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# Generators in Python

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There are two terms when discussing generators.

For another example, here’s a Fibonacci number generator.

 ` # Simple generator for Fibonacci numbers ` ` def ` ` fib (limit): `   ` # Initialize the first two Fibonacci numbers ` ` a, b ` ` = ` ` 0 ` `, ` ` 1 ` ` `  ` # One by one inferior to the next Fibonacci number ` ` while ` ` a & lt; limit: ` ` yield ` ` a ` ` a, b ` ` = ` ` b, a ` ` + ` ` b `   ` # Create object generator ` ` x ` ` = ` ` fib (` ` 5 ` `) `   ` # Loop through the generator object using next ` ` print ` ` (x. ` ` next ` ` ()); ` ` # In Python 3 __next __ () ` ` print ` ` (x. ` ` next ` ` ()); ` ` print ` ` (x. ` ` next ` ` ()); ` ` print ` ` (x. ` ` next ` ` ()); ` ` print ` ` (x. ` ` next ` ` ()); `   ` # Loop through the generator object using for ` ` # in a loop. ` ` print ` ` (` ` "Using for in loop" ` `) ` ` for ` ` i ` ` in ` ` fib (` ` 5 ` `): ` ` print ` ` (i) `

Output:

` 0 1 1 2 3 Using for in loop 0 1 1 2 3 `

Applications: Suppose we are creating a stream of Fibonacci numbers, applying the approach generator makes it trivial; we just need to call next (x) to get the next Fibonacci number without worrying about where or when the stream of numbers ends.
A more practical type of stream handling — processing large data files such as log files. Generators provide an efficient way to do this because only portions of the file are processed at a time. We can also use Iterators for these purposes, but Generator provides a quick way (we don’t need to write __next__ and __iter__ methods here).

http://www.dabeaz.com/finalgenerator/

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