We already know that for
there are several types of data that can be directly acting on a loop:
A class is a collection of data types, such as,,, list
tuple
, and dict
set
str
so on;
One is generator
to include the generator and yield
the generator function with the band.
These objects, which can be directly applied to for
the loop, are called iterative objects: Iterable
.
You can use to isinstance()
determine whether an object is an Iterable
object:
fromCollectionsImportiterableisinstance ([],iterable) trueisinstance ('ABC haha', iterable) Trueisinstance (Set ('Hello'), iterable) trueisinstance ({1:'a', 2:'b'},iterable) trueisinstance ((I* * forIinchRange (10) , iterable) trueisinstance (range (10), iterable) trueisinstance (1234, iterable) False
The generator can not only be used for for
loops, but it can also be next()
called by the function and return the next value until the last throw StopIteration
error indicates that the next value cannot continue to be returned.
* An object that can be called by next()
a function and continually returns the next value is Iterator
called an iterator:.
You can use to isinstance()
determine whether an object is an Iterator
object:
Isinstance (Iterator)falseisinstance ({},iterator) falseisinstance ((I-in Range (+), Iterator) trueisinstance (range (ten), Iterator) False
Generators are Iterator
objects, but,, list
dict
str
Though Iterable
they are, they are not Iterator
.
Turn list
, dict
and str
wait for the Iterable
Iterator
function to be used iter()
:
Isinstance (ITER ([]), Iterator) Trueisinstance (ITER ((+)), Iterator) True
You may ask, why, list
dict
, str
etc. data types are not Iterator
?
This is because the Python Iterator
object represents a data stream, and the iterator object can be next()
called by the function and will return the next data continuously until there is no data to throw an StopIteration
error. You can think of this data stream as an ordered sequence, but we can't know the length of the sequence in advance, only by continuously using the next()
function to calculate the next data on demand, so Iterator
the calculation is lazy, and it will only be calculated when the next data needs to be returned.
Iterator
It can even represent an infinitely large stream of data, such as the whole natural number. Using list is never possible to store all natural numbers.
Summary
Any object that can be used for for
the loop is a Iterable
type;
All objects that can be used for next()
functions are Iterator
types, which represent a sequence of lazy computations;
Collection data types such as list
, dict
,, and str
so on are Iterable
not Iterator
, however, you can iter()
get an object from a function Iterator
.
The Python for
loop is essentially implemented by calling next()
functions, such as:
for
x
in
[
1
,
2
,
3
,
4
,
5
]:
pass
Equivalent:
# first Get Iterator object:it = iter ([1, 2, 3, 4, 5])# loop: while True: Try : # get the next value: x = Next (it) except stopiteration: # Exit loop break when encountering stopiteration
The above reference Alex Teacher's, the current iterator does not need to understand this concept first
Http://www.cnblogs.com/alex3714/articles/5765046.html
Python Learning-day6-iterator (iterator)