This is the repository for the Scipy 2017 tutorial. The tutorial will be presented as a set of Jupyter notebooks with exercises sprinkled throughout.
We strongly, strongly, strongly encourage you to use conda to install
the required packages for this tutorial. There are non-Python dependencies
required that make manual installation or installing with pip very involved.
Note also that this tutorial is written for Python 3.6. Most things will still work on Python 3.4+.
No guarantees of any kind are made that it will be compatible with Python 2.
Download the environment.yml file in the root of this repository, e.g.
wget https://raw.githubusercontent.com/gforsyth/numba_tutorial_scipy2017/master/environment.ymland then create the environment with
conda env create -f environment.ymlThis will create a conda environment named numbatutorial with all of the required packages.
You can activate the environment with
source activate numbatutorialor on Windows:
activate numbatutorialconda install jupyter ipython numpy numba line_profiler matplotlibNo hands-on work requires these, but if you want to play with some of the
examples. If you installed using either environments.yml or requirements.txt
these are already installed.
conda install cythonpip install cythonWe recommend you also install the Jupyter notebook extensions.
conda install -c conda-forge jupyter_contrib_nbextensionsOnce they are installed, start a notebook server
jupyter notebookand (assuming port 8888) navigate to http://localhost:8888/nbextensions where
you can choose which extensions to enable. One that is helpful (for us!) when
using Numba in the notebook is the Skip-Traceback extension. You're welcome to
enable whichever extensions you like (we're also fans of Codefolding and the
Comment/Uncomment Hotkey).
Once you have downloaded all of the requires libraries/packages, you can run the
check_install.py script to confirm that everything is working as expected.
Either download the file directly or clone this repository and then run
python check_install.py