Managing Python Environments with Conda

Environments and environment managers

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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

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Conda Python installs

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Conda for projects

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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