{"id":80181,"date":"2021-01-20T09:00:21","date_gmt":"2021-01-20T03:30:21","guid":{"rendered":"https:\/\/techvidvan.com\/tutorials\/?p=80181"},"modified":"2021-01-20T09:00:21","modified_gmt":"2021-01-20T03:30:21","slug":"python-generators-vs-iterators","status":"publish","type":"post","link":"https:\/\/techvidvan.com\/tutorials\/python-generators-vs-iterators\/","title":{"rendered":"Difference between Iterator and Generator in Python"},"content":{"rendered":"

In this article, we\u2019ll mainly learn about the difference between iterator and generator in Python, but of course, we need to know them separately as well.<\/p>\n

Let’s start!!!!<\/p>\n

What is Python Generators<\/h2>\n

A python generator\u2019s typical function lends coder a sequence of values to iterate on.<\/p>\n

The following is a general example of generators in python.<\/p>\n

Python Generator Example<\/strong><\/p>\n

a=(1,2,3,4,5,6,7,8,9,10,11)\nfor i in range(1,10,2):\n    print(i)\n   \n<\/pre>\n
Output:<\/strong><\/p>\n
1
\n3
\n5
\n7
\n9<\/div>\n
Creating Generators in Python<\/h3>\n
It is quite simple to create a generator in Python in runtime. If a function contains an output statement then the generator needs to work as a library. Both yield and Return will return some value from a function from a particular code.<\/p>\n
Python Generators with a Loop Example<\/strong><\/p>\n
def thisistech(string):\n    tech = len(string)\n    for k in range(tech - 1, -1, -1):\n        yield string[k]\n\nfor char in thisistech(\"whassup\"):\n    print(char)\n<\/pre>\n
Output:<\/strong><\/p>\n
p
\nu
\ns
\ns
\na
\nh
\nw<\/div>\n
Python Generator Expression<\/h3>\n
Simple python generator can be easily created by importing from the library directly.<\/p>\n
Python generator Expression Example<\/strong><\/p>\n
myfirstlist = [1, 10,9,0]\n\nlistmy = [k**2 for k in myfirstlist]\n\ngenerator = (k**2 for k in myfirstlist)\n\nprint(listmy)\nprint(generator)\n<\/pre>\n
Output:<\/strong><\/p>\n
[1, 100,81,0]<\/div>\n
Code:<\/strong><\/p>\n
mysecondlist = [1, 10]\n\np = (j**2 for j in mysecondlist)\nprint(next(p))\n<\/pre>\n
Output:<\/strong><\/p>\n
1<\/div>\n
Generator expressions can be used as function arguments in any code, as:<\/p>\n
Syntax:<\/strong><\/p>\n
>>> sum(w**2 for x in mysecondlist)\n<\/pre>\n
Advantages of Python Generators<\/h3>\n
1. Easy to Implement Anywhere<\/strong>
\nThe python generators are easy to implement in the dynamic as well as user-defined codes. They generally fetch values from libraries, which make them accessible on every python version.<\/p>\n
2. Highly Memory Efficient<\/strong>
\nA normal function to return a sequence will create the entire sequence in memory before returning the result within the runtime itself.<\/p>\n
3. Represent Infinite Stream<\/strong>
\nGenerators can represent the length of a series of infinite numbers taken at a time. And this is supported by the library function.<\/p>\n
4. Pipelining Generators in Python<\/strong>
\nMultiple generators can be used to pipeline a series of operations within the runtime itself.<\/p>\n
Advanced Generators<\/h4>\n
These generators work on the yielding property of the libraries. They are basically used in data and csv files.<\/p>\n
Python Iterators<\/h2>\n
A Python iterator typically returns us an iterator object- one value at a time. An example of an iterator in python.<\/p>\n
Example of Python iterators<\/strong><\/p>\n
>>> next(it)\n<\/pre>\n
Output:<\/strong><\/p>\n
Traceback (most recent call last)<\/div>\n
Iterables in Python<\/h3>\n
As the name suggests, the iterables are those defined objects which can iterate different values for a code.<\/p>\n
They are generally in the form of arrays.<\/p>\n
it[Symboloftheiterator] = function* () \n  yield 2;\n  yield 1;\n<\/pre>\n
Comparison Between Python Generator and Iterator<\/h2>\n\n\n\n\n\n\n\n\n\n\n\n\n
S.no\u00a0<\/b><\/td>\nParameters<\/b><\/td>\nGenerator<\/b><\/td>\nIterator<\/b><\/td>\n<\/tr>\n
1<\/b><\/td>\nImplementation\u00a0<\/b><\/td>\nImplemented using a function defined in the runtime.<\/span><\/td>\nImplemented using a class in the code.<\/span><\/td>\n<\/tr>\n
2<\/b><\/td>\nYield usage for coder<\/b><\/td>\nGenerator uses the \u2018yield\u2019 keyword<\/span><\/td>\nIterator does not use any keyword<\/span><\/td>\n<\/tr>\n
3<\/b><\/td>\nClass variable<\/b><\/td>\nGenerator does not need a class in python.<\/span><\/td>\nIterator implements its own class<\/span><\/td>\n<\/tr>\n
4<\/b><\/td>\nGlobals and locals\u00a0<\/b><\/td>\nGenerator saves the states of the local variables<\/span><\/td>\nIterator also does not uses local variable<\/span><\/td>\n<\/tr>\n
5<\/b><\/td>\nYield usage for user<\/b><\/td>\nUses the yield keyword for the output.<\/span><\/td>\nDoes not use the yield keyword anywhere in the code.<\/span><\/td>\n<\/tr>\n
6<\/b><\/td>\nEfficiency\u00a0<\/b><\/td>\nGenerators\u00a0 write fast and compact code<\/span><\/td>\n Iterator writes custom and long codes<\/span><\/td>\n<\/tr>\n
7<\/b><\/td>\nFunctions<\/b><\/td>\n Generator use python functions<\/span><\/td>\nIterator,use the iter() and next() functions<\/span><\/td>\n<\/tr>\n
8<\/b><\/td>\nStorage capacity<\/b><\/td>\nGenerator is not memory efficient<\/span><\/td>\nIterator is memory-efficient<\/span><\/td>\n<\/tr>\n
9<\/b><\/td>\nRelative working<\/b><\/td>\nUsage results in a concise code in any\u00a0 relative function.<\/span><\/td>\nUsage results in a relatively less concise code as compared in the whole python code.<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Code:<\/strong><\/p>\n
def thisisnew():\n#this defines new variable\nif i==1:\n   While i>0:\n      Yield i\n i-=1\n#this executes only when first is not satisfied\nFor i in thisistech():\n    print(i)\nFor i in thisisnew():\n    print()\n\n<\/pre>\n
Output:<\/strong><\/p>\n
error<\/div>\n
A generator function class can be identified in a python code.<\/p>\n
Code:<\/strong><\/p>\n
def thisisgen():\n    print(\"class is a generator\")\n<\/pre>\n
Output:<\/strong><\/p>\n
>>> thisisgen()
\nclass is a generator
\n>>><\/div>\n
Common Relationship Between Python Iterators and Generators<\/h3>\n
A python iterator and generator both fetch information from the predefined libraries. They help in the proper conduct of the code.<\/p>\n
Code:<\/strong><\/p>\n
def thisistech():\n    print(\"this is true\")\n<\/pre>\n
Output:<\/strong><\/p>\n
>>> thisistech()
\nthis is true
\n>>><\/div>\n
Conclusion<\/h2>\n
Having learnt Generators vs Iterators in Python, now we know that coders can easily interpret and manipulate these two, but this is only possible with practice.<\/p>\n
We also learnt how a coder can easily use generators to make code more efficient.<\/p>\n","protected":false},"excerpt":{"rendered":"
In this article, we\u2019ll mainly learn about the difference between iterator and generator in Python, but of course, we need to know them separately as well. Let’s start!!!! What is Python Generators A python...<\/p>\n","protected":false},"author":1,"featured_media":80182,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1053],"tags":[1508,3349,3350,3351,1473,3352],"class_list":["post-80181","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","tag-generators-in-python","tag-iterator-and-generator-in-python","tag-iterator-vs-generator-in-python","tag-iterator-vsgenerator-in-python","tag-iterators-in-python","tag-iterators-vs-generators"],"yoast_head":"\nDifference between Iterator and Generator in Python - TechVidvan<\/title>\n<meta name=\"description\" content=\"Learn the comparison between Iterator and Generator in Python. 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