Python est un puissant langage de programmation idéal pour les scripts et le développement rapide d'applications. Il est utilisé dans le développement Web (comme: Django et Bottle), l'informatique scientifique et mathématique (Orange, SymPy, NumPy) pour les interfaces utilisateur graphiques de bureau (Pygame, Panda3D).
Ce didacticiel vous présente les concepts et fonctionnalités de base de Python 3. Après avoir lu le didacticiel, vous serez capable de lire et d'écrire des programmes Python de base et d'explorer Python en profondeur par vous-même.
Ce didacticiel est destiné aux personnes qui connaissent d'autres langages de programmation et souhaitent se familiariser rapidement avec Python.
Python pour les débutants
Si vous êtes un débutant en programmation, nous vous suggérons de visiter:
- Programmation Python - Un guide complet sur ce qu'est Python, comment démarrer en Python, pourquoi vous devriez l'apprendre et comment vous pouvez l'apprendre.
- Tutoriels Python - Suivez les liens de la barre latérale un par un.
- Exemples Python - Exemples simples à suivre pour les débutants.
Que couvre ce didacticiel?
- Exécutez Python sur votre ordinateur
- Introduction (variables, opérateurs, E / S,…)
- Structures de données (liste, dictionnaire, ensemble,…)
- Flux de contrôle (si, boucle, rupture,…)
- Fichier (gestion de fichiers, répertoire,…)
- Exceptions (traitement, exception définie par l'utilisateur,…)
- POO (objet et classe, héritage, surcharge,…)
- Bibliothèque standard (fonction intégrée, méthodes de liste,…)
- Divers (Générateurs, décorateurs,…)
Exécutez Python sur votre ordinateur
Vous n'avez pas besoin d'installer Python sur votre ordinateur pour suivre ce tutoriel. Cependant, nous vous recommandons d'exécuter les programmes Python inclus dans ce didacticiel sur votre propre ordinateur.
- Exécutez Python sur Windows
- Exécutez Python sur MacOS
Introduction à Python
Écrivons notre premier programme Python, "Hello, World!". C'est un programme simple qui imprime Hello World! sur le périphérique de sortie standard (écran).
"Bonjour le monde!" Programme
print("Hello, World!")
Lorsque vous exécutez le programme, la sortie sera:
Bonjour le monde!
Dans ce programme, nous avons utilisé la fonction intégrée print () pour imprimer Hello, world! chaîne.
Variables et littéraux
Une variable est un emplacement nommé utilisé pour stocker des données dans la mémoire. Voici un exemple:
a = 5
Ici, a est une variable. Nous avons attribué 5à la variable a
Nous n'avons pas besoin de définir le type de variable en Python. Vous pouvez faire quelque chose comme ceci:
a = 5 print("a =", 5) a = "High five" print("a =", a)
Initialement, une valeur entière 5est affectée à la variable a. Ensuite, la chaîne High five est affectée à la même variable.
À propos, 5est un littéral numérique et "High five"est un littéral de chaîne.
Lorsque vous exécutez le programme, la sortie sera:
a = 5 a = cinq élevé
Visitez Variables, constantes et littéraux Python pour en savoir plus.
Les opérateurs
Les opérateurs sont des symboles spéciaux qui effectuent des opérations sur des opérandes (variables et valeurs).
Parlons des opérateurs d'arithmétique et d'affectation dans cette partie.
Les opérateurs arithmétiques sont utilisés pour effectuer des opérations mathématiques telles que l'addition, la soustraction, la multiplication, etc.
x = 14 y = 4 # Add two operands print('x + y =', x+y) # Output: x + y = 18 # Subtract right operand from the left print('x - y =', x-y) # Output: x - y = 10 # Multiply two operands print('x * y =', x*y) # Output: x * y = 56 # Divide left operand by the right one print('x / y =', x/y) # Output: x / y = 3.5 # Floor division (quotient) print('x // y =', x//y) # Output: x // y = 3 # Remainder of the division of left operand by the right print('x % y =', x%y) # Output: x % y = 2 # Left operand raised to the power of right (x^y) print('x ** y =', x**y) # Output: x ** y = 38416
Les opérateurs d'affectation sont utilisés pour affecter des valeurs aux variables. Vous avez déjà vu l'utilisation de l' =opérateur. Essayons d'autres opérateurs d'affectation.
x = 5 # x += 5 ----> x = x + 5 x +=5 print(x) # Output: 10 # x /= 5 ----> x = x / 5 x /= 5 print(x) # Output: 2.0
D' autres opérateurs d'affectation couramment utilisés: -=, *=, %=, //=et **=.
Visitez Opérateurs Python pour en savoir plus sur tous les opérateurs.
Obtenir les commentaires de l'utilisateur
En Python, vous pouvez utiliser la fonction input () pour prendre l'entrée de l'utilisateur. Par exemple:
inputString = input('Enter a sentence:') print('The inputted string is:', inputString)
Lorsque vous exécutez le programme, la sortie sera:
Entrez une phrase: Bonjour. La chaîne saisie est: Bonjour.
Commentaires Python
Il existe 3 façons de créer des commentaires en Python.
# Ceci est un commentaire
"" "Ceci est un commentaire multiligne." ""
'' 'Ceci est également un commentaire multiligne.' ''
Pour en savoir plus sur les commentaires et la docstring, visitez: Commentaires Python.
Conversion de type
Le processus de conversion de la valeur d'un type de données (entier, chaîne, flottant, etc.) en un autre est appelé conversion de type. Python a deux types de conversion de type.
Conversion de type implicite
La conversion implicite ne nécessite aucune implication de l'utilisateur. Par exemple:
num_int = 123 # integer type num_flo = 1.23 # float type num_new = num_int + num_flo print("Value of num_new:",num_new) print("datatype of num_new:",type(num_new))
Lorsque vous exécutez le programme, la sortie sera:
Valeur de num_new: 124.23 type de données de num_new: type de données de num_new:
Ici, num_new a un type de données float car Python convertit toujours un type de données plus petit en type de données plus grand pour éviter la perte de données.
Voici un exemple où l'interpréteur Python ne peut pas taper implicitement convert.
num_int = 123 # int type num_str = "456" # str type print(num_int+num_str)
Lorsque vous exécutez le programme, vous obtenez
TypeError: type (s) d'opérande non pris en charge pour +: 'int' et 'str'
Cependant, Python a une solution pour ce type de situation qui est connue sous le nom de conversion explicite.
Conversion explicite
In case of explicit conversion, you convert the datatype of an object to the required data type. We use predefined functions like int(), float(), str() etc. to perform explicit type conversion. For example:
num_int = 123 # int type num_str = "456" # str type # explicitly converted to int type num_str = int(num_str) print(num_int+num_str)
To lean more, visit Python type conversion.
Python Numeric Types
Python supports integers, floating point numbers and complex numbers. They are defined as int, float and complex class in Python. In addition to that, booleans: True and False are a subtype of integers.
# Output: print(type(5)) # Output: print(type(5.0)) c = 5 + 3j # Output: print(type(c))
To learn more, visit Python Number Types.
Python Data Structures
Python offers a range of compound datatypes often referred to as sequences. You will learn about those built-in types in this section.
Lists
A list is created by placing all the items (elements) inside a square bracket () separated by commas.
It can have any number of items and they may be of different types (integer, float, string etc.)
# empty list my_list = () # list of integers my_list = (1, 2, 3) # list with mixed data types my_list = (1, "Hello", 3.4)
You can also use list() function to create lists.
Here's how you can access elements of a list.
language = ("French", "German", "English", "Polish") # Accessing first element print(language(0)) # Accessing fourth element print(language(3))
You use the index operator () to access an item in a list. Index starts from 0. So, a list having 10 elements will have index from 0 to 9.
Python also allows negative indexing for its sequences. The index of -1 refers to the last item, -2 to the second last item and so on.
Check these resources for more information about Python lists:
- Python lists (slice, add and remove item etc.)
- Python list methods
- Python list comprehension
Tuples
Tuple is similar to a list except you cannot change elements of a tuple once it is defined. Whereas in a list, items can be modified.
Basically, list is mutable whereas tuple is immutable.
language = ("French", "German", "English", "Polish") print(language)
You can also use tuple() function to create tuples.
You can access elements of a tuple in a similar way like a list.
language = ("French", "German", "English", "Polish") print(language(1)) #Output: German print(language(3)) #Output: Polish print(language(-1)) # Output: Polish
You cannot delete elements of a tuple, however, you can entirely delete a tuple itself using del operator.
language = ("French", "German", "English", "Polish") del language # NameError: name 'language' is not defined print(language)
To learn more, visit Python Tuples.
String
A string is a sequence of characters. Here are different ways to create a string.
# all of the following are equivalent my_string = 'Hello' print(my_string) my_string = "Hello" print(my_string) my_string = '''Hello''' print(my_string) # triple quotes string can extend multiple lines my_string = """Hello, welcome to the world of Python""" print(my_string)
You can access individual characters of a string using indexing (in a similar manner like lists and tuples).
str = 'programiz' print('str = ', str) print('str(0) = ', str(0)) # Output: p print('str(-1) = ', str(-1)) # Output: z #slicing 2nd to 5th character print('str(1:5) = ', str(1:5)) # Output: rogr #slicing 6th to 2nd last character print('str(5:-2) = ', str(5:-2)) # Output: am
Strings are immutable. You cannot change elements of a string once it is assigned. However, you can assign one string to another. Also, you can delete the string using del operator.
Concatenation is probably the most common string operation. To concatenate strings, you use + operator. Similarly, the * operator can be used to repeat the string for a given number of times.
str1 = 'Hello ' str2 ='World!' # Output: Hello World! print(str1 + str2) # Hello Hello Hello print(str1 * 3)
Check these resources for more information about Python strings:
- Python Strings
- Python String Methods
- Python String Formatting
Sets
A set is an unordered collection of items where every element is unique (no duplicates).
Here is how you create sets in Python.
# set of integers my_set = (1, 2, 3) print(my_set) # set of mixed datatypes my_set = (1.0, "Hello", (1, 2, 3)) print(my_set)
You can also use set() function to create sets.
Sets are mutable. You can add, remove and delete elements of a set. However, you cannot replace one item of a set with another as they are unordered and indexing have no meaning.
Let's try commonly used set methods: add(), update() and remove().
# set of integers my_set = (1, 2, 3) my_set.add(4) print(my_set) # Output: (1, 2, 3, 4) my_set.add(2) print(my_set) # Output: (1, 2, 3, 4) my_set.update((3, 4, 5)) print(my_set) # Output: (1, 2, 3, 4, 5) my_set.remove(4) print(my_set) # Output: (1, 2, 3, 5)
Let's tryout some commonly used set operations:
A = (1, 2, 3) B = (2, 3, 4, 5) # Equivalent to A.union(B) # Also equivalent to B.union(A) print(A | B) # Output: (1, 2, 3, 4, 5) # Equivalent to A.intersection(B) # Also equivalent to B.intersection(A) print (A & B) # Output: (2, 3) # Set Difference print (A - B) # Output: (1) # Set Symmetric Difference print(A B) # Output: (1, 4, 5)
More Resources:
- Python Sets
- Python Set Methods
- Python Frozen Set
Dictionaries
Dictionary is an unordered collection of items. While other compound data types have only value as an element, a dictionary has a key: value pair. For example:
# empty dictionary my_dict = () # dictionary with integer keys my_dict = (1: 'apple', 2: 'ball') # dictionary with mixed keys my_dict = ('name': 'John', 1: (2, 4, 3))
You can also use dict() function to create dictionaries.
To access value from a dictionary, you use key. For example:
person = ('name':'Jack', 'age': 26, 'salary': 4534.2) print(person('age')) # Output: 26
Here's how you can change, add or delete dictionary elements.
person = ('name':'Jack', 'age': 26) # Changing age to 36 person('age') = 36 print(person) # Output: ('name': 'Jack', 'age': 36) # Adding salary key, value pair person('salary') = 4342.4 print(person) # Output: ('name': 'Jack', 'age': 36, 'salary': 4342.4) # Deleting age del person('age') print(person) # Output: ('name': 'Jack', 'salary': 4342.4) # Deleting entire dictionary del person
More resources:
- Python Dictionary
- Python Dictionary Methods
- Python Dictionary Comprehension
Python range()
range() returns an immutable sequence of numbers between the given start integer to the stop integer.
print(range(1, 10)) # Output: range(1, 10)
The output is an iterable and you can convert it to list, tuple, set and so on. For example:
numbers = range(1, 6) print(list(numbers)) # Output: (1, 2, 3, 4, 5) print(tuple(numbers)) # Output: (1, 2, 3, 4, 5) print(set(numbers)) # Output: (1, 2, 3, 4, 5) # Output: (1: 99, 2: 99, 3: 99, 4: 99, 5: 99) print(dict.fromkeys(numbers, 99))
We have omitted optional step parameter for range() in above examples. When omitted, step defaults to 1. Let's try few examples with step parameter.
# Equivalent to: numbers = range(1, 6) numbers1 = range(1, 6 , 1) print(list(numbers1)) # Output: (1, 2, 3, 4, 5) numbers2 = range(1, 6, 2) print(list(numbers2)) # Output: (1, 3, 5) numbers3 = range(5, 0, -1) print(list(numbers3)) # Output: (5, 4, 3, 2, 1)
Python Control Flow
if… else Statement
The if… else statement is used if you want perform different action (run different code) on different condition. For example:
num = -1 if num> 0: print("Positive number") elif num == 0: print("Zero") else: print("Negative number") # Output: Negative number
There can be zero or more elif parts, and the else part is optional.
Most programming languages use () to specify the block of code. Python uses indentation.
A code block starts with indentation and ends with the first unindented line. The amount of indentation is up to you, but it must be consistent throughout that block.
Generally, four whitespace is used for indentation and is preferred over tabs.
Let's try another example:
if False: print("I am inside the body of if.") print("I am also inside the body of if.") print("I am outside the body of if") # Output: I am outside the body of if.
Before you move on to next section, we recommend you to check comparison operator and logical operator.
Also, check out Python if… else in detail.
while Loop
Like most programming languages, while loop is used to iterate over a block of code as long as the test expression (condition) is true. Here is an example to find the sum of natural numbers:
n = 100 # initialize sum and counter sum = 0 i = 1 while i <= n: sum = sum + i i = i+1 # update counter print("The sum is", sum) # Output: The sum is 5050
In Python, while loop can have optional else block that is executed if the condition in the while loop evaluates to False. However, if the loop is terminated with break statement, Python interpreter ignores the else block.
To learn more, visit Python while Loop
for Loop
In Python, for loop is used to iterate over a sequence (list, tuple, string) or other iterable objects. Iterating over a sequence is called traversal.
Here's an example to find the sum of all numbers stored in a list.
numbers = (6, 5, 3, 8, 4, 2) sum = 0 # iterate over the list for val in numbers: sum = sum+val print("The sum is", sum) # Output: The sum is 28
Notice the use of in operator in the above example. The in operator returns True if value/variable is found in the sequence.
In Python, for loop can have optional else block. The else part is executed if the items in the sequence used in for loop exhausts. However, if the loop is terminated with break statement, Python interpreter ignores the else block.
To learn more, visit Python for Loop
break Statement
The break statement terminates the loop containing it. Control of the program flows to the statement immediately after the body of the loop. For example:
for val in "string": if val == "r": break print(val) print("The end")
When you run the program, the output will be:
s t The end
continue Statement
The continue statement is used to skip the rest of the code inside a loop for the current iteration only. Loop does not terminate but continues on with the next iteration. For example:
for val in "string": if val == "r": continue print(val) print("The end")
When you run the program, the output will be:
s t i n g The end
To learn more on break and continue with detail explanation, visit Python break and continue.
pass Statement
Suppose, you have a loop or a function that is not implemented yet, but want to implement it in the future. They cannot have an empty body. The interpreter would complain. So, you use the pass statement to construct a body that does nothing.
sequence = ('p', 'a', 's', 's') for val in sequence: pass
Python Function
A function is a group of related statements that perform a specific task. You use def keyword to create functions in Python.
def print_lines(): print("I am line1.") print("I am line2.")
You have to call the function to run the codes inside it. Here's how:
def print_lines(): print("I am line1.") print("I am line2.") # function call print_lines()
A function can accept arguments.
def add_numbers(a, b): sum = a + b print(sum) add_numbers(4, 5) # Output: 9
You can also return value from a function using return statement.
def add_numbers(a, b): sum = a + b return sum result = add_numbers(4, 5) print(result) # Output: 9
Here are few resources to check:
- Python Function
- Python Function Arguments (Default, Keyword, Arbitrary)
Recursion (Recursive function)
A function that calls itself is known as recursive function and this process is called recursion.
Every recursive function must have a base condition that stops the recursion or else the function calls itself infinitely.
# Recursive function to find the factorial of a number def calc_factorial(x): if x == 1: return 1 else: return (x * calc_factorial(x-1)) num = 6 print("The factorial of", num, "is", calc_factorial(num)) # Output: The factorial of 6 is 720
Visit Python recursion to learn more.
Lambda Function
In Python, you can define functions without a name. These functions are called lambda or anonymous function. To create a lambda function, lambda keyword is used.
square = lambda x: x ** 2 print(square(5)) # Output: 25
We use lambda functions when we require a nameless function for a short period of time. Lambda functions are used along with built-in functions like filter(), map() etc.
To learn more, visit:
- Python Lambda Function
- Python map()
- Python filter()
Modules
Modules refer to a file containing Python statements and definitions.
A file containing Python code, for e.g.: example.py, is called a module and its module name would be example.
Let us create it and save it as example.py.
# Python Module example def add(a, b): return a + b
To use this module, we use import keyword.
# importing example module import example # accessing the function inside the module using . operator example.add(4, 5.5)
Python has a ton of standard modules readily available for use. For example:
import math result = math.log2(5) # return the base-2 logarithm print(result) # Output: 2.321928094887362
You can import specific names from a module without importing the module as a whole. Here is an example.
from math import pi print("The value of pi is", pi) # Output: The value of pi is 3.141592653589793
More Resources:
- Python Modules
- Python Packages
Python File I/O
A file operation takes place in the following order.
- Open a file
- Read or write (perform operation)
- Close the file
How to open a file?
You can use open() function to open a file.
f = open("test.txt") # open file in current directory f = open("C:/Python33/README.txt") # specifying full path
We can specify the mode while opening a file.
| Mode | Description |
|---|---|
| 'r' | Open a file for reading. (default) |
| 'w' | Open a file for writing. Creates a new file if it does not exist or truncates the file if it exists. |
| 'x' | Open a file for exclusive creation. If the file already exists, the operation fails. |
| 'a' | Open for appending at the end of the file without truncating it. Creates a new file if it does not exist. |
| 't' | Open in text mode. (default) |
| 'b' | Open in binary mode. |
| '+' | Open a file for updating (reading and writing) |
f = open("test.txt") # equivalent to 'r' or 'rt' f = open("test.txt",'w') # write in text mode f = open("img.bmp.webp",'r+b') # read and write in binary mode
How to close a file?
To close a file, you use close() method.
f = open("test.txt",encoding = 'utf-8') # perform file operations f.close()
How to write to a file?
In order to write into a file in Python, we need to open it in write 'w', append 'a' or exclusive creation 'x' mode.
with open("test.txt",'w',encoding = 'utf-8') as f: f.write("my first file") f.write("This file") f.write("contains three lines")
Here, we have used with statement to open a file. This ensures that the file is closed when the block inside with is exited.
How to read files?
To read a file in Python, you must open the file in reading mode.
There are various methods available for this purpose. We can use the read(size) method to read in size number of data.
f = open("test.txt",'r',encoding = 'utf-8') f.read(4) # read the first 4 data
Visit Python File I/O to learn more.
Python Directory
A directory or folder is a collection of files and sub directories. Python has the os module, which provides many useful methods to work with directories and files.
import os os.getcwd() // present working directory os.chdir('D:\Hello') // Changing current directory to D:Hello os.listdir() // list all sub directories and files in that path os.mkdir('test') // making a new directory test os.rename('test','tasty') // renaming the directory test to tasty os.remove('old.txt') // deleting old.txt file
Visit Python Directory to learn more.
Python Exception Handling
Errors that occur at runtime are called exceptions. They occur, for example, when a file we try to open does not exist FileNotFoundError, dividing a number by zero ZeroDivisionError etc.
Visit this page to learn about all built-in exceptions in Python.
If exceptions are not handled, an error message is spit out and our program come to a sudden, unexpected halt.
In Python, exceptions can be handled using try statement. When exceptions are caught, it's up to you what operator to perform.
# import module sys to get the type of exception import sys randomList = ('a', 0, 2) for entry in randomList: try: print("The entry is", entry) r = 1/int(entry) break except: print("Oops!",sys.exc_info()(0),"occurred.") print("Next entry.") print() print("The reciprocal of",entry,"is",r)
When you run the program, the output will be:
The entry is a Oops! occurred. Next entry. The entry is 0 Oops! occurred. Next entry. The entry is 2 The reciprocal of 2 is 0.5
To learn about catching specific exceptions and finally clause with try statement, visit Python exception handling.
Also, you can create user-defined exceptions in Python. For that, visit Python Custom Exceptions
Python OOP
Everything in Python is an object including integers, floats, functions, classes, and None. Let's not focus on why everything in Python is an object. For that, visit this page. Rather, this section focuses on creating your own classes and objects.
Class and Objects
Object is simply a collection of data (variables) and methods (functions) that act on data. And, class is a blueprint for the object.
How to define a class?
class MyClass: a = 10 def func(self): print('Hello')
As soon as you define a class, a new class object is created with the same name. This class object allows us to access the different attributes as well as to instantiate new objects of that class.
class MyClass: "This is my class" a = 10 def func(self): print('Hello') # Output: 10 print(MyClass.a) # Output: print(MyClass.func) # Output: 'This is my class' print(MyClass.__doc__)
You may have noticed the self parameter in function definition inside the class but, we called the method simply as ob.func() without any arguments. It still worked.
This is because, whenever an object calls its method, the object itself is passed as the first argument. So, ob.func() translates into MyClass.func(ob).
Creating Objects
You can also create objects of the class yourself.
class MyClass: "This is my class" a = 10 def func(self): print('Hello') obj1 = MyClass() print(obj1.a) # Output: 10 obj2 = MyClass() print(obj1.a + 5) # Output: 15
Python Constructors
In Python, a method with name __init()__ is a constructor. This method is automatically called when an object is instantiated.
class ComplexNumber: def __init__(self,r = 0,i = 0): # constructor self.real = r self.imag = i def getData(self): print("(0)+(1)j".format(self.real,self.imag)) c1 = ComplexNumber(2,3) # Create a new ComplexNumber object c1.getData() # Output: 2+3j c2 = ComplexNumber() # Create a new ComplexNumber object c2.getData() # Output: 0+0j
Visit Python Class and Object to learn more.
Python Inheritance
Inheritance refers to defining a new class with little or no modification to an existing class. Let's take an example:
class Mammal: def displayMammalFeatures(self): print('Mammal is a warm-blooded animal.')
Let's derive a new class Dog from this Mammal class.
class Mammal: def displayMammalFeatures(self): print('Mammal is a warm-blooded animal.') class Dog(Mammal): def displayDogFeatures(self): print('Dog has 4 legs.') d = Dog() d.displayDogFeatures() d.displayMammalFeatures()
Notice that we are able to call method of base class displayMammalFeatures() from the object of derived class d.
To learn more about inheritance and method overriding, visit Python Inheritance.
We also suggest you to check multiple inheritance and operator overloading if you are interested.
Miscellaneous and Advance Topics
Iterators
Iterator in Python is simply an object that can be iterated upon. An object which will return data, one element at a time.
Technically speaking, Python iterator object must implement two special methods, __iter__() and __next__(), collectively called the iterator protocol.
An object is called iterable if we can get an iterator from it. Most of built-in containers in Python like: list, tuple, string etc. are iterables.
The iter() function (which in turn calls the __iter__() method) returns an iterator from them.
my_list = (4, 7, 0, 3) # get an iterator using iter() my_iter = iter(my_list) print(next(my_iter)) # Output: 4 print(next(my_iter)) # Output: 7
To learn more about infinite iterators and how to create custom iterators, visit: Python Iterators.
Generators
There is a lot of overhead in building an iterator in Python; we have to implement a class with __iter__() and __next__() method, keep track of internal states, raise StopIteration when there was no values to be returned etc.
This is both lengthy and counter intuitive. Generator comes into rescue in such situations.
Python generators are a simple way of creating iterators.
Learn more about Python Generators.
Closures
This technique by which some data gets attached to the code is called closure in Python.
def print_msg(msg): # outer enclosing function def printer(): # inner function print(msg) return printer # this got changed another = print_msg("Hello") # Output: Hello another()
Here, the print_msg() function is called with the string "Hello" as an argument and the returned function was bound to the name another. On calling another(), the message was still remembered although we had already finished executing the print_msg() function.
The criteria that must be met to create closure in Python are summarized in the following points.
- We must have a nested function (function inside a function).
- The nested function must refer to a value defined in the enclosing function.
- The enclosing function must return the nested function.
Visit Python closures to learn more about closures and when to use them.
Decorators
Python has an interesting feature called decorators to add functionality to an existing code.
Ceci est également appelé métaprogrammation car une partie du programme essaie de modifier une autre partie du programme au moment de la compilation.
Pour en savoir plus sur les décorateurs en détail, visitez les décorateurs Python.
Ai-je manqué quelque chose dans ce didacticiel Python?
