From Code Like a Pro by Dane Hillard
Six Questions for David Kopec, author of Classic Computer Problems in Python
By Frances Lefkowitz
David Kopec is Assistant Professor in computer science at Vermont’s Champlain College and author of two books in the Classic Problems series. If you want more, find @davekopec on Twitter.
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.