Šajā apmācībā ir sniegta īsa informācija par visiem Python izmantotajiem atslēgvārdiem.
Atslēgvārdi ir Python rezervētie vārdi. Mēs nevaram izmantot atslēgvārdu kā mainīgā nosaukumu, funkcijas nosaukumu vai citu identifikatoru.
Šeit ir visu Python programmēšanas atslēgvārdu saraksts
Atslēgvārdi Python programmēšanas valodā| Nepatiesa | gaidi | cits | importēt | iziet |
| Nav | pārtraukums | izņemot | iekšā | paaugstināt |
| Patiesi | klasē | beidzot | ir | atgriešanās |
| un | Turpināt | priekš | lambda | mēģiniet |
| kā | def | no | nevietā | kamēr |
| apgalvot | del | globāls | nē | ar |
| asinhronais | elif | ja | vai | raža |
Iepriekš minētie atslēgvārdi dažādās Python versijās var tikt mainīti. Daži papildu līdzekļi var tikt pievienoti vai daži var tikt noņemti. Jūs vienmēr varat iegūt atslēgvārdu sarakstu savā pašreizējā versijā, uzvednē ierakstot šo.
>>> 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')
Atslēgvārdu apraksts Python ar piemēriem
Patiesi, nepatiesi
Trueun Falseir patiesības vērtības Python. Tie ir Python salīdzināšanas darbību vai loģisko (Būla) darbību rezultāti. Piemēram:
>>> 1 == 1 True >>> 5> 3 True >>> True or False True >>> 10 >> 3> 7 False >>> True and False False
Šeit mēs varam redzēt, ka pirmie trīs apgalvojumi ir patiesi, tāpēc tulks atgriežas Trueun atgriežas Falsepar pārējiem trim apgalvojumiem. Trueun Falsepitonā ir tāds pats kā 1un 0. To var pamatot ar šādu piemēru:
>>> True == 1 True >>> False == 0 True >>> True + True 2
Nav
None ir īpaša konstante Python, kas norāda vērtības vai nulles vērtības neesamību.
Tas ir sava veida datu objekts NoneType. Mēs nevaram izveidot vairākus Noneobjektus, bet mēs varam tos piešķirt mainīgajiem. Šie mainīgie lielumi būs vienādi.
Mums ir īpaši rūpējas, kas Nonenenozīmē False, 0vai jebkuru tukšu sarakstu, vārdnīcas, auklas utt Piemēram:
>>> None == 0 False >>> None == () False >>> None == False False >>> x = None >>> y = None >>> x == y True
Void funkcijas, kas neko neatgriež, Noneautomātiski atgriezīs objektu. Nonetiek atgriezta arī ar funkcijām, kurās programmas plūsma nesaskaras ar atgriešanās paziņojumu. Piemēram:
def a_void_function(): a = 1 b = 2 c = a + b x = a_void_function() print(x)
Rezultāts
Nav
Šai programmai ir funkcija, kas neatgriež vērtību, lai gan tā veic dažas darbības iekšpusē. Tātad, drukājot x, mēs saņemam to, Nonekas tiek automātiski atgriezts (netieši). Līdzīgi, šeit ir vēl viens piemērs:
def improper_return_function(a): if (a % 2) == 0: return True x = improper_return_function(3) print(x)
Rezultāts
Nav
Lai arī šai funkcijai ir returnpaziņojums, tā netiek sasniegta visos gadījumos. Funkcija atgriezīsies Truetikai tad, kad ievade būs vienmērīga.
Ja funkcijai piešķiram nepāra skaitli, Nonenetieši tiek atgriezta.
un, vai ne
and, or, notIr loģiskie operatori Python. andradīs vērā Truetikai tad, ja abi operandi ir True. Turpmāk andsniegta patiesības tabula :
and Patiesības tabula
| A | B | A un B |
|---|---|---|
| Patiesi | Patiesi | Patiesi |
| Patiesi | Nepatiesa | Nepatiesa |
| Nepatiesa | Patiesi | Nepatiesa |
| Nepatiesa | Nepatiesa | Nepatiesa |
orradīsies, Trueja kāds no operandiem ir True. Turpmāk orsniegta patiesības tabula :
or Patiesības tabula
| A | B | A vai B |
|---|---|---|
| Patiesi | Patiesi | Patiesi |
| Patiesi | Nepatiesa | Patiesi |
| Nepatiesa | Patiesi | Patiesi |
| Nepatiesa | Nepatiesa | Nepatiesa |
notoperators tiek izmantots, lai apgrieztu patiesības vērtību. Turpmāk notsniegta patiesības tabula :
not Patiesības tabula
| A | nevis A |
|---|---|
| Patiesi | Nepatiesa |
| Nepatiesa | Patiesi |
daži to izmantošanas piemēri ir sniegti zemāk
>>> True and False False >>> True or False True >>> not False True
kā
astiek izmantots, lai izveidotu aizstājvārdu, importējot moduli. Tas nozīmē, ka, importējot moduli, tiek piešķirts cits nosaukums (lietotāja definēts).
As for example, Python has a standard module called math. Suppose we want to calculate what cosine pi is using an alias. We can do it as follows using as:
>>> import math as myAlias >>>myAlias.cos(myAlias.pi) -1.0
Here we imported the math module by giving it the name myAlias. Now we can refer to the math module with this name. Using this name we calculated cos(pi) and got -1.0 as the answer.
assert
assert is used for debugging purposes.
While programming, sometimes we wish to know the internal state or check if our assumptions are true. assert helps us do this and find bugs more conveniently. assert is followed by a condition.
If the condition is true, nothing happens. But if the condition is false, AssertionError is raised. For example:
>>> 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
yieldtiek izmantots tādas funkcijas iekšienē kā returnpaziņojums. Bet yieldatgriež ģeneratoru.
Ģenerators ir iterators, kas vienlaikus ģenerē vienu vienumu. Liels vērtību saraksts aizņems daudz atmiņas. Ģeneratori šajā situācijā ir noderīgi, jo vienlaikus tiek ģenerēta tikai viena vērtība, nevis visas vērtības tiek glabātas atmiņā. Piemēram,
>>> g = (2**x for x in range(100))
izveidos ģeneratoru g, kas ģenerē jaudu 2 līdz skaitlim divi, kas paaugstināti līdz jaudai 99. Skaitļus varam ģenerēt, izmantojot next()funkciju, kā parādīts zemāk.
>>> next(g) 1 >>> next(g) 2 >>> next(g) 4 >>> next(g) 8 >>> next(g) 16
Un tā tālāk … Šāda veida ģeneratorus atgriež yieldfunkcijas paziņojums. Šeit ir piemērs.
def generator(): for i in range(6): yield i*i g = generator() for i in g: print(i)
Rezultāts
0 1 4 9 16 25
Šeit funkcija generator()atgriež ģeneratoru, kas ģenerē skaitļu kvadrātu no 0 līdz 5. Tas tiek izdrukāts forcilpā.
