In the Terminal, set your directory to the cloned earth-analytics-python-env dir using cd to change directories (e.g.Git Bash for Windows or Terminal on a Mac/Linux). If it’s not already open, open the Terminal on your computer (e.g.For a refresher on forking/cloning repositories, see the section below on Fork and Clone GitHub Repository at the bottom of this lesson.This repository contains a file called environment.yml that contains the instructions to install the environment.Fork and clone a GitHub repository from to your earth-analytics directory.To install the earth-analytics-python environment, you will need to follow these steps: Install the Earth Analytics Python Conda Environment You can also check out the documentation on conda environments. To avoid conflicts, we created an environment called earth-analytics-python that contains all of the libraries that you will need for the Earth Analytics Python course lessons on this website.ĭata Tip: For general information about conda environments, see the section below on About Conda Environments.įor a more detailed explanation of conda environments, see the Intro to Earth Data Science textbook page on Using Conda Environments to Manage Python Dependencies. Sometimes libraries conflict which causes errors and packages not to work. Why Use Conda Environments for PythonĬonda allows you to have different environments installed on your computer to access different versions of Python and different libraries. Information below is adapted from materials developed by the Conda documentation for installing conda and managing conda environments. Created a earth-analytics directory on your computer.Completed the setup for Git, Bash and Conda.You should have Bash and the Miniconda distribution of Python 3.x setup on your computer and an earth-analytics working directory. Activate, update and delete conda environments.View a list of the available environments in conda.At the end of this activity, you will be able to:
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