Chapter 4. Connecting NumPy with the Rest of the World

In this chapter, we will cover:

  • Using the buffer protocol
  • Using the array interface
  • Exchanging data with MATLAB and Octave
  • Installing RPy2
  • Interfacing with R
  • Installing JPype
  • Sending a NumPy array to JPype
  • Installing Google App Engine
  • Deploying NumPy code in the Google cloud
  • Running NumPy code in a Python Anywhere web console
  • Setting up PiCloud

Introduction

This chapter is about interoperability . We have to keep reminding ourselves that NumPy is not alone in the scientific (Python) software ecosystem. Working together with SciPy and Matplotlib is pretty easy. Protocols exist for interoperability with other Python packages. Outside of the Python ecosystem languages such as Java, R, C, and FORTRAN are pretty popular. We will go into the details of exchanging data with these environments.

Also, we will discuss how to get our NumPy code in the cloud. This is a continuously evolving technology, in a fast-moving space. Many options are available to you, of which Google App Engine, PiCloud, and Python Anywhere will be covered.

Note

The danger here is to seem subjective, so please be assured that the author is in no way affiliated with any of these companies.

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