Python for Scientists – Environments

Why make environments? Why can't I just install everything into the root, or base, python environment and go happily on my way? Because sooner or later this is going to happen.

You find a new feature in the latest release for a library that finally allows you to simplify your code. This is great! You quickly type the command to update the package in your base environment. The installation is going fine until you get a message that installation failed and Conda will try to roll back changes. The roll back seems to work fine and you decide to live without the new feature. Then you try to run your script again and it fails due to a library conflict. What!? My script worked just a few minutes ago! After searching online for an hour for a fix, you decide to delete Miniconda3 and reinstall everything. You try to remember all of the libraries that were used, but other scripts from different projects rely on different libraries. Oh no. You're in for a terrible, horrible, no good, very bad day(s).

Python for Scientists – Installation for Linux

If used properly, Anaconda can take most of the annoyances out of managing Python libraries and virtual environments. Even if corruption occurs (yes, it will happen), this series will equip you with means to replicate your working environments. Before we get to disaster recovery, we need a solid base installation. Remember, this post covers installation... Continue Reading →

Python for Scientists – Installation for Windows

If used properly, Anaconda can take most of the annoyances out of managing Python libraries and virtual environments. Even if corruption occurs (yes, it will happen), this series will equip you with means to replicate your working environments. Before we get to disaster recovery, we need a solid base installation. Remember, this post covers installation... Continue Reading →

Proudly powered by WordPress | Theme: Baskerville 2 by Anders Noren.

Up ↑