4 ms·

Easy of prototyping would be one thing

• cm2187 10y ago
  If the syntax is about the same, how is that easier?
  • sourceless 10y ago
    The syntax doesn't make too much difference. With a dynamic or duck type system, though, you can avoid a lot of writing out interfaces or making class hierarchies. You end up with something less structurally uniform, but with a much shorter time to get results. If you care about type mismatches, use a statically typed language. If you just want to get something working, use a dynamically typed one.
  • danudey 10y ago
    Well, there are a few responses to that. First, there aren't really any compiled languages where the syntax is similar in ease of use to Python (or any other popular dynamic language I'm familiar with). All the compiled languages with which I'm familiar require a significant amount more work to accomplish the same thing; C apps are full of boilerplate to detect error cases, allocate memory, check buffer lengths, etc.; dynamic languages handle this for you so the total amount of code tends to be lower. Writing a simple program to test an algorithm or proof of concept is generally significantly less code, the code/test/debug loop tends to be significantly shorter, and you can often get to a solution significantly quicker while avoiding the typical bugs that come with lower-level languages. Python also has a pretty substantial standard library which is easy to learn and use and very consistent, meaning much less copypasta code or external dependencies. On top of that, a great deal of use-cases for languages like Python aren't CPU-bound, but rather I/O bound (disk or network). In cases where your app is CPU-dependent, it can often be trivial to replace that inner loop with optimized native code written in C or other languages, while still keeping the rest of your application easy to read and maintain. Lastly, for complex algorithmic work, there's a lot of packages which implement standard data structures and algorithms in native code and provide usable, idiomatic interfaces in Python, which means that for a lot of things you can work in native code with the ease of Python, at a minuscule performance hit but a dramatic increase in programming efficiency.
    • cm2187 10y ago
      The thing is I can understand if we are comparing C and Python, but if you compare C# or modern VB.net to Python, I am not so sure the syntax is much heavier. Now if you are not doing something that requires performance, I think there is still a good case for static typing: advanced tooling. Dynamic language limit a lot the ability of the IDE to help you finding bug, making the language and the API self discoverable, auto completing the code, providing advanced analysis (who calls what) or refactoring (rename a property). Some people do not need that, but to those who rely on that, dynamic languages must really be easier to write by an order of magnitude to end up being faster to prototype. If I was suggesting a language to a beginner, I would push for a language with a strong IDE.