Introduction to Generators in Python
In Python, a generator is a special type of iterator that allows us to iterate over a sequence of values without the need to store the entire sequence in memory. This is particularly useful when dealing with large datasets or streams of data where memory efficiency is crucial. Generators are defined using functions that yield items one at a time, allowing for lazy evaluation. This means that the value is produced only when requested, rather than all at once.
To understand how generators work, let’s consider a simple example. Instead of generating a list of numbers and storing them all in memory, we can create a generator that yields numbers on-the-fly. This can be achieved using the yield
statement, which pauses the function remembering its state for the next iteration.
What is ‘yield from’?
The yield from
expression is an enhanced version of the yield
statement introduced in Python 3.3. It allows one generator to delegate part of its operations to another generator. This makes it easier to organize complex generators and to write cleaner code. When using yield from
, the delegating generator will yield all values from the sub-generator, effectively simplifying the process of chaining multiple generators together.
To put it simply, yield from
provides a way to