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Have you tried it? Python has gained most of its popularity before type hints, and I would (wildly) guess 99% of Python programmers don't even use type checking

Have you tried it? Python has gained most of its popularity before type hints, and I would (wildly) guess 99% of Python programmers don't even use type checking at all. Static typing is completely viable and I hear those arguments mostly from those who didn't use Python for a long time. The added productivity makes up for a little more debugging while the program is running. I'd also posit that many Python codebases are somewhat less "untyped" than one might assume. Django for example does a lot in its ORM and Form classes to make sure the right stuff goes in the right slot.

smohare 5y ago
If you mean “Python programmers” to be random sysadmins that write hack code residing on a random EC2 instance then maybe you’re right. But most I get the sense you haven’t looked at many Python libs lately. The added productivity of non-typed Python is such a ridiculous myth to anyone who has to maintain significant Python code bases. Sure, it makes you more productive for one-off exercises but the moment you’re having someone else inspect your code the productivity gains vanish. This largely true of dynamic languages more generally except in niche caches (e.g., ORMs) where types are strongly implicit. I say all this as a mathematician that is used to reading papers full of symbols packed with implicit information. The code I’ve read from gung-ho dynamic typing advocates is some of the most painful drivel I’ve ever had to wade through.
- bayesian_horse 5y ago
  Python libraries aren't representative of Python code. The majority of Python programmers (not "just sysadmins" wherever that slur comes from) never publish or contribute to any libraries. I can compare Python's productivity to other languages, and it beats all of them so far. Another lesson I learned from working with statically typed languages: The quality of the code is more dependent on who writes it than on the language or even the ecosystem. But people are productive much sooner in Python than they are in C# or F#, and then we can work on the foot-gunning. Python's productivity isn't a myth. This is proven by its popularity and by successful projects across academia and industry alike.
  - tibyat 5y ago
  - grumpyprole 5y ago
    You might be more productive in Python versus anything else for the scale and complexity of the software you are involved in, but you cannot make sweeping generalisations like this. I also think you fail to understand that in many situations, static type systems actually improve productivity, especially at scale or for non-trivial domains. This is of course why Python is now trying to retrofit them. There's also the argument that one is most productive in what they know. As someone who has spent far too long with Haskell and OCaml, Python's semantics and libraries often seem surprising and counterintuitive to me.
    - bayesian_horse 5y ago
      I "fail to understand" something you actually never did or experienced, right? I know that a lot of companies are maintaining large Python codebases, and the "lack of typechecking" might be one of the biggest pain points, but the total pain is a lot less. That was always my experience and most people who say differently haven't actually used Python that ... I know that Typescript helped me over Javascript. I don't get that benefit from Mypy yet, but the "pain" just isn't as great as it was with JS. And I've seen what inexperienced programmers do when a static typecheckers try to force or encourage them to do the right thing. It's not necessarily the right thing, just a lot more complicated than it needs to be.
      - grumpyprole 5y ago
        > I "fail to understand" something you actually never did or experienced, right? No, I have worked at a variety of large institutions that have millions of lines of Python. I work with it often. The use of Python is more about it being accessible for non-developers, which is why they also teach it in schools; and the need for a standard. It is the new "Visual Basic". Again, it is not more productive in all situations.
  - rwmj 5y ago
mountainriver 5y ago
I have absolutely tried it and worked on many code bases big and small before typing happened. I've also worked on other languages and paradigms and seen what works and doesn't. In my experience its the other way around. Most people who are a fan of dynamic typing have worked in systems with types. The world is largely coming around to the view that types make more consumable and safe software
saila 5y ago
I'm not sure I'm following your comment correctly, but you seem to be implying that adding type hints in Python results in some lost productivity? If so, I would counter that adding types isn't particularly onerous and adds very little overhead to development time, and over time they'll tend to increase your productivity since you'll make less errors, IDEs can give you better hints, etc. As to the percent of Python developers who use types / type checking, it seems to me that's been changing somewhat rapidly over the past few years. It's certainly greater than 1%.
- tezzy 5y ago
  I disagree, dependencies can change causing types to change which requires you to alter hundreds of lines across multiple repos. Each new line or character is a line to maintain, there is a cost associated with that. Tests have costs but are extremely valuable, they are a no brainer to me, types are way less obvious. I have spent a lot of time maintaining python types. I have no idea how many bugs it has prevented. I am not sure it is a large number. I know there have been bugs in types, bugs in mypy and dependency changes which created work which only existed because types were in place. There have definitely been days worth of types maintain. There are the extra type imports, extra time to run tests and integration tests etc. It is not as straightforward as you might initially assume.
- bayesian_horse 5y ago
  I did not say type hints damaged productivity. There is no evidence to point either way, actually. Gradual typing is based on effort. Most people won't spend the effort. And they don't need to, most of the time, either.

smohare 5y ago

If you mean “Python programmers” to be random sysadmins that write hack code residing on a random EC2 instance then maybe you’re right. But most I get the sense you haven’t looked at many Python libs lately. The added productivity of non-typed Python is such a ridiculous myth to anyone who has to maintain significant Python code bases. Sure, it makes you more productive for one-off exercises but the moment you’re having someone else inspect your code the productivity gains vanish. This largely true of dynamic languages more generally except in niche caches (e.g., ORMs) where types are strongly implicit. I say all this as a mathematician that is used to reading papers full of symbols packed with implicit information. The code I’ve read from gung-ho dynamic typing advocates is some of the most painful drivel I’ve ever had to wade through.

bayesian_horse 5y ago
Python libraries aren't representative of Python code. The majority of Python programmers (not "just sysadmins" wherever that slur comes from) never publish or contribute to any libraries. I can compare Python's productivity to other languages, and it beats all of them so far. Another lesson I learned from working with statically typed languages: The quality of the code is more dependent on who writes it than on the language or even the ecosystem. But people are productive much sooner in Python than they are in C# or F#, and then we can work on the foot-gunning. Python's productivity isn't a myth. This is proven by its popularity and by successful projects across academia and industry alike.
- tibyat 5y ago
- grumpyprole 5y ago
  You might be more productive in Python versus anything else for the scale and complexity of the software you are involved in, but you cannot make sweeping generalisations like this. I also think you fail to understand that in many situations, static type systems actually improve productivity, especially at scale or for non-trivial domains. This is of course why Python is now trying to retrofit them. There's also the argument that one is most productive in what they know. As someone who has spent far too long with Haskell and OCaml, Python's semantics and libraries often seem surprising and counterintuitive to me.
  - bayesian_horse 5y ago
    I "fail to understand" something you actually never did or experienced, right? I know that a lot of companies are maintaining large Python codebases, and the "lack of typechecking" might be one of the biggest pain points, but the total pain is a lot less. That was always my experience and most people who say differently haven't actually used Python that ... I know that Typescript helped me over Javascript. I don't get that benefit from Mypy yet, but the "pain" just isn't as great as it was with JS. And I've seen what inexperienced programmers do when a static typecheckers try to force or encourage them to do the right thing. It's not necessarily the right thing, just a lot more complicated than it needs to be.
    - grumpyprole 5y ago
      > I "fail to understand" something you actually never did or experienced, right? No, I have worked at a variety of large institutions that have millions of lines of Python. I work with it often. The use of Python is more about it being accessible for non-developers, which is why they also teach it in schools; and the need for a standard. It is the new "Visual Basic". Again, it is not more productive in all situations.
- rwmj 5y ago

mountainriver 5y ago

I have absolutely tried it and worked on many code bases big and small before typing happened. I've also worked on other languages and paradigms and seen what works and doesn't. In my experience its the other way around. Most people who are a fan of dynamic typing have worked in systems with types. The world is largely coming around to the view that types make more consumable and safe software

saila 5y ago

I'm not sure I'm following your comment correctly, but you seem to be implying that adding type hints in Python results in some lost productivity? If so, I would counter that adding types isn't particularly onerous and adds very little overhead to development time, and over time they'll tend to increase your productivity since you'll make less errors, IDEs can give you better hints, etc. As to the percent of Python developers who use types / type checking, it seems to me that's been changing somewhat rapidly over the past few years. It's certainly greater than 1%.

tezzy 5y ago
I disagree, dependencies can change causing types to change which requires you to alter hundreds of lines across multiple repos. Each new line or character is a line to maintain, there is a cost associated with that. Tests have costs but are extremely valuable, they are a no brainer to me, types are way less obvious. I have spent a lot of time maintaining python types. I have no idea how many bugs it has prevented. I am not sure it is a large number. I know there have been bugs in types, bugs in mypy and dependency changes which created work which only existed because types were in place. There have definitely been days worth of types maintain. There are the extra type imports, extra time to run tests and integration tests etc. It is not as straightforward as you might initially assume.
bayesian_horse 5y ago
I did not say type hints damaged productivity. There is no evidence to point either way, actually. Gradual typing is based on effort. Most people won't spend the effort. And they don't need to, most of the time, either.