p-map

From a security perspective, p-map is refreshingly simple. It's essentially a controlled iteration wrapper with no external dependencies, which means zero transitive supply chain risk. The library does one thing—map over promises with concurrency control—and does it without touching network, filesystem, or any sensitive operations. This makes it nearly impossible to introduce vulnerabilities through p-map itself.

The error handling is straightforward: if any promise rejects, p-map stops spawning new work and rejects with that error. You get the first error, not aggregated errors, which is fine for most use cases but means you need your own try-catch wrapper if you want partial success handling. The stopOnError option (default true) gives you control here. No sensitive information leaks through errors—it just propagates whatever your mapper function throws.

Input validation is minimal but adequate. It'll throw TypeError on invalid concurrency values, but won't validate your iterable deeply. The concurrency limit is crucial for security—preventing resource exhaustion when processing untrusted input counts. Just remember to set appropriate limits based on your workload characteristics.

In production use across multiple projects, p-map has proven to be a reliable workhorse for controlled concurrent operations. The API is straightforward—you provide an array, a mapper function, and a concurrency limit. What makes it shine is the thoughtful error handling: by default it uses 'stopOnError: true', which immediately rejects on first failure and prevents runaway operations from consuming resources.

From a security perspective, this is one of the safest concurrency libraries I've used. It doesn't hide errors, sanitize stack traces, or introduce any dependency bloat—just pure Promise orchestration. The concurrency limiting is critical for preventing resource exhaustion attacks when processing untrusted input. I've used it successfully for rate-limited API calls, batch database operations, and file processing without any surprises.

The error propagation is particularly well-designed: when a mapper throws, you get the original error with full context, not a wrapped or sanitized version. This makes debugging straightforward while not exposing anything that wasn't already in your code.

From a security perspective, p-map is refreshingly simple - it's a pure utility function with no network calls, no filesystem access, and zero dependencies in recent versions. The attack surface is essentially nonexistent, which is exactly what you want for a concurrency control primitive. The library does one thing: map over an array with promise concurrency limits.

In practice, it's been rock-solid for rate-limiting API calls and controlling parallelism in data processing pipelines. The error handling is straightforward - if any promise rejects, p-map rejects with that error and stops processing new items (existing in-flight promises complete). The `stopOnError: false` option lets you collect all errors, which is critical for batch processing where you need to know all failures, not just the first one.

The main security consideration isn't with p-map itself but how you use it: improper concurrency limits can lead to resource exhaustion or accidental DoS of downstream services. The library makes no assumptions about backpressure or retry logic - you need to implement those yourself. Input validation is your responsibility; p-map won't sanitize the data flowing through it.