Python advanced topic - comprehension, iterator and generator

In this blog, I am going to talk about some advanced technology in Python. Why they are called acvanced is because they are not very common in other programming languages.

comprehension:

comprehension is an efficient way to build up tuple, list or dict.If we want to get the even number between 1 and 10, we may get by a traditional programming way.

evens = []

for index in xrange(2,10,2):

       evens.append(index)

here is the list comprehension:

evens = [ i for in range(10) if i %2 == 2]

you may use comprehension to build a dictionary like this:

mydict = { i : "number %d" %i for i in xrange(10)}

the advantage of using comprehension:

• for human readable
• more compact and faster than an explicit for loop building a list/dict. Will generate all element first then assign to list/tuple/dict

iterator:

iterator is a way to visit the (set, string, list, tuple) from the first element to the last element

it is the only way to traverse the set.

There are two ways to build an iterator

Using iter(iterable) or iterable.__iter__() to generate an iterator.

Iterator has a lazy evaluation feature, so it can be very efficient when traverse an big or even infinative set

any class implemented __iter__() function, it can be used as iteralbe for iterator

The iterator can be traversed by next function, and it will raise StopIteration exception

The common code is like

try:

       while True:

              element = myiter.next()

              #do something here

except StopIteration:

       pass

generator:

Generators are a simple and powerful funciton for creating iterators. They are written like regular functions but use the yield statement whenever they want to return data. Each time next() is called, the generator resumes where it left-off (it remembers all the data values and which statement was last executed).

For example, the fibonacci funciton can be a generator

def fibonacci():

       a,b = 0, 1

       while True:

              yield b

              a , b = b , a+b

fib = fibonacci()

fib.next()

fib.next()

fib.next()

when we need a function whose return value will be used in a list or in a loop, generator should be considerd.