4 ms·

Almost none of these things are used in scientific computing though. Maybe asyncio and yield from.

• ubernostrum 11y ago
  I suspect enums have uses, as do the improved async code constructs (and there's more of that in the pipeline).
  • m_mueller 11y ago
    Yes, I do use python for scientific applications and enums are one of the things I miss - I've built around it in python 2.x by using this construct: def enum(*sequential, **named): enums = dict(zip(sequential, range(len(sequential))), **named) return type('Enum', (), enums) Init = enum("NOTHING_LOADED", "DEPENDANT_ENTRYNODE_ATTRIBUTES_LOADED", "ROUTINENODE_ATTRIBUTES_LOADED", "DECLARATION_LOADED" ) myState = Init.NOTHING_LOADED 3.x is still a non starter for me since many clusters where I want my software to work still only come with 2.6, e.g. I can't even use dictionary comprehensions. Adoption for scientific software is heavily influenced by how many external dependencies you have - requiring users without root access to compile python 3.x for their cluster home is a no-go.
    • ubernostrum 11y ago
      No offense meant, but if you're at a stage where you use a pre-2.7 version because that's what comes with the OS, then it's not really a case of "looked at 3.x and decided it didn't have anything". OS vendors who will be supporting ancient Python versions until the next decade are a blight on the entire ecosystem.
      • m_mueller 11y ago
        > it's not really a case of "looked at 3.x and decided it didn't have anything" I agree, this isn't the main reason why I'm not looking at 3.x.
  • lqdc13 11y ago
    Yup, enums I use as well, you're right. Still... like 3 trivial things that can be overlooked.