RU version is available. Content is displayed in original English for accuracy.
Advertisement
Advertisement
⚡ Community Insights
Discussion Sentiment
67% Positive
Analyzed from 1659 words in the discussion.
Trending Topics
#protobuf#google#implementation#python#buf#proto#don#code#implementations#standard
Discussion (40 Comments)Read Original on HackerNews
It's great to have a healthy ecosystem in the world around Protobuf. Google can't possibly fill all use cases, there's many tools and Buf makes good tooling. The Protobuf team at Google intentionally tries to enable an ecosystem around Protobuf including examples like this. Google Cloud APIs are intentionally usable with any compatible thing that can understand Protobuf encoding including this one.
Kudos to Buf for making something that I'm sure a ton of people will find useful and which takes conformance so seriously.
Just to chime in with some context about Google's own implementations here though (since that's a lot of the discussion otherwise).
Google definitely takes Protobuf seriously including for the long term: you can't really understand how engrained it is within the Google stack without seeing it for yourself. It's not just RPC layer, it's storage, logging, FFI. Html templating is driven off Protobuf messages. Systems which interact with bank XML based systems uses Protobuf schemas. Internally it's widely used for in-memory library api types even without any direct/obvious connection to serialization just because it makes internal details like logging easier. This extremely large surface does create constraints and use-cases to balance. You can see Buf's reported numbers reflect that it is faster for a usecase they expect is typical, but at scale users do fall into the other buckets shown, affecting the performance of preexisting code is a major concern for our implementations that a greenfield implementation doesn't have.
Wide exposure in critical paths alongside long term support directly causes some quirks: for example some of our APIs followed PEP8 when it was created but PEP8 changed. It looks stupid that we have wrong style APIs but also it would be stupider to break compatibility for style reasons. JavaProto as another example still supports Java8 and the runtime is compatible with 2014 gencode which is a pretty major constraint.
Google Py Proto implementation has one extra interesting choice of the same gencode is reused with 3 different implementations (upb, a complete pure python one, and one that uses C++Proto as the in memory representation which libraries like TensorFlow can use to share memory between Python and C++), which is why design the way that it is with runtime created classes, the pyi files are readable but the .py files not.
This definitely has pros and cons, and the direct approach taken by Buf here really makes a ton of sense. It's just that Google's maintained implementation falls into a different spot in a larger technical tradeoff space.
If you see things that appear to make no sense with the official implementations, feel free to file an issue on GitHub and we can look, sometimes there is no reason and we can fix it, and sometimes there's a reason which we can explain.
Kudos again to Buf here, I'm fully sure this will solve some set of real business needs better than Google's (but not because Google isn't maintaining our offerings too).
This is a valid explanation for the odd implementation of the Python protobuf library (the only convincing one I've heard). But, the last time I looked into it (just a couple of years ago), it didn't seem reasonably possible to make use of this.
I can't remember the exact issue I think maybe the C++ library would be statically linked into the Python C extension module, which made it virtually impossible to use it from your own C++ code. Or maybe the issue was just that there was no C++ version prebuilt on pypi (the default is the upb version).
Anyway, it seems a pity to go to such enormous lengths for one feature and then make it essentially unavailable.
But its kind of a clear example of a surprisingly complicated technical space. The big picture is that it's actually not weird when a simpler thing which has less constraints can be better on some axes users when compared to a complicated thing that delivers on many advanced constraints.
If "readability of the .py gencode instead of the .pyi gencode" was the worst pain point (or pet peeve) here then I actually suspect Buf wouldn't have even bothered, it's just one of these that is easy to see and explain.
Why?
Often Python, with the most critical parts written in a compiled extension module (like this one), offers acceptable performance with enormously less complexity than writing the whole thing in a compiled language.
I don't see that anywhere. I see "Fast where it counts."
So, without further ado: Protobuf isn't a standard. You can't have a non-standard implementation of something that doesn't have a standard to begin with. In reality, you have Google's implementation for C++ and then everything else. Everything else was, for the most part, not written by Google. And it doesn't always align 100% with the C++ Google's stuff.
Furthermore, C++ implementation has a lot of idiosyncrasies specific to that language that can't be translated one-to-one into other languages, or, in some cases, shouldn't be, even if they could (eg. C++ implementation is all about source code generation because generating runtime entities s.a. classes in C++ is very difficult, while in languages like Python, generating classes at runtime is easy.)
Furthermore, C++ implementation has a specific way of parsing the binary payload (lazy: only the top definitions are parsed, the inner structure of messages is parsed on-demand). But, is this how every parser should behave? What if you want a SAX-like parser?
----
In the hindsight, I just think that Protobuf is not a good format for writing reliable software that aims for decades of usage. We, as in the whole programming world, don't have good formats in general, and whenever we come to the point of having to use some, we either go with an existing popular but crooked or roll our own, probably also crooked. The standard you alluded to would've been great (perhaps a refinement of ASN with more attention to parser implementation, more concrete versions etc.?) But we aren't there yet, and there isn't even a work group to try and address the issue.
I am not a fan of Protobuf at all, but it's already demonstrated its ability to ship extremely reliable software with multi-decade lifespans. It's one of the few things Google _hasn't_ deprecated, and it's the backbone of the search and ads stack.
The important part of protobuf is the spec of the wire format. That is what makes the standard an interop format.
Personally I also prefer code generation over dynamic parsers and generators. This is not an idiosyncrasy of C++, it is just the objectively good way to handle IDLs regardless of programming language.
[1] https://protobuf.dev/programming-guides/encoding/
This is where I feel there are better alternatives. If you go with protobuf, you're picking 2 out of 3: simplicity, fast, idiomatic.
Please consider "uvx tsc-py --help" for things that don't fit.
https://pypi.org/project/tsc-py/
TFA seems to say that they’re just thin proxies over the underlying C++ APIs, which would more than do it, and does not surprise me (the re2 Python bindings are similar, not as bad since they don’t generate Python code but they’re really c++-y — in Google’s flavour too — and uncomfortable).
Here's how it looks to convert from encoded protobuf to json (protojson).
And just invert the arguments to convert back.