Generators in Python: How to Use Them Author
Posted: Thu Jan 23, 2025 3:21 am
Content: List Generators Set generators Generator expressions Generator functions Python generators are a class of functions that allow you to create and store in memory your own iterators that return the value of functions on request. Generators process data in portions, step by step, and are used when working with large amounts of information when there is a risk of memory overflow. The need to use generators may arise in the following cases: working with large files (tens of gigabytes): comparing lines of several such files, processing, searching by condition, etc.; web scraping; analysis of an endless stream of data (network traffic, stock quotes, instrument and sensor readings); mathematical calculations; refactoring (reworking) existing code.
Generators as objects (functions) should not be confused with the following constructs: list generators; set generators. Lists and sets have nothing to do with generator objects. In this case, the word "generator" is just a australia email list syntactic construction that arises when translating from English "list comprehension". Let's first look at list and set generators, so that there is no confusion later when using the generators themselves. Generators in Python: How to Use ThemGenerators in Python:
How to Use Them Receive a grant covering 50% of your tuition fees And learn a new profession online from anywhere in the world Get a grant List Generators To create a long list programmatically, a loop with an additional condition is used. The expression is enclosed in square brackets and in general will look like this: [expression for item in iterable if condition]. Let's first create a list of numbers from 1 to 30, and then select only even numbers from this range: nums = [i for i in range(1, 10)] even_nums = [i for i in range(1, 10) if n % 2 == 0] print(nums) print(even_nums) > [1, 2, 3, 4, 5, 6, 7, 8, 9] [2, 4, 6, 8] In the example, the expression is the item element itself, the numbers from 1 to 30 are the iterable set, and divisibility without remainder is the condition.
Generators as objects (functions) should not be confused with the following constructs: list generators; set generators. Lists and sets have nothing to do with generator objects. In this case, the word "generator" is just a australia email list syntactic construction that arises when translating from English "list comprehension". Let's first look at list and set generators, so that there is no confusion later when using the generators themselves. Generators in Python: How to Use ThemGenerators in Python:
How to Use Them Receive a grant covering 50% of your tuition fees And learn a new profession online from anywhere in the world Get a grant List Generators To create a long list programmatically, a loop with an additional condition is used. The expression is enclosed in square brackets and in general will look like this: [expression for item in iterable if condition]. Let's first create a list of numbers from 1 to 30, and then select only even numbers from this range: nums = [i for i in range(1, 10)] even_nums = [i for i in range(1, 10) if n % 2 == 0] print(nums) print(even_nums) > [1, 2, 3, 4, 5, 6, 7, 8, 9] [2, 4, 6, 8] In the example, the expression is the item element itself, the numbers from 1 to 30 are the iterable set, and divisibility without remainder is the condition.