• Applicative Functors – Haskell

    Applicative functors, or simply Applicatives, are a fundamental concept in Haskell that bridge the gap between Functors and Monads. Applicative functors allow us to apply functions wrapped in a context (like Maybe, List, or IO) to values that are also wrapped in a context. They add a layer of flexibility to functional programming in Haskell,…

  • Parameterized Algebraic Data Types – Haskell

    Haskell’s algebraic data types (ADTs) are fundamental to the language’s type system, providing a powerful way to define custom data structures that represent complex information. Parameterized ADTs, sometimes known as generic types, add an extra layer of flexibility by allowing these data types to work with different types as parameters. This enables Haskell developers to…

  • Polymorphism – Haskell

    Polymorphism, in programming, allows functions and data types to operate in a generalized way, enabling flexibility and reusability in code. Haskell, a purely functional language, provides powerful forms of polymorphism that enable functions to handle various types and allow developers to write concise, elegant code. This article will delve into the types of polymorphism in…

  • Exceptions – Haskell

    In Haskell, exceptions provide a way to handle errors or unexpected situations during runtime, such as file I/O failures, network errors, or division by zero. While Haskell is primarily known for its strong type system and use of Maybe and Either to handle errors explicitly, exceptions are still necessary for dealing with unforeseen errors and…

  • Bytestrings – Haskell

    In Haskell, strings are typically represented as lists of characters ([Char]). However, this representation can be inefficient, especially when working with large amounts of text or binary data. For high-performance applications that involve file handling, networking, or binary processing, ByteStrings provide a more efficient way to work with raw data and text in Haskell. This…

  • Laziness – Haskell

    Haskell is a lazy programming language, meaning it delays computations until their results are actually needed. This approach, known as lazy evaluation, allows Haskell to evaluate expressions “on demand,” which can lead to powerful optimizations, efficiency improvements, and unique ways of handling infinite data structures. However, laziness also has its own challenges, particularly when it…

  • Files & Streams – Haskell

    In Haskell, working with files and streams is an essential skill for reading and writing data. Haskell’s approach to file handling is slightly different from imperative languages, due to its focus on functional programming and immutability. To manage files and streams, Haskell provides a set of I/O functions that allow you to read, write, and…

  • Type Synonyms – Haskell

    In Haskell, type synonyms are a way to create new names for existing types, making code easier to read and understand without introducing new types or changing the underlying data structure. Type synonyms are especially useful for simplifying complex type definitions, improving code readability, and providing meaningful context for types in your code. This article…

  • Tree Structures – Haskell

    In Haskell, tree structures are a powerful way to organize hierarchical data, enabling efficient storage, retrieval, and manipulation of elements. Among tree structures, binary trees and especially binary search trees (BSTs) are widely used for their efficiency in operations like searching, inserting, and deleting data. This article will explain the basics of tree structures in…

  • Functors – Haskell

    In Haskell, functors are a key concept in the functional programming paradigm that enable you to apply a function to values inside a container-like structure without altering the structure itself. Functors provide a way to map over data structures in a consistent and generalized way. Understanding functors is crucial because they allow you to write…