We generally use and recommend Miniconda Python distribution: https://docs.conda.io/en/latest/miniconda.html. But feel free to use whatever one works for you (and the course materials). We will be using Miniconda3-py37_4.8.3.
You can get this specific version here for:
Follow the prompts (the default recommendations in the installer are generally fine.) Once installed, launch an “Anaconda Prompt” from the Start Menu / Applications Folder to begin your Python adventure.
Next we need to set up an environment with all the additional packages and libraries we will be using throughout the course.
conda env create --name geopy --file=C:\Users\nbutter\Downloads\environment.yml
If you are working on a Mac or Linux machine, the following will work:
conda env create -f ~/Downloads/environment.yml
Upon successful completion the command prompt should look like this:
After the installation completes, activate the new environment with the following command:
conda activate geopy
At anytime in the future you can install additional packages or create separate environments. We will discuss this more in the course. This particular environment should have the correct balance of versions with any dependencies accounted for.
Also, setup your workspace where we will be creating files and generating data, you can do this in your prompt (or just in Windows Explorer/OSX Finder). For me I will be working in top-level folder on my Desktop called geopython
and a subdirectory called notebooks
.
cd C:\Users\nbutter\Desktop\
mkdir geopython
cd geopython
mkdir notebooks
Now you have built your environment with all the packages we need, you can launch it. We will be working mostly with Python Notebooks to run Python (as opposed to running an interpreter on the command line/prompt). Each time you restart your work you will have to follow these steps:
geopy
environment.cd C:\Users\nbutter\Desktop\geopython
conda activate geopy
jupyter notebook
This will launch the Notebook server (and may automatically launch a web-browser and take you to the page). If the Notebook does not automatically start, copy the generated link into a browser.
Download the data (280 MB inflated to 500 MB) for all the exercises from here:
https://cloudstor.aarnet.edu.au/plus/s/IfOvRpOXhJyqTT0
Extract this to a directory you can work in. Your file tree should look like something like this
.
|-- geopython
| +-- notebooks
| +-- data
| | +-- ...
We have hosted a pre-prepared environment on AWS, follow these instructions for details.
If the above options do not work for you, Google Colab can be used for an on-demand Python notebook. You will require a Google Account for this.
The data is also available on Google Drive here: https://drive.google.com/drive/folders/1b5TuOIZDhwf1UEMNQ0Jl5zDyn9dRwaRo?usp=sharing
And an example Colab notebook (linking to that data) is here: https://colab.research.google.com/drive/1Uw78l8SDyRjdeanSvnsGayFWf_AJbZL1?usp=sharing
If you are familiar with Docker you may use our Docker image with something like:
sudo docker run -it -p 8888:8888 nbutter/geopy:latest /bin/bash -c "jupyter notebook --allow-root --ip=0.0.0.0 --no-browser"
This will launch the Python notebook server in the /notebooks
folder. Access the notebook by entering the generated link in a web-browser, e.g.
http://127.0.0.1:8888/?token=9b16287ab91dc69d6b265e6c9c31a49586a35291bb20d0ab