Lista de palabras clave en la programación de Python

Este tutorial proporciona información breve sobre todas las palabras clave utilizadas en Python.

Las palabras clave son las palabras reservadas en Python. No podemos usar una palabra clave como nombre de variable, nombre de función o cualquier otro identificador.

Aquí hay una lista de todas las palabras clave en la programación de Python

Palabras clave en el lenguaje de programación Python

Falso	esperar	más	importar	pasar
Ninguna	descanso	excepto	en	aumento
Cierto	clase	finalmente	es	regreso
y	Seguir	para	lambda	tratar
como	def	de	no local	mientras
afirmar	del	global	no	con
asincrónico	elif	Si	o	rendimiento

Las palabras clave anteriores pueden modificarse en diferentes versiones de Python. Es posible que se agreguen algunos extra o se eliminen algunos. Siempre puede obtener la lista de palabras clave en su versión actual escribiendo lo siguiente en el mensaje.

  >>> 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') 

Descripción de palabras clave en Python con ejemplos

Verdadero Falso

Truey Falseson valores de verdad en Python. Son el resultado de operaciones de comparación u operaciones lógicas (booleanas) en Python. Por ejemplo:

  >>> 1 == 1 True >>> 5> 3 True >>> True or False True >>> 10 >> 3> 7 False >>> True and False False 

Aquí podemos ver que las tres primeras declaraciones son verdaderas, por lo que el intérprete regresa Truey regresa Falsepara las tres declaraciones restantes. Truey Falseen python es lo mismo que 1y 0. Esto se puede justificar con el siguiente ejemplo:

 >>> True == 1 True >>> False == 0 True >>> True + True 2 

Ninguna

None es una constante especial en Python que representa la ausencia de un valor o un valor nulo.

Es un objeto de su propio tipo de datos, el NoneType. No podemos crear varios Noneobjetos, pero podemos asignarlos a variables. Estas variables serán iguales entre sí.

Debemos tener especial cuidado que Noneno implique False, 0ni ninguna lista vacía, diccionario, cadena etc. Por ejemplo:

 >>> None == 0 False >>> None == () False >>> None == False False >>> x = None >>> y = None >>> x == y True 

Las funciones nulas que no devuelven nada devolverán un Noneobjeto automáticamente. Nonetambién es devuelto por funciones en las que el flujo del programa no encuentra una declaración de retorno. Por ejemplo:

  def a_void_function(): a = 1 b = 2 c = a + b x = a_void_function() print(x) 

Salida

 Ninguna 

Este programa tiene una función que no devuelve un valor, aunque hace algunas operaciones dentro. Entonces, cuando imprimimos x, obtenemos Noneque se devuelve automáticamente (implícitamente). Del mismo modo, aquí hay otro ejemplo:

 def improper_return_function(a): if (a % 2) == 0: return True x = improper_return_function(3) print(x) 

Salida

 Ninguna 

Aunque esta función tiene una returndeclaración, no se alcanza en todos los casos. La función regresará Truesolo cuando la entrada sea par.

Si le damos a la función un número impar, Nonese devuelve implícitamente.

y, o, no

and, or, notSon los operadores lógicos en Python. andresultará en Truesolo si ambos operandos son True. La tabla de verdad para andse da a continuación:

and Tabla de la verdad para

UN	segundo	A y B
Cierto	Cierto	Cierto
Cierto	Falso	Falso
Falso	Cierto	Falso
Falso	Falso	Falso

orresultará en Truesi alguno de los operandos es True. La tabla de verdad para orse da a continuación:

or Tabla de la verdad para

UN	segundo	A o B
Cierto	Cierto	Cierto
Cierto	Falso	Cierto
Falso	Cierto	Cierto
Falso	Falso	Falso

notEl operador se utiliza para invertir el valor de verdad. La tabla de verdad para notse da a continuación:

not Tabla de la verdad para

UN	No un
Cierto	Falso
Falso	Cierto

algunos ejemplos de su uso se dan a continuación

 >>> True and False False >>> True or False True >>> not False True 

como

asse utiliza para crear un alias al importar un módulo. Significa dar un nombre diferente (definido por el usuario) a un módulo al importarlo.

Como por ejemplo, Python tiene un módulo estándar llamado math. Supongamos que queremos calcular qué coseno pi está usando un alias. Podemos hacerlo de la siguiente manera usando as:

 >>> import math as myAlias >>>myAlias.cos(myAlias.pi) -1.0 

Aquí importamos el mathmódulo dándole el nombre myAlias. Ahora podemos referirnos al mathmódulo con este nombre. Con este nombre calculamos cos (pi) y obtuvimos -1.0la respuesta.

afirmar

assert se utiliza con fines de depuración.

Mientras programamos, a veces deseamos conocer el estado interno o comprobar si nuestras suposiciones son ciertas. assertnos ayuda a hacer esto y encontrar errores de manera más conveniente. assertva seguido de una condición.

Si la condición es verdadera, no pasa nada. Pero si la condición es falsa, AssertionErrorse plantea. Por ejemplo:

 >>> a = 4 >>> assert a >> assert a> 5 Traceback (most recent call last): File "", line 301, in runcode File "", line 1, in AssertionError 

For our better understanding, we can also provide a message to be printed with the 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 

At this point we can note that,

 assert condition, message 

is equivalent to,

 if not condition: raise AssertionError(message)

async, await

The async and await keywords are provided by the asyncio library in Python. They are used to write concurrent code in Python. For example,

 import asyncio async def main(): print('Hello') await asyncio.sleep(1) print('world')

To run the program, we use

 asyncio.run(main())

In the above program, the async keyword specifies that the function will be executed asynchronously.

Here, first Hello is printed. The await keyword makes the program wait for 1 second. And then the world is printed.

break, continue

break and continue are used inside for and while loops to alter their normal behavior.

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

yieldse usa dentro de una función como una returndeclaración. Pero yielddevuelve un generador.

Generator es un iterador que genera un elemento a la vez. Una gran lista de valores ocupará mucha memoria. Los generadores son útiles en esta situación, ya que generan solo un valor a la vez en lugar de almacenar todos los valores en la memoria. Por ejemplo,

 >>> g = (2**x for x in range(100)) 

creará un generador g que genera potencias de 2 hasta el número dos elevado a la potencia 99. Podemos generar los números usando la next()función como se muestra a continuación.

 >>> next(g) 1 >>> next(g) 2 >>> next(g) 4 >>> next(g) 8 >>> next(g) 16 

Y así sucesivamente … Este tipo de generador es devuelto por la yielddeclaración de una función. Aquí hay un ejemplo.

 def generator(): for i in range(6): yield i*i g = generator() for i in g: print(i) 

Salida

 0 1 4 9 16 25 

Aquí, la función generator()devuelve un generador que genera un cuadrado de números del 0 al 5. Esto se imprime en el forciclo.