search
HomeBackend DevelopmentPython TutorialMust-see Python tips for beginners
Must-see Python tips for beginnersMar 17, 2017 pm 03:51 PM
python skills

The following are some Python practical tips and tools that I have collected in recent years. I hope they can be helpful to you.

ExchangeVariables

x = 6
y = 5
x, y = y, x
print x
>>> 5
print y
>>> 6

if Statement in line

print "Hello" if True else "World"
>>> Hello

Connection

The last one below This method is very cool when binding two objects of different types.

nfc = ["Packers", "49ers"]
afc = ["Ravens", "Patriots"]
print nfc + afc
>>> ['Packers', '49ers', 'Ravens', 'Patriots']
 
print str(1) + " world"
>>> 1 world
 
print `1` + " world"
>>> 1 world
 
print 1, "world"
>>> 1 world
print nfc, 1
>>> ['Packers', '49ers'] 1

Number skills

#除后向下取整
print 5.0//2
>>> 2
# 2的5次方
print 2**5
>> 32

Pay attention to the division of floating point numbers

print .3/.1
>>> 2.9999999999999996
print .3//.1
>>> 2.0

Numerical comparison

This is one of the few languages ​​I have seen that is so awesome Simple method

x = 2
if 3 > x > 1:
   print x
>>> 2
if 1  0:
   print x
>>> 2

Iterate two lists simultaneously

nfc = ["Packers", "49ers"]
afc = ["Ravens", "Patriots"]
for teama, teamb in zip(nfc, afc):
     print teama + " vs. " + teamb
>>> Packers vs. Ravens
>>> 49ers vs. Patriots

Indexed list iteration

teams = ["Packers", "49ers", "Ravens", "Patriots"]
for index, team in enumerate(teams):
    print index, team
>>> 0 Packers
>>> 1 49ers
>>> 2 Ravens
>>> 3 Patriots

List comprehension

Given a list, we can The method of brushing to select an even number list:

numbers = [1,2,3,4,5,6]
even = []
for number in numbers:
    if number%2 == 0:
        even.append(number)

changes to the following:

numbers = [1,2,3,4,5,6]
even = [number for number in numbers if number%2 == 0]

Isn’t it awesome, haha.

Dictionary comprehension

Similar to list comprehension, a dictionary can do the same job:

teams = ["Packers", "49ers", "Ravens", "Patriots"]
print {key: value for value, key in enumerate(teams)}
>>> {'49ers': 1, 'Ravens': 2, 'Patriots': 3, 'Packers': 0}

Initialize the value of the list

items = [0]*3
print items
>>> [0,0,0]

Convert the list to String

teams = ["Packers", "49ers", "Ravens", "Patriots"]
print ", ".join(teams)
>>> 'Packers, 49ers, Ravens, Patriots'

Get elements from dictionary

I admit that the try/except code is not elegant, but here is a simple method, try to find the key in the dictionary, if not found The corresponding alue will be set to its variable value using the second parameter.

data = {'user': 1, 'name': 'Max', 'three': 4}
try:
   is_admin = data['admin']
except KeyError:
   is_admin = False

Replace with this:

data = {'user': 1, 'name': 'Max', 'three': 4}
is_admin = data.get('admin', False)

Getting a subset of a list

Sometimes, you only need some of the elements in a list. Here are some ways to get a subset of a list.

x = [1,2,3,4,5,6]
#前3个
print x[:3]
>>> [1,2,3]
#中间4个
print x[1:5]
>>> [2,3,4,5]
#最后3个
print x[3:]
>>> [4,5,6]
#奇数项
print x[::2]
>>> [1,3,5]
#偶数项
print x[1::2]
>>> [2,4,6]

60 characters to solve FizzBuzz

Some time ago Jeff Atwood promoted a simple programming exercise called FizzBuzz. The question is quoted as follows:

Write a The program prints the numbers 1 to 100, replacing the number with "Fizz" for multiples of 3, "Buzz" for multiples of 5, and "FizzBuzz" for numbers that are both multiples of 3 and 5.

Here is a short, interesting way to solve this problem:

for x in range(101): print"fizz"[x%3*4::]+"buzz"[x%5*4::] or x

Collection

In addition to python's built-in

data type, in the collection module It also includes some special use cases, where Counter is very useful. If you participated in this year's Facebook HackerCup, you can even find its practicality.

from collections import Counter
print Counter("hello")
>>> Counter({'l': 2, 'h': 1, 'e': 1, 'o': 1})

Iteration tool

Like the collections library, there is also a library called itertools, which can really solve certain problems efficiently. One of the use cases is to find all combinations, which can tell you all the impossible combinations of elements in a group

from itertools import combinations
teams = ["Packers", "49ers", "Ravens", "Patriots"]
for game in combinations(teams, 2):
    print game
>>> ('Packers', '49ers')
>>> ('Packers', 'Ravens')
>>> ('Packers', 'Patriots')
>>> ('49ers', 'Ravens')
>>> ('49ers', 'Patriots')
>>> ('Ravens', 'Patriots')
False == True

This is a very interesting thing compared to practical technology. In python, True and False is a global variable, so:

False = True
if False:
   print "Hello"
else:
   print "World"
>>> Hello

The above is the detailed content of Must-see Python tips for beginners. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
How to Use Python to Find the Zipf Distribution of a Text FileHow to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AM

This tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th

How Do I Use Beautiful Soup to Parse HTML?How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PM

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

How to Perform Deep Learning with TensorFlow or PyTorch?How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PM

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Mathematical Modules in Python: StatisticsMathematical Modules in Python: StatisticsMar 09, 2025 am 11:40 AM

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

Serialization and Deserialization of Python Objects: Part 1Serialization and Deserialization of Python Objects: Part 1Mar 08, 2025 am 09:39 AM

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

What are some popular Python libraries and their uses?What are some popular Python libraries and their uses?Mar 21, 2025 pm 06:46 PM

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

Professional Error Handling With PythonProfessional Error Handling With PythonMar 04, 2025 am 10:58 AM

In this tutorial you'll learn how to handle error conditions in Python from a whole system point of view. Error handling is a critical aspect of design, and it crosses from the lowest levels (sometimes the hardware) all the way to the end users. If y

Scraping Webpages in Python With Beautiful Soup: Search and DOM ModificationScraping Webpages in Python With Beautiful Soup: Search and DOM ModificationMar 08, 2025 am 10:36 AM

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

Repo: How To Revive Teammates
1 months agoBy尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
2 weeks agoBy尊渡假赌尊渡假赌尊渡假赌
Hello Kitty Island Adventure: How To Get Giant Seeds
1 months agoBy尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Atom editor mac version download

Atom editor mac version download

The most popular open source editor

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

PhpStorm Mac version

PhpStorm Mac version

The latest (2018.2.1) professional PHP integrated development tool

Safe Exam Browser

Safe Exam Browser

Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.