Welcome to the Earth Analytics Environment Repository! Here you will find a conda envt 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
- Tim Head
- Chris Holdgraf
- Max Joseph
- Martha Morrissey
To begin, install git and conda for Python 3.x (we suggest 3.6).
Installing git: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git
Installing conda: https://www.anaconda.com/
We recommend installing geo-related dependencies with conda-forge
. We
have created a custom yaml list with all of the dependencies that you will
need to run the lessons in this course. Follow
these steps below to get your environment ready.
About Conda Environments: https://conda.io/docs/user-guide/tasks/manage-environments.html
An environment for conda has been created specifically for this course. To load it, run:
conda env create -f environment.yml
- Note that it takes a bit of time to run this setup
- Also note that for the code above to work, you need to be in the directory where the
environment.yml
file lives (ex: cd earth-analytics-python-env).
To update this environment from a yaml file use:
conda env update -f environment.yml
To manage your conda environments, use the following commands:
conda info --envs
On Mac or Linux:
source activate earth-analytics-python
On Windows:
activate earth-analytics-python
The environment name is earth-analytics-python
as
defined in the environment.yml
file.
To run a docker container you need to do the following:
-
Install docker and make sure it is running.
-
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
- 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!!
If you wish to update the earth analytics environment, do the following.
- make a PR with changes to master
- think about your changes - don't do silly things or break things :)
- merge the PR into the master branch
- Check & wait till Dockerhub has built the image for the merging of the PR you can see builds in progress, here
- Finally, once the build is complete you can then you can update hub-ops repo with the newly tagged image.
If the update the earthpy
package, you must specify the commit number that you
wish to build earthpy
against. This will ensure that the docker image
automagically rebuilds using the latest version of earthpy
like this: - git+https://github.com/earthlab/earthpy.git@283683affac9e46b1690c7913ebd2621c82ba43a
This PR should kick off a rebuild of the docker image. But that docker image will not be usable until it's built off of the master branch.
NOTE 2: The DockerHub build actually takes forever and ever. So it's best to check out the build status rather than assuming it's built.