By poor support for higher-order functions, I mean that e.g. you have to do "from functools import reduce, partial" for fold or partial function application. It's a trivial complaint, I'll give you, but it's one that's bitten me on more than one occasion (you think I'd learn!). There's also no foldr unless you implement it yourself.

I badly misspoke when I said that you could pickle comprehensions, because what I meant was that the language gives you no hint that you might be able to. Pickling

  sum([ os.stat(f).st_size for f in os.listdir(".") ])

  [ lambda n: n % 2 == 0 ]

E.g., this doesn't work:

    Dump.py:
      def isEven(n):
          return n % 2 == 0
      import pickle
      with open('pickled','w') as dumpfile:
          pickle.dump(isEven, dumpfile)

    Loader.py
      import pickle
      with open('pickled') as loadfile:
          isEven = pickled.load(loadfile)

    AttributeError: 'module' object has no attribute 'isEven'

    import marshal
    marshal.dump(isEven.func_code, file)
    #Then to load
    isEven = types.FunctionType(marshal.load(file), globals())

    import marshal
    marshal.dump((lambda n: n % 2 == 0).func_code, file)
    #Loading is the same
    isEven = types.FunctionType(marshal.load(file), globals())
    isEven(4)

Right - that's usually what I want. (I've used pickle to store tests against game assets, e.g. that a model has all of its textures checked into perforce, or that a texture for a model does not exceed 128x128, unless otherwise specified). Marshalling functions is usually a non-starter for this, since a) it's complicated to analyse the call graph before execution, and b) native functions can't be marshalled - an awful lot of code executed against this asset pipeline is thin bindings over native/Java/C# code. Maybe I have found the 1% of the Python use-cases where lambdas suck a bit and everywhere else it's fine--it would be great if my experience was exceptional and no-one else had ever had a similar problem doing something else.