Building Python Data Applications with Blaze and Bokeh Tutorial, SciPy 2015

git clone https://github.com/chdoig/scipy2015-blaze-bokeh.git
cd scipy2015-blaze-bokeh

• Option A: Anaconda

If you don't have Anaconda installed, you can install it from here. After following the instructions, you should be ready to go. Check it with:

python check_env.py

If you already have Anaconda installed, make sure to update both conda and the dependencies to the latest versions, by running:

conda update conda
conda install bokeh=0.9
conda install blaze=0.8
conda install ipython=3.2
conda install netcdf4

• Option B: Miniconda or Conda Environments

If you want one the following:

• a lightweight alternative to Anaconda, you can install Miniconda from here.

or

• isolate this scipy tutorial dependencies from your default Anaconda by using conda environments.

Follow this commands after cloning this repository:

cd scipy2015-blaze-bokeh
conda env create

If you are running Linux or OS X run:

source activate scipy-tutorial

If you are running Windows, run:

activate scipy-tutorial

Make sure you have the right environment setup by running the following script:

python check_env.py

Also, try to run the testing notebook (0 - Test Notebook.ipynb):

ipython notebook

and run all the cells.

This tutorial will be using datasets from the following projects:

• Berkeley Earth
• Sean Lahman Baseball

For your convenience I have uploaded the datasets we are going to use directly to s3. Download the datasets before attending the tutorial from:

• https://s3.amazonaws.com/scipy-blaze-bokeh/Land_and_Ocean_LatLong1.nc ~400MB
• https://s3.amazonaws.com/scipy-blaze-bokeh/lahman2013.sqlite ~50MB

Move those datasets to the folder ~/scipy2015-blaze-bokeh/data

• Slides

• Docs:

  • Bokeh
  • Blaze
  • Odo