Extraits de code Python

Tableaux

Listes

# 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()

Permutation et combinaison

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

Générer manuellement des permutations
Vous pouvez également générer des permutations manuellement en utilisant la récursivité. Voici une mise en œuvre simple :

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

Empiler

(la liste peut être utilisée comme pile)

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

Conseils

1) Bande :
Il est utilisé pour supprimer les espaces de début et de fin (ou d'autres caractères spécifiés) d'une chaîne

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

2) N'utilisez pas de dictionnaire normal

from collections import defaultdict
dictionary=defaultdict(int)

3) Vérification et conversion importantes

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

4) Non trivial

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)))

Trié

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)

Énumérer

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

Passer par référence d'objet

Types immuables (comme les entiers, les chaînes, les tuples) :

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

Types mutables (comme les listes, les dictionnaires, les ensembles) :

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]

Tableaux Numpy (pour les opérations numériques)

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]])

Type

C'est une fonction de NumPy utilisée pour convertir un tableau numpy en différents types de données.

# 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)

Remodeler

C'est un outil puissant pour changer la forme d'un tableau sans altérer ses données

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()

Dictionnaire

# 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}")

Défautdict

from collections import defaultdict

d = defaultdict(int)

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

Ensemble

# 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

Chaîne

# 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

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