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Slice semantics potentially differ per object; new semantics can be introduced when operator overloading the indexing operator. With Python standard lists (which are dynamic arrays), every slice is a copy. Slices of NumPy arrays, by contrast, are views onto the same underlying buffer.
In other array types, a slice can be replaced by an array of different size, with subsequent elements being renumbered accordingly – as in Python's list assignment A[5:5] = [10,20,30], that inserts three new elements (10, 20, and 30) before element "A[5]".
Slice indexes may be omitted—for example, a [:] returns a copy of the entire list. Each element of a slice is a shallow copy. In Python, a distinction between expressions and statements is rigidly enforced, in contrast to languages such as Common Lisp, Scheme, or Ruby. This leads to duplicating some functionality. For example:
The following list contains syntax examples of how a range of element of an array can be accessed. In the following table: first – the index of the first element in the slice; last – the index of the last element in the slice; end – one more than the index of last element in the slice; len – the length of the slice (= end - first)
In computer science, a dynamic array, growable array, resizable array, dynamic table, mutable array, or array list is a random access, variable-size list data structure that allows elements to be added or removed. It is supplied with standard libraries in many modern mainstream programming languages.
Using this technique, when a user asks the system to copy an object, it instead merely creates a new reference that still points to the same object. As soon as a user attempts to modify the object through a particular reference, the system makes a real copy, applies the modification to that, and sets the reference to refer to the new copy.
3.4 Bit-slice trees. 3.5 Multi-way trees. 3.6 Space-partitioning trees. 3.7 Application-specific trees. 4 Hash-based structures. ... This is a list of well-known data ...
Program slicing can be used in debugging to locate source of errors more easily. Other applications of slicing include software maintenance, optimization, program analysis, and information flow control. Slicing techniques have been seeing a rapid development since the original definition by Mark Weiser. At first, slicing was only static, i.e ...