Python path: iterators and yield generators

One, iterator

For the Python list's for loop, his internal principle: to see if the next element exists, if it exists, then remove it, and if it does not, stopiteration the exception. (Python internal to exception has been handled)

one of the obvious benefits of using iterators is that you only read one piece of data from the object at a time, without causing too much memory overhead .

For example, to read the contents of a file row by line, using the ReadLines () method, we can write:

For line in open ("Test.txt"). ReadLines ():
Print Line

This can work, but not the best way. Because he was actually loading the file into memory at once and then printing it one line at a time. This method has a large memory cost when the file is large.

Using the file iterator, we can write:
For line in open ("Test.txt"): #use file iterators
Print Line

This is the simplest and fastest-running notation, and he does not read the file explicitly, but instead uses the iterator to read one row at a time.

Second, generator

Range is not a generator and xrange is a generator

ReadLines is not a generator and xreadlines is a generator

>>> print Range [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]>>> print xrange (Ten) xrange (10)

Within the generator, based on yield creation,

PS: Created for builders only when used, thus avoiding memory waste

Practice:
such as the following table: [13, 22, 6, 99, 11] Follow the rules: 13 and 22 Compare, put large values on the right side, namely: [13,22,99,11,88,44]22 and 99 Compare, place large values on the right side, i.e.: [13,22,99,11,88,44]99 and 11 comparison, put the big value on the right side, namely: [13,22,99,11,88,44]

etc...

Li = [13,22,99,11,88,44]

For M in range (Len (LI)-1):
    For n in range (m+1, Len (LI)):
        If Li[m]> Li[n]:
            temp = Li[n]
            Li[n] = Li[m]
            LI[M] = Temp
Print Li

The yield keyword is used to define the generator (Generator), and its specific function is to return a value from the function when return is used , the difference is that after yield is returned, the function can be executed from the place where the last yield returned. That is, yield returns a function, gives the caller a return value, and then "teleport" back, allowing the function to continue running until the yield statement is startled to return a new value

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Links: http://www.cnblogs.com/wupeiqi/articles/4911365.html Wu sir

Python path: iterators and yield generators