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Earth Analytics Python Conda Environment

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Welcome to the Earth Analytics Python Environment Repository! Here you will find a conda environment that can be installed on your computer using a .yaml file. You will also find a docker image that can be used to actually run the environment in a containerized environment.


  • Leah A. Wasser (@lwasser)
  • Filipe fernandes (@ocefpaf)
  • Tim Head (@betatim)
  • Chris Holdgraf (@choldgraf)
  • Max Joseph (@mbjoseph)
  • Martha Morrissey

Getting started with the Conda Environment

1. Install the Earth Lab Conda Environment on your Local Computer.

To begin, install git and conda for Python 3.x (we suggest 3.6).

Installing git:

Installing miniconda:

About Conda Environments:

Tutorial On Setup

If you want a more detailed tutorial on setting up this environment using miniconda, please visit our learning portal:

We recommend installing everything using the with conda-forge channel.

Quick Start: Setup Your Environment

The tutorial above will provide you with more detailed setup instructions. But here are the cliff notes:

To begin, install the environment using:

conda env create -f environment.yml

This will take a bit of time to run.

  • Also note that for the code above to work, you need to be in the directory where the environment.yml file lives so CD to that directory first

$ cd earth-analytics-python-env

Update Your EA Environment from the YAML File

You can update your environment at any time using:

conda env update -f environment.yml

To manage your conda environments, use the following commands:

View envs installed

conda info --envs

Activate the environment that you'd like to use

Conda 4.6 and later versions (all operating systems):

conda activate earth-analytics-python

The environment name is earth-analytics-python as defined in the environment.yml file.

Docker Build

Docker Automated build

To run a docker container you need to do the following:

  1. Install docker and make sure it is running.

  2. Build the docker image on your compute locally. Be patient - this will take a bit of time. Run the following lines to build the docker image locally:

cd earth-analytics-python-env
docker build -t earthlab/earth-analytics-python-env .
docker run -it -p 8888:8888 earthlab/earth-analytics-python-env

  1. Run the image.

To run your earth-analytics image, use the following code:

docker run --hostname localhost -it -p 8888:8888 earthlab/earth-analytics-python-env

NOTE: earthlab/earth-analytics-python-env is the name of this image as built above. To view all images on your computer, type docker images --all

One you run your image, you will be given a URL at the command line. Paste that puppy into your browser to run jupyter with the earth analytics environment installed!!

Updating the Earth Analytics Environment

If you wish to update the earth analytics environment, do the following.

  1. make a PR with changes to master
  2. An code admin will merge the PR into the master branch
  3. Check & wait till Dockerhub has built the image for the merging of the PR you can see builds in progress, here


A conda environment and docker container to support using earth and environmental data in Python.







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