python iterator and itertools module
Iterator In python, the iterator protocol is to implement the __iter() method and next() method of the object, where the former returns the object itself , which returns the next element of the container. Objects that implement these two methods are iterable objects. Iterators are lazy and are only generated when used, which provides benefits for processing large amounts of data, unlike writing all data to memory at once. Below I wrote an iterator myself. You can see that you can use a for loop to process the iterator you wrote. For objects that implement the iterator protocol, you can use any iterator tool similar to a for loop. However, looking at the output below, the second output is empty. Why is this? When we use a list, we can output the same object multiple times. What is the difference between this and an object that implements its own iterator protocol?
class it(object):def __init__(self, n):
self.a = 0self.n = n
def __iter__(self):
<br/>
class TestIt(object): def __init__(self, a): self.a = a def __iter__(self): return it(self.a)
Infinite iterator
1 count(), accepts two parameters, the first The first is the starting number, the second is the stride, starting from 0 by default, the usage is as follows
import itertools as it
c = it.count(10, 2)
for i in c:
if i > 20:
break
print i,
# 10 12 14 16 18 20
c = it.cycle([1, 2, 3])
i = 1
for j in c:
if i > 7:
break
print j,
i += 1
for j in it.repeat([1, 2, 3], 4):
print j
1 chain(), accepts multiple iterator objects as parameters and connects them Up chain('abc', [1, 2, 3])
2 compress(data, selectors), filter the previous parameters according to the latter parameters, both parameters need to be Iterator object
3
dropwhile(pre, iterable), the pre parameter is a function, When pre(i) is True, return this item and all following items
#4 groupby(iterable[, keyfunc]), where ##iterable is an iterable object, keyfunc is a grouping function, used to The consecutive items in iterable are grouped. If not specified, the consecutive identical items in iterable are grouped by default and an iterator of (key, sub-iterator) is returned. 5 ifilter(function or None, sequence),将 iterable 中 function(item) 为 True 的元素组成一个迭代器返回,如果 function 是 None,则返回 iterable 中所有计算为 True 的项 6 tee(iterable [,n]), <br/> <br/> 组合生成器 1 permutations(iterable[, r]),用于生成一个排列,r是生成排列的元素长度,不指定则为默认长度 <br/> <br/> 2 combinations(iterable, r), 求序列的组合,其中,r 指定生成组合的元素的长度,是必需的参数 3 combinations_with_replacement(iterable, r),生成的组合包含自身元素 更多python迭代器以及itertools模块相关文章请关注PHP中文网!tee
用于从 iterable 创建 n 个独立的迭代器,以元组的形式返回,n 的默认值是 2。 for j in it.tee('abc', 4):
print list(j)
list(it.permutations( list(it.permutations(, 2
print list(it.combinations_with_replacement('abc', 2))
# [('a', 'a'), ('a', 'b'), ('a', 'c'), ('b', 'b'), ('b', 'c'), ('c', 'c')]

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.
