„Python“ programavimo raktinių žodžių sąrašas

Šioje pamokoje pateikiama trumpa informacija apie visus „Python“ naudojamus raktinius žodžius.

Raktiniai žodžiai yra „Python“ rezervuoti žodžiai. Negalime naudoti raktinio žodžio kaip kintamojo vardo, funkcijos pavadinimo ar kito identifikatoriaus.

Čia pateikiamas visų „Python“ programavimo raktinių žodžių sąrašas

Raktiniai žodžiai „Python“ programavimo kalba

Klaidinga	laukti	Kitas	importas	praeiti
Nė vienas	pertrauka	išskyrus	į	pakelti
Tiesa	klasė	pagaliau	yra	grįžti
ir	Tęsti	dėl	lambda	bandyti
kaip	def	nuo	nevietinė	kol
tvirtinti	del	globalus	ne	su
asinchroninis	elifas	jei	arba	derlius

Pirmiau minėti raktiniai žodžiai gali būti pakeisti skirtingose ​​„Python“ versijose. Kai kurie papildomi priedai gali būti pridėti arba kiti gali būti pašalinti. Visada galite gauti raktinių žodžių sąrašą savo dabartinėje versijoje, įvedę toliau pateiktą eilutę.

  >>> 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') 

„Python“ raktinių žodžių aprašymas su pavyzdžiais

Tiesa, melas

Trueir Falseyra „Python“ tiesos vertybės. Tai yra „Python“ palyginimo operacijų arba loginių (loginių) operacijų rezultatai. Pavyzdžiui:

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

Čia galime pamatyti, kad pirmieji trys teiginiai yra teisingi, taigi vertėjas grįžta Trueir grįžta Falseuž likusius tris teiginius. Trueir Falsepitone yra tas pats kaip 1ir 0. Tai galima pateisinti tokiu pavyzdžiu:

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

Nė vienas

None yra speciali „Python“ konstanta, reiškianti vertės ar nulinės vertės nebuvimą.

Tai yra savo duomenų tipo objektas NoneType. Negalime sukurti kelių Noneobjektų, bet galime priskirti juos kintamiesiems. Šie kintamieji bus lygūs vienas kitam.

Turime imtis specialių atsargumo priemonių, kad Noneneturi reikšti False, 0ar bet kokį tuščią sąrašą, žodynas, eilutę ir tt Pavyzdžiui:

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

Panaikintos funkcijos, kurios nieko negrąžina, grąžins Noneobjektą automatiškai. Nonetaip pat grąžina funkcijos, kuriose programos srautas nesusiduria su grąžinimo sakiniu. Pavyzdžiui:

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

Rezultatas

 Nė vienas 

Ši programa turi funkciją, kuri negrąžina vertės, nors ji atlieka kai kurias operacijas viduje. Taigi, kai atspausdiname x, gauname, Nonekuris grąžinamas automatiškai (netiesiogiai). Panašiai čia yra dar vienas pavyzdys:

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

Rezultatas

 Nė vienas 

Nors ši funkcija turi returnteiginį, ji pasiekiama ne visais atvejais. Funkcija grįš Truetik tada, kai įvestis bus lygi.

Jei funkcijai suteiksime nelyginį skaičių, Nonegrąžinama netiesiogiai.

ir, ar ne

and, or, notYra loginiai operatoriai Python. andrezultatas bus Truetik tuo atveju, jei abu operandai yra True. Toliau pateikiama tiesos lentelė and:

and Tiesos lentelė

A	B	A ir B
Tiesa	Tiesa	Tiesa
Tiesa	Klaidinga	Klaidinga
Klaidinga	Tiesa	Klaidinga
Klaidinga	Klaidinga	Klaidinga

oratsiras, Truejei kuris nors iš operandų yra True. Toliau pateikiama tiesos lentelė or:

or Tiesos lentelė

A	B	A arba B
Tiesa	Tiesa	Tiesa
Tiesa	Klaidinga	Tiesa
Klaidinga	Tiesa	Tiesa
Klaidinga	Klaidinga	Klaidinga

notoperatorius naudojamas invertuoti tiesos vertę. Toliau pateikiama tiesos lentelė not:

not Tiesos lentelė

A	ne A
Tiesa	Klaidinga
Klaidinga	Tiesa

žemiau pateikiami keli jų naudojimo pavyzdžiai

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

kaip

asyra naudojamas slapyvardžiui sukurti importuojant modulį. Tai reiškia, kad moduliui suteikiant kitą pavadinimą (vartotojo apibrėžtą) jį importuojant.

Pavyzdžiui, „Python“ turi standartinį modulį, vadinamą math. Tarkime, kad mes norime apskaičiuoti, kokį kosinusą pi naudoja, naudodamiesi pseudonimu. Mes galime tai padaryti taip as:

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

Čia mes importavome mathmodulį, suteikdami jam pavadinimą myAlias. Dabar galime kreiptis į mathmodulį tokiu pavadinimu. Naudodami šį pavadinimą apskaičiavome cos (pi) ir gavome -1.0atsakymą.

tvirtinti

assert yra naudojamas derinimo tikslams.

Programuodami kartais norime sužinoti vidinę būseną arba patikrinti, ar mūsų prielaidos teisingos. assertpadeda mums tai padaryti ir patogiau rasti klaidas. assertseka sąlyga.

Jei sąlyga teisinga, nieko neįvyksta. Bet jei sąlyga yra klaidinga, AssertionErrorkeliama. Pavyzdžiui:

 >>> 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

yieldyra naudojamas funkcijos, tokios kaip returnsakinys, viduje. Bet yieldgrąžina generatorių.

Generatorius yra iteratorius, generuojantis vieną elementą vienu metu. Didelis vertybių sąrašas užims daug atminties. Generatoriai yra naudingi šioje situacijoje, nes jie sugeneruoja tik vieną vertę vienu metu, užuot saugoję visas reikšmes atmintyje. Pavyzdžiui,

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

sukurs generatorių g, kuris generuos 2 galias iki skaičiaus dviejų, pakeltų iki galios 99. Skaičius galime sugeneruoti naudodamiesi next()funkcija, kaip parodyta žemiau.

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

Ir taip toliau … Tokio tipo generatorius grąžinamas yieldfunkcijos sakiniu. Štai pavyzdys.

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

Rezultatas

 0 1 4 9 16 25 

Čia funkcija generator()grąžina generatorių, kuris sukuria skaičių kvadratą nuo 0 iki 5. Tai atspausdinta forkilpoje.