How to Solve LeetCode Problems in Go

Solving LeetCode problems in Go requires mastering standard library patterns like slices for arrays, maps for hash tables, and the container package for stacks and queues. Use the sort package for sorting and strings for string manipulation, while implementing custom data structures like linked lists or trees using pointers and structs.

// Example: Two Sum using a map for O(n) lookup
func twoSum(nums []int, target int) []int {
    seen := make(map[int]int)
    for i, num := range nums {
        if j, ok := seen[target-num]; ok {
            return []int{j, i}
        }
        seen[num] = i
    }
    return nil
}

For graph problems, use adjacency lists (map[int][]int) and implement BFS/DFS with slices as queues or stacks. Practice common patterns: two pointers for sorted arrays, sliding window for subarrays, and binary search for monotonic functions. Always handle edge cases like empty inputs or nil pointers explicitly.

Go is great for LeetCode because it's fast and has built-in tools for common tasks. You use maps to store data quickly, slices to handle lists, and structs to build custom shapes like trees. Think of it like using a Swiss Army knife: you pick the right tool for the job without needing to build everything from scratch.