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I find that people doing these claims have seldomly really worked in large Python codebases... Personally, I find it pretty workable in Python with a big codeb

by fabioz 9y ago

I find that people doing these claims have seldomly really worked in large Python codebases... Personally, I find it pretty workable in Python with a big codebase (but you have to respect the rules like having a good test suite -- you change the time from compiling to running your test suite -- which you should have anyways)... I find that the current Python codebase I'm working on (which has 15 years and around 15k modules -- started back in Python 2.4, currently in Python 2.7 and going to 3.5) pretty good to work in -- there's a whole class of refactoring that you do on typed languages to satisfy the compiler that you don't even need to care about in the Python world (I also work on a reasonably big Java source codebase and refactorings are needed much more because of that). I must say I'm usually happier on the Python realm, although, we do use some patterns for types such as the adapter protocol quite a bit (so, you ask for a type and expect to get it regardless of needing a compiler to tell you it's correct and I remember very few cases of errors related to having a wrong type -- I definitely had much more null pointer exceptions on java than typing errors on Python) and we do have some utilities to specify an interface and check that another class implements all the needed methods (so, you can do light type checking on Python without a full static checking language and I don't really miss a compiler for doing that type checking...). I do think about things such immutability, etc, but feel like the 'we're all responsible grown ups' stance of Python easier to work with... i.e.: if I prefix something with '_' you should not access it, the compiler doesn't have to scream that it's private and I don't need to clutter my code -- you do need good/responsible developers though (I see that as an advantage).

orclev 9y ago
> I definitely had much more null pointer exceptions on java than typing errors on Python Null pointers are a type error. The fact that several nominally "statically" typed languages don't differentiate between nullable and non-nullable types is a significant source of failure in their type systems. Using a modern language that properly identifies nullable values as a distinct type from non-nullable ones goes a long way towards eliminating a whole host of problems. It will be interesting to see what things look like in 10 years or so once Rust has had time to really displace a significant portion of the C and C++ code in the wild, and hopefully Kotlin has killed off Java (and if we're really lucky Typescript has done the same more or less with Javascript).
agentultra 9y ago
I'd worked in OpenStack for 4 years and with Python in general for about 10 years. I can say from my experience it is definitely possible to maintain large codebases in Python. The type errors of the superficial variety that the OP refers to were usually caught before they made it to production (and were rare besides if you were experienced enough to avoid them). It requires discipline to maintain tests and write code in a way that avoids errors. I've been learning OCaml and Haskell for a couple of years along with formal methods using TLA+ and Lean. I used to think type theory was the accounting of maths. I still think that's at least partly true but the power it brings you as a programmer is quite powerful. I find working with Haskell or OCaml to be much more productive. Instead of stepping through a debugger or following tracebacks (a descriptive error) I get prescriptive errors as I make changes to a Haskell codebase. The propositions in the type system form a much better specification than unit tests alone. I still like Python and C for many reasons and will continue using them where appropriate. However I think Haskell/OCaml offer quite enough power that everyone should at least consider what they bring to the table.

by fabioz 9y ago

orclev 9y ago

> I definitely had much more null pointer exceptions on java than typing errors on Python Null pointers are a type error. The fact that several nominally "statically" typed languages don't differentiate between nullable and non-nullable types is a significant source of failure in their type systems. Using a modern language that properly identifies nullable values as a distinct type from non-nullable ones goes a long way towards eliminating a whole host of problems. It will be interesting to see what things look like in 10 years or so once Rust has had time to really displace a significant portion of the C and C++ code in the wild, and hopefully Kotlin has killed off Java (and if we're really lucky Typescript has done the same more or less with Javascript).

agentultra 9y ago

I'd worked in OpenStack for 4 years and with Python in general for about 10 years. I can say from my experience it is definitely possible to maintain large codebases in Python. The type errors of the superficial variety that the OP refers to were usually caught before they made it to production (and were rare besides if you were experienced enough to avoid them). It requires discipline to maintain tests and write code in a way that avoids errors. I've been learning OCaml and Haskell for a couple of years along with formal methods using TLA+ and Lean. I used to think type theory was the accounting of maths. I still think that's at least partly true but the power it brings you as a programmer is quite powerful. I find working with Haskell or OCaml to be much more productive. Instead of stepping through a debugger or following tracebacks (a descriptive error) I get prescriptive errors as I make changes to a Haskell codebase. The propositions in the type system form a much better specification than unit tests alone. I still like Python and C for many reasons and will continue using them where appropriate. However I think Haskell/OCaml offer quite enough power that everyone should at least consider what they bring to the table.