Generators are useful when we want to produce a large sequence of values, but we don’t want to store all of them in memory at once.
Create Python Generator
In Python, similar to defining a normal function, we can define a generator function using the
def keyword, but instead of the
return statement we use the
def generator_name(arg): # statements yield something
yield keyword is used to produce a value from the generator.
When the generator function is called, it does not execute the function body immediately. Instead, it returns a generator object that can be iterated over to produce the values.
Example: Python Generator
Here’s an example of a generator function that produces a sequence of numbers,
def my_generator(n): # initialize counter value = 0 # loop until counter is less than n while value < n: # produce the current value of the counter yield value # increment the counter value += 1 # iterate over the generator object produced by my_generator for value in my_generator(3): # print each value produced by generator print(value)
Output0 1 2
In the above example, the
my_generator() generator function takes an integer
n as an argument and produces a sequence of numbers from 0 to
yield keyword is used to produce a value from the generator and pause the generator function’s execution until the next value is requested.
for loop iterates over the generator object produced by
my_generator(), and the print statement prints each value produced by the generator.
We can also create a generator object from the generator function by calling the function like we would any other function as,
generator = my_range(3) print(next(generator)) # 0 print(next(generator)) # 1 print(next(generator)) # 2
Python Generator Expression
In Python, a generator expression is a concise way to create a generator object.
It is similar to a list comprehension, but instead of creating a list, it creates a generator object that can be iterated over to produce the values in the generator.
Generator Expression Syntax
A generator expression has the following syntax,
(expression for item in iterable)
expression is a value that will be returned for each item in the
The generator expression creates a generator object that produces the values of
expression for each item in the
iterable, one at a time, when iterated over.
Example 2: Python Generator Expression
# create the generator object squares_generator = (i * i for i in range(5)) # iterate over the generator and print the values for i in squares_generator: print(i)
Output0 1 4 9 16
Here, we have created the generator object that will produce the squares of the numbers 0 through 4 when iterated over.
And then, to iterate over the generator and get the values, we have used the
Advantages of Generators Over Other Iterators
Generators have some advantages over other iterators in Python:
- Easy to implement and can be more memory-efficient than storing an entire sequence in memory.
- Can be used to produce an “infinite” sequence of values, by using a while True loop and yielding values indefinitely.
- They can be combined with other iterators using the itertools module to produce complex sequences of values.