CSC/ECE 517 Summer 2008/wiki1 2 itr: Difference between revisions

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Generators are a simple and powerful tool 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).
Generators are a simple and powerful tool 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).
====Using generator in python to count form 10 to 20 ====
====Using generator in python to count form 10 to 20 ====
def countfrom(n):
 
def countfrom(n):
     while True:
     while True:
         yield n
         yield n
         n += 1
         n += 1
for i in countfrom(10):
for i in countfrom(10):
     if i <= 20:
     if i <= 20:

Revision as of 17:54, 30 May 2008

Introduction

One of the beloved feature of Ruby is the block based Iterator. A Ruby Iterator is simply a method that loops over the contents of an object without exposing its underlying representation. The verb `iterate' means "do the same thing many times' so `iterator' means "one which does the same thing many times'. It can also be considered as an object that behaves like a generic pointer. The iterator usually reference to one particular element in the object collection and then modify itself so that it points to the next element. Generators are a similar feature in Python. The name came as it is the entity which generate iterators. It allows you to write a function that can return a result and pause, resuming in the same place the next time you call the function. The generator feature in Ruby can be implemented by adding a library class called Generator or external iterator. In python the generator is a feature and part of the language.

Problem Definition

Ruby, like Java, has iterators to facilitate doing operations on each member of a set. Python has generators as well. Describe how generators differ from iterators, and find examples of code sequences using generators that would be awkward with iterators.

Iterator

The word "iterator" means different things in different contexts and programming languages, but it's always got something to do with visiting each one of a set of objects, where "object" doesn't necessarily mean "class instance": Just take "object" to mean "some instance of some data type, somewhere". Iterators may provide additional features or behaves in a different way depending on the languages.

Implementing Iterator

Most of the OOP languages provide ways to make iterations easy, for example some languages provide class controlling iteration, etc. But Ruby allows the definition of control structures directly. In terms of ruby, such user-defined control structures are called iterators. Examples of different iterators are given below.

Using Each

a = [ 1, 2, 3 ]
a.each { |x| print x }
==>1
   2
   3

x is the local variable in which each value of a is stored. And, each is probably the simplest iterator which yield successive elements of its collection.

Using Find

a = [ 1, 2, 3, 4, 5 ]
a.find { |n| n % 2 == 0 }
==>2

The find iterator method in ruby will compare each element using some comparison operator (<, >, ==, etc.) and based on the boolean result (true or false), it will return the first matching value.

Using Collect

a = [ 1, 2, 3, 4, 5 ]
b = a.collect { |n| n + 1 }
==>[2, 3, 4, 5, 6]

Another common iterator is the collect that returns an array of elements that is taken from the corresponding collections.


Using interator to count form

a = [ 10,11,12,13,14,15,16,17,18,19,20 ]
b = a.collect { |n| n + 1 }
==>[2, 3, 4, 5, 6]


Generators

Generators are a simple and powerful tool 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).

Using generator in python to count form 10 to 20

def countfrom(n):

   while True:
       yield n
       n += 1

for i in countfrom(10):

   if i <= 20:
       print i
   else:
       break

Note that this iteration terminates normally, despite countfrom() being


Numbering

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    1. a
  2. B
    1. b

Bullets

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  • B
    • b

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