Dieses Tutorial enthält kurze Informationen zu allen in Python verwendeten Schlüsselwörtern.
Schlüsselwörter sind die reservierten Wörter in Python. Wir können ein Schlüsselwort nicht als Variablennamen, Funktionsnamen oder andere Bezeichner verwenden.
Hier ist eine Liste aller Schlüsselwörter in der Python-Programmierung
Schlüsselwörter in der Programmiersprache PythonFalsch | erwarten | sonst | importieren | bestehen |
Keiner | brechen | außer | im | erziehen |
Wahr | Klasse | schließlich | ist | Rückkehr |
und | fortsetzen | zum | Lambda | Versuchen |
wie | def | von | nicht lokal | während |
behaupten | del | global | nicht | mit |
asynchron | elif | wenn | oder | Ausbeute |
Die oben genannten Schlüsselwörter können in verschiedenen Versionen von Python geändert werden. Einige zusätzliche werden möglicherweise hinzugefügt oder andere werden möglicherweise entfernt. Sie können die Liste der Schlüsselwörter in Ihrer aktuellen Version jederzeit abrufen, indem Sie Folgendes in die Eingabeaufforderung eingeben.
>>> 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')
Beschreibung der Schlüsselwörter in Python mit Beispielen
Wahr falsch
True
und False
sind Wahrheitswerte in Python. Sie sind das Ergebnis von Vergleichsoperationen oder logischen (Booleschen) Operationen in Python. Beispielsweise:
>>> 1 == 1 True >>> 5> 3 True >>> True or False True >>> 10 >> 3> 7 False >>> True and False False
Hier können wir sehen, dass die ersten drei Anweisungen wahr sind, sodass der Interpreter für die verbleibenden drei Anweisungen zurückgibt True
und zurückgibt False
. True
und False
in Python ist das gleiche wie 1
und 0
. Dies kann mit folgendem Beispiel begründet werden:
>>> True == 1 True >>> False == 0 True >>> True + True 2
Keiner
None
ist eine spezielle Konstante in Python, die das Fehlen eines Werts oder eines Nullwerts darstellt.
Es ist ein Objekt seines eigenen Datentyps, der NoneType
. Wir können nicht mehrere None
Objekte erstellen , sondern sie Variablen zuweisen. Diese Variablen sind einander gleich.
Wir müssen besonders vorsichtig sein, was None
nicht impliziert False
, 0
oder eine leere Liste, ein Wörterbuch, eine Zeichenfolge usw. Zum Beispiel:
>>> None == 0 False >>> None == () False >>> None == False False >>> x = None >>> y = None >>> x == y True
Leere Funktionen, die nichts zurückgeben, geben ein None
Objekt automatisch zurück. None
wird auch von Funktionen zurückgegeben, bei denen der Programmablauf keine return-Anweisung findet. Beispielsweise:
def a_void_function(): a = 1 b = 2 c = a + b x = a_void_function() print(x)
Ausgabe
Keiner
Dieses Programm verfügt über eine Funktion, die keinen Wert zurückgibt, obwohl einige Operationen darin ausgeführt werden. Wenn wir also x drucken, erhalten wir, None
was automatisch (implizit) zurückgegeben wird. In ähnlicher Weise ist hier ein anderes Beispiel:
def improper_return_function(a): if (a % 2) == 0: return True x = improper_return_function(3) print(x)
Ausgabe
Keiner
Obwohl diese Funktion eine return
Anweisung hat, wird sie nicht in jedem Fall erreicht. Die Funktion wird True
nur zurückgegeben, wenn die Eingabe gerade ist.
Wenn wir der Funktion eine ungerade Zahl geben, None
wird sie implizit zurückgegeben.
und oder nicht
and
, or
, not
Sind die logischen Operatoren in Python. and
wird True
nur dann resultieren, wenn beide Operanden sind True
. Die Wahrheitstabelle für and
ist unten angegeben:
and
Wahrheitstabelle für
EIN | B. | A und B |
---|---|---|
Wahr | Wahr | Wahr |
Wahr | Falsch | Falsch |
Falsch | Wahr | Falsch |
Falsch | Falsch | Falsch |
or
wird ergeben, True
wenn einer der Operanden ist True
. Die Wahrheitstabelle für or
ist unten angegeben:
or
Wahrheitstabelle für
EIN | B. | A oder B |
---|---|---|
Wahr | Wahr | Wahr |
Wahr | Falsch | Wahr |
Falsch | Wahr | Wahr |
Falsch | Falsch | Falsch |
not
Der Operator wird verwendet, um den Wahrheitswert zu invertieren. Die Wahrheitstabelle für not
ist unten angegeben:
not
Wahrheitstabelle für
EIN | kein |
---|---|
Wahr | Falsch |
Falsch | Wahr |
Einige Beispiele für ihre Verwendung sind unten angegeben
>>> True and False False >>> True or False True >>> not False True
wie
as
wird verwendet, um beim Importieren eines Moduls einen Alias zu erstellen. Dies bedeutet, dass einem Modul beim Importieren ein anderer Name (benutzerdefiniert) zugewiesen wird.
Wie zum Beispiel hat Python ein Standardmodul namens math
. Angenommen, wir möchten berechnen, welcher Cosinus pi einen Alias verwendet. Wir können es wie folgt machen as
:
>>> import math as myAlias >>>myAlias.cos(myAlias.pi) -1.0
Hier haben wir das math
Modul importiert, indem wir ihm den Namen gegeben haben myAlias
. Jetzt können wir auf das math
Modul mit diesem Namen verweisen . Mit diesem Namen haben wir cos (pi) berechnet und -1.0
als Antwort erhalten.
behaupten
assert
wird zum Debuggen verwendet.
Während der Programmierung möchten wir manchmal den internen Status kennen oder prüfen, ob unsere Annahmen zutreffen. assert
hilft uns dabei und hilft bequemer, Fehler zu finden. assert
wird von einer Bedingung gefolgt.
Wenn die Bedingung erfüllt ist, passiert nichts. Aber wenn die Bedingung falsch ist, AssertionError
wird ausgelöst. Beispielsweise:
>>> 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
yield
wird in einer Funktion wie einer return
Anweisung verwendet. Aber yield
gibt einen Generator.
Generator ist ein Iterator, der jeweils ein Element generiert. Eine große Liste von Werten beansprucht viel Speicher. Generatoren sind in dieser Situation nützlich, da sie jeweils nur einen Wert generieren, anstatt alle Werte im Speicher zu speichern. Beispielsweise,
>>> g = (2**x for x in range(100))
erzeugt einen Generator g, der Potenzen von 2 bis zu der Zahl zwei erzeugt, die auf die Potenz 99 angehoben wird. Wir können die Zahlen mit der next()
unten gezeigten Funktion erzeugen .
>>> next(g) 1 >>> next(g) 2 >>> next(g) 4 >>> next(g) 8 >>> next(g) 16
Und so weiter … Dieser Generatortyp wird von der yield
Anweisung einer Funktion zurückgegeben. Hier ist ein Beispiel.
def generator(): for i in range(6): yield i*i g = generator() for i in g: print(i)
Ausgabe
0 1 4 9 16 25
Hier gibt die Funktion generator()
einen Generator zurück, der ein Zahlenquadrat von 0 bis 5 generiert. Dieses wird in der for
Schleife gedruckt .