Getting Started with Python Class 11 Notes

Getting Started with Python Class 11 Notes, Python is a user-friendly programming language. These notes will help you get familiar with writing your first Python programs, understanding the syntax, and learning about data types. These notes are aligned with the CBSE Class 11 curriculum.

Introduction to Python

Python is a high-level, general-purpose programming language. Python can be used in a wide range of applications, from website development and data analysis to machine learning and automation.

Features of Python

• Python is a high-level language. It is a free and open-source language.
• It is an interpreted language, as Python programs are executed by an interpreter.
• Python programs are easy to understand
• Python is case-sensitive. For example, NUMBER and number are not same in Python.
• Python is platform independent, means it can run on various operating systems and hardware platforms.
• Python has a rich library of predefined functions.
• Python is also helpful in web development. Many popular web services and applications are built using Python.

Executing a simple “hello world” program

To execute a simple “hello world” program in Python, write the following program.

print("Hello, World!")

Execution Modes

There are two ways to use the Python interpreter:

• Interactive mode
• Script mode

Interactive Mode

Programmers can quickly run the commands and try out or test code without generating a file by using the Python interactive mode, commonly known as the Python interpreter or Python shell.

Script Mode

In the script mode, a Python programme can be written in a file, saved, and then run using the interpreter.
Python scripts are stored in files with the “.py” extension. Python scripts are saved by default in the Python installation folder.

Python character set

The character set in Python refers to the collection of characters used in writing Python programs. Python supports various characters, including:

• Letter: Python allows both uppercase (A – Z) and lowercase (a – z) letters.
• Digit: Digits (0 – 9) can be used but cannot be the first character of a variable.
• Special Characters: Python supports special characters like arithmetic operators (+, -, *, /), special symbols (@, #, %, $), and brackets ({}, [], ()).
• Escape Sequences: Python uses backslash (\) for escape sequences. New line (\n), tab (\t)
• Unicode Characters: Python supports Unicode characters, emojis and mathematical symbols. smiley = “😊”

Python Keywords

Keywords are reserved words. Each keyword has a specific meaning to the Python interpreter, and we can use a keyword in our program only for the purpose for which it has been defined. As Python is case sensitive, keywords must be written exactly.

Identifiers

Identifiers are names used in programming languages to identify a variable, function, or other things in a programme. Python has the following guidelines for naming an identifier:

• The name should begin with an uppercase or a lowercase alphabet or an underscore sign (_).
• It can be of any length.
• It should not be a keyword or reserved word.
• We cannot use special symbols like !, @, #, $, %, etc.

Literal in Python

In Python, a literal represents a fixed value directly using the program. It is raw data assigned to a variable. Literals are immutable, meaning the value of a literal cannot be changed during program execution.

Python supports several types of literals:

• Numeric Literals: integer_literal = 100, float_literal = 10.5, complex_literal = 3 + 5j
• String Literals: string_literal = ‘Hello, Python!’
• Boolean Literals: boolean_literals = True
• Special Literals: x = None
• List Literals: my_list = [1, “Amit”, 34]
• Tuple Literals: my_tuple = (1, “Amit”, 34)
• Dictionary literals: my_dict = {“rollno”: 1, “name”: “Amit”, “age”: 34}
• Set Literal: my_set = {1, 2, 3}

Operator in Python

Operators are specialized symbols that perform arithmetic or logical operations. The operation in the variable is applied using operands. The python operators are:

• Arithmetic operators (+, -, * /, %, **, //)
• Bitwise operators (&, ^, |)
• Shift operators (<<, >>)
• Identity operators (is, is not)
• Relational operators (>, <, >=, <=, ==, !=)
• Logical operators (and, or)
• Assignment operator ( = )
• Membership operators (in, not in)
• Arithmetic-assignment operators (/=, +=, -=, %=, **=, //=).

Punctuator in Python

The structures, statements, and expressions in Python are organized using these symbols known as punctuators. Several punctuators are in python [ ] { } ( ) @ -= += *= //= **== = , etc.

Variables

A variable is used to hold the values. In Python, the term “variable” refers to an object, where a variable points to objects in memory. A variable’s value can be a string, such as “Amit”, or a number, such as “345”, or any combination of alphanumeric characters (CD67). In Python, we can create new variables and give them particular values by using an assignment operator (=).

gender = ‘M’
message = “Keep Smiling”
price = 987.9

Concept of l-value and r-value

In Python, “L-value” refers to a memory location that identifies an object, and “R-value” refers to the data value that is stored at some address in memory.

Example,

• L – Value: This refers to the variable name which helps to hold the R – Values. Example, x = 10 (‘x’ is the l-value)
• R – Value: This refers to the actual data or object being assigned to the l-value. Example, y = x + 5 (‘x + 5’ is the r-value)

Comments

In the source code, comments are used to add remarks or notes in the program. The interpreter uses comments to make the source code simpler and easy to understand for the programmer. Comments always start with #.

Example,

#Add your python comments

Data Types

In Python, each value corresponds to a certain data type. A variable’s data type describes the kinds of data values it can store and the types of operations it can execute on that data. The data types that Python.

Number

Only numerical values are stored in the Number data type. Three other categories are used to further categories it: int, float, and complex.

Sequence

An ordered group of things, each of which is identified by an integer index, is referred to as a Python sequence. Strings, Lists, and Tuples are the three different forms of sequence data types that are available in Python.

1. String – A string is a collection of characters. These characters could be letters, numbers, or other special characters like spaces. Single or double quotation marks are used to surround string values for example, ‘Hello’ or “Hello”).
2. List – List is a sequence of items separated by commas and the items are enclosed in square brackets [ ]. example list1 = [5, 3.4, “New Delhi”, “20C”, 45]
3. Tuple – A tuple is a list of elements enclosed in parenthesis and separated by commas ( ). Compared to a list, where values are denoted by brackets [], this does not. We cannot alter the tuple once it has been formed. example tuple1 = (10, 20, “Apple”, 3.4, ‘a’)

Set

A set is a group of elements that are not necessarily in any particular order and are enclosed in curly brackets. The difference between a set and a list is that a set cannot include duplicate entries. A set’s components are fixed once it is constructed. examle set1 = {10,20,3.14,”New Delhi”}

None

A unique data type with only one value is called None. It is employed to denote a situation’s lack of worth. None is neither True nor False, and it does not support any special operations (zero). example myVar = None

Mapping

Python has an unordered data type called mapping. Python currently only supports the dictionary data type as a standard mapping data type.

1. Dictionary – Python’s dictionary stores data elements as key-value pairs. Curly brackets are used to surround words in dictionaries. Dictionary use enables quicker data access. example, dict1 = {‘Fruit’:’Apple’, ‘Climate’:’Cold’, ‘Price(kg)’:120}

Mutable and Immutable Data Types

Once a variable of a certain data type has been created and given values, Python does not enable us to modify its values. Mutable variables are those whose values can be modified after they have been created and assigned. Immutable variables are those whose values cannot be modified once they have been created and assigned.

Expressions

Expressions are fundamental building blocks of Python code. They are a combination of values, variables, operators, and function calls that the interpreter can evaluate to produce a result.

For example:

• 5 + 3: This equation is an expression that adds two numbers.
• x * 2: If x = 4, this expression would evaluate to 8.
• ‘Hello’ + ‘ World’: This joins two strings to form “Hello World.”

Order of Precedence

Statement

In Python, a statement is a unit of code that the Python interpreter can execute.

x = 4                           #assignment statement
cube = x ** 3              #assignment statement
print (x, cube)            #print statement
4 64

Input and Output

The input() function allows a program to receive data from the user and the print() function allows a program to display data to the user.

fname = input("Enter your first name: ")
age = input("Enter your age: ")
print(fname + age)

Type Conversion

Type conversion is also known as type casting in Python. Type conversion refers to the process of changing a value from one data type to another. Python supports two main types of type conversion:

1. Explicit Conversion
2. Implicit Conversion

Explicit Conversion

Explicit type conversion, also known as type casting, is used when a programmer manually converts a value from one data type to another using a built-in function, such as int(), float(), or str().

Type Conversion between Numbers and Strings

num_str = "10"                      # A string
num_int = int(num_str)         # Convert string to integer

print(num_int)                       # Output: 10
print(type(num_int))              # Output: <class 'int'>

Implicit Conversion

When Python converts data types automatically without a programmer’s instruction, this is referred to as implicit conversion, also known as coercion.

Implicit type conversion from int to float

num_int = 5              # Integer
num_float = 2.5         # Float
result = num_int + num_float

print(result)                 # Output: 7.5
print(type(result))       # Output: <class 'float'>

Debugging

Debugging is the process of finding and fixing errors, or ‘bugs,’ in programming code. It involves identifying the type of error—whether it is a syntax error, runtime error, or logical error—and resolving it to ensure the program runs correctly. There are three types of errors:

1. Syntax errors
2. Logical errors
3. Runtime errors

Syntax Errors

When the code does not follow the rules of the programming language. Example: missing parentheses in Python.

print("Hello"                    # SyntaxError: missing closing parenthesis

Logical Errors

Logical errors do not crash the program but generate incorrect output due to incorrect logic.

x = 10
y = 5

result = x - y                          # Logical error: should be x + y
print("Result:", result)            # Expected output: 15, but prints 5

Runtime Error

A runtime error occurs when the program is running, and an error is generated due to invalid operations like dividing by zero.

num = 5 / 0               # RuntimeError: division by zero

Computer Science Class 11 Notes important links

• Computer Systems and Organisation
• Introduction to problem solving
• Getting Started with Python
• Flow of Control statements in Python
• String in Python
• Lists in Python
• Tuples in Python
• Dictionary in Python
• Society, Law and Ethics

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