Ce didacticiel fournit de brèves informations sur tous les mots-clés utilisés dans Python.
Les mots clés sont les mots réservés en Python. Nous ne pouvons pas utiliser un mot-clé comme nom de variable, nom de fonction ou tout autre identifiant.
Voici une liste de tous les mots-clés dans la programmation Python
Mots-clés en langage de programmation PythonFaux | attendre | autre | importer | passer |
Aucun | Pause | sauf | dans | élever |
Vrai | classe | enfin | est | revenir |
et | continuer | pour | lambda | essayer |
comme | def | de | non local | tandis que |
affirmer | del | global | ne pas | avec |
asynchrone | elif | si | ou | rendement |
Les mots-clés ci-dessus peuvent être modifiés dans différentes versions de Python. Certains extras peuvent être ajoutés ou certains peuvent être supprimés. Vous pouvez toujours obtenir la liste des mots-clés dans votre version actuelle en tapant ce qui suit dans l'invite.
>>> import keyword >>> print(keyword.kwlist) ('False', 'None', 'True', 'and', 'as', 'assert', 'async', 'await', 'break', 'class', 'continue', 'def', 'del', 'elif', 'else', 'except', 'finally', 'for', 'from', 'global', 'if', 'import', 'in', 'is', 'lambda', 'nonlocal', 'not', 'or', 'pass', 'raise', 'return', 'try', 'while', 'with', 'yield')
Description des mots-clés en Python avec des exemples
Vrai faux
True
et False
sont des valeurs de vérité en Python. Ce sont les résultats d'opérations de comparaison ou d'opérations logiques (booléennes) en Python. Par exemple:
>>> 1 == 1 True >>> 5> 3 True >>> True or False True >>> 10 >> 3> 7 False >>> True and False False
Ici, nous pouvons voir que les trois premières instructions sont vraies, donc l'interpréteur retourne True
et retourne False
pour les trois autres instructions. True
et False
en python est identique à 1
et 0
. Cela peut être justifié par l'exemple suivant:
>>> True == 1 True >>> False == 0 True >>> True + True 2
Aucun
None
est une constante spéciale en Python qui représente l'absence d'une valeur ou d'une valeur nulle.
C'est un objet de son propre type de données, le NoneType
. Nous ne pouvons pas créer plusieurs None
objets mais pouvons les affecter à des variables. Ces variables seront égales les unes aux autres.
Nous devons faire attention qui None
n'implique pas False
, 0
ou toute liste vide, dictionnaire, chaîne etc. Par exemple:
>>> None == 0 False >>> None == () False >>> None == False False >>> x = None >>> y = None >>> x == y True
Les fonctions vides qui ne renvoient rien None
renverront automatiquement un objet. None
est également retourné par des fonctions dans lesquelles le flux du programme ne rencontre pas d'instruction return. Par exemple:
def a_void_function(): a = 1 b = 2 c = a + b x = a_void_function() print(x)
Production
Aucun
Ce programme a une fonction qui ne renvoie pas de valeur, bien qu'il effectue certaines opérations à l'intérieur. Ainsi, lorsque nous imprimons x, nous obtenons None
ce qui est retourné automatiquement (implicitement). De même, voici un autre exemple:
def improper_return_function(a): if (a % 2) == 0: return True x = improper_return_function(3) print(x)
Production
Aucun
Bien que cette fonction ait une return
instruction, elle n'est pas atteinte dans tous les cas. La fonction ne retournera True
que lorsque l'entrée est paire.
Si nous donnons à la fonction un nombre impair, elle None
est renvoyée implicitement.
et, ou, pas
and
, or
, not
Sont les opérateurs logiques en python. and
résultera en True
seulement si les deux opérandes sont True
. La table de vérité pour and
est donnée ci-dessous:
and
Table de vérité pour
UNE | B | A et B |
---|---|---|
Vrai | Vrai | Vrai |
Vrai | Faux | Faux |
Faux | Vrai | Faux |
Faux | Faux | Faux |
or
se traduira par True
si l'un des opérandes est True
. La table de vérité pour or
est donnée ci-dessous:
or
Table de vérité pour
UNE | B | A ou B |
---|---|---|
Vrai | Vrai | Vrai |
Vrai | Faux | Vrai |
Faux | Vrai | Vrai |
Faux | Faux | Faux |
not
L'opérateur est utilisé pour inverser la valeur de vérité. La table de vérité pour not
est donnée ci-dessous:
not
Tableau de vérité pour
UNE | pas A |
---|---|
Vrai | Faux |
Faux | Vrai |
quelques exemples de leur utilisation sont donnés ci-dessous
>>> True and False False >>> True or False True >>> not False True
comme
as
est utilisé pour créer un alias lors de l'importation d'un module. Cela signifie donner un nom différent (défini par l'utilisateur) à un module lors de son importation.
Comme par exemple, Python a un module standard appelé math
. Supposons que nous voulions calculer quel cosinus pi utilise un alias. Nous pouvons le faire comme suit en utilisant as
:
>>> import math as myAlias >>>myAlias.cos(myAlias.pi) -1.0
Ici, nous avons importé le math
module en lui donnant le nom myAlias
. Nous pouvons maintenant nous référer au math
module avec ce nom. En utilisant ce nom, nous avons calculé cos (pi) et obtenu -1.0
comme réponse.
affirmer
assert
est utilisé à des fins de débogage.
Lors de la programmation, nous souhaitons parfois connaître l'état interne ou vérifier si nos hypothèses sont vraies. assert
nous aide à le faire et à trouver les bogues plus facilement. assert
est suivi d'une condition.
Si la condition est vraie, rien ne se passe. Mais si la condition est fausse, AssertionError
est levée. Par exemple:
>>> a = 4 >>> assert a >> assert a> 5 Traceback (most recent call last): File "", line 301, in runcode File "", line 1, in AssertionError
Pour une meilleure compréhension, nous pouvons également fournir un message à imprimer avec le AssertionError
.
>>> a = 4 >>> assert a> 5, "The value of a is too small" Traceback (most recent call last): File "", line 301, in runcode File "", line 1, in AssertionError: The value of a is too small
À ce stade, nous pouvons noter que,
assert condition, message
est équivalent à,
if not condition: raise AssertionError(message)
asynchrone, attendez
Les mots-clés async
et await
sont fournis par la asyncio
bibliothèque en Python. Ils sont utilisés pour écrire du code simultané en Python. Par exemple,
import asyncio async def main(): print('Hello') await asyncio.sleep(1) print('world')
Pour exécuter le programme, nous utilisons
asyncio.run(main())
Dans le programme ci-dessus, le async
mot - clé spécifie que la fonction sera exécutée de manière asynchrone.
Ici, le premier Hello est imprimé. Le await
mot-clé fait attendre le programme pendant 1 seconde. Et puis le monde est imprimé.
pause, continue
break
et continue
sont utilisés à l'intérieur for
et des while
boucles pour modifier leur comportement normal.
break
will end the smallest loop it is in and control flows to the statement immediately below the loop. continue
causes to end the current iteration of the loop, but not the whole loop.
This can be illustrated with the following two examples:
for i in range(1,11): if i == 5: break print(i)
Output
1 2 3 4
Here, the for
loop intends to print numbers from 1 to 10. But the if
condition is met when i is equal to 5 and we break from the loop. Thus, only the range 1 to 4 is printed.
for i in range(1,11): if i == 5: continue print(i)
Output
1 2 3 4 6 7 8 9 10
Here we use continue
for the same program. So, when the condition is met, that iteration is skipped. But we do not exit the loop. Hence, all the values except 5 are printed out.
Learn more about Python break and continue statement.
class
class
is used to define a new user-defined class in Python.
Class is a collection of related attributes and methods that try to represent a real-world situation. This idea of putting data and functions together in a class is central to the concept of object-oriented programming (OOP).
Classes can be defined anywhere in a program. But it is a good practice to define a single class in a module. Following is a sample usage:
class ExampleClass: def function1(parameters):… def function2(parameters):…
Learn more about Python Objects and Class.
def
def
is used to define a user-defined function.
Function is a block of related statements, which together does some specific task. It helps us organize code into manageable chunks and also to do some repetitive task.
The usage of def
is shown below:
def function_name(parameters):…
Learn more about Python functions.
del
del
is used to delete the reference to an object. Everything is object in Python. We can delete a variable reference using del
>>> a = b = 5 >>> del a >>> a Traceback (most recent call last): File "", line 301, in runcode File "", line 1, in NameError: name 'a' is not defined >>> b 5
Here we can see that the reference of the variable a was deleted. So, it is no longer defined. But b still exists.
del
is also used to delete items from a list or a dictionary:
>>> a = ('x','y','z') >>> del a(1) >>> a ('x', 'z')
if, else, elif
if, else, elif
are used for conditional branching or decision making.
When we want to test some condition and execute a block only if the condition is true, then we use if
and elif
. elif
is short for else if. else
is the block which is executed if the condition is false. This will be clear with the following example:
def if_example(a): if a == 1: print('One') elif a == 2: print('Two') else: print('Something else') if_example(2) if_example(4) if_example(1)
Output
Two Something else One
Here, the function checks the input number and prints the result if it is 1 or 2. Any input other than this will cause the else
part of the code to execute.
Learn more about Python if and if… else Statement.
except, raise, try
except, raise, try
are used with exceptions in Python.
Exceptions are basically errors that suggests something went wrong while executing our program. IOError
, ValueError
, ZeroDivisionError
, ImportError
, NameError
, TypeError
etc. are few examples of exception in Python. try… except
blocks are used to catch exceptions in Python.
We can raise an exception explicitly with the raise
keyword. Following is an example:
def reciprocal(num): try: r = 1/num except: print('Exception caught') return return r print(reciprocal(10)) print(reciprocal(0))
Output
0.1 Exception caught None
Here, the function reciprocal()
returns the reciprocal of the input number.
When we enter 10, we get the normal output of 0.1. But when we input 0, a ZeroDivisionError
is raised automatically.
This is caught by our try… except
block and we return None
. We could have also raised the ZeroDivisionError
explicitly by checking the input and handled it elsewhere as follows:
if num == 0: raise ZeroDivisionError('cannot divide')
finally
finally
is used with try… except
block to close up resources or file streams.
Using finally
ensures that the block of code inside it gets executed even if there is an unhandled exception. For example:
try: Try-block except exception1: Exception1-block except exception2: Exception2-block else: Else-block finally: Finally-block
Here if there is an exception in the Try-block
, it is handled in the except
or else
block. But no matter in what order the execution flows, we can rest assured that the Finally-block
is executed even if there is an error. This is useful in cleaning up the resources.
Learn more about exception handling in Python programming.
for
for
is used for looping. Generally we use for
when we know the number of times we want to loop.
In Python we can use it with any type of sequences like a list or a string. Here is an example in which for
is used to traverse through a list of names:
names = ('John','Monica','Steven','Robin') for i in names: print('Hello '+i)
Output
Hello John Hello Monica Hello Steven Hello Robin
Learn more about Python for loop.
from, import
import
keyword is used to import modules into the current namespace. from… import
is used to import specific attributes or functions into the current namespace. For example:
import math
will import the math
module. Now we can use the cos()
function inside it as math.cos()
. But if we wanted to import just the cos()
function, this can done using from
as
from math import cos
now we can use the function simply as cos()
, no need to write math.cos()
.
Learn more on Python modules and import statement.
global
global
is used to declare that a variable inside the function is global (outside the function).
If we need to read the value of a global variable, it is not necessary to define it as global
. This is understood.
If we need to modify the value of a global variable inside a function, then we must declare it with global
. Otherwise, a local variable with that name is created.
Following example will help us clarify this.
globvar = 10 def read1(): print(globvar) def write1(): global globvar globvar = 5 def write2(): globvar = 15 read1() write1() read1() write2() read1()
Output
10 5 5
Here, the read1()
function is just reading the value of globvar
. So, we do not need to declare it as global
. But the write1()
function is modifying the value, so we need to declare the variable as global
.
We can see in our output that the modification did take place (10 is changed to 5). The write2()
also tries to modify this value. But we have not declared it as global
.
Hence, a new local variable globvar
is created which is not visible outside this function. Although we modify this local variable to 15, the global variable remains unchanged. This is clearly visible in our output.
in
in
is used to test if a sequence (list, tuple, string etc.) contains a value. It returns True
if the value is present, else it returns False
. For example:
>>> a = (1, 2, 3, 4, 5) >>> 5 in a True >>> 10 in a False
The secondary use of in
is to traverse through a sequence in a for
loop.
for i in 'hello': print(i)
Output
h e l l o
is
is
is used in Python for testing object identity. While the ==
operator is used to test if two variables are equal or not, is
is used to test if the two variables refer to the same object.
It returns True
if the objects are identical and False
if not.
>>> True is True True >>> False is False True >>> None is None True
We know that there is only one instance of True
, False
and None
in Python, so they are identical.
>>> () == () True >>> () is () False >>> () == () True >>> () is () False
An empty list or dictionary is equal to another empty one. But they are not identical objects as they are located separately in memory. This is because list and dictionary are mutable (value can be changed).
>>> '' == '' True >>> '' is '' True >>> () == () True >>> () is () True
Unlike list and dictionary, string and tuple are immutable (value cannot be altered once defined). Hence, two equal string or tuple are identical as well. They refer to the same memory location.
lambda
lambda
is used to create an anonymous function (function with no name). It is an inline function that does not contain a return
statement. It consists of an expression that is evaluated and returned. For example:
a = lambda x: x*2 for i in range(1,6): print(a(i))
Output
2 4 6 8 10
Here, we have created an inline function that doubles the value, using the lambda
statement. We used this to double the values in a list containing 1 to 5.
Learn more about Python lamda function.
nonlocal
The use of nonlocal
keyword is very much similar to the global
keyword. nonlocal
is used to declare that a variable inside a nested function (function inside a function) is not local to it, meaning it lies in the outer inclosing function. If we need to modify the value of a non-local variable inside a nested function, then we must declare it with nonlocal
. Otherwise a local variable with that name is created inside the nested function. Following example will help us clarify this.
def outer_function(): a = 5 def inner_function(): nonlocal a a = 10 print("Inner function: ",a) inner_function() print("Outer function: ",a) outer_function()
Output
Inner function: 10 Outer function: 10
Here, the inner_function()
is nested within the outer_function
.
The variable a is in the outer_function()
. So, if we want to modify it in the inner_function()
, we must declare it as nonlocal
. Notice that a is not a global variable.
Hence, we see from the output that the variable was successfully modified inside the nested inner_function()
. The result of not using the nonlocal
keyword is as follows:
def outer_function(): a = 5 def inner_function(): a = 10 print("Inner function: ",a) inner_function() print("Outer function: ",a) outer_function()
Output
Inner function: 10 Outer function: 5
Here, we do not declare that the variable a inside the nested function is nonlocal
. Hence, a new local variable with the same name is created, but the non-local a is not modified as seen in our output.
pass
pass
is a null statement in Python. Nothing happens when it is executed. It is used as a placeholder.
Suppose we have a function that is not implemented yet, but we want to implement it in the future. Simply writing,
def function(args):
in the middle of a program will give us IndentationError
. Instead of this, we construct a blank body with the pass
statement.
def function(args): pass
We can do the same thing in an empty class
as well.
class example: pass
return
return
statement is used inside a function to exit it and return a value.
If we do not return a value explicitly, None
is returned automatically. This is verified with the following example.
def func_return(): a = 10 return a def no_return(): a = 10 print(func_return()) print(no_return())
Output
10 None
while
while
is used for looping in Python.
The statements inside a while
loop continue to execute until the condition for the while
loop evaluates to False
or a break
statement is encountered. Following program illustrates this.
i = 5 while(i): print(i) i = i - 1
Output
5 4 3 2 1
Note that 0 is equal to False
.
Learn more about Python while loop.
with
with
statement is used to wrap the execution of a block of code within methods defined by the context manager.
Context manager is a class that implements __enter__
and __exit__
methods. Use of with
statement ensures that the __exit__
method is called at the end of the nested block. This concept is similar to the use of try… finally
block. Here, is an example.
with open('example.txt', 'w') as my_file: my_file.write('Hello world!')
This example writes the text Hello world!
to the file example.txt
. File objects have __enter__
and __exit__
method defined within them, so they act as their own context manager.
First the __enter__
method is called, then the code within with
statement is executed and finally the __exit__
method is called. __exit__
method is called even if there is an error. It basically closes the file stream.
yield
yield
est utilisé dans une fonction comme une return
instruction. Mais yield
renvoie un générateur.
Le générateur est un itérateur qui génère un élément à la fois. Une longue liste de valeurs prendra beaucoup de mémoire. Les générateurs sont utiles dans cette situation car ils ne génèrent qu'une seule valeur à la fois au lieu de stocker toutes les valeurs en mémoire. Par exemple,
>>> g = (2**x for x in range(100))
va créer un générateur g qui génère des puissances de 2 jusqu'au nombre deux élevé à la puissance 99. Nous pouvons générer les nombres en utilisant la next()
fonction ci-dessous.
>>> next(g) 1 >>> next(g) 2 >>> next(g) 4 >>> next(g) 8 >>> next(g) 16
Et ainsi de suite… Ce type de générateur est renvoyé par l' yield
instruction d'une fonction. Voici un exemple.
def generator(): for i in range(6): yield i*i g = generator() for i in g: print(i)
Production
0 1 4 9 16 25
Ici, la fonction generator()
renvoie un générateur qui génère un carré de nombres de 0 à 5. Celui-ci est imprimé dans la for
boucle.