runs scripts in the environment’s Python debugger.
• ppjson: Pretty print JSON from a file or curl output. If you work with JSON and RESTful web apps, then you need this!
• module-locate: Locate the system file path to a particular Python module, which can be useful when debugging. This is actually a script on my machine, but to keep this post brief, I did a quick one-liner to capture the gist of my script.

Let's do a quick tutorial of ppjson. I generally use this to test JSON responses from web apps in conjunction with curl, treq, and/or requests. For example, lets get some Star Wars JSON from SWAPI and pipe it to our new ppjson alias:

curl -L http://swapi.co/api/people/1 | ppjson

{
      "name": "Luke Skywalker",
      "height": "1.72 m",
      "mass": "77 Kg",
      "hair_color": "Blond",
      "skin_color": "Caucasian",
      "eye_color": "Blue",
      "birth_year": "19 BBY",
      "gender": "Male",
      "homeworld": "http://swapi.co/api/planets/1/",
      "films": [
          "http://swapi.co/api/films/1/",
          "http://swapi.co/api/films/2/",
          "http://swapi.co/api/films/3/"
      ],
      "species": [
          "http://swapi.co/api/species/1/"
      ],
      "vehicles": [
          "http://swapi.co/api/vehicles/14/",
          "http://swapi.co/api/vehicles/30/"
      ],
      "starships": [
          "http://swapi.co/api/starships/12/",
          "http://swapi.co/api/starships/22/"
      ],
      "created": "2014-12-09T13:50:51.644000Z",
      "edited": "2014-12-10T13:52:43.172000Z",
      "url": "http://swapi.co/api/people/1/"
}

ppjson also works with files containing JSON.

Documentation

• pydoc: Reference the environment PyDocs. This is generally very helpful (despite the HTML pages looking very ugly) when you need to get documentation of a module in your virutalenv. I regularly start the web server so that I can quickly reference builtin and installed modules without the need to google. Example: pydoc -b -p 9001