Palantir runs a distinctive interview format known as the learning round. It is not a typical coding interview where you are handed a self-contained problem and asked to write a solution from a blank editor. Instead, the interviewer teaches you a concept, a library, or an API on the spot, hands you an existing codebase, and asks you to first explain what the code does and then improve it using what you just learned.
Because the round is built around live teaching and an existing code snippet that the interviewer walks you through, there is no single fixed problem statement to reproduce here. This page describes the scenario, the specific code transformation you are asked to make, and how to prepare. It does not attempt to reproduce exact starter files or a full reference solution, so the focus below is on the shape of the task rather than a complete answer.
You are given an NPM-style single-threaded package manager and asked to convert it toward a multi-threaded one. [Source: darkinterview.com]
The interviewer sets it up carefully:
Package and Repository class definitions, and ask you to explain what each piece does.The core skill being tested is whether you can absorb an unfamiliar concept quickly, reason about existing code out loud, and then apply the new idea to make the code better. Communicating your thinking clearly and making steady, visible progress matters as much as the final code.
The package manager looks up a package by iterating over a list of repositories and requesting the package from each one over the network. The starter code resembles this: [Source: darkinterview.com]
for repo in self.repos:
try:
return self.__getPackageFuture(repo, pkg).result()
except PackageNotFound:
continue
raise PackageNotFound(pkg)
The problem is that result() blocks. Each iteration fires one network request and then waits for that request to finish before moving on to the next repository. The requests run one at a time even though they are independent.
The improvement is to let the requests run concurrently. Instead of calling result() immediately inside the loop, you kick off each request and collect the returned futures, then process them once results are ready:
packageFuture (the value returned by __getPackageFuture(repo, pkg)) to a queue or array, without calling result() yet.result() on the futures, so the function no longer waits on each repository serially before starting the next one.The exact traversal mechanics are open. One approach is a pointer advancing through the array in a while loop, checking for completed calls; other iteration strategies work too. Reading up on threads and thread pools beforehand makes this part much easier to follow when the interviewer introduces the futures API. [Source: darkinterview.com]
The second part centers on caching. The surrounding code is large, but the bug lives inside a single function.
The issue is that the code caches the packages themselves, which may be too large to hold in the cache. The fix is to cache the repositories the packages live in rather than the packages, and to correct the value stored in the hash table accordingly.