GENERATOR

1. efine a Function with yield Statements:
   Generators are defined like regular functions but use yield to return values. Each yield pauses the function, saving its state for the next call.

   python

   Copy

   Download

   def count_up_to(max):
       count = 0
       while count <= max:
           yield count
           count += 1

2. Create a Generator Object:
   Call the function to get a generator object. The function doesn’t execute immediately; it starts on the first next() call.

   python

   Copy

   Download

   gen = count_up_to(3)  # Generator object created

3. Iterate Over the Generator:
   Use next() to get values one at a time or loop with for:

   python

   Copy

   Download

   print(next(gen))  # Output: 0
   print(next(gen))  # Output: 1
   
   for num in gen:  # Continues from 2
       print(num)   # Output: 2, 3

Examples:

• Even Numbers Generator:

  python

  Copy

  Download

  def even_numbers(max_num):
      current = 0
      while current <= max_num:
          yield current
          current += 2
  
  for num in even_numbers(6):
      print(num)  # Output: 0, 2, 4, 6

• Reverse List Generator:

  python

  Copy

  Download

  def reverse_generator(lst):
      index = len(lst) - 1
      while index >= 0:
          yield lst[index]
          index -= 1
  
  for item in reverse_generator([1, 2, 3]):
      print(item)  # Output: 3, 2, 1

• Generator Expression:
  Use parentheses for concise generators:

  python

  Copy

  Download

  squares = (x**2 for x in range(5))
  print(list(squares))  # Output: [0, 1, 4, 9, 16]

Key Points:

• Memory Efficiency: Generators produce items on-the-fly, ideal for large datasets.

• State Retention: Resumes execution from the last yield.

• Use Cases: Large file processing, infinite sequences (e.g., Fibonacci), and data pipelines.

Advanced Use:

• .send(value): Send values back into a generator.

• yield from: Delegate to another generator.

Example of an Infinite Fibonacci Generator:

def fibonacci():
    a, b = 0, 1
    while True:
        yield a
        a, b = b, a + b

fib = fibonacci()
for _ in range(5):
    print(next(fib))  # Output: 0, 1, 1, 2, 3

Generators streamline handling of sequences with minimal memory usage and efficient iteration.