I think you’re seeing over-allocation patterns this is a sample from the source: /* This over-allocates proportional to the list size, making room * for additional growth. The over-allocation is mild, but is * enough to give linear-time amortized behavior over a long * sequence of appends() in the presence of a poorly-performing * system … Read more
You could use a generator expression and next instead. This would be more efficient as well, since an intermediate list is not created and iteration can stop once a match has been found: actor = next(actor for actor in self.actors if actor.name==actorName) And as senderle points out, another advantage to this approach is that you … Read more
List comprehension is basically just a “syntactic sugar” for the regular for loop. In this case the reason that it performs better is because it doesn’t need to load the append attribute of the list and call it as a function at each iteration. In other words and in general, list comprehensions perform faster because … Read more
Use a function to raise StopIteration and list to catch it: >>> def end_of_loop(): … raise StopIteration … >>> even = list(end_of_loop() if n == 412 else n for n in numbers if 0 == n % 2) >>> print(even) [402, 984, 360, 408, 980, 544, 390, 984, 592, 236, 942, 386, 462, 418, 344, … Read more
Lets break it down. A simple list-comprehension: [x for x in collection] This is easy to understand if we break it into parts: [A for B in C] A is the item that will be in the resulting list B is each item in the collection C C is the collection itself. In this way, … Read more
Maybe something like this? $out=array_map(function($x) {return $x*$x;}, range(0, 9)) This will work in PHP 5.3+, in an older version you’d have to define the callback for array_map separately function sq($x) {return $x*$x;} $out=array_map(‘sq’, range(0, 9));
You could use numpy.concatenate, which as the name suggests, basically concatenates all the elements of such an input list into a single NumPy array, like so – import numpy as np out = np.concatenate(input_list).ravel() If you wish the final output to be a list, you can extend the solution, like so – out = np.concatenate(input_list).ravel().tolist() … Read more
Backticks are a deprecated alias for repr(). Don’t use them any more; the syntax was removed in Python 3.0. Using backticks seems to be faster than using repr(num) or num.__repr__() in version 2.x. I guess it’s because additional dictionary lookup is required in the global namespace (for repr), or in the object’s namespace (for __repr__), … Read more
_ is a standard placeholder name for ignored members in a for-loop and tuple assignment, e.g. [” for _ in myList] [a+d for a, _, _, d, _ in fiveTuples] BTW your list could be written without list comprehension (assuming you want to make a list of immutable members like strings, integers etc.). [”] * … Read more
You can have nested iterations in a single list comprehension: [filename for path in dirs for filename in os.listdir(path)] which is equivalent (at least functionally) to: filenames = [] for path in dirs: for filename in os.listdir(path): filenames.append(filename)