Programming Leftovers

posted by Roy Schestowitz on Aug 12, 2022

• Writing project documentation in HTML | Opensource.com

  Documentation is an important part of any technical project. Good documentation tells the end user how to run the program, how to use it, or how to compile it. For many projects, plain text documentation is the standard. After all, every system can display plain text files.

  However, plain text is limiting. Plain text files lack formatting elements like italics text, bold text, and titles. To add these elements, we can leverage HTML. HyperText Markup Language (HTML) is the markup language used in all web browsers. And with a little extra effort, you can use HTML to write project documentation that can be read by everyone.

  HTML uses a series of tags enclosed in angle brackets to control how different parts of a document should be displayed. These tags define elements in an HTML document, such as document headings, paragraphs, italics text, bold text, and other kinds of text. Almost every tag comes in a pair: an opening tag, like

  to start a paragraph, and a closing tag to end the element, such as

  to end a paragraph. When using these tags, remember this rule: if you open a tag, you need to close it. Not closing a tag properly can result in the web browser incorrectly.

• RTKit, portals, and Pipewire - Hubert Figuière

  Pipewire needs to request realtime priorities for threads. Inside Flatpak pipewire is provided by the freedesktop-sdk, and what that bug report show is that pipewire can't find the module it uses to handle realtime priorities. This was a bug in the SDK, where it was too eager in removing unused files ­ pipewire-module-rt is the new name of the module. I submitted a fix for the 22.08 release, learning how to build the SDK in the process. freedesktop-sdk 22.08, to be released later this month, should become the base of GNOME 44 (and I think the current nightly), as well as a future KDE SDK release.

• How I get students excited about math with Python and Raspberry Pi | Opensource.com

  I am teaching Python using Raspberry Pi 400 computers in a local library for the second year in a row. A couple of this year's students have not experienced success with mathematics in their school. One asked me if she needed algebra to attend our class. I told her I had failed algebra, geometry, and trigonometry in school. She was relieved. Another student rushed in the door a bit late because she was taking geometry in summer school after failing to pass the course during the school year. I shared my own story of learned helplessness and my distress at the thought of math tests. My own bad experiences impacted my high school and early college years.

  I like Python, and in particular, the turtle module, because of an experience in graduate school in the early 1990s. The exercise used Apple's logo to teach students geometry, leading to an epiphany that completely changed my attitude toward mathematics. This week's class has four eighth-grade students. Two have math backgrounds, and two have math phobias. On the first day of class in the Olean Public Library, we started with a brief explanation of the RaspberryPi 400 and how to connect each of those computers to old VGA monitors that came from storage. I gave the students a brief overview and tour of the ports, peripheral mouse, and microHDMI cable we would use. We proceeded, step by step, to assemble the parts of the Raspberry Pi 400 units and connect them to the monitors. We powered up the units, and I assisted the students as they properly configured their computers for the United States and the Eastern Time Zone. We connected to the library's wireless network and were ready to begin.

• PySpark radians() and degrees() Functions

  The radians() function in PySpark returns the radians of any given number present in a DataFrame column.

  It can be used with the select() method because the select() function is used to display the values in the PySpark DataFrame.

• PySpark desc_nulls_first() and desc_nulls_last() Functions

  If you want to sort the values in a column in the PySpark DataFrame having nulls in descending order, then you can go with the desc_nulls_first() and desc_nulls_last() functions. Before discussing these functions, we will create a sample PySpark DataFrame.

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