Welcome to the SciPy 2017 Cython tutorial! This blog aims to guide you through setting up your environment to make the most out of the tutorial. Let’s dive in!

End Goal

Before we begin, ensure you have the following:

• The contents of this repository.
• A CPython interpreter (Python 3).
• The Cython package (version 0.25) and other dependencies (check requirements_conda.txt).
• A working C/C++ compiler.

Note that the last requirement can pose a challenge depending on your operating system (OS). However, we will use a Docker container to streamline everything, making it uniform across platforms.

Setup Instructions

Follow these steps to get started:

1. Clone this repository and navigate into it:

git clone git@github.com:kwmsmith/scipy-2017-cython-tutorial.git
cd scipy-2017-cython-tutorial

2. If you’ve cloned earlier, update your repository:

git pull

One-stop-shop via Jupyter Docker Containers

The tutorial recommends using self-contained Docker containers from the Jupyter project. This method ensures a functional environment similar to that of the instructor’s:

• Install Docker for your OS.
• For Mac/Linux:

  .launch-container.sh

  Leave this terminal open, verifying its status:

  docker ps

  You should see “cython-tutorial” listed under the NAME column.

• For Windows:

  launch-container.bat

  This will download and run the Jupyter SciPy notebook Docker image.

If successful, you should see a URI like http://localhost:8888?token=.... Enter this in your browser to access the Jupyter notebook server.

Troubleshooting

If you encounter an error like Error: No such container: cython-tutorial, this likely means you shut down the Docker container prematurely. Simply re-launch it using .launch-container.sh and run the test script again.

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Platform-Specific Setup Instructions

For those who can’t or choose not to use Docker, follow these platform-specific instructions:

Mac-specific Setup

• Ensure you have XCode and the Mac OS command line tools installed. Verify with:

gcc --version

Linux-specific Setup

• Ensure you have GCC and its necessary headers. Verify with:

gcc --version

Windows-specific Setup

Note: These steps remain untested. Please provide feedback!

• Install Visual Studio 2017 and select the Python development workload, along with the Native development tools option.

General Setup

After you have your compiler and development tools installed (non-Docker):

• Install Miniconda:

conda install -y miniconda

• Create a new environment with:

conda create --yes -n cython-tutorial --file requirements_conda.txt

• Activate the environment:

source activate cython-tutorial

• Launch a Jupyter notebook server:

jupyter notebook

• Open the test-setup notebook and run all cells. They should all execute without any errors!

Conclusion

That’s it! You are now set up to engage with the SciPy 2017 Cython tutorial. If you run into any issues, remember to check the troubleshooting section.

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