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Python uses the following syntax to express list comprehensions over finite lists: S = [ 2 * x for x in range ( 100 ) if x ** 2 > 3 ] A generator expression may be used in Python versions >= 2.4 which gives lazy evaluation over its input, and can be used with generators to iterate over 'infinite' input such as the count generator function which ...
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)
Following Lisp, other high-level programming languages which feature linked lists as primitive data structures have adopted an append. To append lists, as an operator, Haskell uses ++, OCaml uses @. Other languages use the + or ++ symbols to nondestructively concatenate a string, list, or array.
the Add method, which adds a key and value and throws an exception if the key already exists in the dictionary; assigning to the indexer, which overwrites any existing value, if present; and; assigning to the backing property of the indexer, for which the indexer is syntactic sugar (not applicable to C#, see F# or VB.NET examples).
Python The use of the triple-quotes to comment-out lines of source, does not actually form a comment. [ 19 ] The enclosed text becomes a string literal, which Python usually ignores (except when it is the first statement in the body of a module, class or function; see docstring ).
The basis behind array programming and thinking is to find and exploit the properties of data where individual elements are similar or adjacent. Unlike object orientation which implicitly breaks down data to its constituent parts (or scalar quantities), array orientation looks to group data and apply a uniform handling.
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
Folds can be regarded as consistently replacing the structural components of a data structure with functions and values. Lists, for example, are built up in many functional languages from two primitives: any list is either an empty list, commonly called nil ([]), or is constructed by prefixing an element in front of another list, creating what is called a cons node ( Cons(X1,Cons(X2,Cons ...