This repository contains the materials for the "Scaling your data work with Dask" tutorial at PyData Global 2020.
There are two ways in which you can set up and go through the tutorial materials. Both of which are outlined in the table below.
| Method | Setup | Description |
|---|---|---|
| Binder |  |
Run the tutorial notebooks on mybinder.org without installing anything locally. Note that due to resource limits, the tutorial notebooks will automatically use smaller datasets when running on Binder. |
| Local install | Instructions | Download the tutorial notebooks and install the necessary packages (via conda) locally. Setting things up locally can take a few minutes, so we recommend going through the installation steps prior to the tutorial. |
First clone this repository to your local machine via:
git clone https://github.com/coiled/pydata-global-dask
Alternatively, you can download a zip file of the repository at the top of the main page of the repository. If you prefer not to use git or don't have experience with it, this a good option.
If you do not already have the conda package manager installed, please follow the instructions here.
Navigate to the pydata-global-dask/ directory and create a new conda environment with the required
packages via:
cd pydata-global-dask
conda env create -f binder/environment.yml
This will create a new environment named "pydata-global-dask". Next, activate the environment:
conda activate pydata-global-dask
and install the JupyterLab extensions used in the tutorial with:
jupyter labextension install dask-labextension @jupyter-widgets/jupyterlab-manager
Finally, launch JupyterLab with:
jupyter lab