It’s true because for every element in the list, all 0 of them, they all are equal to 2. You can think of all being implemented as: def all(my_list, condition): for a in my_list: if not condition(a): return False return True Whereas any is: def any(my_list, condition): for a in my_list: if condition(a): return True … Read more
You are never calling your squares function, so it is not doing anything. List comprehensions are in fact faster: >>> import timeit >>> def squares(values): … lst = [] … for x in range(values): … lst.append(x*x) … return lst … >>> def squares_comp(values): … return [x*x for x in range(values)] … >>> timeit.timeit(‘f(10)’, ‘from __main__ … Read more
Consider: [leaf for branch in tree for leaf in branch] It unrolls like: for branch in tree: for leaf in branch: yield leaf If we write it the other way [leaf for leaf in branch for branch in tree] It might make more sense in plain English on some level, but a possible counter-argument is … Read more
You have many options to achieve that. With a list comprehension you can do: my_list = [i for i in my_list if i >= 0] With filter(): my_list = filter(lambda i: i >= 0, my_list) Note: In Python 3, filter() returns a filter object (not list), to convert it to a list, you can do: … Read more
As Ken said, it can’t, but with 2.6’s multiprocessing module, it’s pretty easy to parallelize computations. import multiprocessing try: cpus = multiprocessing.cpu_count() except NotImplementedError: cpus = 2 # arbitrary default def square(n): return n * n pool = multiprocessing.Pool(processes=cpus) print(pool.map(square, range(1000))) There are also examples in the documentation that show how to do this using … Read more
Just use max with a generator expression: >>> lst = [[1, 2, 3], [2, 4, 2], [0, 1, 1]] >>> max(l[2] for l in lst) 3 Also, don’t name your variables list, you are shadowing the type.
This is a generator expression. To get it to work in the standalone case, use braces: y = (x for x in range(10)) and y becomes a generator. You can iterate over generators, so it works where an iterable is expected, such as the sum function. Usage examples and pitfalls: >>> y = (x for … Read more
List comprehensions (in fact, Monad comprehensions) can be desugared into do notation. do i <- [1..4] j <- [i+1..4] return (i,j) Which can be desugared as usual: [1..4] >>= \i -> [i+1..4] >>= \j -> return (i,j) It is well known that a >>= \x -> return b is the same as fmap (\x -> … Read more
a = next(i for i in userInput if i in wordsTask) To break it down somewhat: [i for i in userInput if i in wordsTask] Will produce a list. What you want is the first item in the list. One way to do this is with the next function: next([i for i in userInput if … Read more
Some quick timing runs seem to give the 2nd option using range() a slight edge over enumerate(): timeit a = [f(n) for n, _ in enumerate(mlist)] 10000 loops, best of 3: 118 us per loop timeit a = [f(n) for n in range(len(mlist))] 10000 loops, best of 3: 102 us per loop and just for … Read more