From Rust in Action by Tim Mcnamara
Our strategy for this article is to use an example that compiles, then make a minor change that triggers an error which appears to emerge without any adjustment to the program’s flow. Working through the fixes to those issues should make the concepts more complete.
From Haskell in Depth by Vitaly Bragilevsky
This article explores text processing in the functional programming style.
From Classic Computer Science Problems in Python by David Kopec
A large number of problems which computational tools solve can be broadly categorized as constraint-satisfaction problems (CSPs). CSPs are composed of variables with possible values which fall into ranges known as domains. Constraints between the variables must be satisfied in order for constraint-satisfaction problems to be solved. Those three core concepts—variables, domains, and constraints—are simple to understand, and their generality underlies the wide applicabilit
By Jean Georges Perrin
This is the third in a series of 4 articles on the topic of ingesting data from files with Spark. This section deals with ingesting a XML file.
Chapters selected by Naomi Ceder
From Math for Programmers by Paul Orland
From Get Programming with Clojure by Yehonathan Sharvit
From The Joy of Kotlin by Pierre-Yves Saumont
This article discusses retying functions in Kotlin.
From C++ Concurrency in Action, Second Edition by Anthony Williams
This article talks about how you can improve the responsiveness by separating concerns with concurrency.
From Modern Fortran by Milan Curcic
Stock price analysis and prediction has been an increasingly popular topic since the early days of high-level programming, and Fortran has been used in the bowels of many financial trading and banking systems, mainly thanks to its robustness, reliability, and efficiency. In this article, we’ll work with a dataset that is freely available, small enough to be easily downloaded, and yet large enough to demonstrate the power of Fortran arrays.