It includes more than 300 of the most popular Python packages for science, math, engineering, and data analysis.' It is available across platforms and installable through a binary.

Anaconda: 'Anaconda is a completely free Python distribution (including for commercial use and redistribution).

Because conda works for any software, it can even install different versions of Python (unlike pip).

It works on Linux, OS X and Windows, and was created for Python programs but can package and distribute any software.' A conda install provides a whole suite of command line tools for installing and managing packages and environments. conda: 'Conda is an open source package management system and environment management system for installing multiple versions of software packages and their dependencies and switching easily between them.I have also switched from using virtualenvs to using conda environments, and I am loving it.īefore explaining my workflow, here's a quick glossary of the similarly-named products that Continuum offers. In 2015, I have almost exclusively used Python installations provided through Continuum Analytics's Conda/Anaconda platform.

You have to install each version yourself and then tell virtualenv to use it. virtualenv also provides no helping in actually managing Python versions.

In my experience, getting started with virtualenv is cumbersome and confusing to this day, I have to look up the command to create a Python 3 virtualenv. If you use virtualenv, each project you work on can have its own version of Python with its own 3rd party packages (hopefully specified in an requirements.txt file).

While this may sound convenient, it causes problems if you (1) install different packages with the same name (2) need to use different versions of the same package (3) upgrade your operating system (OS X will delete all the packages you have installed).įor many years, best practice for Python developers was to use virtualenv to create a sandbox-ed environment for each project. Secondly, if you install 3rd party packages with pip, every package is installed into the same globally accessible directory. First, it's probably an old version of Python. There are several good reasons to stop using the system Python. Many new Python programmers rely on their system install of Python to run their scripts.

Conda env list