Pypi has fewer than one million projects. The searchable content for each package is what? 300 bytes? That's a 200mb index. You don't even need fancy full text search, you could literally split the query by word and do a grep over a text file. No need for elasticsearch or anything fancy.
And anyway, hit rates are going to be pretty good. You're not taking arbitrary queries, the domain is pretty narrow. Half the queries are going to be for requests, pytorch, numpy, httpx, and the other usual suspects.
2. apt repositories are cryptographically signed, centrally controlled, and legally accountable.
3. apt search is understood to be approximate, distro-scoped, and slow-moving. Results change slowly and rarely break scripts. PyPI search rankings change frequently by necessity
4. Turning PyPI search into an apt-like experience would require distributing a signed, periodically refreshed global metadata corpus to every client. At PyPI’s scale, that is nontrivial in bandwidth, storage, and governance terms
5. apt search works because the repository is curated, finite, and opinionated
The install side is basically Merkle-friendly (immutable artifacts, append-only metadata, hashes, mirrors).
Search isn’t. Search results are derived, subjective, and frequently rewritten (ranking tweaks, spam/malware takedowns, popularity signals). That’s more like constantly rebasing than appending commits.
You can Merklize “what files exist”; you can’t realistically Merklize “what should rank for this query today” without freezing semantics and turning CLI search into a hard API contract.
The searchable context for a distribution on PyPI is unbounded in the general case, assuming the goal is to allow search over READMEs, distribution metadata, etc.
(Which isn’t to say I disagree with you about scale not being the main issue, just to offer some nuance. Another piece of nuance is the fact that distributions are the source of metadata but users think in terms of projects/releases.)
> assuming the goal is to allow search over READMEs, distribution metadata, etc.
Why would you build a dedicated tool for this instead of just using a search engine? If I'm looking for a specific keyword in some project's very long README I'm searching kagi, not npm.
I'd expect that the most you should be indexing is the data in the project metadata (setup.py). That could be unbounded but I can't think of a compelling reason not to truncate it beyond a reasonable length.
You would definitely use a search engine. I was just responding to a specific design constraint.
(Note PyPI can’t index metadata from a `setup.py` however, since that would involve running arbitrary code. PyPI needs to be given structured metadata, and not all distributions provide that.)
>The searchable context for a distribution on PyPI is unbounded in the general case, assuming the goal is to allow search over READMEs, distribution metadata, etc.
And anyway, hit rates are going to be pretty good. You're not taking arbitrary queries, the domain is pretty narrow. Half the queries are going to be for requests, pytorch, numpy, httpx, and the other usual suspects.