github.com/samber/lo

Using lo daily in production services has been mostly positive. The generic-based API is clean and the functions do exactly what they promise. Filter, Map, Reduce, and GroupBy cover 90% of common collection operations without ceremony. The library has zero external dependencies which keeps your vendor tree lean, and the implementation is straightforward - you can read the source when behavior isn't obvious.

The performance story is nuanced. Simple operations like Contains or Keys are fast with minimal allocations. However, chaining multiple operations (Filter then Map then Uniq) creates intermediate slice copies each time, which shows up in heap profiles under load. For hot paths processing large slices, you'll want to write custom loops. The library also lacks any retry logic, timeouts, or error wrapping - it's purely functional transformations, so error handling remains your responsibility.

In practice, lo shines for readability in business logic where performance isn't critical. API handlers, config processing, and response transformations benefit greatly. For high-throughput data pipelines or request-critical paths, measure first - the convenience sometimes costs more allocations than manual iteration.

lo is a pure utility library providing lodash-style functional helpers for Go. From a security perspective, it's refreshingly low-risk: no network calls, no file I/O, no dependencies beyond the standard library. The package manipulates data structures in memory, which limits attack surface significantly.

The library follows secure-by-default principles through its immutability patterns - functions like Map, Filter, and Uniq return new slices rather than mutating input. This prevents entire classes of bugs where shared state causes unintended side effects. Error handling is explicit where needed (like in ForEach error variants), though most functions panic on nil dereferences which requires defensive coding.

From a supply chain perspective, the zero-dependency approach is ideal. No transitive CVE risk to manage. The code is straightforward to audit - it's essentially safe transformations on built-in types. Input validation is your responsibility as these are low-level primitives, but there's no parsing or deserialization that could introduce injection vulnerabilities. The biggest gotcha is accidentally using these in hot paths without considering allocations, but that's a performance concern rather than security.

Lo provides a clean functional programming toolkit for Go that genuinely simplifies slice/map operations in production code. The API is intuitive—Map, Filter, Reduce, GroupBy work exactly as you'd expect. Performance is reasonable for most use cases since it's just syntactic sugar over standard loops, but be aware that every operation allocates new collections. Chain multiple operations and you'll see heap pressure.

In practice, the zero-config nature is both strength and limitation. Functions like Chunk, Uniq, and Keys eliminate boilerplate, but there's no way to tune behavior—no capacity hints, no in-place operations, no context cancellation for long-running transforms. Error handling follows Go conventions (return tuples with errors), which is fine but means you can't short-circuit chains elegantly.

Observability is non-existent—no hooks for tracing or metrics. For high-throughput pipelines processing thousands of items per second, profile carefully. For typical CRUD operations and business logic, it's a productivity win that doesn't introduce mysterious runtime costs.