Haskell Coding Basics

When your Haskell function needs to check several conditions, guards offer a cleaner alternative to nested if-then-else. In this lecture, you will learn how to use the pipe character followed by a Boolean condition to define multiple branches in a Haskell function definition. You will write functions that use guards with the otherwise keyword as a catch-all case, and you will see how this style reads almost like a mathematical piecewise function. Guards in Haskell let you lay out your logic like a choose-your-own-adventure book — each condition is clearly visible, and the path your code takes is easy to trace at a glance.

Pattern matching is one of Haskell's superpowers, and this lecture introduces it by matching on specific values. You will learn how to define a Haskell function with multiple equations, each matching a different input value, so the function behaves differently depending on what it receives. You will write functions that pattern match on integers and characters, and you will see how the underscore wildcard _ serves as a catch-all for any value you have not explicitly handled. Pattern matching in Haskell is like a bouncer at an exclusive club — it checks each guest against the list and knows exactly what to do with everyone who shows up.

Sometimes you need to bundle two or more values together without creating a full data structure, and Haskell's tuples are perfect for this. In this lecture, you will learn how to create and deconstruct tuples in Haskell using the parentheses-and-comma syntax like (3, "hello"). You will use the built-in functions fst and snd to extract elements from pairs, and you will also pattern match on tuples directly in function definitions to pull out their components. Tuples in Haskell are like those combo meals at your favorite restaurant — a convenient package that bundles a few things together when you do not need a full custom order.

While pattern matching in function definitions is powerful, sometimes you need to match patterns in the middle of an expression, and that is where case expressions shine. In this lecture, you will learn how to write case-of expressions in Haskell to perform pattern matching anywhere within your code, not just at the top level of a function. You will see how case expressions compare to guards and if-then-else, and you will practice writing them with different patterns including wildcards and literal values. Case expressions in Haskell give you surgical precision — you can pattern match exactly where you need to without restructuring your entire function around it.

Lists are everywhere in Haskell, and this lecture teaches you how to create and examine them. You will learn how to construct lists using square bracket notation in Haskell, how to prepend elements with the cons operator :, and how to use head, tail, length, and null to inspect list contents. You will also discover that all elements in a Haskell list must share the same type, which prevents the kind of mixed-bag surprises you might encounter in dynamically typed languages. Think of a Haskell list as a train — each car carries the same kind of cargo, and you can always check the locomotive at the front or detach it to see what is behind it.

Haskell makes it wonderfully easy to generate sequences of values, and this lecture shows you how. You will learn how to use range notation like [1..10] and [2,4..20] to create lists in Haskell without manually typing every element. You will also explore essential list operations including concatenation with ++, indexing with !!, and the take and drop functions that let you slice lists into pieces. These operations in Haskell give you a toolkit for quickly assembling and reshaping data, like having a set of precision cookie cutters for any shape you need.

If you have ever used set-builder notation in math class, Haskell's list comprehensions will feel like a homecoming. In this lecture, you will learn how to generate new lists in Haskell by describing the pattern you want using the syntax [expression | variable <- list, condition]. You will write comprehensions that draw from one or more source lists, apply filters with Boolean conditions, and transform elements with expressions. List comprehensions in Haskell are one of those features that make you wonder why every language does not have them — they let you describe what you want instead of spelling out each step of how to get it.

Here is a fun secret about Haskell: a String is just a list of Char values. In this lecture, you will explore what that means in practice by applying list functions to strings in Haskell. You will use head, tail, length, reverse, and list concatenation on strings, and you will see how you can pattern match on strings the same way you pattern match on any list. You will also learn useful character functions from Data.Char like toUpper, toLower, and isAlpha that let you inspect and transform individual characters. Understanding that strings are lists in Haskell unlocks a whole world of text processing without needing any special string libraries.

Three of the most important functions in all of Haskell are map, filter, and foldl, and this lecture brings them together. You will learn how map applies a function to every element of a list in Haskell, how filter keeps only the elements that satisfy a predicate, and how foldl reduces a list down to a single value by accumulating results from left to right. You will write examples of each and see how they chain together to process data in clean, readable pipelines. These three functions in Haskell are the power trio of functional programming — once you master them, you will start seeing loops in other languages as unnecessarily verbose.

One of the most elegant techniques in Haskell is deconstructing lists with pattern matching, and this lecture shows you how it works. You will learn how to match on the empty list [] and the cons pattern (x:xs) to separate a list into its first element and everything else in Haskell. You will write recursive functions that process lists element by element using these patterns, such as computing the sum or length of a list from scratch. Pattern matching on lists in Haskell is like peeling an onion — you handle one layer at a time, and the structure tells you exactly when you have reached the core.

Not every function deserves a name, and Haskell's lambda expressions let you create throwaway functions on the fly. In this lecture, you will learn how to write anonymous functions in Haskell using the backslash syntax like \x -> x + 1 and pass them directly to higher-order functions like map and filter. You will see how lambdas in Haskell are perfect for short, one-off transformations that do not warrant a full named definition, and you will practice writing them with multiple parameters. Lambdas are like sticky notes in your code — small, quick, and exactly where you need them without cluttering up your desk with formal memos.

Every function in Haskell is automatically curried, which means applying fewer arguments than expected gives you a new function back instead of an error. In this lecture, you will explore how partial application works in Haskell by supplying one argument to a two-argument function and using the result as a specialized function. You will write examples like defining a double function as (* 2) and an addFive function as (+ 5), and you will see how this technique integrates beautifully with map and filter. Currying in Haskell is like ordering a customizable sandwich — you lock in your bread choice first, and now you have a specialized sandwich-maker that just needs the fillings.

Haskell lets you snap functions together like building blocks using the dot operator, and this lecture shows you how to wield it. You will learn how the . operator in Haskell composes two functions so that the output of one feeds directly into the input of the next, written as (f . g) x which means f(g(x)). You will practice composing multiple functions into pipelines that transform data step by step, and you will see how composition in Haskell often eliminates the need for intermediate variables. Function composition is like a Rube Goldberg machine that actually makes your code simpler — each piece does one thing, and they chain together into something elegant.

Parentheses can pile up fast in Haskell, and the $ operator is your tool for cutting through the clutter. In this lecture, you will learn how the $ operator works in Haskell as a low-precedence function application operator that lets you write putStrLn $ show $ 1 + 2 instead of putStrLn (show (1 + 2)). You will practice rewriting nested parentheses using $ and develop an intuition for when it makes your Haskell code more readable versus when explicit parentheses are clearer. Think of $ in Haskell as the semicolon of function calls — it tells the compiler to evaluate everything to its right first before feeding the result leftward.

You have used higher-order functions like map and filter, and now it is time to write your own in Haskell. In this lecture, you will learn how to define Haskell functions that accept other functions as parameters, complete with type signatures that use the arrow notation for function arguments, such as applyTwice :: (a -> a) -> a -> a. You will write utility functions that take a function and apply it in custom ways, and you will see how this pattern makes your Haskell code incredibly flexible and reusable. Writing your own higher-order functions in Haskell is like becoming the architect instead of just the tenant — you design the building that others get to live in.

Haskell lets you invent your own types, and this lecture shows you how to do it with the data keyword. You will learn how to define simple enumeration types in Haskell like data Color = Red | Green | Blue and how to create type aliases with the type keyword for readability, such as type Name = String. You will write functions that operate on your custom types and pattern match on their constructors. Defining your own types in Haskell is like creating a custom vocabulary for your program — suddenly you can name exactly what you mean, and the compiler makes sure everyone uses the words correctly.

When your Haskell types need to carry data along with them, algebraic data types with fields are the answer. In this lecture, you will learn how to define data types in Haskell where each constructor holds one or more values, like data Shape = Circle Double | Rectangle Double Double. You will write functions that pattern match on these constructors to extract their fields and compute results, such as calculating the area of each shape. Algebraic data types in Haskell are like filling out different forms at a government office — each form has its own required fields, and the system knows exactly what information to expect from each one.

Null pointer exceptions are the billion-dollar mistake of programming, and Haskell sidesteps them entirely with the Maybe type. In this lecture, you will learn how Maybe works in Haskell with its two constructors, Just and Nothing, and how to write functions that return Maybe values when a result might not exist. You will pattern match on Maybe to safely extract values, and you will see how this forces you to explicitly handle the absence case instead of letting it crash at runtime. Maybe in Haskell is like a package delivery notification — it tells you either exactly what arrived or clearly states that nothing came, so you are never left guessing.

When something goes wrong and you need to know why, Haskell's Either type gives you a way to return error information alongside your result. In this lecture, you will learn how Either works in Haskell with its Left constructor for errors and Right constructor for success values, and you will write functions that use Either String to provide descriptive error messages. You will pattern match on Either values to handle both the success and failure cases, and you will see how this approach eliminates the need for exceptions or error codes. Either in Haskell is like getting a detailed rejection letter instead of just a slammed door — at least you know what went wrong and what to try next.

Typeclasses are Haskell's elegant solution to making different types share common behavior, and this lecture introduces the most essential ones. You will learn how to derive Show, Eq, and Ord for your custom types in Haskell so they can be printed, compared for equality, and ordered. You will also explore what these typeclasses look like under the hood by writing a manual instance of Eq for a custom type, defining exactly what equality means for your data. Typeclasses in Haskell are like professional certifications — they guarantee that a type can perform certain operations, and any function that requires those capabilities can trust the certification without knowing the specific type.

When your Haskell data types have many fields, remembering their order becomes a chore, and record syntax solves this beautifully. In this lecture, you will learn how to define data types in Haskell using record syntax, which gives each field a name and automatically generates accessor functions. You will write types like data Person = Person { firstName :: String, age :: Int } and see how you can create values using named fields in any order and access them by name. Record syntax in Haskell transforms your data types from cryptic positional tuples into self-documenting structures — like switching from a phone number you have memorized to a contact list with proper names.

Once you understand how to use existing typeclasses in Haskell, the natural next step is creating your own. In this lecture, you will learn how to define a custom typeclass in Haskell using the class keyword, specifying the function signatures that any instance must implement. You will create a simple typeclass like Describable with a describe function, then write instances of it for multiple types so each one provides its own implementation. Defining your own typeclasses in Haskell is like writing the rules for a new board game — you decide what moves are required, and then each player type gets to decide exactly how they execute those moves within the rules you set.