Quantum Bayesian Networks

June 17, 2019

Pip Qubiter, Pip Qubiter, Hurray!

Filed under: Uncategorized — rrtucci @ 3:34 am

The purpose of this brief blog post is to announce that the Qubiter team (me and my friend Dr. Tao Yin) are finally getting serious about pip installation of Qubiter. Previously, Tao had uploaded what is, by now, a very old version (0.0.0) of Qubiter, onto the PyPi servers that provide the pip installation service. But as of today, you can pip install the latest version 1.0.1 of Qubiter. Just type

pip install qubiter --user

in your shell command line. This new version (unlike 0.0.0) has the canonical, pip compliant folder structure at its github repository


V 1.0.1 of Qubiter also includes a myriad of small improvements over the version of just a few weeks ago. Qubiter changes at a very fast pace! Last time I blogged about Qubiter improvements, I touted its new native Tensorflow backend, and its new implementation of a novel multi-threaded algorithm for computing gradients of quantum cost functions.

Since then, I have added to Qubiter two simple yet very useful tools for doing Continuous Integration (CI). Usually, for CI, what the big boys like Rigetti PyQuil, Google Cirq and IBM Qiskit do, is to write a matching pytest (or unittest) module for each app module and run all those pytest modules in batch via a service like travis. What I do for CI of Qubiter is not as industrial strength as the pytest/travis route, but it is much less onerous to the programmer and almost as effective at catching bugs.

Most Qubiter py files have a main() method at the end that tests the methods defined in that file. Qubiter also has a large library of Jupyter notebooks that put Qubiter through its paces. The new version 1.0.1 of Qubiter includes two py scripts,


The first script batch runs all the Jupyter notebooks, and the second script batch runs all those py files with a main() method at the end. These 2 py scripts together constitute a homemade tool for doing rudimentary (but pretty effective!) CI.

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