Search results
Results from the WOW.Com Content Network
If you want to see the dependency with the length of the list n: Pure python. I tested for list length up to n=10000 and the behavior remains the same. So the integer multiplication method is the fastest with difference. Numpy. For lists with more than ~300 elements you should consider numpy. Benchmark code:
A list of lists named xss can be flattened using a nested list comprehension: flat_list = [ x for xs in xss for x in xs ] The above is equivalent to: flat_list = [] for xs in xss: for x in xs: flat_list.append(x) Here is the corresponding function: def flatten(xss): return [x for xs in xss for x in xs]
Agree with @Bogdan. This answer creates a string in which the list elements are joined together with no whitespace or comma in between. You can use ', '.join(list1) to join the elements of the list with comma and whitespace or ' '.join(to) to join with only white space –
joined_list = [item for list_ in [list_one, list_two] for item in list_] It has all the advantages of the newest approach of using Additional Unpacking Generalizations - i.e. you can concatenate an arbitrary number of different iterables (for example, lists, tuples, ranges, and generators) that way - and it's not limited to Python 3.5 or later.
set - unordered collection of unique elements. List of elements can be passed to set's constructor. So, pass list with duplicate elements, we get set with unique elements and transform it back to list then get list with unique elements. I can say nothing about performance and memory overhead, but I hope, it's not so important with small lists.
@loved.by.Jesus: Yeah, they added optimizations for Python level method calls in 3.7 that were extended to C extension method calls in 3.8 by PEP 590 that remove the overhead of creating a bound method each time you call a method, so the cost to call alist.copy() is now a dict lookup on the list type, then a relatively cheap no-arg function call that ultimately invokes the same thing as slicing.
That is a list in Python 2.x and behaves mostly like a list in Python 3.x. If you are running Python 3 and ...
Python >= 3.5 alternative: unpack into a list literal [*newdict]. New unpacking generalizations (PEP 448) were introduced with Python 3.5 allowing you to now easily do:
There are several methods to convert string numbers in a list to integers. In Python 2.x you can use the map function: >>> results = ['1', '2', '3'] >>> results = map(int, results) >>> results [1, 2, 3] Here, It returns the list of elements after applying the function. In Python 3.x you can use the same map
For 99 out of 100 use cases, making an actual list is inefficient and pointless, since range itself acts like an immutable sequence in almost every way, sometimes more efficiently to boot (e.g. containment tests for ints are O(1), vs. O(n) for lists). In Python 2, people tended to use range by default, even though xrange was almost always the ...