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For example, one could define a dictionary having a string "toast" mapped to the integer 42 or vice versa. The keys in a dictionary must be of an immutable Python type, such as an integer or a string, because under the hood they are implemented via a hash function. This makes for much faster lookup times, but requires keys not change.
In computer science, a for-loop or for loop is a control flow statement for specifying iteration. Specifically, a for-loop functions by running a section of code repeatedly until a certain condition has been satisfied. For-loops have two parts: a header and a body. The header defines the iteration and the body is the code executed once per ...
(loop for item in list do instructions) or (loop for item across vector do instructions) or (dolist (item list) instructions) or (mapc function list) or (map type function sequence) Scheme (do (notcondition) instructions) or (let loop (if condition (begin instructions (loop)))) (let loop (instructions (if condition (loop))))
Specifically, the for loop will call a value's into_iter() method, which returns an iterator that in turn yields the elements to the loop. The for loop (or indeed, any method that consumes the iterator), proceeds until the next() method returns a None value (iterations yielding elements return a Some(T) value, where T is the element type).
In computer programming, foreach loop (or for-each loop) is a control flow statement for traversing items in a collection. foreach is usually used in place of a standard for loop statement.
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
List comprehensions vs. for-loops; Conditional expressions vs. if blocks; The eval() vs. exec() built-in functions (in Python 2, exec is a statement); the former is for expressions, the latter is for statements
In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.