Programming Leftovers

posted by Roy Schestowitz on Aug 29, 2023

• Mohamed Ahmed: NVK YCbCr Support - GSoC 2023 Final Report

  This is the final report of the work I did as a Google Summer of Code 2023 contributor to NVK. My work revolved around the implementation of YCbCr format support, which came in form of enabling three Vulkan extensions. Mesa is the open-source, default graphics driver stack on Linux, with implementations for graphics hardware from most vendors.

• Arthur Grillo: GSoC 2023 Final Report

  The GSoC journey is coming to a close. In just over 100 days, I gained more experience in open-source development than I could ever imagine in this period.

  Prior to GSoC, I was not used to regularly submit patches to the mailing lists. Now, I’ve sent many patches and revisions. I believe my interaction with the community will only grow. I learned so much about the tools and workflow of kernel development.

  After this experience, I’m more than certain that I want to make this a job, contributing to open-source is fun, so why not make this a living :)

• Mike Blumenkrantz: Server Down

  gitlab is down, post low-effort blogs and touch grass until it returns

• Two Erlang patterns I love

  Although there are probably a dozen patterns in Erlang that I love dearly, there are two that I consider my darlings.

  Now, these patterns are truly two sides of the same coin, but each do have their specific applications and aren’t used interchangeably.

  But first, some background.

• Building a Live Coding Audio Playground

  My initial goal at RC was to build an Audio Units (AU) extension. AU is Apple’s audio plugin system, which works with apps like Logic and GarageBand. There are other plugin systems, 1 but I use Logic when recording audio for myself and for my band, so I wanted to try extending it.

• [Old] Particle playground

  My most recent useless programing project is a particle emitter engine with an interactive playground. It involves a nice combination of mathematics and creativity that results in a visual reward. I've lost quite a bit of time by unintentionally getting sucked into tinkering with this!

  It enables you to create animated patterns from thousands of particles using a few lines of code. It works by automatically producing new particles every few frames, and you just specify the initial properties and the update behavior in JavaScript. The engine does the rest!

• Python IO Module

  In Python, the “IO” module is used to provide several functions and classes for handling and performing input/output operations on data.

• Pandas Floor

  The “numpy.floor()” function is used along with the “df.apply()” method to determine the floor value of the Pandas DataFrame and Series object.

• Python File readable() Method

  The inbuilt “file.readable()” method is utilized in Python to determine whether the particular file is readable or not by retrieving the Boolean value.

• Pandas Get_Dummies()

  In Python, the “pandas.get_dummies()” method of the “pandas” module is utilized to convert the categorical variables into dummy variables.

• Pandas Standard Deviation

  The “DataFrame.std()” method of the “pandas” module is used to compute the standard deviation of the specified DataFrame over the requested axis.

• Python Math Isclose() Method

  In Python, the “math.isclose()” method of the “math” module is used to determine whether the input values are close to each other or not.

• Python chr() Function

  The inbuilt “chr()” function in Python is utilized to determine the character of the specified valid Unicode integers point.

• Pandas Read Text File

  The “pandas.read_csv()”, “pandas.read_table()”, and “pandas.read_fwf()” methods are used to read a text file using Pandas in Python.

• Pandas From JSON

  In this tutorial, we have discussed the JSON data files— how we can read them by using the read_json() function— and the syntax of the read_json() method.

• Pandas Covariance

  In Python, the “DataFrame.cov()” method of the “Pandas” module computes/calculates the pairwise column covariance and excludes the NA/Null values.

• Python Hex() Function

  In Python, the “hex()” function is utilized for converting particular integer numbers to the hexadecimal number representation.

• Pandas Change Column Type

  The “df.astype()”, “pd.to_numeric()”, “convert_dtypes()”, and “df.infer_objects()” methods are used to change the column type of Pandas DataFrame.

• Pandas Print Column

  The “to_string()”, “Square Brackets”, “df.loc[ ]”, and “df.iloc[ ]” methods are used to print Pandas DataFrame columns in Python.

• Python File Write() Method

  The “file.write()” method in Python is utilized to write or insert the text to the specified files based on the file mode.

• Python File Tell() Method

  In Python, the “file.tell()” method is utilized to retrieve the present/current position of the file pointer or handle from the beginning of the file.

• Python Max() Function

  In Python, the “max()” function is utilized to retrieve the largest item in an iterable or between the input-specified variables.

• Pandas insert() Column

  The “DataFrame.insert()” method is utilized to add/insert the column with a default value or a different value to Pandas DataFrame.

• Python Gets thread id

  The “threading.get_ident()” method, “threading.get_native_id()” method, and “Logging” module are used to get the thread id in Python.

• Python Math Pi

  In Python, we utilized the “math.pi” constant of the “math” module to print the value of “pi” and used it for various mathematical operations.

• Pandas Convert Column to DateTime

  The “pd.to_datetime()”, “df.astype()”, and the “df.apply()” with “lambda” methods are used to convert columns to DateTime objects in Python.

• Pandas Read JSON

  The “pandas.read_json()” method of the “pandas” module is used to read the JSON file or JSON string and retrieve Pandas DataFrame.