搜索

Python Code Snippets

数组

列表

# Creating a list
my_list = []
my_list = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

# List of different data types
mixed_list = [1, "hello", 3.14, True]

# Accessing elements
print(my_list[0])  # Output: 1
print(my_list[-1]) # Output: 5

# Append to the end
my_list.append(6)

# Insert at a specific position
my_list.insert(2, 10)

# Find an element in an array
index=my_list.find(element)

# Remove by value
my_list.remove(10)

# Remove by index
removed_element = my_list.pop(2)

# Length of the list
print(len(my_list))

# Slicing [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
# sequence[start:stop:step]

print(my_list[1:4])  # Output: [1, 2, 3]
print(my_list[5:])  # Output: [5, 6, 7, 8, 9]
print(my_list[:5])  # Output: [0, 1, 2, 3, 4]
print(my_list[::2])  # Output: [0, 2, 4, 6, 8]
print(my_list[-4:])  # Output: [6, 7, 8, 9]
print(my_list[:-4])  # Output: [0, 1, 2, 3, 4, 5]
print(my_list[::-1])  # Output: [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
print(my_list[8:2:-2])  # Output: [8, 6, 4]
print(my_list[1:8:2])  # Output: [1, 3, 5, 7]
print(my_list[-2:-7:-1])  # Output: [8, 7, 6, 5, 4]

# Reversing a list
my_list.reverse()

# Sorting a list
my_list.sort()

排列组合

import itertools

# Example list
data = [1, 2, 3]

# Generating permutations of the entire list
perms = list(itertools.permutations(data))
print(perms)
# Output: [(1, 2, 3), (1, 3, 2), (2, 1, 3), (2, 3, 1), (3, 1, 2), (3, 2, 1)]

# Generating permutations of length 2
perms_length_2 = list(itertools.permutations(data, 2))
print(perms_length_2)
# Output: [(1, 2), (1, 3), (2, 1), (2, 3), (3, 1), (3, 2)]

combinations(iterable, r) #order does not matter

手动生成排列
您还可以使用递归手动生成排列。这是一个简单的实现:

def permute(arr):
    result = []

    # Base case: if the list is empty, return an empty list
    if len(arr) == 0:
        return [[]]

    # Recursive case
    for i in range(len(arr)):
        elem = arr[i]
        rest = arr[:i] + arr[i+1:]
        for p in permute(rest):
            result.append([elem] + p)

    return result

(列表可以用作堆栈)

st=[]
st.append()
st.pop()
top_element = stack[-1]

尖端

1) 脱衣:
它用于从字符串中删除前导和尾随空格(或其他指定字符)

#EX. (1,2) to 1,2
s.strip('()')

2)不要使用普通词典

from collections import defaultdict
dictionary=defaultdict(int)

3) 重要检查和转换

s.isdigit()
s.isalpha()
s.isalnum()
s.islower()
s.isupper()
s.lower()
s.upper()

4) 重要

round(number, decimal_digits)
ord(each)-ord('a')+1 # value of an alphabet
#/ (Floating-Point Division)
#// (Floor Division)
maxim = float('-inf')
minim = float('inf')
unique_lengths.sort(reverse=True)
s.count('x')

list1 = [1, 2, 3]
iterable = [4, 5, 6]
list1.extend(iterable)

position.replace('(', '').replace(')', '')

expression = "2 + 3 * 4"
result = eval(expression)
print(result) 

#Determinant
import numpy as 
arr=[[1,2,3],[3,4,5],[5,6,7]]
print(np.linalg.det(np.array(arr)))

已排序

my_list = [3, 1, 4, 1, 5]
sorted_list = sorted(my_list)

my_tuple = (3, 1, 4, 1, 5)
sorted_list = sorted(my_tuple)

my_dict = {'apple': 3, 'banana': 1, 'cherry': 2}
sorted_keys = sorted(my_dict)

my_list = [3, 1, 4, 1, 5]
sorted_list = sorted(my_list, reverse=True)

枚举

my_list = ['a', 'b', 'c']
for index, value in enumerate(my_list):
    print(index, value)

通过对象引用传递

不可变类型(如整数、字符串、元组):

def modify_immutable(x):
    x = 10  # Rebinding the local variable to a new object
    print("Inside function:", x)

a = 5
modify_immutable(a) #prints 10
print("Outside function:", a) #prints 5

可变类型(如列表、字典、集合):

def modify_mutable(lst):
    lst.append(4)  # Modifying the original list object
    print("Inside function:", lst)

my_list = [1, 2, 3]
modify_mutable(my_list) # [1,2,3]
print("Outside function:", my_list) # [1,2,3,4]

Numpy 数组(用于数值运算)

import numpy as np

# Creating a 1D array
arr_1d = np.array([1, 2, 3, 4, 5])

# Creating a 2D array
arr_2d = np.array([[1, 2, 3], [4, 5, 6]])

# Creating an array filled with zeros
zeros = np.zeros((3, 4))

# Creating an array filled with ones
ones = np.ones((2, 3))

# Creating an array with a range of values
range_arr = np.arange(0, 10, 2)

# Creating an array with evenly spaced values
linspace_arr = np.linspace(0, 1, 5)

# Creating an identity matrix
identity_matrix = np.eye(3)

# Shape of the array
shape = arr_2d.shape  # Output: (2, 3)

# Size of the array (total number of elements)
size = arr_2d.size  # Output: 6

# Element-wise addition
arr_add = arr_1d + 5  # Output: array([6, 7, 8, 9, 10])

# Element-wise subtraction
arr_sub = arr_1d - 2  # Output: array([ -1, 0, 1, 2, 3])

# Element-wise multiplication
arr_mul = arr_1d * 2  # Output: array([ 2, 4, 6, 8, 10])

# Element-wise division
arr_div = arr_1d / 2  # Output: array([0.5, 1. , 1.5, 2. , 2.5])

# Sum
total_sum = np.sum(arr_2d)  # Output: 21

# Mean
mean_value = np.mean(arr_2d)  # Output: 3.5

# Standard deviation
std_dev = np.std(arr_2d)  # Output: 1.707825127659933

# Maximum and minimum
max_value = np.max(arr_2d)  # Output: 6
min_value = np.min(arr_2d)  # Output: 1

# Reshaping
reshaped_arr = arr_1d.reshape((5, 1))

# Flattening
flattened_arr = arr_2d.flatten()

# Transposing
transposed_arr = arr_2d.T

# Indexing
element = arr_2d[1, 2]  # Output: 6

# Slicing
subarray = arr_2d[0:2, 1:3]  # Output: array([[2, 3], [5, 6]])

阿斯型

它是 NumPy 中的一个函数,用于将 numpy 数组转换为不同的数据类型。

# Datatypes: np.int32,np.float32,np.float64,np.str_
import numpy as np

# Create an integer array
int_array = np.array([1, 2, 3, 4, 5], dtype=np.int32)

# Convert to float
float_array = int_array.astype(np.float32)

print("Original array:", int_array)
print("Converted array:", float_array)

重塑

它是一个强大的工具,可以在不改变数据的情况下改变数组的形状

import numpy as np

# Create a 1D array
array = np.arange(12)

# Reshape to a 2D array (3 rows x 4 columns)
reshaped_array = array.reshape((3, 4))

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

# Create a random 2D array
data = np.random.rand(10, 10)

# Create a figure with a specific size and resolution
plt.figure(figsize=(8, 6), dpi=100)

# Display the 2D array as an image
plt.imshow(data, cmap='viridis', interpolation='nearest')

# Add a color bar to show the scale of values
plt.colorbar()

# Show the plot
plt.show()

字典

# Creating an empty dictionary
# Maintains ascending order like map in cpp
my_dict = {}

# Creating a dictionary with initial values
my_dict = {'name': 'Alice', 'age': 25, 'city': 'New York'}

# Creating a dictionary using the dict() function
my_dict = dict(name='Alice', age=25, city='New York')

# Accessing a value by key
name = my_dict['name']  # Output: 'Alice'

# Using the get() method to access a value
age = my_dict.get('age')  # Output: 25
country = my_dict.get('country')  # Output: None

# Adding a new key-value pair
my_dict['email'] = 'alice@example.com'

# Updating an existing value
my_dict['age'] = 26

# Removing a key-value pair using pop()
age = my_dict.pop('age')  # Removes 'age' and returns its value

# Getting all keys in the dictionary
keys = my_dict.keys()  # Output: dict_keys(['name', 'email'])

# Getting all values in the dictionary
values = my_dict.values()  # Output: dict_values(['Alice', 'alice@example.com'])

# Iterating over keys
for key in my_dict:
    print(key)

# Iterating over values
for value in my_dict.values():
    print(value)

# Iterating over key-value pairs
for key, value in my_dict.items():
    print(f"{key}: {value}")

默认字典

from collections import defaultdict

d = defaultdict(int)

# Initializes 0 to non-existent keys
d['apple'] += 1
d['banana'] += 2

# Creating an empty set
my_set = set()

# Creating a set with initial values
my_set = {1, 2, 3, 4, 5}

# Creating a set from a list
my_list = [1, 2, 3, 4, 5]
my_set = set(my_list)

# Creating a set from a string
my_set = set('hello')  # Output: {'e', 'h', 'l', 'o'}

# Adding an element to a set
my_set.add(6)  # my_set becomes {1, 2, 3, 4, 5, 6}

# Removing an element from a set (raises KeyError if not found)
my_set.remove(3)  # my_set becomes {1, 2, 4, 5, 6}

# Removing and returning an arbitrary element from the set
element = my_set.pop()  # Returns and removes an arbitrary element

细绳

# Single quotes
str1 = 'Hello'

# Double quotes
str2 = "World"

# Triple quotes for multi-line strings
str3 = '''This is a 
multi-line string.'''

# Raw strings (ignores escape sequences)
raw_str = r'C:\Users\Name'

str1 = 'Hello'

# Accessing a single character
char = str1[1]  # 'e'

# Accessing a substring (slicing)
substring = str1[1:4]  # 'ell'

# Negative indexing
last_char = str1[-1]  # 'o'

# Using + operator
concatenated = 'Hello' + ' ' + 'World'  # 'Hello World'

# Using join method
words = ['Hello', 'World']
concatenated = ' '.join(words)  # 'Hello World'

name = 'Alice'
age = 25

# String formatting
formatted_str = f'My name is {name} and I am {age} years old.'

# Convert to uppercase
upper_str = str1.upper()  # 'HELLO WORLD'

# Convert to lowercase
lower_str = str1.lower()  # 'hello world'

# Convert to capitalize
capital_str = str1.capitalize()  # 'Hello world'

str1 = '  Hello World  '

# Remove leading and trailing whitespace
trimmed = str1.strip()  # 'Hello World'

str1 = 'Hello World Python'

# Split the string into a list of substrings
split_list = str1.split()  # ['Hello', 'World', 'Python']

# Split the string with a specific delimiter
split_list = str1.split(' ')  # ['Hello', 'World', 'Python']

# Join a list of strings into a single string
joined_str = ' '.join(split_list)  # 'Hello World Python'

str1 = 'Hello World'

# Find the position of a substring
pos = str1.find('World')  # 6


str1 = 'Hello123'

# Check if all characters are alphanumeric
is_alnum = str1.isalnum()  # True

# Check if all characters are alphabetic
is_alpha = str1.isalpha()  # False

# Check if all characters are digits
is_digit = str1.isdigit()  # False

# Check if all characters are lowercase
is_lower = str1.islower()  # False

# Check if all characters are uppercase
is_upper = str1.isupper()  # False

保持联系!
如果您喜欢这篇文章,请不要忘记在社交媒体上关注我以获取更多更新和见解:

推特: madhavganesan
Instagram:madhavganesan
领英: madhavganesan

以上是Python 代码片段的详细内容。更多信息请关注PHP中文网其他相关文章!

声明
本文内容由网友自发贡献,版权归原作者所有,本站不承担相应法律责任。如您发现有涉嫌抄袭侵权的内容,请联系admin@php.cn
Python和时间:充分利用您的学习时间Python和时间:充分利用您的学习时间Apr 14, 2025 am 12:02 AM

要在有限的时间内最大化学习Python的效率,可以使用Python的datetime、time和schedule模块。1.datetime模块用于记录和规划学习时间。2.time模块帮助设置学习和休息时间。3.schedule模块自动化安排每周学习任务。

Python:游戏,Guis等Python:游戏,Guis等Apr 13, 2025 am 12:14 AM

Python在游戏和GUI开发中表现出色。1)游戏开发使用Pygame,提供绘图、音频等功能,适合创建2D游戏。2)GUI开发可选择Tkinter或PyQt,Tkinter简单易用,PyQt功能丰富,适合专业开发。

Python vs.C:申请和用例Python vs.C:申请和用例Apr 12, 2025 am 12:01 AM

Python适合数据科学、Web开发和自动化任务,而C 适用于系统编程、游戏开发和嵌入式系统。 Python以简洁和强大的生态系统着称,C 则以高性能和底层控制能力闻名。

2小时的Python计划:一种现实的方法2小时的Python计划:一种现实的方法Apr 11, 2025 am 12:04 AM

2小时内可以学会Python的基本编程概念和技能。1.学习变量和数据类型,2.掌握控制流(条件语句和循环),3.理解函数的定义和使用,4.通过简单示例和代码片段快速上手Python编程。

Python:探索其主要应用程序Python:探索其主要应用程序Apr 10, 2025 am 09:41 AM

Python在web开发、数据科学、机器学习、自动化和脚本编写等领域有广泛应用。1)在web开发中,Django和Flask框架简化了开发过程。2)数据科学和机器学习领域,NumPy、Pandas、Scikit-learn和TensorFlow库提供了强大支持。3)自动化和脚本编写方面,Python适用于自动化测试和系统管理等任务。

您可以在2小时内学到多少python?您可以在2小时内学到多少python?Apr 09, 2025 pm 04:33 PM

两小时内可以学到Python的基础知识。1.学习变量和数据类型,2.掌握控制结构如if语句和循环,3.了解函数的定义和使用。这些将帮助你开始编写简单的Python程序。

如何在10小时内通过项目和问题驱动的方式教计算机小白编程基础?如何在10小时内通过项目和问题驱动的方式教计算机小白编程基础?Apr 02, 2025 am 07:18 AM

如何在10小时内教计算机小白编程基础?如果你只有10个小时来教计算机小白一些编程知识,你会选择教些什么�...

如何在使用 Fiddler Everywhere 进行中间人读取时避免被浏览器检测到?如何在使用 Fiddler Everywhere 进行中间人读取时避免被浏览器检测到?Apr 02, 2025 am 07:15 AM

使用FiddlerEverywhere进行中间人读取时如何避免被检测到当你使用FiddlerEverywhere...

See all articles

热AI工具

Undresser.AI Undress

Undresser.AI Undress

人工智能驱动的应用程序,用于创建逼真的裸体照片

AI Clothes Remover

AI Clothes Remover

用于从照片中去除衣服的在线人工智能工具。

Undress AI Tool

Undress AI Tool

免费脱衣服图片

Clothoff.io

Clothoff.io

AI脱衣机

AI Hentai Generator

AI Hentai Generator

免费生成ai无尽的。

热门文章

R.E.P.O.能量晶体解释及其做什么(黄色晶体)
3 周前By尊渡假赌尊渡假赌尊渡假赌
R.E.P.O.最佳图形设置
3 周前By尊渡假赌尊渡假赌尊渡假赌
R.E.P.O.如果您听不到任何人,如何修复音频
3 周前By尊渡假赌尊渡假赌尊渡假赌
WWE 2K25:如何解锁Myrise中的所有内容
4 周前By尊渡假赌尊渡假赌尊渡假赌

热工具

SublimeText3 Linux新版

SublimeText3 Linux新版

SublimeText3 Linux最新版

EditPlus 中文破解版

EditPlus 中文破解版

体积小,语法高亮,不支持代码提示功能

PhpStorm Mac 版本

PhpStorm Mac 版本

最新(2018.2.1 )专业的PHP集成开发工具

SublimeText3 Mac版

SublimeText3 Mac版

神级代码编辑软件(SublimeText3)

记事本++7.3.1

记事本++7.3.1

好用且免费的代码编辑器