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However, a generator is an object with persistent state, which can repeatedly enter and leave the same scope. A generator call can then be used in place of a list, or other structure whose elements will be iterated over. Whenever the for loop in the example requires the next item, the generator is called, and yields the next item.
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.
There are subtle differences and distinctions in the use of the terms "generator" and "iterator", which vary between authors and languages. [5] In Python, a generator is an iterator constructor: a function that returns an iterator. An example of a Python generator returning an iterator for the Fibonacci numbers using Python's yield statement ...
Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance.
for item in iterable_collection: # Do something with item Python's tuple assignment, fully available in its foreach loop, also makes it trivial to iterate on (key, value) pairs in dictionaries : for key , value in some_dict . items (): # Direct iteration on a dict iterates on its keys # Do stuff
Jinja is a web template engine for the Python programming language. It was created by Armin Ronacher and is licensed under a BSD License. Jinja is similar to the Django template engine, but provides Python-like expressions while ensuring that the templates are evaluated in a sandbox. It is a text-based template language and thus can be used to ...
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Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.