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Today in class, we learned that retrieving an element from a list is O(1) in Python. Why is this the case? Suppose I have a list of four items, for example:
li = ["perry", 1, 23.5, "s"]
These items have different sizes in memory. And so it is not possible to take the memory location of li[0] and add three times the size of each element to get the memory location of li[3]. So how does the interpreter know where li[3] is without having to traverse the list in order to retrieve the element?
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A Python list can also contain duplicates, and it can also contain multiple elements of different data types. This way, you can store integers, floating point numbers, positive or negatives, strings, and even boolean values in a list.
If you want to extract only duplicate elements from the original list, use collections. Counter() that returns collections. Counter (dictionary subclass) whose key is an element and whose value is its count. Since it is a subclass of a dictionary, you can retrieve keys and values with items() .
We can remove duplicate element in an array by 2 ways: using temporary array or using separate index. To remove the duplicate element from array, the array must be in sorted order. If array is not sorted, you can sort it by calling Arrays. sort(arr) method.
However, such results are unpredictable to the caller unless they know the specific implementation of Set used. For retrieving an element at a specific position, there is the function elementAt (). Call it with the integer number as an argument, and you'll receive the collection element at the given position.
Then the ArrayList.get () method is used to retrieve the element at index 3 and this is displayed. A code snippet which demonstrates this is as follows
However, in the previous article the original elements are not recovered. Only the minimum element is returned at any given point of time. In this article, the previous approach is modified so that original elements can also be retrieved during a pop () operation. Consider a variable minimum in which we store the minimum element in the stack.
The first element has the position 0, and the last one is (size - 1). elementAt () is useful for collections that do not provide indexed access, or are not statically known to provide one.
A list in Python is implemented as an array of pointers1. So, what's really happening when you create the list:
["perry", 1, 23.5, "s"]
is that you are actually creating an array of pointers like so:
[0xa3d25342, 0x635423fa, 0xff243546, 0x2545fade]
Each pointer "points" to the respective objects in memory, so that the string "perry" will be stored at address 0xa3d25342 and the number 1 will be stored at 0x635423fa, etc.
Since all pointers are the same size, the interpreter can in fact add 3 times the size of an element to the address of li[0] to get to the pointer stored at li[3].
1 Get more details from: the horse's mouth (CPython source code on GitHub).
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When you say a = [...], a is effectively a pointer to a PyObject containing an array of pointers to PyObjects.
When you ask for a[2], the interpreter first follows the pointer to the list's PyObject, then adds 2 to the address of the array inside it, then returns that pointer. The same happens if you ask for a[0] or a[9999].
Basically, all Python objects are accessed by reference instead of by value, even integer literals like 2. There are just some tricks in the pointer system to keep this all efficient. And pointers have a known size, so they can be stored conveniently in C-style arrays.
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Short answer: Python lists are arrays.
Long answer: The computer science term list usually means either a singly-linked list (as used in functional programming) or a doubly-linked list (as used in procedural programming). These data structures support O(1) insertion at either the head of the list (functionally) or at any position that does not need to be searched for (procedurally). A Python ``list'' has none of these characteristics. Instead it supports (amortized) O(1) appending at the end of the list (like a C++ std::vector or Java ArrayList). Python lists are really resizable arrays in CS terms.
The following comment from the Python documentation explains some of the performance characteristics of Python ``lists'':
It is also possible to use a list as a queue, where the first element added is the first element retrieved (“first-in, first-out”); however, lists are not efficient for this purpose. While appends and pops from the end of list are fast, doing inserts or pops from the beginning of a list is slow (because all of the other elements have to be shifted by one).
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