Python

Learn to create back-end and front-end applications using plain Kubernetes instead of OpenShift. The Developer Sandbox lets you gain hands-on skills.

Take a closer look at the practice of using editable dependencies, and the issues --editable can introduce for data scientists using Project Thoth.

Explore the challenges of installing and managing Python dependencies in containerized environments and the benefits of micropipenv in maintaining lock files.

Get an overview of Red Hat OpenShift Data Science and discover the benefits of the new managed cloud service for developing your machine learning projects.

Learn how Project Thoth uses Kafka and Argo workflows to create an event-driven infrastructure for optimized Python software stacks.

Use SystemTap (stap), the Dyninst instrumentation framework, and Python to write instrumentation for a live running kernel or a user space application.

Red Hat's Performance & Scale team shares the process and results of performance testing Apicurio Registry under various storage configurations.

Use the Thoth Jupyterlab extension to manage Python dependencies in your JupyterLab notebooks and ensure that your code and experiments are reproducible.

Use Red Hat Ansible Tower to create a dynamic inventory. You'll start with an inventory script, then transform the script into a versatile plugin.

Combine the machine learning logic you developed in Part 1 with a human-readable knowledge context. The end result is an "AI-augmented" decision model.

Learn how to use Red Hat Decision Manager to create your own machine learning model that blends the domains of knowledge enginering and machine learning.

Explore the updates in the odo 2.0 CLI, which now integrates with Kubernetes, defaults to devfile deployments, and lets you deploy Operators.

Tackle security vulnerabilities in your open source code with the latest CodeReady Dependency Analytics and its Snyk Intel Vulnerability DB integration.

Explore the range of Kubernetes 1.18-based technology updates that improve the operational and development experience when using OpenShift 4.5.

Improve Python 3.8's run speed by 30% in RHEL 8.2 by compiling with GCC's -fno-semantic-interposition flag.

Explore the Red Hat Enterprise Linux (RHEL) 7 language and runtime updates available in Red Hat Software Collections 3.5 and Red Hat Developer Toolset 9.1.

Learn how to use Nagios passive checks and OpenShift's Watchdog alert to make sure that alerting is still working in your cluster.

Write a Python-based application binary interface (ABI) checker to ensure backward compatibility between shared libraries in Linux systems

Support for Python 2 ends January 1, 2020; make plans to move to Python 3 now.

The Red Hat Dependency Analytics IDE plugin is now available; we explain the new capabilities of this release.

Guidance for creating ABI compatible Python wheels for RHEL and the new manylinux2014 standard

You can use Red Hat Enterprise Linux 8 Universal Base Images and application streams to develop in containers even if you are still running RHEL 7

How to configure a Python application running within Red Hat OpenShift to communicate with the OpenShift cluster via the openshift-restclient-python.

The Raspberry Pi is a popular, powerful, low-cost Linux machine that can do amazing things. This article shows you how to build a photo booth with one.