flatten = lambda x: [y for l in x for y in flatten(l)] if type(x) in [tuple, list, np.ndarray] else [x] a = [[1, 2], 5, [6], (7, 8), (9)] print(flatten(a)) [1, 2, 5, 6, 7, 8, 9] Note:1. sum(iterable, start=None): Return the sum of an iterable o...
print(f"unique_to_each: { list(unique_to_each([1, 2, 3], [3, 4, 5])) }") # sample: 抽样 samples = list(sample(range(100), 5)) print(f"sample: { list(sample(range(100), 5)) }") # consecutive_groups: 连续分组 print(f"consecutive_groups: { list(sample(range(100), 5)...
示例7: flatten_links ▲点赞 1▼ defflatten_links(self):"""Return a recursive list of dependencies (unchain if you will, but with links intact)."""returnlist(_chain.from_iterable(_chain( [[self]], (link.flatten_links()forlinkinmaybe_list(self.options.get('link'))or[]) ))) 开发者...
处理更复杂列表的flatten实现:flatten = lambda x: [y for l in x for y in flatten(l)] if type(x) in [tuple, list, np.ndarray] else [x] a = [[1, 2], 5, [6], (7, 8), (9)]print(flatten(a)) [1, 2, 5, 6, 7, 8, 9] 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. ...
): "Flatten one level of nesting" return chain.from_iterable(list_of_lists) def repeatfunc(func, times=None, *args): """Repeat calls to func with specified arguments.Example: repeatfunc(random.random) """ if times is None: return starmap...
(iterable, n):"Returns the sequence elements n times"returnchain.from_iterable(repeat(tuple(iterable), n))defdotproduct(vec1, vec2):returnsum(map(operator.mul, vec1, vec2))defflatten(listOfLists):"Flatten one level of nesting"returnchain.from_iterable(listOfLists)defrepeatfunc(func, times...
chain.from_iterable(repeat(tuple(iterable), n)) def dotproduct(vec1, vec2): return sum(map(operator.mul, vec1, vec2)) def flatten(list_of_lists): "Flatten one level of nesting" return chain.from_iterable(list_of_lists) def repeatfunc...
chain.from_iterable(repeat(tuple(iterable), n)) def dotproduct(vec1, vec2): return sum(map(operator.mul, vec1, vec2)) def flatten(list_of_lists): "Flatten one level of nesting" return chain.from_iterable(list_of_lists) def repeatfunc...
The chain() function has a class method .from_iterable() that takes a single iterable as an argument. The elements of the iterable must themselves be iterable, so the net effect is that chain.from_iterable() flattens its argument:
>>>frommore_itertoolsimportflatten>>>iterable=[(0,1), (2,3)]>>>list(flatten(iterable)) [0,1,2,3] Several new recipes are available as well: >>>frommore_itertoolsimportchunked>>>iterable=[0,1,2,3,4,5,6,7,8]>>>list(chunked(iterable,3)) [[0,1,2], [3,4,5], [6,7,8...