In Python, what is the efficiency of the in
keyword, such as in:
a = [1, 2, 3] if 4 in a: ...
Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. When analyzing the time complexity of an algorithm we may find three cases: best-case, average-case and worst-case.
C++ is the best language for not only competitive but also using to solve the algorithm and data structure problems . C++ use increases the computational level of thinking in memory , time complexity and data flow level.
The complexity for lists is:
O(n)
For sets it is:
O(1)
http://wiki.python.org/moin/TimeComplexity
It depends on the right hand operand:
The operators
in
andnot in
test for collection membership. [...] The collection membership test has traditionally been bound to sequences; an object is a member of a collection if the collection is a sequence and contains an element equal to that object. However, it make sense for many other object types to support membership tests without being a sequence. In particular, dictionaries (for keys) and sets support membership testing.
Classes can implement the special method __contains__
to override the default behavior (iterating over the sequence) and thus can provide a more (or less) efficient way to test membership than comparing every element of the container.
The membership test operators (
in
andnot in
) are normally implemented as an iteration through a sequence. However, container objects can supply the following special method with a more efficient implementation, which also does not require the object be a sequence.
Since you have a list in your example, it is iterated over and each element is compared until a match is found or the list is exhausted. The time complexity is usually O(n)
.
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