What takes 3 lines in Python, takes 10-30 on Go.
Code reviewers glazing over copy-pasted boilerplate blocks can more easily lose track of the whole, and miss an error which is obvious when the whole is expressed in 10 lines.
There is some optimal range of expressive density for comfortable use by humans. APL or K likely above that level, and Go feels below it, not as low as COBOL, but still.
Boilerplate distracts from what is actually going on. I can generally identify code smells from the shape of python code (like, blur all the text so I can't read the words, and the shape of the blocks tells me everything I need), I can't do the same in go, because there's so much more indentation and visual stuff happening, and most of it (boilerplate error handling) isn't interesting.
Have a look at Haskell which goes to great lengths to eliminate boilerplate and I think you'll experience the opposite--Haskell becomes very difficult to read precisely because the code is so dense. Similarly, take the indentation, newlines, etc out of a JavaScript file or JSON blob (minify it, more or less) and see if it's more or less readable as a result. I think you'll find that visual structure is actually important.
> I think you'll find that visual structure is actually important.
I didn't say otherwise. What I did say is that go adds visual noise that isn't present in python. (and it is noise: the proposal to add try! shows that the error handling style is noisy. It can be basically entirely removed by an automated transformation). Actual pattern matching like rust has, or even what Google C++ has with StatusOr and [1] our nonsense RETURN_IF_ERROR macros are better than what go does, and just as explicit (actually often moreso, since its more difficult to forget an error condition)
[1]: https://github.com/protocolbuffers/protobuf/blob/d0f91c863ae...
Yeah, preference distributions are hard to assess. Either of us could be wrong.
> I didn't say otherwise. What I did say is that go adds visual noise that isn't present in python. (and it is noise: the proposal to add try! shows that the error handling style is noisy. It can be basically entirely removed by an automated transformation).
I’m glad we agree that terseness is not readability and visual structure is valuable. How do we meaningfully debate whether some boilerplate is noise or useful visual structure? Why is Python’s implicit propagation of errors elegant and beautiful visual structure while Go’s explicit error handling is ugly noise? Specifically how do we know that you aren’t prejudiced by your disproportionate experience with Python (even assuming my disproportionate experience with Python and preference for Go is an outlier)? What are the criteria?
All my projects now use poetry for the full build tooling and I love it. No setup.py needed just include any settings in the standard pyproject.toml file example: https://github.com/timothycrosley/portray/blob/master/pyproj..., which can be generated with poetry's help using poetry init.
> text-editor support
I feel like Python with type hints (for all their current flaws) does give you this exactly.
> dependency management
Again I think poetry solves the problems here very nicely
> documentation generator
Personally, I like portray better than anything in the Golang world for this https://timothycrosley.github.io/portray/ I may be biased since I wrote it.
I write a lot of Python tools so I'm genuinely curious because if there were unfilled needs I would want to address them as one of my 52 projects: https://timothycrosley.com/
We have yet to try poetry in our org. I'm hesitant to stray off the well-trodden path, but it might be worth a shot. Any idea about installing packages with system dependencies? Packages like `pygraphviz` (which depends on the `graphviz` or `graphviz-devel` system library) has always given us a lot of trouble, for example.
> I feel like Python with type hints (for all their current flaws) does give you this exactly.
I've noticed that some editors try to use these hints, but they seem to have a hard time in many cases loading the modules. It's possible that the editor extensions (e.g., VS Code) are just buggy, but it's still a problem. Further, they require that all of your dependencies have annotations or type stubs.
> Personally, I like portray better than anything in the Golang world for this https://timothycrosley.github.io/portray/ I may be biased since I wrote it.
I haven't tried portray.
The killer thing about Go's documentation generation is that it uses type annotations and exposes them in the generated documentation. This is critical because 95% of the reason I'm looking at documentation (especially in Python) is because I need to know the type signatures (and often Python docs omit types, or the types are wrong or vague--e.g., "the type is 'binary'" with no indication if that means a bytestring or a BytesIO or what). This is tablestakes for documentation systems in statically typed languages, but I have yet to find a Python tool that does this well. Further, `godoc.org` also generates links to types including across packages--this is _not_ tablestakes for statically typed languages--so you just have to click the type name and it will take you to the docs for other packages. Further, there is no CI needed to build/publish your documentation; `godoc.org` just needs access to your repo on github or elsewhere (you can run your own godoc.org inside your corporate firewall). Another nice-to-have feature is that documentation is just comments; there's no formal/obscure syntax a la sphinx.
> I write a lot of Python tools so I'm genuinely curious because if there were unfilled needs I would want to address them as one of my 52 projects: https://timothycrosley.com/
Cool. I'll take a look!
Which is positive mind you, but they would be better served by adopting PyPy.
- I hate it's module system and package eco-system story. - I don't like its syntax. - I don't like its error handling. - I'd much prefer gradual typing. - I want to maintain the ability to use interactive interpreters. - I don't like the fact that instead of being community driven it is Google driven.
But, anecdotally, I see go being used as a second language to Python more than anything else and at an ever accelerating rate.
I agree, but if you for instance look at the TypeScript comparison sub-thread, you'll see that all the issues with both the syntax and implementation of the type-system are being aggressively resolved, and likely will all be so by 3.9.
> Good way to constrain the dynamism so performance could be improved
Couldn't agree more!
> environment
I find poetry a joy to use. If you want to bypass venvs all together, there's a lot of work to make that a reality, such as https://github.com/David-OConnor/pyflow.
> packaging
Python in 3.5 added complete zip app support, which has improved this dramatically from my perspective. Extended by things like shiv https://github.com/linkedin/shiv make it fairly complete.
> async/await
This is interesting to me. I prefer async/await in general, because it has become a standard across programming languages and I find it really easy to reason about. I also find channels to be too widely seen as a cure-all, when the only study so far has shown they actually led to an increase bug count. But I don't discount the value of real-parallelism, and am glad to see that Python has been pushing harder on that lately, with things like subshells that allow bypassing the GIL on a single thread.
I'm happy to hear that; hopefully the efforts really do address these issues well.
> I find poetry a joy to use. If you want to bypass venvs all together, there's a lot of work to make that a reality, such as https://github.com/David-OConnor/pyflow.
I'll have to check those out, but one inherent problem is that even if these tools really do solve my pain points, adopting them means I'm leaving my org on a relatively small island, isolated from the Python community. If these really are the holy grail, why isn't the broader Python community adopting them? Please don't take this as me looking for something wrong--whatever Python build tool I use, I'll eventually need support and there's a lot to be said for having a thriving community that has almost always run into my exact problem before.
> Python in 3.5 added complete zip app support, which has improved this dramatically from my perspective. Extended by things like shiv https://github.com/linkedin/shiv make it fairly complete.
We're currently using this via pex. It mostly works, but we still run into problems occassionally (system dependencies, for example). Figuring out how to integrate these tools into the broader build process is another problem to solve--we're using `pants` which supports pex out of the box, but we're running into lots of bugs or other problems. I'll keep an eye on shiv.
> This is interesting to me. I prefer async/await in general, because it has become a standard across programming languages and I find it really easy to reason about. I also find channels to be too widely seen as a cure-all, when the only study so far has shown they actually led to an increase bug count. But I don't discount the value of real-parallelism, and am glad to see that Python has been pushing harder on that lately, with things like subshells that allow bypassing the GIL on a single thread.
My biggest issues with async/await are
(1) every package needs an async variant (async boto, async docker, etc etc). We work around this by running them in a thread pool executor, and I think that works, but I don't know if I'm holding the GIL unnecessarily and causing performance issues (fundamentally difficult to diagnose). This is roughly the "what color is my function" problem.
(2) it's really easy to starve the event loop by calling into something that transitively makes a sync call or otherwise just does a lot of CPU-heavy work. We've run into both kinds in production and they've been really hard to troubleshoot (because the requests that time out often aren't the ones that are actually causing the problems).
(3) dynamic typing means it's super easy to forget to await things. Tests should catch this, but we find ourselves writing tests _just_ to catch this (e.g., we now write tests for entrypoints that _just_ `await lib_function(params)`; we would normally not write tests for such simple functions, but now we have to). Static typing is the right way to solve this and mypy does, but mypy has too many other issues (at the moment) for our org.
One substantial criticism of goroutines is that they're less safe than async/await because you need to make sure the code you're running is threadsafe. I appreciate this criticism, but I think it's the right tradeoff for Go's performance aspirations (another great high-performance alternative is Rust's borrow checker, but that's the wrong tradeoff for Go's developer productivity aspirations).
Only because they are so new. portray was built a few weeks ago and already has a thriving community building around it - but of course it's still a small drop of the whole ecosystem. Older tools I've built like isort, are now ingrained into the community: https://github.com/timothycrosley/isort, but that took years, even without major issues or complaints being present. It just takes people time to adopt new things.
However golang doesn't have that. So you get the danger of a dynamic language without the features that make powerful.
Very dynamic code shouldn’t be easy; the happy path should encourage clear, simple code. By encouraging people to stay on the happy path, their code is more performant, maintainable, etc and it keeps the average code quality quite high across the ecosystem.
1) Super easy. That way doing it right is trivial. 2) Impossiblely difficult so the only people who are doing it can be trusted to do it right.
To me go falls between those two. It’s real easy to say interface{} (indeed it is more difficult to make a non empty interface) but doing it in a way that is safe isn’t easy.
I don’t think expressive power is the point here. As they are both compleate languages. More it is an issue of what trade offs and comprises have been made.
These problems simply don't crop up in Go, or at least they're in a different ballpark in terms of frequency and severity. So yeah, Go lacks typesafe generics, but I'll make that tradeoff all day every day in exchange for the maintainability, performance, tooling, distribution, etc improvements that Go offers today. No contest.
C has void *, writing generic code using it is hell. Enough so that people went through a lot of trouble creating C++ and later Rust to escape it.
I'd say the type casting from interface{} to whatever you assume is in there qualifies as different.
Pretty much every single aspect of these languages is different from what I can see, the only thing they have in common is included batteries, the rest is growing popularity and consequences thereof.