Why Learn Algorithms with Go?

Most algorithm resources use Python, Java, or C++. So why would you learn algorithms in Go? Because Go’s design philosophy — simplicity, clarity, and minimal magic — makes it one of the best languages for understanding what your code actually does.

Go is Readable

Go was designed to be read. There’s usually one obvious way to write something, and the language actively discourages clever tricks. Compare a binary search implementation:

Python:

def binary_search(nums, target):
    lo, hi = 0, len(nums) - 1
    while lo <= hi:
        mid = (lo + hi) // 2
        if nums[mid] == target: return mid
        elif nums[mid] < target: lo = mid + 1
        else: hi = mid - 1
    return -1

Go:

func binarySearch(nums []int, target int) int {
    lo, hi := 0, len(nums)-1
    for lo <= hi {
        mid := (lo + hi) / 2
        if nums[mid] == target {
            return mid
        } else if nums[mid] < target {
            lo = mid + 1
        } else {
            hi = mid - 1
        }
    }
    return -1
}

The Go version is barely longer, and every line is explicit. No hidden behavior, no implicit type conversions, no list comprehension magic. When you’re learning algorithms, you want to focus on the algorithm, not the language features.

Explicit is Better

Go makes you write out things that other languages hide:

• Error handling is explicit — you see every error path
• There are no classes or inheritance — just structs and functions
• Memory layout is transparent — slices, maps, and pointers behave predictably
• No operator overloading — + always means addition

This explicitness is a feature when learning algorithms. You understand exactly what’s happening at each step, which makes it easier to reason about time and space complexity.

The Standard Library is Enough

For algorithm practice, you rarely need external packages. Go’s standard library gives you:

• sort — sorting with custom comparators
• container/heap — priority queue interface
• container/list — doubly linked list
• strings and strconv — string manipulation
• math — numeric operations

No need to install frameworks or manage dependencies. A single .go file with go run is all you need.

How Algos by Example is Structured

Each example on Algos by Example is a single, self-contained Go file. The format is simple:

1. Documentation on the left — explains the pattern, approach, and key insights
2. Code on the right — a complete, runnable implementation

The documentation and code are interleaved in the source file using Go comments. This means you can read the explanation alongside the exact lines it describes — no jumping between files or tabs.

Examples are organized by pattern (arrays & hashing, two pointers, sliding window, etc.) rather than by difficulty. This helps you see how the same pattern applies across different problems.

Getting Started

If you’re new to Go and algorithms, here’s a suggested path:

1. Learn basic Go syntax — variables, functions, slices, maps, loops (for is the only loop!)
2. Start with hash map problems — they’re the most common and build intuition for when O(1) lookup is useful
3. Move to two pointers and sliding window — these patterns show how a small technique can dramatically improve efficiency
4. Try trees and recursion — Go’s explicit style makes recursive solutions easy to trace

Each example is runnable — clone the repo, pick an example, read through it, then modify it. Change the input, add print statements, break things. That’s how you learn.