Complete Upgrade Guide to Linux Mint 21 (Vanessa) from 20.3

A complete tutorial on how to upgrade to Linux Mint 21 (Vanessa) from Linux Mint 20.3 with the graphical method.

Red Hat Leftovers

• SSH from RHEL 9 to RHEL 5 or RHEL 6 | Richard WM Jones

  RHEL 9 no longer lets you ssh to RHEL ≤ 6 hosts out of the box. You can weaken security of the whole system but there’s no easy way to set security policy per remote host.

• IT leadership: You gotta have H.E.A.R.T.

  Humility, Empathy, Adaptability, Resilience, and Transparency: H.E.A.R.T.

• Artificial Intelligence: 3 ways the pandemic accelerated its adoption

  The need for organizations to quickly create new business models and marketing channels has accelerated AI adoption throughout the past couple of years. This is especially true in healthcare, where data analytics accelerated the development of COVID-19 vaccines. In consumer-packaged goods, Harvard Business Review reported that Frito-Lay created an e-commerce platform, Snacks.com, in just 30 days.

• How open organizations can harness energy disruptions

  Many people talk a lot about the values of Open Organization Principles, but in many ways, they require people to change how they do things, which can be difficult. That is true for businesses and industries as well. Disruption in many sectors is coming. How do we use Open Principles to address them? This article looks at what's happening in industries related to energy and transportation when it comes to drastic costing changes that will lead to industrial disruption. Business disruption is happening through new technology or methods, which will slash costs. This is forcing industrial change. Consider the oil, coal, natural gas, nuclear, petroleum, biofuels, and charcoal (the primary energy in many developing countries) industries. All these industries are grouped in the fossil fuel-burning energy-generating industry. Imagine them all becoming obsolete and totally replaced by the solar and wind industries in the next decade or so because of costs. That is industrial disruption.

• OpenTelemetry: A Quarkus Superheroes demo of observability

  Are you building microservices? Do you struggle with observability and with capturing telemetry data between distributed services? This article shows how to quickly and easily introduce OpenTelemetry into a distributed system built on Java with Quarkus. This combination allows you to visualize the interactions between all the microservices within an overall system. The article introduces the official Quarkus sample application, Quarkus Superheroes, deploys it on the free Developer Sandbox for Red Hat OpenShift, and demonstrates how to collect and visualize telemetry data in order to observe microservices' behavior.

today's leftovers

• Package bumps and extra b43 firmware

  Getting ready to build the next 64-bit release of EasyOS, have been working on a few things and not documenting. So, had better report some of it...

• Dirk Eddelbuettel: RcppCCTZ 0.2.11 on CRAN: Updates

  A new release 0.2.11 of RcppCCTZ is now on CRAN. RcppCCTZ uses Rcpp to bring CCTZ to R. CCTZ is a C++ library for translating between absolute and civil times using the rules of a time zone. In fact, it is two libraries. One for dealing with civil time: human-readable dates and times, and one for converting between between absolute and civil times via time zones. And while CCTZ is made by Google(rs), it is not an official Google product. The RcppCCTZ page has a few usage examples and details. This package was the first CRAN package to use CCTZ; by now four others packages include its sources too. Not ideal, but beyond our control.

• Aurélien Jarno - GNU libc 2.34 in unstable

  The GNU libc version 2.34 has just been accepted into unstable. Getting it ready has been more challenging than other versions, as this version integrates a few libraries (libpthread, libdl, libutil, libanl) into libc.

• Power10 Entry Machines: The Power S1024 And Power L1024 [Ed: Missing disclosure: IBM pays for all of these puff pieces]

• Thoroughly Modern: Latest IT Trends – Bring Security, Speed, And Consistency To IT With Automation

• Big Blue Unveils New Scalable VTL For IBM i

• IBM i PTF Guide, Volume 24, Number 32

• As I See It: Thank God It’s Thursday

Python Programming

• How to Install Plotly Dash in Python

  In this guide, we'll show you how to install Plotly Dash on your Linux system. You must have Python installed on your system Dash.

• How to use Python to Calculate Percentage

  In this guide, We will learn how to use the Python IDLE shell to figure out percentages. You can use any IDE you want because the logic doesn't change.

• Python requirements.txt File

  “We need to employ a lot of modules while creating Python apps for various functionalities. The number of modules a given application uses can be considerable. Generally, it is advised to create a virtual environment tailored to the project when developing such massive programs, as well as smaller ones, because doing so enables us to install anything we want and of any version without overburdening the available package space. The script and dependencies must be installed on the user’s computers for them to utilize the developer. Because the dependencies are set up in a virtual environment, it would be useless to share the entire virtual environment because the folder size would be enormous, and there would be a risk of integrity problems. When this occurs, programmers include a requirements.txt file in the project that contains a list of all the dependencies that have been installed in the virtual environment as well as information on the version that is being utilized. To utilize the program, the borrower or end-user merely needs to set up a virtual environment and install any necessary components. This post will explain how to create the requirements.txt file and install dependencies using it.”

• Python Argparse Examples

  “The interpretation of command line arguments has been made by the use of the Python module argparse. By providing user input elements to be processed, argparse would be used to give customization and reuse of the program in place of explicitly specifying variables within the function.”

• Plotly.graph_objects.choroplethmapbox

  According to the aggregated statistics, a choropleth map is a statistical map comprised of colored polygons. It is mainly applied in geographical areas, such as countries, states, counties, and postal codes. When working with statistical analysis, you often encounter scenarios where you must plot a choropleth map. Therefore, this article will discuss how you can create a choropleth Mapbox using Plotly’s graph_objects.

• Dplotly.graph_objects.choropleth

  A choropleth map, or Choropleth for short, is a map made up of colored polygons that describe data. This tutorial will cover how to create a choropleth map using go.Choropleth.