https://howto.cs.uchicago.edu/ 2026-06-20T00:00:46+00:00 FeedCreator 1.8 (info@mypapit.net) 2019-01-25T11:28:04+00:00 2019-01-25T11:28:04+00:00 https://howto.cs.uchicago.edu/python:conda?rev=1548437284&do=diff Anonymous anonymous@undisclosed.example.com Anaconda Use system installed version Conda is installed by default and you should be able to use it without doing anything. If it does not work for you automatically all you need to do is source the right file. $ source /opt/conda/etc/profile.d/conda.sh

Anaconda Use system installed version Conda is installed by default and you should be able to use it without doing anything. If it does not work for you automatically all you need to do is source the right file. $ source /opt/conda/etc/profile.d/conda.sh

2017-05-02T12:37:06+00:00 2017-05-02T12:37:06+00:00 https://howto.cs.uchicago.edu/python:pip?rev=1493746626&do=diff Anonymous anonymous@undisclosed.example.com PIP (Python Modules) Installation These are general guide lines and not hard and fast rules. The recommended method of installing via pip is: python[3] -m pip install --user <somepackage> System Wide Installing python modules system wide is normally done when a larger group of people need a particular module.

PIP (Python Modules) Installation These are general guide lines and not hard and fast rules. The recommended method of installing via pip is: python[3] -m pip install --user <somepackage> System Wide Installing python modules system wide is normally done when a larger group of people need a particular module.

2016-06-30T11:56:55+00:00 2016-06-30T11:56:55+00:00 https://howto.cs.uchicago.edu/python:virtual_environments?rev=1467305815&do=diff Anonymous anonymous@undisclosed.example.com Python Virtual Environments What and Why A Virtual Environment is a tool to keep the dependencies required by different projects in separate places, by creating virtual Python environments for them. It solves the “Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keeps your global site-packages directory clean and manageable. For example, you can work on a project which requires Django 1.3 while also maintaining a project which requires Django 1.0.

Python Virtual Environments What and Why A Virtual Environment is a tool to keep the dependencies required by different projects in separate places, by creating virtual Python environments for them. It solves the “Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keeps your global site-packages directory clean and manageable. For example, you can work on a project which requires Django 1.3 while also maintaining a project which requires Django 1.0.