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Contributors should go through theContributing Guide to learn how you can contribute to the project.

byAnkit Mahato [About]
Version 2022.10

This book can be consumed in 3 ways:

• A nice web interface -Link
• A Downloadable PDF -Link
• Directly on GitHub -Link

• Introduction
  • Introduction to Programming Languages
  • Introduction to Python
  • Advantages of Python
  • Installing Python in Windows
  • Installing Python in macOS (Apple)
  • Execution Modes
  • Interactive Mode of Execution
  • Script Mode of Execution
• Python Fundamentals
  • Tokens: Introduction
  • Tokens: Keywords
  • Tokens: Identifiers
  • Tokens: Literals
  • Tokens: Operators
  • Tokens: Delimiters
  • Character Set
  • Blocks and Indentation
  • Comments
• Variables, Objects & Data Types
  • What are Objects & Variables?
  • Variables & Assignment Statements
  • Built-in Data Types
  • Type Checking
  • Type Casting
    • Implicit Type Casting
    • Explicit Type Casting
  • Mutable & Immutable Data Types
    • Immutable Data Types
    • Mutable Data Types
• Input / Output
  • How to Accept User Input
  • Displaying Output
• Operators & Expressions
  • Introduction to Operators
  • Arithmetic Operators
  • Relational Operators
  • Assignment Operators
  • Logical Operators
  • Identity Operators
  • Membership Operators
  • Expressions
  • Operator Precedence with Examples
• Errors & Exception Handling
  • Error Types
  • Syntax Error
  • Runtime Error
  • Logical Error
  • Exceptions
  • Exception Handling
• Control Flow
  • Introduction to Control Flow
  • Sequential Flow
  • Selection Statements: if .. else
  • Iteration: for
  • Iteration: while
  • Jump Statements
    • pass
    • break
    • continue
  • Nested Loops
• Strings
  • Strings: Introduction & Creation
  • Accessing Characters of a String
  • String Operations
  • Introduction to String Methods
  • Convert Case of Strings
  • Check Characters of a String
  • Split a String
  • Strip Characters from a String
  • Check Prefix or Suffix in a String
  • Find & Replace Characters in a String
  • Traversing a String
• List
  • What is a Python List? How to Create a List?
  • Accessing Items of a List
    • Negative Indexing
  • Modifying a List
  • Removing Item from a List
  • List Operations
  • Traversing a List
  • Built-in Functions that can be used for a List
  • Introduction to List Methods
  • Adding Items to a List
  • Removing Items from a List
  • Counting or Locating Items in a List
  • Reversing Items
  • Sorting a List
  • Copying a List
  • Nested List
  • List Comprehension
    • Member-wise Operation
    • Filtering or Subsequence
  • Sample Programs
• Tuple
  • List vs Tuple
  • How to Create Tuple?
  • What is a Singleton?
  • Accessing Items of a Tuple
  • Tuples are Immutable
  • Tuple Operations
  • Traversing a Tuple
  • Built-in Functions that can be used for a Tuple
  • Locating Items in a Tuple
  • Counting the Occurrence of an Item
  • New Tuple with Reversed Items
  • New Tuple with Sorted Items
  • Nested Tuple
  • Understanding the Immutable Nature of Tuples
• Dictionary
  • What is a Dictionary?
  • How to Create a Dictionary
    • Key: Value Pairs
    • Sequence of (key, value) Tuples
    • Keyword/Named Arguments
    • Key and Value Lists
    • Keys with Default Value
  • Accessing Items (Key:Value) of a Dictionary
  • Updating a Dictionary
  • Removing an Item (Key:Value) from a Dictionary
  • Dictionary Operations
  • Traversing a Dictionary
  • Built-in Functions for a Dictionary
  • Creating a Copy of a Dictionary
  • Nested Dictionary
  • Sample Programs
• Python Standard Library
  • Built-in Functions
  • Mathematical Functions
  • Type Functions
    • Type Checking
    • Built-in Type Functions
  • I/O Functions
  • Base/Unicode Conversion Functions
  • What are Built-in Modules?
  • math Module
    • Constants
    • Functions
  • random Module
  • statistics Module
• File Handling
  • File Handling in Python - Introduction & Overview
  • Text Files vs Binary Files - Use Case, File Formats, Examples
  • File Opening & Closing
  • File Reading
    • Sequential Reading
    • Ad-hoc Reading
  • Writing a File
  • Reading & Writing Binary Files using pickle Module
    • Dumping Data
    • Loading Data
    • Example: Traversing a Binary File
  • Reading & Writing a CSV File using csv Module
    • Reading CSV File
    • Writing CSV File
• User Defined Functions, Modules & Packages
  • User Defined Functions
  • Function Structure
    • Function Header
    • Function Body
  • Parameters and Arguments
  • Scope of Variables
    • Local Variables
    • Global Variables
  • Passing Objects of Mutable Type to a Function
    • Passing a List
    • Passing a Dictionary
  • What is a Module? How to Create a Module?
  • Executable Scripts / Modules
  • What is a Package? Introduction to PyPi. How to Create a Python Package?

In today's digital era, we depend on computers, smartphones and the internet to perform a plethora of tasks, like:

• A mathematical task, such as finding the square root of a number or solving a set of simultaneous equations.
• A text-based task such as reading a document and performing search/replace.
• Streaming and playing multimedia files containing audio and video.
• Using a search engine to find and visit a website.
• Playing an online multiplayer game with friends.
• and many more...

Softwares play an important role as they translate human activity into corresponding machine instructions which are executed to accomplish these tasks.

Asoftware is a collection of programs where each program provides a sequence of instructions specifying how the computer should act.

These instructions have to be provided inmachine language orlow level language (0s and 1s) that is difficult to read or write for a human being.

This led to the invention ofhigh-level programming languages in which programs can be easily written and managed. The human-readable programs written using high-level languages are converted into computer-readable machine code or byte-code usingcompilers orinterpreters.

There are many high-level programming languages that are currently in wide use.

Some of the popular languages are Java, C, C++, C#, Go, Swift, JavaScript, PHP, Dart, Kotlin and Python.

Guido van Rossum started the development of Python in December 1989. He released the first version (0.9.0) of Python for general public on February 20, 1991.

The language evolved over the next few decades and so did its definition, the current version of which is stated below:

Python is a high-level, interpreted, object-oriented programming language with dynamic semantics.

Let us break down and analyze the above definition to gain a better understanding of Python:

High-level

Python is ahigh-level programming language which can be used to write a program in natural language (english) making it readable, writable, shareable and manageable.

While developing a Python program one is not required to handle the various components of computer architecture like registers, memory addresses and call stacks which have to be handled if an assembly language or a low-level language is used for development.

Python includes high-level language features like variables, data structures (lists, dictionaries, etc.), objects, expressions, modules, classes, functions, loops, threads, file handling, string handling, error handling and other computer science abstraction concepts.

Interpreted

In traditional programming languages like C or C++, codes are compiled into computer-readable machine code before it can be executed.

Python is aninterpreted language where the Python interpreter reads and executes the program line by line.

The process is more time consuming compared to compiled code execution, but allows faster development as one does not have to go through the entire compilation step during testing and debugging. Also, the code can run on any platform as long as it has a valid Python installation (which includes interpreter) as there is no generation of platform dependent binaries.

Object-oriented

Python does not enforceObject-oriented programming (OOP), but completely supports it.

A programmer can define Classes specifying the data in the form of attributes (or properties) and some programming logic in the form of member functions (or methods). Once a class is defined, the user can create an instance of that class which is known as an object.

In Python, everything (int,list,dict, etc.) is an object. We will cover more about objects in detail in the later sections.

Dynamic Semantics

As Python is an interpreted language in which the code is executed line-by-line, a python statement or expression is evaluated during run-time. This allowsdynamic typing (type of a variable can change over its lifetime) and creation of dynamic objects during run-time, which provides more flexibility, usability and fewer lines of code as compared to statically-typed compiled languages like C/C++.

The key advantages of Python are as follows:

1. Easy to Learn

The Python programming language is easy to learn with low technical and conceptual overhead. This makes it an ideal language for beginners to learn programming.

2. Clear Syntax & Fewer Lines of Code

Python's simple and easy to learn syntax increases code readability and leads to fewer lines of code.

A typical task which requires an average of twenty lines of code in C and seven in Java can often be done with just one line in Python.

Also, due to fewer lines of code the chances of making any error is significantly reduced.

3. Open Source

Python is an open source programming language, so anyone can view and contribute to its source code.

4. Portable & Platform Independent

The Python programming language is portable & platform independent as it can work on any Linux, MacOS or Windows device.

5. Standard Library & Python Packages

Python has a rich and extensive Standard Library, a collection of predefined functions for various tasks.

Python programmers also have at their disposal the vast ecosystem of more than 250,000 community contributed libraries in the Python Package Index (PyPI), where one can find a solution to every conceivable task.

6. Web Application Development

Some of the most popular web development frameworks (django, flask, etc.) are written in Python. This coupled with the availability of packages to connect to any database makes Python a great choice for web application development.

Let's start with the Python 3 installation process on Windows operating system.

Step 1: Download Installer

Download the latest Windows installer from thePython Software Foundation website.

Step 2: Install Python 3

Once the download is complete double-click and run it.

Select the checkbox ✅Add Python 3.9 to PATH. This will enable you to install python packages and run python script via command-line.

Hit 🛡️Install Now and complete the setup.

Step 3: Verify Installation

Once the setup is complete, click on theStart menu and openPython 3.9 -> IDLE (Python 3.9 64 bit) to launch the Python interpreter.

Python 3.9 is now successfully installed on your computer.

Let's start with the Python 3 installation process on macOS operating system.

Step 1: Download Installer

Download the latest macOS installer from thePython Software Foundation website.

Step 2: Install Python 3

Once the download is complete double-click and run it.

HitContinue and complete the setup.

Step 3: Verify Installation

Once the setup is complete, click on theLaunchpad -> IDLE to launch the Python interpreter.

Python 3.9 is now successfully installed on your computer.

After installing the latest version of the Python interpreter, we can now write and execute some basic Python codes.

There are two ways to execute a Python program:

1. Interactive Mode: When the IDLE application is launched, the Python interpreter or the Python shell pops up on the screen. User can interact with the Python interpreter and execute statements (single line or multiline code snippets) directly in this Python shell.
2. Script Mode: This is the most commonly used method for executing a Python program. The entire Python program is written and saved in a file (.py extension) which can be executed using the IDLE application.

Let us execute some basic Python statements and interact with the Python shell.

Launching the Python Shell

To launch the IDLE application click[Windows Start Menu Button] -> [Python 3.9 Folder] -> [IDLE (Python 3.9 64 bit)].

The Python interpreter or the Python shell will pop-up on the screen.

The version (3.9) of the Python interpreter is displayed at the top of the window followed by the>>> symbol which indicates that the interpreter is ready to take instructions.

Python commands or statements can be input on this prompt. The input statements are executed instantaneously and any variable assignments are retained as long as the session is not terminated.

Basic Arithmetic

Let us perform some basic arithmetic operations in the interactive mode using an integer number (2) and a floating-point number (3.5):

>>>2+24>>>2*3.57.0

It can be observed that the results of each of the above computations are displayed immediately in the shell.

Storing Values/Results

Instead of immediately displaying the results, they can also be stored in variables using the assignment symbol (=) as shown below:

>>>a=2+2>>>b=2*3.5

The values ofa andb can be accessed later for future calculations as shown below:

>>>a4>>>b7.0>>>a*520>>>b/32.3333333333333335

Basic String Operation

Interactive mode is not just restricted to basic arithmetic or assignments. Let us join two strings -"Hello, " and"world!".

>>>"Hello, "+"world!"'Hello, world!'

The complete functionality of Python is easily accessible to a user via theInteractive Mode.

This makes it convenient for testing and instant execution of small code snippets (single line or few lines of code), a feature not available in compiled languages like C, C++ and Java.

But, the statements cannot be saved for future use and have to retyped for re-execution. This disadvantage is overcome by the use of Python inScript Mode as described in the next section.

To write reusable codes, script mode is the most preferred mode of code execution.

File Creation

To create a new file using the IDLE application click[File] -> [New File]

Write a simple Python program as shown below

a=2+2a

and save the script asexample.py (.py file extension for all Python scripts) using[File] -> [Save As...]

Script Execution

Now run this script using[Run] -> [Run Module].

It can be observed that the code has been executed, but no output is displayed on the console (or the standard output) as all outputs have to be explicitly specified when running a code in the script mode.

This can be done by using theprint() function which is used in Python scripts to display output on the output stream. Let us quickly add theprint() function in the above code and execute it.

a=2+2print(a)

Now, when you run the script you will observe that the value ofa, that is4, is now displayed on the console.

When a Python code is executed, the Python interpreter reads each logical line and breaks it into a sequence of lexical units.

These lexical units are better known astokens - the smallest individual units of a program. They are the building blocks of a Python code and can be classified into one of the following categories:

• Keywords : Reserved words that convey special meaning when processed by the Python interpreter.
• Identifiers : Names defined by the programmer to refer to objects that can represent variables, functions, classes, etc.
• Literals : Values specified in the program which belong to exactly one of the Python's built-in data types.
• Delimiters : Symbols that denote grouping, punctuation, and assignment/binding.
• Operators : Symbols that can operate on data and compute results.

Keywords are reserved words that have special meaning when processed by the Python interpreter. They are case-sensitive and cannot be used for naming identifiers (class, function, variable or structure names).

The list of keywords in Python are provided below:

Identifiers are used for defining the names of Python objects such as variables, functions, classes, modules, etc. The naming convention for identifiers is as follows:

• Must begin with a lowercase character (a-z) or an uppercase character (A-Z) or underscore sign (_).
• Followed by any number of letters (a-z,A-Z), digits (0-9), or underscores (_).
• Should not be a keyword.
• No special symbols are allowed like!,@,#,$,%, etc.

Some points to keep in mind while naming identifiers:

• Identifiers are case-sensitive in nature and any difference in case of any character refers to a different identifier. e.g.,length andLength are different identifiers.
• Identifiers differing by only underscores are different. e.g.,unitlength andunit_length are different identifiers.

It is also a good practice (although not compulsory) to follow the following procedure while naming identifiers:

• Identifiers should be named carefully with an emphasis on clarity and readability. For example, in a program that calculates the area of a rectangle, a good choice for identifier names are -length,breadth andarea.
• Class names should start with uppercase character.
• Identifiers starting with an underscore have special meaning in a program.
• Variable, function and method names should be in lowercase characters, with underscores separating multiple words likearea_of_square,area_of_triangle, etc.

Literals are tokens in the source code which represent fixed or constant values. They are often used in assignment statements for initializing variables or in comparison expressions.

The various types of literals available in Python are as follows:

Numeric literals are used for representing numeric values in the source code. They can be of three types - integers, float point numbers and imaginary numbers.

Integer literals are numbers without any fractional component.

In Python, integer literals can be written in four positional (base) numeral systems:

i. Decimal or base-10 Integer

A decimal integer literal consists of one or more digits (0-9) and cannot have any zeros preceding the first non-zero digit, except when the number is0.

Example base-10 integers:

3432832988640

092 is not a valid decimal integer literal as a zero precedes the first non-zero digit9.

ii. Binary or base-2 Integer

A binary integer or base-2 integer begins with0b or0B followed by binary digits0-1.

For example,27 can be written as a binary integer literal0b11011.

iii. Octal or base-8 Integer

An octal integer or base-8 integer begins with0o or0O followed by octal digits0-7.

For example,27 can be written as an octal integer literal0o33.

iv. Hexadecimal or base-16 Integer

A hexadecimal integer or base-16 integer begins with0x or0X followed by digits0-9 or lettersA-F (case insensitive).

For example,27 can be written as a hexadecimal integer literal0x1B or0x1b.

Thus, it can be observed that number27 can be written in the program as27 (decimal),0b11011 (binary),0o33 (octal) or0x1B (hexadecimal).

Underscores in Integer Literals

An optional character_ (underscore) is also allowed in an integer literal to group digits for enhanced readability.

One underscore can occur between digits, and after base specifiers like0o.

They are ignored while determining the actual numerical value of the literal.

Some valid underscore usages are -10_00_00_000,0b_1110_0101,0x23_123.

Floating point literals are real numbers present in the source code. They contain fractional component and/or exponential component.

The fractional component includes the digits after the decimal point (.).

Example floating point literals:

3.4.48.3.4E23.4e-2

In the above example,.4 is equivalent to0.4 and8. is equivalent to8.0.

The exponential component can be identified by the lettere orE followed by an optional sign (+ or-) and digits (0-9). This exponent is equivalent to multiplying the real number with the power of10.

For example,3.4E2 is equivalent to3.4 x 10^2 or340.0, whereas3.4e-2 is equivalent to3.4 x 10^-2 or.034.

To specify complex numbers and perform complex number mathematics, Python supports imaginary literals which are given by real or integer number followed by the letterj orJ which represents the unit imaginary number.

Example imaginary literals:

3.5j   15.j    12j     .005j   3e100j   3.5e-10j

Points to Note

In Python,

• there is no specialized literal such as a complex literal. A complex number is actually represented in the program using an expression comprising a real number (integer/float numeric literal) and an imaginary number (imaginary literal). For example,1 + 2j consists of an integer literal (1) and a imaginary literal (2j).
• numeric literals do not include the minus sign (-).- is actually a unary operator it combines with a numeric literal to represent negative numbers. For example, in-3.14 the numeric literal is3.14 and- is an operator.

The reserved wordsTrue andFalse are also boolean literals which can be used to specify the truth value in a program.

String literals are texts which can be specified in a variety of ways in Python:

• Single quotes:'python'
• Double quotes:"python"
• Triple quoted:'''Triple python''',"""Three python""".

Triple quoted strings can also span multiple lines.

Example:

s="I am a String"s1="""AmultilineString"""s2='''Also amultilineString'''

The backslash (\) character can be used in a string literal to escape characters that otherwise have a special meaning, such as newline, linefeed, or the quote character.

Although\' and\" can be used to specify quote characters, Python allows embedding double quotes inside a single-quoted string ('My name is "Python".') and single quotes inside a double-quoted string ("Python's World").

String literals also support unicode characters which can be specified using\u escape sequence followed by the 4 letter unicode.

>>>print("E = mc\u00B2")E=mc²

In the above example,\u00B2 is the unicode character which represents the 'SUPERSCRIPT TWO'.

None is a special literal which is used to denote the absence of value.

It should not be confused with0 as0 is an integer literal with a defined finite value, whereasNone implies nothingness.

>>>a=None>>>a>>>

In the above example, the Python shell does not display any value ofa as it is assigned asNone which has no value.

Python has the provision for specifying a collection of literals in the source code using a special syntax known as"displays".

One can create specialized containers like list, set and dictionary using this syntax.

Some example collection of literals (displays) are provided below:

• List:a = ['a', 'b', 'c']
• Set:a = {'a', 'b', 'c'}
• Dictionary:a = {'a':1, 'b':2, 'c':3}

List, set and dictionary will be covered in detail in later chapters.

Operators are tokens which can be combined with values and variables to create expressions which evaluate to a single value. Python supports a rich set of operators:

+-***///%      @<<>>&|^~       :=<><=>===!=

Each of the above operators are covered in detail in the chapter - Operators.

Delimiters are tokens which are useful for organizing a program and are used in statements, expressions, functions, literal collections, and various other code structures.

They can be classified based on utility as follows:

(),[] and{} are delimiters used for:

• grouping expressions which can be spread across multiple physical lines.
• creating collection of literals like list display, dictionary display, set display.
• creating parenthesized sub-expression having the highest operator precedence (evaluated first) in a complex expression.

Example

days= ['Sunday','Monday','Tuesday','Wednesday','Thursday','Friday','Saturday']sum_6= (1+2+3+4+5+6)

is equivalent to

days= ['Sunday','Monday','Tuesday','Wednesday','Thursday','Friday','Saturday']sum_6= (1+2+3+4+5+6)

Tokens in Python which are used for punctuation, decoration and annotation are:

.       ,       :;       @       ->

The assignment or binding delimiters are used for binding objects to names via assignment statements. The complete list of tokens are provided below:

=       +=      -=      *=/=      //=     %=      **=@=      &=      |=      ^=<<=     >>=

Except=, the rest of the tokens have an operator followed by= character.

These delimiters are also known as augmented assignment operators as they perform an operation in combination with assignment.

A set of valid characters that a programming language recognizes is known as itscharacter set.

Python is a new age programming language which supports Unicode encoding standard. The default encoding for Python source code is UTF-8 (Unicode Transformation Format – 8-bit) which enables developers to use Unicode characters not only as literals, but also as identifiers.

This makes Python one of the very few programming languages that support multiple languages as shown in the example below:

Code

message="हिन्दी में print करे"print(message)क=1# Devanagari Letter KAক=2# Bengali Letter KAக=3# Tamil Letter KAક=4# Gujarati Letter KAprint(क+ক+க+ક)

Output

हिन्दी में print करे10

In traditional programming languages like C++ or Java, programs are organised in form of code blocks.

Each code block contains one or more statements which are enclosed between braces -{ and} and are executed sequentially.

A sample C++/Java code is provided below which checks for an inputx.

C++

if (x <10) {    cout <<"x is less than 10" << endl;if (x <=5) {        cout <<"x is less than or equal to 5" << endl;    }else {        cout <<"x is more than 5 but less than 10" << endl;    }}else {    cout <<"x is not less than 10" << endl;}

Java

if (x <10) {System.out.println("x is less than 10");if (x <=5) {System.out.println("x is less than or equal to 5");    }else {System.out.println("x is more than 5 but less than 10");    }  }else {System.out.print("x is not less than 10");}

It can be seen how indentations (tab at the beginning of line) are added (not required by programming language) to the code to increase readability, which helps in guiding readers through the code.

Python

Code blocks in Python are inspired by this idea as it makes it easier to understand a Python code.

A block of code is denoted by line indentation, typically4 spaces (preferred) or atab. This indentation is used to determine the logical group of statements, with all statements within a group having the same level of indentation.

The corresponding Python code for the above C++/java examples is provided below.

Notice how the code blocks are indented according to the logic.

ifx<10:print("x is less than 10")ifx<=5:print("x is less than or equal to 5")else:print("x is more than 5 but less than 10")else:print("x is not less than 10")

Python supports single-line comments and multi-line comments to enhance code readability via adding documentation.

A single line comment begins with#. Everything between# and the end of line is ignored by the Python interpreter.

# A single line comment.a=1# assign a

A multiline comment begins with''' or""" and ends with the same.

"""I ama multilinecomment."""'''I amalso a multilinecomment.'''

As compared to single line comments, multiline comments should begin at the same indentation level corresponding to their code block.

For example,

"""Begin programhere"""ifx<10:"""    Enter code block when x    is less than 10    """print("x is less than 10")ifx<=5:"""        Enter code block when x        is less than or equal to 5        """print("x is less than or equal to 5")else:"""        Enter code block when x        is more than 5 but less than 10        """print("x is more than 5 but less than 10")else:"""    Enter code block when x    is not less than 10    """print("x is not less than 10")

A program is a sequence of instructions which often acts on information (data) provided by the user.

The process of creating, storing and manipulating this data helps in the computation of new data or the end result.

Variables are the fundamental building blocks of a program which provide a way to store, access and modify values during the life-cycle of a program.

Each variable has:

• a name (handle),
• a type or data-type (kind of data), and
• a value (actual data).

In traditional programming languages like Java or C++, the type of the variable is pre-defined.

For example, if you want to use the value1 inside the program, you can store it in a variable nameda of typeint.

int a = 1;

Thisa is synonymous to a box of fixed dimensions (fixed type) holding something (value1) inside it.

In case we want to change the contents of the box, we can replace it with something similar (same type).

a = 2;

The contents of this box can be replicated and placed in a similar (same type) box:

int b = a;

Multiple boxes can exist, each containing an item having the same value.

int x = 3;int y = 3;int z = 3;

As shown above, the programming languages in which the variables (named boxes) are declared along with their types (size of the boxes) are known asstatically typed languages.

The size of these boxes cannot change later in the program until the variable is re-initialized with the same name and different type.

Python is a dynamically-typed language, where every value or data item (of any type like numeric, string, etc.) is an object.

The variable names are just name-tags pointing to the actual object containing data of any type.

As there is no need of any variable declaration in Python before usage, there is no concept of default value (an empty box ornull) which exists in other programming languages.

Whenever a new object is created in Python, it is assigned a unique identity (ID) which remains the same throughout the lifetime of that object. This ID is the address of the object in memory and the built-in functionid() returns the value of this address.

>>>a=1>>>id(a)140407745943856>>>a=2>>>id(a)140407745943888

In the above example, the ID ofa changes as it points to a new object (2).

>>>b=a>>>id(b)140407745943888

Also, whena is assigned tob, instead of creating a new copy,b points to the same object asa.

A variable is uniquely identified by a name (identifier) and follows the same naming convention:

• Must begin with a lowercase character (a-z) or an uppercase character (A-Z) or underscore sign (_).
• Followed by any number of letters (a-z,A-Z), digits (0-9), or underscores (_).
• Should not be a keyword.
• No special symbols are allowed like!,@,#,$,%, etc.

Variables can be bound to a reference of an object (of any type) using assignment statements.

You can create an object (data) and bind it's reference to a variable using equal sign (=):

count=100# integerpi=3.141# real numbername="Python"# string

Here, L-value refers to the assignable variables (count,pi,name) on the left side of the assignment and R-value refers to the expression on the right side of the assignment operator that has a value (100,3.141,"Python").

As variables are just references, you can rebind them to another object of same or different type:

a=100# integera=3.141# real numbera="Python"# string

Thedel statement can be used to unbind the reference to an object.

>>>a=10>>>dela>>>aTraceback (mostrecentcalllast):File"<stdin>",line1,in<module>NameError:name'a'isnotdefined

Accessinga results in aNameError as the reference (variable) to the object holding value10 is deleted.

The object is also automatically cleaned up from the memory if there is no other variable referencing to it (garbage collection).

In Python, multiple assignment can be used to condense variables which are set to the same value:

>>>x=y=z='foo'>>>x'foo'>>>y'foo'>>>z'foo'

In Python, a temporary variable is not required to swap values of two variables. Values can be directly swapped (tuple swapping) as shown below:

>>>a='Hello'>>>b='World'>>>b,a=a,b>>>a'World'>>>b'Hello'

In Python, thetype of a data (or value) is not linked to the variable, but to the actual object which contains it. This type is also known as the object's data type and is used for identifying the operations that can be performed on the data.

The following built-in data types are available in Python:

• Numeric Types -int,float,complex,bool
• Sequence Types -list,tuple,str
• Set Type -set
• Mapping Type -dict
• Special Type -None

Often sequence, set and mapping types are also collectively known asiterables as they are a collection of items on which a user can traverse (iterate).

Numeric data types are used for storing the following types of numbers:

Integer Numbers

Objects holding integer numbers like-1, 0, 200 are ofint data type.

Real or Floating-point Numbers

Objects holding real or floating point numbers like-1.1, 3e2, 20.0 are offloat data type.

Complex Numbers

Objects storing complex numbers like2 + 1j, -3j, -1 + 2J are of typecomplex.

Each complex number has two parts, the real part which is a numeric integer or floating point literal, and the imaginary part which is an imaginary literal.

Boolean

The boolean data type (bool) is a subtype ofint. It stores the evaluated value of expressions represented as keywords -True (integer value1) andFalse (integer value0).

An ordered collection of items where each item can be accessed using an integer index is known as a sequence. The following three sequence data types are available in Python:

String

A string (str data type) is a sequence of zero or more unicode characters enclosed within a pair of single (') or double (") quotes.

Some example strings are -"42", 'hello', "python".

List

Alist is sequence of items of same or different data types which are enclosed within brackets -[ ].

Some example lists are -[1, 2, 3],['abc', 23, 3.14],['edpunk', 'python'].

Tuple

Atuple is an immutable sequence of items of same or different data types which are enclosed within parentheses -( ).

Some example tuples are -(1, 2, 3),('abc', 23, 3.14),('edpunk', 'python').

Aset is an unordered collection of unique items of same of different data types which are enclosed in curly braces -{ }.

Some example sets are -{1, 2, 3},{'abc', 23, 3.14},{'edpunk', 'python'}.

dict is a mapping data type which stores values in the form of key-value pairs.

It is used for representing data where you can quickly access the value (any data type) corresponding to a key (any data type exceptlist,set ordict), just like a dictionary where you can lookup the meaning of a given word.

Keys and corresponding values are separated by colon (:).

The key-value pairs are separated by comma (,) and enclosed within curly braces -{ }.

Some example dictionaries are -{1: "a", 2: "b", 3: "c"},{"name": "edpunk", "language": "python"}.

None is a special data type which is used to denote the absence of value in an object.

It is neither0 norFalse as these are defined finite values, whereasNone implies nothingness.

The built-intype() function can be used to fetch the data type of an object.

Examples:

>>>count=100>>> type(count)<class'int'>>>>pi=3.141>>> type(pi)<class'float'>>>>name="Python">>> type(name)<class'str'>

This function can be used along with theis operator in an expression to test whether the object is of the given type.

>>>count=100>>>type(count)isintTrue

Thein operator can be used along with thetype() function to test if the data type is one of the mentioned types.

# count is of type int or float>>>type(count)in (int,float)True

The process of converting the data type of an object from one type to another is known asType Casting orType Conversion.

The two kinds of type casting supported in Python are:

The Python interpreter automatically converts the data type without the need of user intervention when evaluating expressions to determine the final data type.

In the below example the final type ofc is automatically determined asfloat by the Python interpreter.

>>>a=1# int>>>b=2.0# float>>>c=a+b>>>c3.0>>> type(c)<class'float'>

When the type conversion is explicitly specified by the user using the various built-in functions available in Python, it is known as explicit type casting.

The built-in functions which can be used for explicit type casting are as follows:

1.int()

Creates anint from abool,float orstr containing integer characters (with or without sign).

>>>int(True)1>>>int(2.3)2>>>int("2")2

2.float()

Creates afloat from abool,int orstr containing floating point literals (with or without sign).

>>>float(True)1.0>>>float(2)2.0>>>float("2.3")2.3

float() also accepts the following string inputs -

• "Infinity"
• "inf"
• "nan" (not a number).

>>>float("Infinity")>1True>>>float("nan")nan

Floating point literals can also contain the following characters -

• ., which denotes the fractional part of a number.
• e orE, which denotes the exponent part of a number.

>>>float("3.14")3.14>>>float("10.")10.0>>>float("1e100")1e+100>>>float("3.14e-10")3.14e-10

3.str()

Converts any object into astr.

>>>str(2)'2'>>>str([1,2,3,4])'[1, 2, 3, 4]'

4.tuple()

Creates atuple from an iterable of typestr,list,set orrange.

>>>tuple('hello')('h','e','l','l','o')>>>tuple([1,2,3,4])(1,2,3,4)>>>tuple(range(6))(0,1,2,3,4,5)

5.list()

Creates alist from an iterable of typestr,tuple,set orrange.

>>>list('hello')['h','e','l','l','o']>>>list({1,2,3,4})[1,2,3,4]>>>list(range(6))[0,1,2,3,4,5]

6.set()

Creates aset from an iterable of typestr,tuple,list orrange.

>>>set('hello'){'o','e','l','h'}>>>set([1,2,3,4]){1,2,3,4}>>>set(range(6)){0,1,2,3,4,5}

A data type is said to be immutable when the value of an object of that type cannot be modified.

The following data types are immutable:

• int
• float
• complex
• bool
• tuple
• str
• None

You might be wondering if some of the above types are immutable then how are we able modify the values of variables?

In case of variable re-assignment, the original objects are not modified, but new objects (with new values) are created in a new memory location and are bound to the variables. The object containing the old value is destroyed if no other variable references it.

Let us take an example,

>>>a=1>>>id_a=id(a)>>>a=2>>>id_a2=id(a)>>>id_a==id_a2False

You can witness in the above example how the object containing the value1 is different from the object containing the value2, anda points to the latest object.

Sequence data types like strings and tuples are also immutable, i.e., no modifications are permitted to any item once it is created and any attempt to do so raises an error.

>>>s="Hello">>>s[1]="P"Traceback (mostrecentcalllast):File"<stdin>",line1,in<module>TypeError:'str'objectdoesnotsupportitemassignment>>>t= (1,2,3)>>>t[1]=0Traceback (mostrecentcalllast):File"<stdin>",line1,in<module>TypeError:'tuple'objectdoesnotsupportitemassignment

Although, similar to numeric types the variables can be re-assigned to new sequences.

>>>s="Hello">>>id_s=id(s)>>>s="Help">>>id_s2=id(s)>>>id_s==id_s2False>>>t= (1,2,3)>>>id_t=id(t)>>>t= (0,2,3)>>>id_t2=id(t)>>>id_t==id_t2False

In Python, the following data types are mutable, i.e., any modification does not create a new object but modifies the existing object:

• list
• set
• dict

Let us take a list and modify its contents.

>>>l= [1,2,3]>>>id_l=id(l)>>>l[0]=0>>>l[0,2,3]>>>id_l2=id(l)>>>id_l==id_l2True

Let us take an example of a dictionary and add a newkey:value pair.

>>>d= {"a":"apple","b":"boy"}>>>id_d=id(d)>>>d["c"]="cat">>>d{'a':'apple','b':'boy','c':'cat'}>>>id_d2=id(d)>>>id_d==id_d2True

Let us take an example of a set and add new item.

>>>s= {"apple","bat"}>>>id_s=id(s)>>>s.add("cat")>>>s{'cat','apple','bat'}>>>id_s2=id(s)>>>id_s==id_s2True

In the above examples, theid of the objects (list,dict,set) do not change, which implies that no new objects are created and the original objects are modified.

input() function is used to accept new input data from the user.

When this function is encountered in the code, the python interpreter waits for the user to type a response which is read as a string and assigned to a variable.

>>>name=input()edpunk>>>name'edpunk'

The function also has an optional string argument which is used as a prompt message for the user.

>>>name2=input("Enter name: ")Entername:EdPunk>>>name2'EdPunk'

User input can be converted into integer or floating point numbers using the type conversion functionsint() andfloat().

>>>num=int(input("Enter n: "))Entern:10>>> type(num)<class'int'>>>>num10>>>pi=float(input("Enter pi: "))Enterpi:3.14>>> type(pi)<class'float'>>>>pi3.14

The built-inprint() function is used to display an output (value of variables, expressions, etc.) on the standard output.

Let us go through a program which computes the area of a rectangle and displays it:

Code

length=10breadth=5area=length*breadthprint("Area:",area)

Output

Area: 50

print() function can also be used to output the value of multiple objects when they are provided as arguments to the function.

Code

a=2+2b=2*3.5print(a,b)

Output

4 7.0

In the above code, the values ofa andb are separated by a blank space (the default value ofsep).

This property can be modified by providing any user defined separator using thesep option.

Let us modify the code and provide"," as the separator.

Code

a=2+2b=2*3.5print(a,b,sep=",")

Output

4,7.0

When expressions are provided as arguments to theprint() function, output is the evaluated value of those expressions.

For example,

Code

print(2+2)print(2*3.5)print("Hello, "+"world!")

Output

47.0Hello, world!

In the above code snippet, eachprint() function invocation creates a new line of output. This is becauseend parameter has the newline character ('\n') as the default value in theprint() function.

This can be modified by the user as shown below:

Code

print(2+2,end=",")print(2*3.5,end=";")print("Hello, "+"world!")

Output

4,7.0;Hello, world!

Note

All non-keyword arguments or expressions are converted to strings and written to the output stream by theprint() function. They are separated bysep and followed byend. An emptyprint() invocation writesend parameter (an empty line asend defaults to the newline character'\n').

Operators are symbols that perform a single simple task or operation on one or more values resulting in a single evaluated value.

The values on which these operators are applied are calledoperands.

Unary operators are applied on a single operand positioned on right side of the operator.

Following are some unary operators available in Python:

• + (plus): The unary+ operator does not change the value of the operand.
• - (minus): The unary- operator changes the sign of the operand.
• ~ (bitwiseNOT): The unary~ results in the bit-wise inversion of the integer operand. The bit-wise inversion ofx is defined as-(x+1).

>>>x=5>>>-x-5>>>+x5>>>~x-6

Binary operators are applied on two operands.

For example, arithmetic operators (+,–,*,/) evaluate the result of mathematical computation of two values.

A rich set of operators are available in Python which can be categorized as follows:

• Arithmetic Operators -+,–,*,/,%,**,//
• Relational Operators -==,!=,>,>=,<,<=
• Assignment Operators -+=,-=,*=,/=,%=,**=,//=
• Logical Operators -not,or,and
• Identity Operators -is,is not
• Membership Operators -in,not in
• Bitwise and Shift Operators -&,|,^,~,<<,>>

Arithmetic operations can be performed in Python using the following arithmetic operators:

Addition

The+ operator adds the values of numeric operands.

>>>2+35>>>2+3.05.0

In case the operands are of typestr,list ortuple, the+ operator concatenates these two sequences or strings.

>>>'edpunk'+'python''edpunkpython'>>> ["ed","punk"]+ ["python", ]['ed','punk','python']

Subtraction

The- operator subtracts the value of operand on right from the value of operand on left.

>>>2-3-1

Multiplication

The* operator multiplies the values of numeric operands.

>>>2*36

In case the operands are of typestr,list ortuple, the* operator returns a sequence or string self-concatenated the specified number of times.

>>>"python"*3'pythonpythonpython'>>> ['ed','py']*3['ed','py','ed','py','ed','py']

Division

The/ operator divides the value of operand on left by the value of operand on right and returns the real number quotient.

>>>6/23.0>>>5/22.5

Floor Division

The// operator divides the value of operand on left by the value of operand on right and returns the integer quotient.

>>>5//22

Modulus

The% operator divides the value of operand on left by the value of operand on right and returns the remainder.

>>>5%21

Exponent

The** operator raises the left operand to the power of the right operand.

>>>5**225

Relational operators are useful for comparing the values of the operands to determine their relationship. Following relational operators are available in Python:

Equals to

The== operator returnsTrue if the value of operand on left is same as the value of operand on right.

>>>2==2True>>>2==3False

In case of sequence operands likestr,list ortuple, the result isTrue if both the sequences are exactly the same.

>>>"python"=="python"True>>>"pypi"=="python"False>>> [1,2,3]== [1,2,3]True

As a sequence is an ordered collection of items, so the order in which the items are positioned is very important.

>>> [2,1,3]== [1,2,3]False

Not equal to

The!= operator returnsTrue if the value of operand on left is not equal to the value of operand on right.

>>>2!=2False>>>2!=3True>>>'py'!='oy'True>>> [2,1,3]!= [1,2,3]True>>> [1,2,3]!= [1,2,3]False

Greater than

The> operator returnsTrue if the value of operand on left is greater than the value of operand on right.

>>>3>2True>>>2>2False

In case of strings operands,> operator perform comparison according to the Unicode code point (integer) of each character one-by-one.

The Unicode code point of a character can be obtained using theord() function in Python.

The code point of first character of both operands are compared. In case they are equal, the code point of next character of both operands are compared and the process continues.

For example,

>>>"python">"Python"True

The code point of"p" (112) is greater than the code point of"P" (80). As112 is greater than80 the expression evaluates toTrue.

Let us take another example:

>>>"pYthon">"python"False

The code point of first character is same (112), so the next set of characters are compared. The code point of"Y" (89) is not greater than the code point of"y" (121) so the expression evaluates toFalse.

If two string operandsp andq are of unequal lengths (len(p) < len(q)) andp is a substring ofq such thatq = pt where t is any string of length greater than0, thenq > p returnsTrue.

>>>"python">"py"True

In case of sequence operands likelist ortuple, the items are compared one-by-one starting from index0.

>>> ["p","py","PY"]> ["p","Py","PY"]True>>> [1,3]> [1,2]True>>> [1,3,4]> [1,2]True

In the above examples,"py" is greater than"Py" and3 is greater than2 respectively.

If two sequences are of unequal lengths and the smaller sequence is the starting subsequence of the larger one, then the larger sequence is considered greater than the smaller one.

>>> [1,2,4]> [1,2]True

Greater than or equal to

The>= operator returnsTrue if the value of operand on left is greater than or equal to the value of operand on right.

>>>3>=3True>>>2>=3False

In case of sequence operands (str,list,tuple), the comparison operation performed is along the same lines as the> operator discussed above.

>>>"python">="Python"True>>>"python">="python"True>>> ["py","py","PY"]>= ["py","Py","PY"]True>>> [1,2]>= [1,2]True>>> [1,2,4]>= [1,2]True

Less than

The< operator returnsTrue if the value of operand on left is less than the value of operand on right.

>>>2<3True>>>3<3False

In case of sequence operands (str,list,tuple), the comparison operation performed is along the same lines as the> operator discussed above.

>>>"file"<"Pile"False# f(102) is > P(80)>>>"py"<"python"True>>> ["Py","PY"]< ["py","PY"]True>>> ['a',2]< ['a',3]True>>> [1,2]< [1,2,4]True

Less than or equal to

The<= operator returnsTrue if the value of operand on left is lesser than or equal to the value of operand on right.

>>>2<=3True>>>3<=3True

In case of sequence operands (str,list,tuple), the comparison operation performed is along the same lines as the> operator discussed above.

>>>"file"<="Pile"False# f(102) is > P(80)>>>"py"<="python"True>>> ["Py","PY"]<= ["py","PY"]True>>> ['a',3]<= ['b',2]True>>> [1,2]<= [1,2,4]True

The assignment symbol (=) serves as a delimiter between the name and value in an assignment statement.

It binds (or rebinds) a value (data, variable, expression) on the right to the target variable on the left.

>>>x=1>>>x1>>>y=x>>>y1>>>y="python">>>y'python'

Binary operators can be combined with the assignment symbol to createAugmented Assignment Operators.

These operators perform the binary operation on the two operands and assign the result to the original target (left operand).

If<op> is a binary operator, then the expressiona <op>= b containing the augmented assignment operator is equivalent toa = a <op> b.

+=

The+= operator adds a value (right operand) to the variable (left operand) and assigns the result to that variable.

>>>a=2>>>a+=3>>>a5>>>x="hello">>>y="world">>>x+=y>>>x'helloworld'

-=

The-= operator subtracts a value (right operand) from the variable (left operand) and assigns the result to that variable.

>>>a=3>>>a-=2>>>a1

*=

The*= operator multiplies a value (right operand) to the variable (left operand) and assigns the result to that variable.

>>>a=3>>>a*=2>>>a6>>>x="hi">>>x*=3>>>x'hihihi'

/=

The/= operator divides the variable (left operand) by a value (right operand) and assigns the result to that variable.

>>>a=4>>>a/=2>>>a2.0

//=

The//= operator floor divides the variable (left operand) by a value (right operand) and assigns the result to that variable.

>>>a=5>>>a//=2>>>a2

**=

The**= operator raises the variable (left operand) to a power (right operand) and assigns the result to that variable.

>>>a=4>>>a**=2>>>a16

%=

The%= operator computes modulus of the variable (left operand) and a value (right operand) and assigns the result to that variable.

>>>a=4>>>a%=3>>>a1

Expressions using logical operators evaluate to a boolean value (True orFalse) based on the logical state of the operands.

In Python, all values except0,None,False,"",'',(),[],{} have their logical state asTrue.

bool() built-in function can be used to determine the logical state of literals, variables or expressions.

The logical state of the following literals isFalse.

>>>bool(False)False>>>bool(0)False>>>bool([])False>>>bool(None)False>>>bool("")False>>>bool([])False>>>bool(())False>>>bool({})False

Some example literals having boolean state asTrue are provided below.

>>>bool(True)True>>>bool(1)True>>>bool(2.0)True>>>bool(100)True>>>bool("python")True>>>bool(["py","thon"])True

not

The logical state of an operand can be reversed (False toTrue, and vice versa) using the logicalnot operator.

>>>n=5>>>bool(n)True>>>bool(notn)False

or

The logicalor operator returnsTrue if the logical state of any of the two operands isTrue.

>>>TrueorFalseTrue>>>bool(1or0)True>>>FalseorFalseFalse

and

The logicaland operator returnsTrue if the logical state of both the operands isTrue.

>>>TrueandTrueTrue>>>TrueandFalseFalse>>>bool(10and20)True>>>bool(1and0)False

We have already witnessed how Python treats every value or data item as an object.

The relational operator== can be used to test whether the operands contain the same value.

>>>n=1>>>n2=1>>>n==n2True

This operator however does not check if both the operands are referring to the same object or different objects.

The identity operatorsis andis not are used to test whether two objects have the same or different identity (pointing to the same location in memory) respectively.

a is b is equivalent toid(a) == id(b), whereid() is the built-in function which returns the identity of an object.

>>>n=1>>>n2=1>>>nisn2True

In the above example, both variablesn andn2 point to that same memory location (same object).

>>>l= [1,2,3]>>>l2= [1,2,3]>>>l==l2True>>>lisl2False

In the above example, both listsl andl2 although contain items with same values, are actually two different objects occupying different memory locations.

The operatorsin andnot in test whether a value is present or not present in an iterable (string, list, tuple, set, dictionary).

>>>1in [1,2,3]True>>>"ed"in ["ed","py","hi"]True>>>"ed"in ("ed","py","hi")True>>>'ed'in {'ed':1,'py':2}True>>>"pen"notin ["pencil","ink"]True>>>"pen"notin ["pen","ink"]False

Literals (constants), identifiers (variables) and operators can be combined to form an expression which always evaluates to a single value.

For example,40 + marks is an expression containing a literal (40), a variable (marks) and an operator (+).

Some valid expressions are provided below:

• 10
• a
• -a
• a - 10
• a + b
• 4.0 * 3.5
• a == b
• c in d
• a is T
• "Hello" + "World"
• 15 - a*4
• 3*num + 9/4 - 10%count**2

As shown above, standalone literals (like10) and variables (likea) are considered as expressions, but standalone operators are not expressions.

Comparison operators can be chained together in Python.

For example,lower <= age <= upper is a valid chained expression which is equivalent to the expression -

lower <= age and age <= upper.

Ifa,b,c, …,y,z are expressions andop1,op2, …,opN are comparison operators, then the chained expressiona op1 b op2 c ... y opN z is equivalent toa op1 b and b op2 c and ... y opN z.

Python does not have ternary operators (?:) like other programming languages. Hence, the keywordsif andelse are used to create conditional expressions which evaluates to a value based on the given condition.

For example,

var=t_valifcondelsef_val

If the above conditioncond evaluates toTrue, then the variablevar is assignedt_val, else it is assignedf_val.

>>>value=1if2>3else-1>>>value-1

While studying mathematics in middle school, we came across theBODMAS (Bracket, Of, Division, Multiplication, Addition, and Subtraction) rule which helps us in understanding how mathematical expressions are computed in the presence of multiple operators (of,x,/,+,-).

In Python, we have a large number of operators and a similar rule to determine the order of evaluation of an expression. This is known asoperator precedence where the operator with higher precedence is evaluated before the operator with lower precedence in an expression.

The table below presents the precedence of operators in Python from highest to lowest. Operators in the same row have the same precedence, so in such cases the expression is evaluated from left to right.

Example 1

Evaluate the expression

15 - 2 * 4

Solution

Step:* has higher precedence over-
15 - 2 * 4
=15 - 8
=7

Example 2

Evaluate the expression

15 - 2 + 4

Solution

Step:- and+ have the same order of precedence so the expression is evaluated left to right
15 - 2 + 4
=13 + 4
=17

Example 3

Evaluate the expression

15 - (2 + 4)

Solution

Parenthesized expression(...) has the highest precedence so+ is evaluated first
15 - (2 + 4)
=15 - 6
=9

Example 4

Evaluate the expression

3 * 2 + 9 / 4 - 10 % 2 ** 2

Step 1

** takes precedence
3 * 2 + 9 / 4 - 10 % 2 ** 2
=3 * 2 + 9 / 4 - 10 % 4

Step 2

*,/ and% have the same precedence so they are evaluated left to right.
3 * 2 + 9 / 4 - 10 % 4
=6 + 2.25 - 2

Step 3

+ and- evaluation
6 + 2.25 - 2
=6.25

Example 5

Evaluate the expression

20 / 4 // 2 * 2 - 4 + 20

Step 1

*,/,// and% have the same precedence so they are evaluated left to right.
20 / 4 // 2 * 2 - 4 + 20
=5 // 2 * 2 - 4 + 20
=2 * 2 - 4 + 20
=4 - 4 + 20

Step 2

+ and- evaluation
4 - 4 + 20
=20

Example 6

Evaluate the expression

not 6 <= 4 and 3 ** 3 > 12 / 3

Step 1

** takes precedence
not 6 <= 4 and 3 ** 3 > 12 / 3
=not 6 <= 4 and 27 > 12 / 3

Step 2

/ is next in line of precedence
not 6 <= 4 and 27 > 12 / 3
=not 6 <= 4 and 27 > 4

Step 3

Comparison operators are next in line of precedence
not 6 <= 4 and 27 > 4
=not False and True

Step 4

BooleanNOT is evaluated
not False and True
=True and True

Step 5

BooleanAND is evaluated
True and True
=True

A program contains"bug(s)" when it is unable to execute or produces an output which is different from what is expected. These bugs are generally introduced by a programmer unknowingly.

The process of identifying and eliminating these bugs or errors is known asdebugging.

The three major types of errors are:

• Syntax Error
• Runtime Error
• Logical Error

Syntax error occurs when the program contains any statement that does not follow the prescribed Python rules or syntax which makes it difficult for the Python interpreter to parse (understand) and execute it.

Some common syntax errors are:

• Missing/Misspelled keyword
• Missing colon or brackets
• Empty block
• Incorrect position of keyword
• Incorrect block indentation

When a code containing syntactically incorrect statement is executed using script mode via IDLE, an error dialog box is displayed.

On closing the dialog box, the incorrect part of the code, the potential cause of error, is highlighted in red.

This error has to be rectified to execute the program correctly.

When a syntactically incorrect statement is executed in the Python console (interactive mode), the Python interpreter displays it and also adds a little arrow (^) pointing at the entry point or token where the error was detected.

Example

>>>whileTrueprint('Hi!')File"<stdin>",line1whileTrueprint('Hi!')^SyntaxError:invalidsyntax

In the above example there is a syntax error with^ pointing toprint function which the parser is unable to understand as there is a missing: (colon) afterTrue.

A runtime error occurs when the program is terminated prematurely by the Python interpreter as it is unable to execute a statement although it is correct syntactically.

Some runtime error examples are:

• ImportError: Raised when theimport statement has trouble loading a module or any definition from a module.
• IOError: Raised when the interpreter is not able to open the file specified in the program.
• ZeroDivisionError: Raised when a number is divided or mod by zero.
• NameError: Raised when an identifier is encountered which has not been defined.
• ValueError: Raised when an argument or operand is of required data type, but has undesired value.
• IndexError: Raised when the provided index in a sequence (string, list, tuple, etc.) is out of range.
• KeyError: Raised when a dictionary key is not found in the set of existing keys.
• TypeError: Raised while performing an operation on incompatible types.
• IndentationError: Raised when the indentation of a statement or code block is incorrect.

ZeroDivisionError

n=100d=0print(n/d)

Traceback (mostrecentcalllast):File"/Users/name/Desktop/test.py",line3,in<module>print(n/d)ZeroDivisionError:divisionbyzero

NameError

n=100print(d)

Traceback (mostrecentcalllast):File"/Users/name/Desktop/test.py",line2,in<module>print(d)NameError:name'd'isnotdefined

KeyError

d= {1:"1st",2:"2nd"}print(d[3])

Traceback (mostrecentcalllast):File"/Users/name/Desktop/test.py",line2,in<module>print(d[3])KeyError:3

TypeError

n=1s="a"tot=n+s

Traceback (mostrecentcalllast):File"/Users/name/Desktop/test.py",line3,in<module>tot=n+sTypeError:unsupportedoperand type(s)for+:'int'and'str'

Logical error or Semantic error is caused when the issue lies in the underlying meaning of the code which leads to an incorrect output.

As compared to syntax or runtime error there is no termination of the program.

Debugging a logical error requires inspection of the entire code as no guiding error message is displayed.

Let us write a program to calculate the average of two numbers

n=10m=20avg=n+m/2print("Average:",avg)

On executing the script the result is

Average: 20.0

This is incorrect as there is a logical error in the code.

Since/ has a higher precedence over+,m / 2 is being computed first.

We can modify the code to get rid of the logical error.

n=10m=20avg= (n+m)/2print("Average:",avg)

On executing the script, we now obtain the correct result

Average: 15.0

We have witnessed that even if a program is syntactically correct, its execution may lead to a run-time error.

This error detected during execution is known as anexception which is an object created by the Python interpreter containing information regarding the error like type of error, file name and the location of the error (line number, token) in the program.

Some of the built-in exceptions that are raised by the Python interpreter are -ImportError,ZeroDivisionError,NameError,ValueError,IndexError,KeyError,TypeError andIndentationError.

Apart from the Python interpreter, a programmer can also trigger and raise an exception (along with a custom message) in the code usingraise orassert statement.

Theraise statement can be used to throw an exception in a program. The exception may or may not contain the custom error message (recommended).

Let us consider a program which accepts two numbers (a andb) from the user and prints the resulta/b.

Code

a=int(input("Enter a: "))b=int(input("Enter b: "))print("a/b =",a/b)

Output

Enter a: 10Enter b: 0Traceback (most recent call last):  File "/Users/name/test.py",   line 3, in <module>    print("a/b =", a/b)ZeroDivisionError: division by zero

It can be observed that the Python interpreter raises aZeroDivisionError when the value ofb is entered as0.

Now we can modify the above code to raise an exception for such scenarios.

Code

a=int(input("Enter a: "))b=int(input("Enter b: "))ifb==0:raiseException()print("a/b =",a/b)

Output

Enter a: 10Enter b: 0Traceback (most recent call last):  File "/Users/name/test.py",   line 4, in <module>    raise Exception()Exception

An exception is raised, but it is not helpful.

Let us add some custom error message.

Code

a=int(input("Enter a: "))b=int(input("Enter b: "))ifb==0:raiseException("b is zero")print("a/b =",a/b)

Output

Enter a: 10Enter b: 0Traceback (most recent call last):  File "/Users/name/test.py",   line 4, in <module>    raise Exception("b is zero")Exception: b is zero

We can also raise any specific type of error as per the program logic as shown below:

Code

a=int(input("Enter a: "))b=int(input("Enter b: "))ifb==0:raiseValueError("The value of b cannot be zero")print("a/b =",a/b)

Output

Enter a: 10Enter b: 0Traceback (most recent call last):  File "/Users/name/test.py",   line 4, in <module>    raise ValueError("The value of b cannot be zero")ValueError: The value of b cannot be zero

Anassert statement is often used during code development to act like a safety valve which notifies the programmer in case the test expression is evaluated asFalse.

If the test expression’s value isTrue, the code execution continues normally.

AnAssertionError is raised if the value isFalse.

Code

a=3b=4asserta==bc=5

Output

Traceback (most recent call last):  File "/Users/name/test.py",   line 3, in <module>    assert a == bAssertionError

The statement also allows for a message to be attached to theAssertionError.

Code

a=3b=4asserta==b,"a is not equal to b"c=5

Output:

Traceback (most recent call last):  File "/Users/name/test.py",   line 3, in <module>    assert a == b, "a is not equal to b"AssertionError: a is not equal to b

Exception handling is the process of properly handling an exception which can potentially crash a program during execution.

When an error occurs, the program throws an exception.

The runtime system attempts to find anexception handler, a block of code that can handle a particular type of error. Once located, the suitable exception handlercatches the exception and executes the code block which can attempt to recover from the error. In case the error is unrecoverable, the handler provides a way to gently exit the program.

Thetry statement in Python specifies the exception handlers and/or cleanup code for a code block.

The various parts of a try statement are:

• try block: The block of statements within which an exception might be thrown.
• except clause(s): One or more exception handlers. Eachexcept clause handles a particular type of exception. In case an exception of a particular type occurs in thetry block, the correspondingexcept clause code block is executed.
• else clause: An optionalelse clause can also be included after the lastexcept block. In case no exception is raised, none of theexcept blocks are executed. In this case, theelse code block is executed.
• finally clause: An optionalfinally clause can be added at the end of the try statement which includes a block of statements that are executed regardless of whether or not any error occurred inside the try block. This block is usually setup for code cleanup and closing all open file objects.

Here's the general form of these statements:

try:    [codeblock]except [exception1 [asidentifier1]]:    [exceptioncodeblock1]except [exception2 [asidentifier2]]:    [exceptioncodeblock2]......else:    [codeblockexecutesifnoerror]finally:    [codeblockalwaysexecuted]

A simple Python program can be treated as a block of code where each statement is executed by the Python interpreter in a sequential order from top to bottom.

But, in real world we would like to have some control over the execution of code such as:

• skip or execute a block (set of statements) based on certain conditions
• execute a block repeatedly
• redirect execution to another set of statements
• breaking up the execution

This control over the flow of execution is provided byControl Flow Statements.

They can be categorized as:

• Sequential
• Selection
• Iteration/Repetition
• Jump
• Procedural Abstraction - A sequence of statements are referenced as a single function or method call
• Recursion - Calling a method/function in the same method/function
• Exception Handling

By default the code statements in Python are executed in Sequential order.

The below flow chart demonstrates how 3 statements are executed in a sequential order.

For example,

a=2b=3c=a*bprint(c)

The above code will be executed in the following sequential order:

Selection statements, also known as Decision making statements, control the flow of a program based on the outcome of one or many test expression(s). If the condition is satisfied (True) then the code block is executed. There is also a provision to execute another code block if the condition is not satisfied.

This process can be demonstrated using the below flowchart:

Python supportsif compound statement which provides this control. Theif statement comprises:

• if keyword followed by the test expression, a colon: and an indented block of code which gets executed if the condition is satisfied
• (optional) one or manyelif clause followed by their test conditions and their corresponding code blocks
• (optional)else clause and the corresponding code block which gets executed if none of the above conditions (if,elif) are satisfied

An exampleif statement is provided below:

'''age - age of loan applicantemp - is employed (bool)cscore - credit scrore of applicant'''result=Noneifage<26andnotemp:result="Loan rejected"elifage>35andcscore<600:result="Loan rejected"else:result="Loan approved"print(result)

The control flow view of the above code is:

Let us go through some programming problems which utilize selection statements.

1. Absolute Value

Write a program to output the magnitude of difference between two numbers using conditional statement.

Code

n1=int(input("Enter 1st number: "))n2=int(input("Enter 2nd number: "))ifn1>n2:diff=n1-n2else:diff=n2-n1print("The difference of",n1,"and",n2,"is",diff)

Output

Enter 1st number: 12Enter 2nd number: 15The difference of 12 and 15 is 3

2. Sorting 3 Numbers

Write a program to accept 3 numbers from the user and print them in ascending order of value.

Code

a=int(input("Enter 1st number: "))b=int(input("Enter 2nd number: "))c=int(input("Enter 3rd number: "))ifb<a:# Swapping the values of a and ba,b=b,aifc<b:b,c=c,bifb<a:a,b=b,aprint("The numbers in sorted order:",a,",",b,",",c)

Output

Enter 1st number: 9Enter 2nd number: 2Enter 3rd number: 6The numbers in sorted order: 2 , 6 , 9

3. Divisibility

Write a program to accept two numbers and test if the first number is divisible by the second number.

Code

a=int(input("Enter 1st number: "))b=int(input("Enter 2nd number: "))ifa%b==0:print(a,"is divisible by",b)else:print(a,"is not divisible by",b)

Output

Enter 1st number: 9Enter 2nd number: 29 is not divisible by 2Enter 1st number: 9Enter 2nd number: 39 is divisible by 3

Iteration statements, also known as Looping statements, allow repeated execution of a code block.

Python providesfor andwhile statements to perform iteration.

Thefor statement can be used to iterate over the items of a sequence (list,string,tuple,range). It can also be used to iterate over unordered sequences likeset anddict.

This process can be demonstrated using the below flowchart:

Let us go through some code examples to demonstrate howfor statement can be used to iterate over sequences.

Code

cars= ["Hyundai","Honda","Ford","Toyota","BMW","Volkswagen"]formakeincars:print(make)

Output

HyundaiHondaFordToyotaBMWVolkswagen

Code

cars= ("Hyundai","Honda","Ford","Toyota","BMW","Volkswagen")formakeincars:print(make)

Output

HyundaiHondaFordToyotaBMWVolkswagen

Code

name="python"forcharinname:print(char)

Output

python

Therange type represents an immutable sequence of numbers that is usually used in for loops for looping a certain number of times.range object always take the same (small) amount of memory, no matter the size of the range it represents, which is an advantage over a regularlist ortuple.

Syntax:range(stop) or
range(start, stop[, step])

>>>range(10)range(0,10)>>>list(range(10))[0,1,2,3,4,5,6,7,8,9]>>>list(range(1,10,2))[1,3,5,7,9]

range() function is widely used in afor statement to control the number of iterations and provide the index value (i) of each iteration.

Example #1

Print multiples of 5 starting from 0 to 20.

Code

foriinrange(5):print(i*5)

Output

05101520

Example #2

Print all integers from 2 to 5 including the boundary values.

Code

foriinrange(2,6):print(i)

Output

2345

Example #3

Print all odd numbers between 2 and 10.

Code

foriinrange(3,10,2):print(i)

or

foriinrange(2,10):ifi%2!=0:print(i)

Output

3579

Example #4

Print the index of all occurrences ofo inpython programming.

Code

s="python programming"foriinrange(len(s)):ifs[i]=="o":print(i)

Output

49

Let us go through some programming problems which utilize thefor iteration statement.

1. Compound Interest

Write a program to calculate the total compound interest payable for given principal, interest rate (compounded annually) and total time (in years).

Code

prin=float(input("Enter the principal amount: "))rate=float(input("Enter the annual interest rate: "))time=int(input("Enter the loan duration (in years): "))amt=prinforninrange(time):amt+=rate*amt/100print("Total interest payable:",amt-prin)

Output

Enter the principal amount: 500000Enter the annual interest rate: 5Enter the loan duration (in years): 3Total interest payable: 78812.5

2. Factorial

The factorial of a positive integern, denoted byn!, is the product of all positive integers less than or equal ton.
n! = n×(n-1)×(n-2)...3×2×1
Write a program to calculaten! for a givenn (assumen is greater than0).

Code

n=int(input("Enter n: "))factorial=1foriinrange(1,n+1):factorial*=iprint("n! :",factorial)

Output

Enter n: 6n! : 720

while statement repeatedly executes a code block as long as the test condition is satisfied.

Usually there is a statement at the end of the code block which updates the value of the variable being used in the test expression, so the the loop does not execute infinitely.

A flowchart of the process is provided below:

For example, let us traverse a list and print the position(index) and value of each element until we reach the end of the list.

Code

cars= ["Hyundai","Honda","Ford","Toyota","BMW","Volkswagen"]i=0whilei<len(cars):print(i,cars[i])i+=1

Output

0 Hyundai1 Honda2 Ford3 Toyota4 BMW5 Volkswagen

In the above example, the test condition isi<len(cars) and the update statement isi+=1.

Let us go through some programming problems which utilize thewhile iteration statement.

1. Compound Interest

Write a program to calculate the total compound interest payable for given principal, interest rate (compounded annually) and total time (in years).

Code

prin=float(input("Enter the principal amount: "))rate=float(input("Enter the annual interest rate: "))time=int(input("Enter the loan duration (in years): "))amt=prinwhiletime>0:amt+=rate*amt/100time=time-1print("Total interest payable:",amt-prin)

Output

Enter the principal amount: 500000Enter the annual interest rate: 5Enter the loan duration (in years): 3Total interest payable: 78812.5

2. Factorial

The factorial of a positive integern, denoted byn!, is the product of all positive integers less than or equal ton.
n! = n×(n-1)×(n-2)...3×2×1
Write a program to calculaten! for a givenn (assumen is greater than0).

Code

n=int(input("Enter n: "))factorial=1whilen>0:factorial*=nn=n-1print("n! :",factorial)

Output

Enter n: 6n! : 720

Jump statements are used to (abruptly) alter the flow of execution.

Some of the jump statements available in Python are:

Apass statement acts as a placeholder and performs null (no) operation.

Various reasons for using the keywordpass are provided below:

1. Syntactical Requirement

Usingpass becomes a syntactical requirement for cases where the Python interpreter can raise aSyntaxError due to missing statements.

The below code will execute successfully without any operation in the loop

foriinrange(6):pass

whereas withoutpass

foriinrange(6):

will throw the followingSyntaxError

File "<ipython-input-18-f2ba5099d499>", line 1    for i in range(6):                    ^SyntaxError: unexpected EOF while parsing

Similarly, inside anif

if2<3:pass

whereas withoutpass

if2<3:

will throw the followingSyntaxError

File "<ipython-input-20-068861cce0a8>", line 1    if 2 < 3:            ^SyntaxError: unexpected EOF while parsing

2. Skipping Code Execution

pass can be used to skip code execution for certain cases.

For example,

Code

l= [2,3,4,5,6]foriinl:ifi%3==0:passelse:print(i,"is not divisible by 3")

Output

2 is not divisible by 34 is not divisible by 35 is not divisible by 3

3. Placeholders

pass can be used to create valid empty functions and classes as placeholders which can be modified in the future versions of code.

defemptyFunction():passclassEmptyClass:pass

Thebreak statement is used to terminate the execution of immediately enclosingfor orwhile statement.

The below code will terminate thefor loop wheni is equal to4

foriinrange(10):print(i)ifi==4:break

01234

In a while statement,

i=0whilei<10:print(i)ifi==4:breaki+=1

break will terminate thewhile loop wheni is equal to4

01234

continue statement is used to skip the execution of successive statements and start the next iteration.

The below code will skip all candidates for an interview who have less than 4 years of work experience.

people=  [{"name":"ABC","experience":6},           {"name":"EFG","experience":2},           {"name":"JKL","experience":5},           {"name":"XYZ","experience":3},]forcandidateinpeople:ifcandidate["experience"]<4:continueprint(candidate["name"],"is selected for interview")

Output:

ABC is selected for interviewJKL is selected for interview

When a loop is present inside another loop, it is known as a nested loop.

For each iteration of the outer loop, the inner loop undergoes complete iteration. Thus, if the outer loop has to undergon iterations and the inner loop has to undergom iterations, the code block inside the inner loop executesn x m times.

Let us go through a nested loop example:

Write a program to print the factorial of all numbers in the range1 to10 (inclusive).

Code

forninrange(1,11):factorial=1foriinrange(1,n+1):factorial*=iprint(n,"! =",factorial)

Output

1 ! = 12 ! = 23 ! = 64 ! = 245 ! = 1206 ! = 7207 ! = 50408 ! = 403209 ! = 36288010 ! = 3628800

Abreak statement inside the inner loop terminates only the inner loop whereas the outer loop is not affected.

To develop a better understanding, let us write a program to find all prime numbers between 2 and 40.

Code

forninrange(2,40):i=2whilei<n/2:ifn%i==0:breaki+=1ifi>n/2:print(n,"is prime")

Output

2 is prime3 is prime5 is prime7 is prime11 is prime13 is prime17 is prime19 is prime23 is prime29 is prime31 is prime37 is prime

A String (str) is animmutable sequence of Unicode characters which is used to handle textual data in Python.

They can be specified by enclosing within:

• Single quotes:'embedded "double" quotes are allowed'
• Double quotes:"embedded 'single' quotes are allowed"
• Triple quotes:'''Three single quotes''',"""Three double quotes""".

Triple quoted strings can also span multiple lines.

Some examples are provided below:

s="I am a String"s1="""AmultilineString"""s2='''Also amultilineString'''

The backslash (\) character can be used in a string to escape characters that otherwise have a special meaning, such as newline, linefeed, or the quote character.

Although\' and\" can be used to specify quote characters, Python allows embedding double quotes inside a single-quoted string ('My name is "Python".') and single quotes inside a double-quoted string ("Python's World").

Python string objects support Unicode characters.

A unicode character can be specified as\u followed by the 4 letter unicode (\uXXXX).

>>>print("E = mc\u00B2")E=mc²

In the above example,\u00B2 is the unicode character which represents the 'SUPERSCRIPT TWO'.

In case you want to create a string object from other data types, just use the built-instr() function as follows:

>>>str(9)'9'>>>str(10.0)'10.0'

Python strings are "immutable", i.e., the state (value) of the objects cannot be modified after they are created.

Using the standard[ ] syntax and zero-based indexing, characters can be accessed in a string.

Ifs = "hello",

• s[0] will result inh
• s[2] will result inl
• s[5] will result inIndexError: string index out of range as the length of string is5 (index0 to4)
• s[2] = 'p' will result inTypeError: 'str' object does not support item assignment ass is immutable

Python also supports negative indexing, i.e., you can access the values of a string from right to left.

Index of-1 denotes the last character of the string,-2 is the second last character and so forth.

Ifs = "hello",

• s[-1] will result ino
• s[-4] will result ine
• s[-6] will result inIndexError: string index out of range as the length of string is5 (negative index-1 to-5)

The built-in functionlen() returns the length of a string which is useful during string traversal or other string operations.

>>>len("hello")5>>>s="sample text">>>len(s)11>>>p="python">>>l=len(p)>>>p[l-1]'n'

We can perform various operations on a string (sequence of characters) such as slicing, membership, concatenation and repetition.

In Python, a character in a string can be easily accessed using its index.

>>>s="Hello">>>s[1]'e'

Python also provides a way to access a substring from a string. This substring is known as aslice and it can be obtained using the slice operator[n:m] which returns the part of the string from the start index (n) to the end index (m), including the first but excluding the last.

>>>s="Hello">>>s[1:3]'el'

If the start index (n) is omitted, the default value ofn is set as0 which denotes the beginning of the string. If the end index (m) is omitted, the substring ends at the last character of the string.

>>>s="Hello">>>s[:3]'Hel'>>>s[3:]'lo'>>>s[:]'Hello'

Negative indexing is also supported in the slice operator.

>>>s="Hello">>>s[-4:-2]'el'

In the above example,-4 is equivalent tolen(s) - 4 = 5 - 4 = 1 and-2 is equivalent to5 - 2 = 3. Thus,s[-4:-2] is same ass[1:3].

The slice operator also allows the usage of a third index which is known as step as it allows a user to step over (skip) characters.

>>>s="Hello">>>s[0:5:2]'Hlo'

In the above example, the substring begins at the start of the string, takes a step size of2 skippinge and ends at the last character again skipping the 4th characterl.

in andnot in operators can be used to determine whether a substring is present/not present in a string.

>>>s="Hello">>>"lo"insTrue>>>"lp"notinsTrue

The+ operator can be used to join two strings.

>>>s1="Hello">>>s2="Python">>>s1+s2'HelloPython'>>>s1+"World"'HelloWorld'

The* operator repeats a string the number of times as specified by the integer operand.

>>>s="Hello">>>s*3'HelloHelloHello'

Apart from the built-in functionlen() which returns the length of the string, String objects have access to several specialized functions (methods) that can:

1. Convert Case of Strings
2. Check Characters of a String
3. Split a String
4. Strip Characters from a String
5. Checking for Prefix or Suffix in a String
6. Find & Replace Characters in a String

Let us discuss these methods in detail in the coming sections.

The following methods are useful in converting the case of the characters in a string:

All cased characters are converted into lowercase.

>>>"PYthon".lower()'python'

All cased characters are converted into uppercase.

>>>"PYthon".upper()'PYTHON'

Uppercase characters are converted into lowercase and lowercase characters are converted into uppercase.

>>>"PYthon".swapcase()'pyTHON'

First character is capitalized and rest all characters are lowercased.

>>>"hello py".capitalize()'Hello py'

For each word present in the string, the first character is uppercased and the remaining characters are lowercased.

>>>"hello python".title()'Hello Python'

The following methods are used to check the type of characters in a string.

ReturnsTrue if all characters in the string are letters (A-Z a-z).

>>>"HelloPython".isalpha()True>>>"Hello Python".isalpha()False# contains whitespace>>>"HelloPython2".isalpha()False# contains digit

ReturnsTrue if all characters in the string are digits.

>>>"Hello24".isdigit()False# contains alphabets>>>"24".isdigit()True

ReturnsTrue if all characters in the string are alphanumeric (Alphabets or Numeric).

>>>"02".isalnum()True>>>"HelloPython".isalnum()True>>>"Hello Python v2".isalnum()False# contains whitespace>>>"HelloPythonv2".isalnum()True

ReturnsTrue if the string is empty or all characters in the string are ASCII.

>>>"".isascii()True>>>"HelloPython".isascii()True>>>"Hello Py\u00B2".isascii()False>>>"पा से python".isascii()False

ReturnsTrue if all characters are lowercase.

>>>"hello".islower()True>>>"Hello".islower()False

ReturnsTrue if all characters are uppercase.

>>>"HELLO".isupper()True>>>"Hello".isupper()False

ReturnsTrue if there are only whitespace characters in the string. Some popular whitespace characters are (space),\t (tab),\n (newline),\r (carriage return),\f (form feed) and\v (vertical tab).

>>>"        ".isspace()True

ReturnsTrue if the string is title-cased, i.e., the first character of every word in the string is uppercased and the remaining characters are lowercased.

>>>"Hello World".istitle()True>>>"Hello world".istitle()False>>>"hello world".istitle()False

Split methods help in splitting/partitioning a string.

partition(sep) method splits the string when the separator (sep) is encountered for the first time, and returns a tuple with three items(string before separator, separator, string after separator).

>>>"Hi|Ed|Punk".partition('|')('Hi','|','Ed|Punk')

split(sep=None, maxsplit=-1) method splits a string into a list based on a string separator (sep).

Ifsep is not specified, it defaults toNone, where whitespace is regarded as separator, and the string is stripped of all leading and trailing whitespaces after which it is split into words contained in the string.

>>>"Hi|Ed|Punk".split('|')['Hi','Ed','Punk']>>>"Hi Ed Punk".split()['Hi','Ed','Punk']>>>"    Hi Ed Punk   ".split()['Hi','Ed','Punk']

Ifmaxsplit is provided, at mostmaxsplit number of splits are performed and the list will contain a maximum ofmaxsplit+1 elements.

maxsplit when not specified defaults to-1, which implies that there is no limit on the number of splits.

>>>"Hi|Ed|Punk|v2".split('|',2)['Hi','Ed','Punk|v2']

Strip methods are useful in removing leading and/or trailing characters in a string.

They accept an optional argumentchars which specifies the set of characters which have to be removed.

If no arguments are provided thenchars defaults to ASCII whitespace and the method removes all leading and/or trailing spaces from the string.

All leading (on the left) characters are removed from the string.

>>>"   Hello|World   ".lstrip()'Hello|World   '>>>"www.edpunk.cc".lstrip('w.')'edpunk.cc'

All trailing (on the right) characters are removed from the string.

>>>"   Hello|World   ".rstrip()'   Hello|World'>>>"www.edpunk.cc".rstrip('.c')'www.edpunk'

All leading and trailing characters are removed from the string.

>>>"   Hello|World   ".strip()'Hello|World'>>>"www.edpunk.cc".strip('cw.')'edpunk'

startswith() andendswith() methods are used check whether a string starts or ends with the provided substring (or a tuple of substrings).

>>>"Hello Py".startswith("He")True>>>"Hello Py".startswith(("He","P"))True>>>"Py Hello".startswith(("He","P"))True>>>"Hello Py".endswith("y")True>>>"Hello Py".endswith(("p","y"))True>>>"Py Hello".endswith(("o","n"))True

The following string methods are useful for locating substring in a string.

count(sub[, start[, end]]) returns the number of non-overlapping occurrences of a substringsub in the range[start, end].

start andend are optional parameters and they default to0 andlen(string) respectively.

>>>s="she sells sea shells">>>s.count("she")2>>>s.count("she",5)1>>>s.count("she",5,10)0>>>s.count("she",5,17)1

It has to be noted that the method counts non-overlapping occurrences, so it does not start a new matching process until the current substring matching is complete.

>>>s="valhala alala">>>s.count("al")4>>>s.count("ala")2

In the above example,ala is counted twice as the first occurrence is invalh"ala" and the next occurrence is in"ala"la. Althoughala can be located again inal"ala", it overlaps with the occurrence"ala"la, hence it is not counted.

find(sub[, start[, end]]) returns the lowest index in the string where substringsub is located in the range[start, end].

start andend are optional parameters and they default to0 andlen(string) respectively.

The method returns-1 in case the substring is not present.

>>>s="she sells sea shells">>>s.find("she")0>>>s.find("she",5)14>>>s.find("see")-1>>>s.find("she",5,10)-1>>>s.find("she",5,17)14

rfind(sub[, start[, end]]) returns the highest index in the string where substringsub is located in the range[start, end].

start andend are optional parameters and they default to0 andlen(string) respectively.

The method returns-1 in case the substring is not present.

>>>s="she sells sea shells">>>s.rfind("she")14>>>s.rfind("she",0,12)0>>>s.rfind("see")-1>>>s.rfind("she",5)14

index(sub[, start[, end]]) is similar tofind(sub[, start[, end]]), but instead of returning-1 it raisesValueError when the substring is not found.

>>>s="she sells sea shells">>>s.index("she")0>>>s.index("she",5)14>>>s.index("see")Traceback (mostrecentcalllast):File"<stdin>",line1,in<module>ValueError:substringnotfound>>>s.index("she",5,10)Traceback (mostrecentcalllast):File"<stdin>",line1,in<module>ValueError:substringnotfound>>>s.index("she",5,17)14

s.rindex(sub[, start[, end]]) is similar torfind(sub[, start[, end]]), but instead of returning-1 it raisesValueError when the substring is not found.

>>>s="she sells sea shells">>>s.rindex("she")14>>>s.rindex("she",0,12)0>>>s.rindex("see")Traceback (mostrecentcalllast):File"<stdin>",line1,in<module>ValueError:substringnotfound>>>s.rindex("she",5)14

replace(oldsub, newsub[, count]) returns a copy of the string with all occurrences ofoldsub substring replaced bynewsub.

count is an optional parameter which when provided, only replaces the firstcount occurrences from the string.

>>>s="Oh Python! Oh">>>s.replace("Oh","Hi")'Hi Python! Hi'>>>s.replace("Oh","Hi",1)'Hi Python! Oh'

for andwhile statements are useful for traversing a string.

As a string is a sequence of characters, thefor statement can be used to iterate over a string as shown below.

Code

name="python"forcharinname:print(char)

Output

python