Managing Python Environments with Conda
Last updated on 2022-11-15 | Edit this page
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Environments and environment managers
Overview
Questions
- How can I make sure the whole team (or lab) gets the same results?
- How can I simplify setup and dependencies for people to use my code or reproduce my results?
Objectives
- Identify an environment, dependencies, and an environment manager
- Use conda to install a different version of python
- Use conda to create an environment per project
- Store a projects dependencies
An environment consists of a certain Python version and some packages
Why use one:
- to delvier code and keep it the same versions
- to contou use ribute to a package y
how to chose which of the main strategies to use: virtualenv and pip or conda
Dependencies
Conda Python installs
Conda for projects
Key Points
- A python dependency is another, independent package that a given project uses and requires to be able to run
- An environment is
- An environment manager enables one step installing and documentation of dependencies, including versions
- Conda is the included environment manager with Anaconda; it is also an installer
- Other popular environment managers are FIXME