Generator knowledge point finishing

list comprehension

• a = [i + 1 for i in range(10)]

generator

• The mechanism of calculating while looping
• A data type that automatically implements the iterator protocol and is an iterable object.
• Implement delayed computing, execute on demand, and save memory

generator classification

• Generator function, using yield to return results and pending status
• Generator expression, the generator returns an object that produces results on demand, called with a for loop or the next() method.

yield

• A function definition contains yield , then calling this function is a generator
• return is in the generator, representing the termination of the generator, reporting a StopIteration error

• The role of yield

  • yield can return the internal data of the generator
  • Suspend the current function execution process
  • Inherit current state
  • Call the generator again to continue execution from where it left off

generator send method

• yield can receive external signals from functions

• The role of generator.send(sign)

  • Wake up the generator and continue execution
  • send a message inside the generator

generator call method

• next() call

• for loop call

  • Can get the return of yield
  • Can't get the return value of the return statement
  • To get the return, the StopIteration error must be caught, and the return value is contained in StopIteration.value

Iterable object (Iterable)

• Objects that can act directly on a for loop are collectively called iterable objects
• data set (list, tuple, dict, set, fronzset, str)
• generator generator

Iterator

• An object that can be called by the next() function and continuously returns the next value is called an iterator

• The iterator represents a data stream, which can be regarded as an ordered sequence, but the length cannot be known in advance

  • Use of next()

    • next(Iterator)
    • Iterator.__next__()

Data collections and generators

• are iterable objects (Iterable)
• A generator is an ordered stream of data that can represent an infinite stream of data
• The data set is of finite length
• can be called in a for loop
• Only generators can be called by _next()_

You can use isinstance() to determine whether an object is an Iterable object:

>>> from collections import Iterable
>>> isinstance([], Iterable)
True
>>> isinstance({}, Iterable)
True
>>> isinstance('abc', Iterable)
True
>>> isinstance((x for x in range(10)), Iterable)
True
>>> isinstance(100, Iterable)
False

You can use isinstance() to determine whether an object is an Iterator object:

>>> from collections import Iterator
>>> isinstance((x for x in range(10)), Iterator)
True
>>> isinstance([], Iterator)
False
>>> isinstance({}, Iterator)
False
>>> isinstance('abc', Iterator)
False