Python Tutorial
Reerence : https://www.geeksforgeeks.org/python-tutorial/?ref=leftbar-rightbar#sequence
Python is a high-level programming language and is widely being used among the developers’ community. Python was mainly developed for emphasis on code readability, and its syntax allows programmers to express concepts in fewer lines of code. Python is a programming language that lets developers work quickly and integrate systems more efficiently.
This Python 3 tutorial provides learners (either beginner or experienced developer) with the topics from Python basics to advanced topics with examples.
Topics:
Key features
Python has many reasons for being popular and in demand. A few of the reasons are mentioned below.
Emphasis on code readability, shorter codes, ease of writing.
Programmers can express logical concepts in fewer lines of code in comparison to languages such as C++ or Java.
Python supports multiple programming paradigms, like object-oriented, imperative and functional programming or procedural.
It provides extensive support libraries(Django for web development, Pandas for data analytics etc)
Dynamically typed language(Data type is based on value assigned)
Philosophy is “Simplicity is the best”.
Application Areas
Getting started with Python
Python is a lot easier to code and learn. Python programs can be written on any plain text editor like notepad, notepad++, or anything of that sort. One can also use an online IDE for writing Python codes or can even install one on their system to make it more feasible to write these codes because IDEs provide a lot of features like intuitive code editor, debugger, compiler, etc. To begin with, writing Python Codes and performing various intriguing and useful operations, one must have Python installed on their System. This can be done by following the step by step instructions provided below:
What if Python already exists? Let’s check
Windows don’t come with Python preinstalled, it needs to be installed explicitly. But unlike windows, most of the Linux OS have Python pre-installed, also macOS comes with Python pre-installed.
To check if your device is pre-installed with Python or not, just go to Command Line(For Windows, search for cmd in the Run dialog( + R), for Linux open the terminal using Ctrl+Alt+T
, for macOS use control+Option+Shift+T
.
Now run the following command: For Python2
For Python3
If Python is already installed, it will generate a message with the Python version available.
Download and Installation
Before starting with the installation process, you need to download it. For that all versions of Python for Windows, Linux, and MacOS are available on python.org.
Download the Python and follow the further instructions for the installation of Python.
Beginning the installation.
Run the Python Installer from downloads folder. Make sure to mark Add Python 3.7 to PATH otherwise you will have to do it explicitly. It will start installing python on windows.
After installation is complete click on Close. Bingo..!! Python is installed. Now go to windows and type IDLE.
How to run a Python program
Let’s consider a simple Hello World Program.filter_none
Generally, there are two ways to run a Python program.
Using IDEs: You can use various IDEs(Pycharm, Jupyter Notebook, etc.) which can be used to run Python programs.
Using Command-Line: You can also use command line options to run a Python program. Below steps demonstrate how to run a Python program on Command line in Windows/Unix Operating System:
Windows
Open Commandline and then to compile the code type python HelloWorld.py. If your code has no error then it will execute properly and output will be displayed.
Unix/Linux
Open Terminal of your Unix/Linux OS and then to compile the code type python HelloWorld.py. If your code has no error then it will execute properly and output will be displayed.
Fundamentals of Python
Python Indentation
Python uses indentation to highlight the blocks of code. Whitespace is used for indentation in Python. All statements with the same distance to the right belong to the same block of code. If a block has to be more deeply nested, it is simply indented further to the right. You can understand it better by looking at the following lines of code.
Output:
The lines print(‘Logging on to geeksforgeeks…’)
and print(‘retype the URL.’)
are two separate code blocks. The two blocks of code in our example if-statement are both indented four spaces. The final print(‘All set!’)
is not indented, and so it does not belong to the else-block.
Note: For more information, refer Indentation in Python.
Python Comments
Comments are useful information that the developers provide to make the reader understand the source code. It explains the logic or a part of it used in the code. There are two types of comment in Python:
Single line comments: Python single line comment starts with hashtag symbol with no white spaces.
Multi-line string as comment: Python multi-line comment is a piece of text enclosed in a delimiter (“””) on each end of the comment.
Note: For more information, refer Comments in Python.
Variables
Variables in Python are not “statically typed”. We do not need to declare variables before using them or declare their type. A variable is created the moment we first assign a value to it.
Output:
Note: For more information, refer Python Variables.
Operators
Operators are the main building block of any programming language. Operators allow the programmer to perform different kinds of operations on operands. These operators can be categorized based upon their different functionality:
Arithmetic operators: Arithmetic operators are used to perform mathematical operations like addition, subtraction, multiplication and division.
Output:
Relational Operators: Relational operators compares the values. It either returns True or False according to the condition.
Output:
Logical Operators: Logical operators perform Logical AND, Logical OR and Logical NOT operations.
Output:
Bitwise operators: Bitwise operator acts on bits and performs bit by bit operation.
Output:
Assignment operators: Assignment operators are used to assign values to the variables.
Special operators: Special operators are of two types-
Identity operator that contains
is
andis not
.Membership operator that contains
in
andnot in
.
Output:
Note: For more information, refer Basic Operators in Python.
Basics of Input/Output
Taking input from user –
Python provides us with two inbuilt functions to read the input from the keyboard.
raw_input(): This function works in older version (like Python 2.x). This function takes exactly what is typed from the keyboard, convert it to string and then return it to the variable in which we want to store. For example:
input(): This function first takes the input from the user and then evaluates the expression, which means Python automatically identifies whether the user entered a string or a number or list. For example:
Note: For more information, refer Python input()
and raw_input()
.
Printing output to console –
The simplest way to produce output is using the print()
function where you can pass zero or more expressions separated by commas. This function converts the expressions you pass into a string before writing to the screen.
Output:
Data Types
Data types are the classification or categorization of data items. It represents the kind of value that tells what operations can be performed on a particular data. Since everything is an object in Python programming, data types are actually classes and variables are instance (object) of these classes.
Numeric
In Python, numeric data type represent the data which has numeric value. Numeric value can be interger, floating number or even complex numbers. These values are defined as int
, float
and complex
class in Python.
Output:
Sequence Type
In Python, a sequence is the ordered collection of similar or different data types. Sequences allow storing multiple values in an organized and efficient fashion. There are several sequence types in Python –
String
List
Tuple
1) String: A string is a collection of one or more characters put in a single quote, double-quote or triple quote. In python there is no character data type, a character is a string of length one. It is represented by str
class. Strings in Python can be created using single quotes or double quotes or even triple quotes.
Output:
Accessing elements of string –
Output:
Deleting/Updating from a String –
In Python, Updation or deletion of characters from a String is not allowed because Strings are immutable. Only new strings can be reassigned to the same name.
Output:
Note: For more information, refer Python String.
Refer to the below articles to know more about Strings:
2) List: Lists are just like the arrays, declared in other languages. A single list may contain DataTypes like Integers, Strings, as well as Objects. The elements in a list are indexed according to a definite sequence and the indexing of a list is done with 0 being the first index. It is represented by list
class.
Output:
Adding Elements to a List: Using append()
, insert()
and extend()
Output:
Accessing elements from the List –
Use the index operator [ ]
to access an item in a list. In Python, negative sequence indexes represent positions from the end of the array. Instead of having to compute the offset as in List[len(List)-3]
, it is enough to just write List[-3]
.
Output:
Removing Elements from the List: Using remove()
and pop()
Output:
Note: For more information, refer Python List.
Refer to the below articles to know more about List:
3) Tuple: Tuple is an ordered collection of Python objects much like a list. The important difference between a list and a tuple is that tuples are immutable. It is represented by tuple
class. In Python, tuples are created by placing a sequence of values separated by ‘comma’ with or without the use of parentheses for grouping of the data sequence.filter_none
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Output:
Accessing element of a tuple –
Use the index operator [ ]
to access an item in a tuple.filter_none
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Output:
Deleting/updating elements of tuple –
Items of a tuple cannot be deleted as tuples are immutable in Python. Only new tuples can be reassigned to the same name.filter_none
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Output:
Note: For more information, refer Python Tuples.
Refer to the below articles to know more about tuples:
Boolean
Booleans are data type with one of the two built-in values, True
or False
. It is denoted by the class bool.
Output:
Set
In Python, Set is an unordered collection of data type that is iterable, mutable and has no duplicate elements. The order of elements in a set is undefined though it may consist of various elements. Sets can be created by using the built-in set()
function with an iterable object or a sequence by placing the sequence inside curly braces {}
, separated by ‘comma’.
Output:
Adding elements: Using add()
and update()
Output:
Accessing a Set: One can loop through the set items using a for
loop as set items cannot be accessed by referring to an index.
Output:
Removing elements from a set: Using remove()
, discard()
, pop() and clear()
Output:
Note: For more information, refer Python Sets.
Refer to the below articles to know more about Sets:
Dictionary
Dictionary in Python is an unordered collection of data values, used to store data values like a map. Dictionary holds key:value
pair. Each key-value pair in a Dictionary is separated by a colon :
, whereas each key is separated by a ‘comma’. A Dictionary can be created by placing a sequence of elements within curly {}
braces, separated by ‘comma’.
Output:
Nested Dictionary:
Output:
Note: For more information, refer Python Nested Dictionary.
Adding elements to a Dictionary: One value at a time can be added to a Dictionary by defining value along with the key e.g. Dict[Key] = ‘Value’
Output:
Accessing elements from a Dictionary: In order to access the items of a dictionary refer to its key name or use get()
method.
Output:
Removing Elements from Dictionary: Using pop()
and popitem()
Output:
Note: For more information, refer Python Dictionary.
Refer to the below articles to know more about dictionary:
Decision Making
Decision Making in programming is similar to decision making in real life. A programming language uses control statements to control the flow of execution of the program based on certain conditions. These are used to cause the flow of execution to advance and branch based on changes to the state of a program.
Decision-making statements in Python
Example 1: To demonstrate if
and if-else
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Output:
Example 2: To demonstrate nested-if
and if-elif
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Output:
Note: For more information, refer Decision Making in Python.
Control flow (Loops)
Loops in programming come into use when we need to repeatedly execute a block of statements. For example: Suppose we want to print “Hello World” 10 times. This can be done with the help of loops. The loops in Python are:
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# Python program to illustrate # while and while-else loopi
=
0while
(i <
3): i
=
i
+
1 print("Hello Geek")
# checks if list still # contains any element a
=
[1,
2,
3,
4] while
a: print(a.pop())
i
=
10
while
i <
12: i
+=
1 print(i) breakelse:
# Not executed as there is a break print("No Break")
Output:
Note: For more information, refer Python While Loops.
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# Python program to illustrate # Iterating over a list print("List Iteration") l
=
["geeks",
"for",
"geeks"] for
i
in
l: print(i)
# Iterating over a String print("\nString Iteration") s
=
"Geeks"for
i
in
s : print(i)
print("\nFor-else loop")for
i
in
s: print(i) else:
# Executed because no break in for print("No Break\n")
for
i
in
s: print(i) breakelse:
# Not executed as there is a break print("No Break")
Output:
Note: For more information, refer Python For Loops.
range() function:
range()
allows user to generate a series of numbers within a given range. Depending on how many arguments user is passing to the function. This function takes three arguments.1) start: integer starting from which the sequence of integers is to be returned 2) stop: integer before which the sequence of integers is to be returned. 3) step: integer value which determines the increment between each integer in the sequence filter_none
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# Python program to demonstrate# range() function
for
i
in
range(5): print(i, end
=" ") print()
for
i
in
range(2,
9): print(i, end
=" ") print()
# incremented by 3 for
i
in
range(15,
25,
3): print(i, end
=" ")
Output:
Note: For more information, refer Python range() function.
Refer to the below articles to know more about Loops:
Loop control statements
Loop control statements change execution from its normal sequence. Following are the loop control statements provided by Python:
Break: Break statement in Python is used to bring the control out of the loop when some external condition is triggered.
Continue: Continue statement is opposite to that of break statement, instead of terminating the loop, it forces to execute the next iteration of the loop.
Pass: Pass statement is used to write empty loops. Pass is also used for empty control statement, function and classes.
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Output:
Note: For more information, refer break, continue and pass in Python.
Functions
Functions are generally the block of codes or statements in a program that gives the user the ability to reuse the same code which ultimately saves the excessive use of memory, acts as a time saver and more importantly, provides better readability of the code. So basically, a function is a collection of statements that perform some specific task and return the result to the caller. A function can also perform some specific task without returning anything. In Python, def
keyword is used to create functions.filter_none
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Function with arguments
Default arguments: A default argument is a parameter that assumes a default value if a value is not provided in the function call for that argument.filter_none
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# Python program to demonstrate # default arguments
def
myFun(x, y
=
50): print("x: ", x) print("y: ", y)
# Driver codemyFun(10)
Output:
Keyword arguments: The idea is to allow caller to specify argument name with values so that caller does not need to remember order of parameters.filter_none
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# Python program to demonstrate Keyword Arguments def
student(firstname, lastname): print(firstname, lastname)
# Keyword arguments student(firstname
='Geeks', lastname
='Practice') student(lastname
='Practice', firstname
='Geeks')
Output:
Variable length arguments: In Python a function can also have variable number of arguments. This can be used in the case when we do not know in advance the number of arguments that will be passed into a function.filter_none
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# Python program to demonstrate# variable length arguments
# variable argumentsdef
myFun1(*argv): for
arg
in
argv: print(arg, end
=" ")
# variable keyword argumentsdef
myFun2(**kwargs): for
key, value
in
kwargs.items(): print
("% s == % s"
%(key, value))
# Driver code myFun1('Hello',
'Welcome',
'to',
'GeeksforGeeks')print()myFun2(first
='Geeks', mid
='for', last
='Geeks')
Output:
Note: For more information, refer Functions in Python.
Refer to the below articles to know more about functions:
Lambda functions
In Python, the lambda/anonymous function means that a function is without a name. The lambda
keyword is used to create anonymous functions. Lambda function can have any number of arguments but has only one expression.filter_none
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Output:
Note: For more information, refer Python lambda (Anonymous Functions).
Refer to the below articles to know more about Lambda:
Object Oriented Programming
Object-oriented programming aims to implement real-world entities like inheritance, hiding, polymorphism, etc in programming. The main aim of OOP is to bind together the data and the functions that operate on them so that no other part of the code can access this data except that function.
Classes and Objects
Class creates a user-defined data structure, which holds its own data members and member functions, which can be accessed and used by creating an instance of that class. A class is like a blueprint for an object.
An Object is an instance of a Class. A class is like a blueprint while an instance is a copy of the class with actual values.filter_none
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Note: For more information, refer Python Classes and Objects.
The self
self represents the instance of the class. By using the “self
” keyword we can access the attributes and methods of the class in python. It binds the attributes with the given arguments.
Note: For more information, refer self in Python class.
Constructors and Destructors
Constructors: Constructors are generally used for instantiating an object.The task of constructors is to initialize(assign values) to the data members of the class when an object of class is created. In Python the __init__()
method is called the constructor and is always called when an object is created. There can be two types of constructors:
Default constructor: The constructor which is called implicilty and do not accept any argument.
Parameterized constructor:Constructor which is called explicitly with parameters is known as parameterized constructor.
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Output:
Note: For more information, refer Constructors in Python.
Destructors: Destructors are called when an object gets destroyed. The __del__()
method is a known as a destructor method in Python. It is called when all references to the object have been deleted i.e when an object is garbage collected.filter_none
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Note: For more information, refer Destructors in Python.
Inheritance
Inheritance is the ability of any class to extract and use features of other classes. It is the process by which new classes called the derived classes are created from existing classes called Base classes.filter_none
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Note: For more information, refer Python inheritance.
Encapsulation
Encapsulation describes the idea of wrapping data and the methods that work on data within one unit. This puts restrictions on accessing variables and methods directly and can prevent the accidental modification of data.filter_none
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Output:
Note: For more information, refer Encapsulation in Python.
Polymorphism
Polymorphism refers to the ability of OOPs programming languages to differentiate between entities with the same name efficiently. This is done by Python with the help of the signature of these entities. filter_none
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Refer to the articles to know more about OOPS:
File Handling
File handling is the ability of Python to handle files i.e. to read and write files along with many other file handling options. Python treats files differently as text or binary and this is important. Each line of code includes a sequence of characters and they form a text file. Each line of a file is terminated with a special character, called the EOL or End of Line characters like comma {, }
or newline character.
Basic File Handling operations in Python are:
1) Open a file: Opening a file refers to getting the file ready either for reading or for writing. This can be done using the open()
function. This function returns a file object and takes two arguments, one that accepts the file name and another that accepts the mode(Access Mode). Python provides six Access Modes:
ACCESS MODE | DESCRIPTION |
Read Only (‘r’) | Open text file for reading. The handle is positioned at the beginning of the file. |
Read and Write (‘r+’) | Open the file for reading and writing. The handle is positioned at the beginning of the file. |
Write Only (‘w’) | Open the file for writing. For existing file, the data is truncated and over-written. The handle is positioned at the beginning of the file. |
Write and Read (‘w+’) | Open the file for reading and writing. For existing file, data is truncated and over-written. The handle is positioned at the beginning of the file. |
Append Only (‘a’) | Open the file for writing. The handle is positioned at the end of the file. |
Append and Read (‘a+’) | Open the file for reading and writing. The handle is positioned at the end of the file. |
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Note: For more information, refer Open a File in Python.
2) Close the file: close()
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3) Reading from a File: There are three ways to read data from a text file.
read(): Returns the read bytes in form of a string. Reads n bytes, if no n specified, reads the entire file.
readline(): Reads a line of the file and returns in form of a string.For specified n, reads at most n bytes. However, does not reads more than one line, even if n exceeds the length of the line.
readlines(): Reads all the lines and return them as each line a string element in a list.
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Output:
Note: For more information, refer How to read from a file in Python.
4) Writing to a file: There are two ways to write in a file.
write(): Inserts the string str1 in a single line in the text file.
writelines(): For a list of string elements, each string is inserted in the text file. Used to insert multiple strings at a single time.
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Note: For more information, refer Writing to file in Python.
Refer to the below articles to know more about File-Handling:
Modules and Packages
Modules
A module is a self-contained Python file that contains Python statements and definitions, like a file named GFG.py
, which can be considered as a module named GFG
which can be imported with the help of import statement
.
Let’s create a simple module named GFG.filter_none
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To use the above created module, create a new Python file in the same directory and import GFG module using the import
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Output:
Note: For more information, refer Python Modules.
Packages
Packages are a way of structuring many packages and modules which helps in a well-organized hierarchy of data set, making the directories and modules easy to access.
To create a package in Python, we need to follow these three simple steps:
First, we create a directory and give it a package name, preferably related to its operation.
Then we put the classes and the required functions in it.
Finally we create an
__init__.py
file inside the directory, to let Python know that the directory is a package.
Example: Let’s create a package for cars.
First we create a directory and name it Cars.
Then we need to create modules. We will create 2 modules – BMW and AUDI.
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# Python code to illustrate the Modules class
Bmw:
def
__init__(self): self.models
=
['i8',
'x1',
'x5',
'x6']
def
outModels(self): print('These are the available models for BMW') for
model
in
self.models: print('\t % s '
%
model)
For Audi.pyfilter_none
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# Python code to illustrate the Module class
Audi:
def
__init__(self): self.models
=
['q7',
'a6',
'a8',
'a3']
def
outModels(self): print('These are the available models for Audi') for
model
in
self.models: print('\t % s '
%
model)
Finally we create the __init__.py file. This file will be placed inside the Cars directory and can be left blank.
Now, let’s use the package that we created. To do this make a sample.py file in the same directory where Cars package is located and add the following code to it:filter_none
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Note: For more information, refer Create and Access a Python Package.
Regular expressions
Module Regular Expressions(RE) specifies a set of strings(pattern) that matches it. To understand the RE analogy, MetaCharacters are useful, important and will be used in functions of module re
. There are a total of 14 metacharacters:
The most frequently used methods are:
re.findall(): Return all non-overlapping matches of pattern in string, as a list of strings. The string is scanned left-to-right, and matches are returned in the order found.filter_none
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# A Python program to demonstrate working of # findall() import
re
string
=
"""Hello my Number is 123456789 and my friend's number is 987654321"""
# A sample regular expression to find digits. regex
=
'\d+'
match
=
re.findall(regex, string) print(match)
Output:
In the above example, metacharacter blackslash
‘\’
has a very important role as it signals various sequences. If the blackslash is to be used without its special meaning as metacharacter, use’\\’
.re.compile(): Regular expressions are compiled into pattern objects, which have methods for various operations such as searching for pattern matches or performing string substitutions.filter_none
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# A Python program to demonstrate working of # compile() import
re
# it is equivalent to [abcde].p
=
re.compile('[a-e]')
print(p.findall("Aye, said Mr. Gibenson Stark"))
Output:
re.match(): This function attempts to match pattern to whole string. The re.match function returns a match object on success, None on failure.filter_none
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# A Python program to demonstrate working # of re.match(). import
re
def
findMonthAndDate(string):
regex
=
r"([a-zA-Z]+) (\d+)" match
=
re.match(regex, string)
if
match
==
None: print("Not a valid date") return
print("Given Data: % s"
%
(match.group())) print("Month: % s"
%
(match.group(1))) print("Day: % s"
%
(match.group(2)))
# Driver Code findMonthAndDate("Jun 24") print("") findMonthAndDate("I was born on June 24")
Output:
re.search(): This method either returns None (if the pattern doesn’t match), or a re.MatchObject that contains information about the matching part of the string.filter_none
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# A Python program to demonstrate working of re.match(). import
re
regex
=
r"([a-zA-Z]+) (\d+)"
match
=
re.search(regex,
"I was born on June 24")
if
match !=
None:
print("Match at index % s, % s"
%
(match.start(), match.end()))
# this will print "June 24" print("Full match: % s"
%
(match.group(0)))
# this will print "June" print("Month: % s"
%
(match.group(1)))
# this will print "24" print("Day: % s"
%
(match.group(2)))
else: print("The regex pattern does not match.")
Output:
Note: For more information, refer Regular Expression in Python.
Exception handling
Like other languages, Python also provides the runtime errors via exception handling method with the help of try-except.
How try-except works?
First try clause is executed i.e. the code between try and except clause.
If there is no exception, then only try clause will run, except clause is finished.
If any exception occured, try clause will be skipped and except clause will run.
If any exception occurs, but the except clause within the code doesn’t handle it, it is passed on to the outer try statements. If the exception left unhandled, then the execution stops.
A try statement can have more than one except clause.
Code 1: No exception, so try clause will run. filter_none
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Code 2: There is an exception so only except clause will run.filter_none
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Else Clause: In python, you can also use else clause on try-except block which must be present after all the except clauses. The code enters the else block only if the try clause does not raise an exception.filter_none
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Raising Exception: The raise statement allows the programmer to force a specific exception to occur. This must be either an exception instance or an exception class. To know more about the list of exception class click here.filter_none
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Note: For more information, refer Python exception handling.
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