Aditya Gupta

Integration testing in Rust involves placing test files in a dedicated tests/ directory outside your main code. These tests interact with your library or binary the way an external user would, and they are compiled as separate crates, giving you full isolation for end-to-end behaviour validation. After getting comfortable with unit testing, I needed a […]

Rust has built-in support for writing unit tests using the #[test] attribute. You can write test functions inside a special tests module, use assertion macros like assert_eq!, and run your tests with cargo test. Testing is part of the standard development flow in Rust, not an afterthought. When I started writing Rust seriously, I was

Rust provides powerful combinator methods like map, and_then, unwrap_or, and others to simplify how you work with Option and Result. These methods let you transform values, chain operations, and provide fallbacks, without writing repetitive match blocks. At first, I handled Option and Result types using match statements everywhere. That worked, but it quickly became repetitive

Rust encourages explicit error handling using custom error types. You can create your own error enums and implement the standard Error trait to integrate cleanly with Rust’s built-in error handling ecosystem. This helps produce descriptive, meaningful errors that are easy to handle and debug. When I first moved beyond using Rust’s built-in errors, I needed

Rust provides powerful built-in collections like HashSet and BTreeMap for managing unique items and sorted key-value pairs. These types are part of the std::collections module and are commonly used in real-world Rust applications where performance, uniqueness, and order matter. After learning the basic collections like Vec and HashMap, I wanted to explore more specialized tools.

The impl Trait syntax in Rust lets you simplify function signatures by saying “this returns something that implements a trait” instead of writing out complex generic types. You can use it for both return values and parameters, especially when working with iterators or closures. After writing several generic functions using <T: Trait> and where clauses,

Higher order iterator methods in Rust like map, filter, and fold let you transform, filter, and reduce sequences of values in a functional style. These methods work on any type that implements the Iterator trait, and they produce new iterators that are lazy and efficient. After learning how to use .next() and build custom iterators,

The Iterator trait in Rust defines how to loop through a sequence of values. If a type implements Iterator, you can use it with for loops, .next(), and many functional-style methods like map, filter, and fold. Every iterator has a next() method that returns one item at a time. When I started using iterators in

Closures in Rust are anonymous functions that you can assign to variables, pass as arguments, and use just like regular functions. They can capture values from their environment, which makes them powerful for callbacks, iterators, and async workflows. The first time I used a closure in Rust, it reminded me of JavaScript arrow functions, but

Lifetimes in Rust tell the compiler how long references should remain valid. They prevent dangling pointers and invalid memory access without using a garbage collector. Rust infers lifetimes in most cases, but in some function and struct signatures, you must annotate them explicitly using symbols like ‘a. When I first came across lifetime annotations in