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:
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