Tux Machines

Programming Leftovers

Posted by Roy Schestowitz on Nov 23, 2022

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Pipenv and S2i: A better way to manage Python dependencies in containers | Red Hat Developer

=> ↺ Pipenv and S2i: A better way to manage Python dependencies in containers | Red Hat Developer

Managing the many libraries and packages used by an application is complex and has some hidden risks. The difficulties increase when you want to run an application in a container, because you need to manage a development environment when creating a different set of libraries and packages for the containerized application. This article discusses some of the common problems Python developers face when containerizing Python applications, and how Pipenv and Source-to-Image (S2I) can help to resolve those problems. We will build a simple Python application on the Red Hat OpenShift container platform using those tools.

Python vs. Bash? Why not both with Python’s subprocess module | Enable Sysadmin

=> ↺ Python vs. Bash? Why not both with Python’s subprocess module | Enable Sysadmin

Python's subprocess module easily integrates Bash into your Python scripts.

Thinking inside the box

=> ↺ Thinking inside the box

A new package made it to CRAN today: spdl. It provides a very simple interface to spdlog with the key focus being that provides the same interface from both R and C++. I had brought spdlog to R a little while ago via RcppSpdlog, but its use was generally limited to C++ code where we would write something like (taken from one of the examples included in the package)...

Build A Map-rich Apps with React and React Simple Maps

=> ↺ Build A Map-rich Apps with React and React Simple Maps

React Simple Maps is a free open-source React Library that allows developer to add interactive colorful SVG maps in their applications.

How I developed a faster Ruby interpreter | Red Hat Developer

=> ↺ How I developed a faster Ruby interpreter | Red Hat Developer

In this article, I will describe my efforts to implement a faster interpreter for CRuby, the Ruby language interpreter, using a dynamically specialized internal representation (IR). I believe this article will interest developers trying to improve the interpreter performance of dynamic programming languages (e.g., CPython developers).

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