<h5 id="51-introduction-to-python">5.1 INTRODUCTION TO PYTHON</h5> <ul> <li>Programming language is a set of instructions written in a form that can be understood and executed by computers.</li> <li>There are two types of programming languages: high-level and low-level. High-level languages, like Python, are easier for humans to understand and use, while low-level languages, like machine language, are written in 0s and 1s and are difficult for humans to comprehend.</li> <li>A programming language translator, like a compiler or interpreter, is needed to translate high-level language code into machine language.</li> <li>Python uses an interpreter to convert its instructions into machine language, processing the program statements one by one until an error is encountered or the whole program is executed successfully.</li> <li>The source code written in Python is called a program, which is a set of instructions executed by a computer to carry out a specific task.</li> </ul> <p>======</p> <h5 id="511-features-of-python">5.1.1 Features of Python</h5> <ul> <li>Python is a high-level, open-source language with a clearly defined syntax.</li> <li>It is an interpreted language, run by an interpreter, and case-sensitive.</li> <li>Python is portable, platform-independent, and has a rich library of predefined functions.</li> <li>It is widely used in web development, with many popular web services built using Python.</li> <li>Python uses indentation for blocks and nested blocks, and its latest version 3 can be downloaded from the official website.</li> </ul> <p>======</p> <h5 id="512-working-with-python">5.1.2 Working with Python</h5> <ul> <li>To write and run a Python program, a Python interpreter is required.</li> <li>This interpreter, also known as the Python shell, can be installed on a computer or used online.</li> <li>The Python prompt, denoted by ‘»’, indicates that the interpreter is ready for instructions.</li> <li>Commands or statements can be typed on this prompt to be executed by the Python interpreter.</li> <li>A sample screen of the Python interpreter is shown in Figure 5.1.</li> </ul> <p>======</p> <h5 id="513-execution-modes">5.1.3 Execution Modes</h5> <ul> <li>The Python interpreter can be used in two ways: Interactive mode and Script mode.</li> <li>Interactive mode allows execution of individual statements instantly, without saving them for future use.</li> <li>Script mode allows writing a Python program in a file, saving it, and then using the interpreter to execute it. Python scripts are saved as files with the extension “.py”.</li> <li>In Script mode, the output appears on the shell, and a program can be executed by typing the file name at the prompt, opening it directly from IDLE, or clicking [Run]->[RunModule] from the menu.</li> <li>An example of a program in Script mode is writing a program to show a print statement (Program 5-1).</li> </ul> <p>======</p> <h5 id="52-python-keywords">5.2 PYTHON KEYWORDS</h5> <ul> <li>The text is about a summary of various Python concepts.</li> <li>The <code>continue</code> statement is used to end the current iteration of a loop and continue with the next iteration.</li> <li>The <code>for</code> loop is used for iterating over a sequence (like list, tuple, string) and <code>lambda</code> is used to create small anonymous functions.</li> <li>The <code>tryTrue</code> statement is not a valid Python concept, it seems to be a mistake.</li> <li>The <code>def</code> keyword is used to define functions, <code>from</code> is used to import specific parts of modules, and <code>nonlocal</code> is used to declare a variable as non-local.</li> <li>The <code>whileand</code> statement is not a valid Python concept, it seems to be a mistake.</li> <li>The <code>del</code> keyword is used to delete an object from memory, <code>global</code> is used to declare a variable as global, and <code>not</code> is a Boolean operator.</li> <li>The <code>withas</code> statement is not a valid Python concept, it seems to be a mistake. It should be <code>with</code> statement which is used to wrap the execution of a block with methods defined by a context manager.</li> <li>The <code>elif</code> and <code>if</code> statements are used for conditional execution of code, <code>or</code> is a Boolean operator, and <code>yield</code> is used in generator functions to produce a value.</li> <li>The <code>assert</code> statement is used for debugging, <code>else</code> is used in <code>if</code> statements for the case when the condition is not met, <code>import</code> is used to import modules, and <code>pass</code> is a placeholder used when a statement is required syntactically.</li> <li>The <code>break</code> statement is used to terminate a loop, <code>except</code> is used to catch and handle exceptions, <code>in</code> is used for membership testing and <code>raise</code> is used to raise an exception.</li> </ul> <p>======</p> <h5 id="53-identifiers">5.3 IDENTIFIERS</h5> <ul> <li>Identifiers are names used to identify a variable, function, or other entities in a program.</li> <li>In Python, identifiers should begin with an uppercase or lowercase alphabet, an underscore, and can be followed by any combination of characters $a-z, A-Z, 0-9$ or underscore.</li> <li>Identifiers cannot start with a digit and can be of any length, but it is preferred to keep them short and meaningful.</li> <li>Identifiers should not be a keyword or reserved word, and special symbols are not allowed.</li> <li>Examples: avg = (marks1 + marks2 + marks3) / 3 (for finding average), area = length * breadth (for calculating area of a rectangle).</li> </ul> <p>======</p> <h5 id="54-variables">5.4 VARIABLES</h5> <ul> <li>A variable in Python is an object that is stored in memory, identified by a unique name or identifier. Its value can be a string, numeric, or any combination of alphanumeric characters.</li> <li>Variables can be created and assigned specific values using an assignment statement. In Python, variable declaration is implicit.</li> <li>Variables must always be assigned values before they are used in expressions to avoid errors.</li> <li>The interpreter replaces the variable name with its value wherever it occurs in an expression.</li> <li>Program 5-3 calculates the area of a rectangle with a length of 10 units and a breadth of 20 units. The area is calculated by multiplying the length and breadth, resulting in an output of 200.</li> </ul> <p>======</p> <h5 id="55-comments">5.5 COMMENTS</h5> <ul> <li>Comments in Python start with a hash sign (#) and extend to the end of the line.</li> <li>They are not executed by the interpreter and are used to add notes or remarks for human understanding.</li> <li>Comments are primarily used for documentation, explaining the purpose, input, and output requirements of the code.</li> <li>They are crucial for large and complex software where multiple programmers may work in teams and maintain each other’s code.</li> <li>Example: In Program 5-4, comments are used to explain the purpose of variables and the process of finding the sum of two numbers.</li> </ul> <p>======</p> <h5 id="56-everything-is-an-object">5.6 Everything is an Object</h5> <ul> <li>In Python, every value or data item is treated as an object, which can be assigned to a variable or passed to a function as an argument.</li> <li>Each object in Python is assigned a unique identity (ID), which remains the same for the lifetime of that object, acting like the memory address of the object. The function <code>id()</code> returns the identity of an object.</li> <li>In the context of Object Oriented Programming (OOP), objects represent real-world entities, such as employee, student, vehicle, box, book, etc., having data or attributes and behavior or methods.</li> <li>However, in Python, the definition of an object is loosely casted, as some objects may not have attributes, and others may not have methods.</li> <li>Example 5.2 demonstrates this concept with <code>num1</code> and <code>num2</code> being objects with the same identity, indicating both refer to the same object, i.e., the integer 20.</li> </ul> <p>======</p> <h5 id="57-data-types">5.7 DATA TYPES</h5> <ul> <li>In Python, every value belongs to a specific data type which determines the operations that can be performed on that data.</li> <li>There are several data types available in Python, including: <ul> <li>int (integer): Whole numbers, e.g., 7, -12, 0.</li> <li>float (floating-point number): Decimal numbers, e.g., 7.5, -12.3, 0.0.</li> <li>str (string): Text, enclosed in quotes, e.g., “hello”, ‘world’, “123”.</li> <li>bool (Boolean): True or False values.</li> <li>list: Ordered, mutable sequence of items (can contain different data types), e.g., [1, 2, 3], [“a”, “b”, “c”].</li> <li>tuple: Ordered, immutable sequence of items (can contain different data types), e.g., (1, 2, 3), (“a”, “b”, “c”).</li> <li>set: Unordered collection of unique items (can contain different data types), e.g., {1, 2, 3}, {“a”, “b”, “c”}.</li> <li>dict (dictionary): Collection of key-value pairs, e.g., {“key1”: “value1”, “key2”: “value2”}.</li> </ul> </li> <li>Variables in Python are assigned a data type based on the value they hold.</li> <li>Data types can be checked using built-in functions like type() and isinstance().</li> </ul> <p>======</p> <h5 id="571-number">5.7.1 Number</h5> <ul> <li>Integers, float, and boolean are types of simple data types in Python.</li> <li>Integer numbers are whole numbers, positive or negative, without decimals, of unlimited length.</li> <li>Float or real/floating point numbers are numbers that contain a decimal point.</li> <li>Boolean data type is a subtype of integer, consisting of two constants, True and False.</li> <li>Complex numbers consist of real and imaginary components. The real component is a whole number or a decimal number. The imaginary component is a number that is multiplied by the imaginary unit i, where i^2 = -1.</li> <li>Python provides data types like tuples, lists, dictionaries, and sets for holding a long list of information.</li> </ul> <p>======</p> <h5 id="572-sequence">5.7.2 Sequence</h5> <ul> <li>A Python sequence is an ordered collection of items, with each item indexed by an integer.</li> <li>String: A group of characters, enclosed in single or double quotation marks. Numerical operations cannot be performed on strings.</li> <li>List: A sequence of items separated by commas and enclosed in square brackets. Items can be changed after creation.</li> <li>Example of List: list1 = [5, 3.4, “New Delhi”, “20C”, 45]</li> <li>Tuple: A sequence of items separated by commas and enclosed in parenthesis. Items cannot be changed after creation.</li> <li>Example of Tuple: tuple1 = (10, 20, “Apple”, 3.4, ‘a’)</li> </ul> <p>======</p> <h5 id="573-set">5.7.3 Set</h5> <ul> <li>A set is an unordered collection of unique items, often denoted using curly brackets {}.</li> <li>Set elements are separated by commas and cannot have duplicate entries.</li> <li>Once a set is created, its elements cannot be changed.</li> <li>Sets are similar to lists, but sets cannot have duplicate entries.</li> <li>Example: set1 = {10, 20, 3.14, “New Delhi”} and set2 = {1, 2, 1, 3} will be printed as {10, 20, 3.14, “New Delhi”} and {1, 2, 3} respectively, with duplicate elements removed in set2.</li> </ul> <p>======</p> <h5 id="574-none">5.7.4 None</h5> <ul> <li>None is a special data type in Python, with a single value: None.</li> <li>It is used to signify the absence of value in a situation.</li> <li>None does not support any special operations.</li> <li>It is not the same as False or 0 (zero).</li> <li>Example: myVar = None; print(type(myVar)) <class ‘NoneType’>; print(myVar) returns None.</li> </ul> <p>======</p> <h5 id="575-mapping">5.7.5 Mapping</h5> <ul> <li>Mapping in Python is an unordered data type, with only one standard mapping data type: dictionary.</li> <li>A dictionary holds data items in key-value pairs, with keys and values separated by a colon (:).</li> <li>Keys are usually strings, and values can be any data type. To access any value, specify its key in square brackets [].</li> <li>Dictionary keys can be accessed directly, and the keys themselves are unique.</li> <li>Dictionary items can be added, updated, or deleted using assignment operators.</li> </ul> <p>(Note: The example provided does not need to be summarized as per instruction #2)</p> <p>======</p> <h5 id="576-mutable-and-immutable-data-types">5.7.6 Mutable and Immutable Data Types</h5> <ul> <li>Variables in Python can be mutable or immutable.</li> <li>Mutable variables are those whose values can be changed after they are created and assigned.</li> <li>Immutable variables are those whose values cannot be changed after they are created and assigned.</li> <li>When an attempt is made to update the value of an immutable variable, a new variable is created with the same name in memory.</li> <li>Python data types such as lists, dictionaries, and sets are mutable, while integers, floats, and tuples are immutable.</li> </ul> <p>======</p> <h5 id="577-deciding-usage-of-python-data-types">5.7.7 Deciding Usage of Python Data Types</h5> <ul> <li>Lists are ideal for simple, iterable collections of data that undergo frequent modifications.</li> <li>Tuples are used when no changes in the data are required, such as the names of months in a year.</li> <li>Sets ensure uniqueness of elements and avoid duplicity, making them suitable for lists of items like artefacts in a museum.</li> <li>When data is constantly modified, or fast lookups based on custom keys are needed, dictionaries are recommended.</li> <li>Dictionaries create a logical association between keys and values, making them suitable for applications like a phone book.</li> </ul> <p>======</p> <h5 id="58-operators">5.8 OPERATORS</h5> <ul> <li>An operator in Python is used to perform specific mathematical or logical operations on values, known as operands.</li> <li>Python supports several kinds of operators, categorized as follows: <ul> <li>Arithmetic Operators (e.g., +, -, *, /, %, //, **)</li> <li>Comparison Operators (e.g., <, <=, >, >=, ==, !=)</li> <li>Assignment Operators (e.g., =, +=, -=, *=, /=, %=, //=, **=)</li> <li>Logical Operators (e.g., and, or, not)</li> <li>Identity Operators (e.g., is, is not)</li> <li>Bitwise Operators (e.g., &, |, ^, ~, «, »)</li> </ul> </li> <li>Python compares strings lexicographically, using ASCII values of the characters.</li> <li>The comparison starts with the first character of both strings, and if they are the same, moves on to the second character, and so on.</li> </ul> <p>======</p> <h5 id="581-arithmetic-operators">5.8.1 Arithmetic Operators</h5> <ul> <li>The addition operator (+) adds two numeric values or concatenates two strings. Example: num1 + num2 = 11, str1 + str2 = “HelloIndia”.</li> <li>The subtraction operator (-) subtracts the operand on the right from the operand on the left. Example: num1 - num2 = -1.</li> <li>The multiplication operator (*) multiplies the two values on both sides of the operator. Example: num1 * num2 = 30.</li> <li>The division operator (/ or /) divides the operand on the left by the operand on the right. Example: num2 / num1 = 0.5, num1 / / num2 = 3.</li> <li>The modulus operator (%) divides the operand on the left by the operand on the right and returns the remainder. Example: num1 % num2 = 3.</li> <li>The exponent operator (** or ^) performs exponential (power) calculation on operands. Example: num1 ** num2 = 81.</li> </ul> <p>======</p> <h5 id="582-relational-operators">5.8.2 Relational Operators</h5> <ul> <li>The equality operator (==) returns true if the values of two operands are equal, otherwise it returns false. For example, num1 == num2 would return false.</li> <li>The not equal to operator (!=) returns true if the values of two operands are not equal, otherwise it returns false. For example, num1 != num2 would return true.</li> <li>The greater than operator (>) returns true if the value of the left-side operand is greater than the value of the right-side operand, otherwise it returns false. For example, num1 > num2 would return true.</li> <li>The less than operator (<) returns true if the value of the left-side operand is less than the value of the right-side operand, otherwise it returns false. For example, num1 < num3 would return false.</li> <li>The greater than or equal to operator (>=) returns true if the value of the left-side operand is greater than or equal to the value of the right-side operand, otherwise it returns false. For example, num1 >= num2 would return true.</li> <li>The less than or equal to operator (<=) returns true if the value of the left-side operand is less than or equal to the value of the right-side operand, otherwise it returns false. For example, num1 <= num2 would return false.</li> </ul> <p>======</p> <h5 id="583-assignment-operators">5.8.3 Assignment Operators</h5> <ul> <li>The ‘+=’ operator assigns the result of addition of right and left operands to the left operand.</li> <li>The ‘-=’ operator assigns the result of subtraction of right operand from left operand to the left operand.</li> <li>The ‘*=’ operator assigns the result of multiplication of right and left operands to the left operand.</li> <li>The ‘/=’ operator assigns the result of division of left operand by right operand to the left operand.</li> <li>The ‘%=’ operator performs modulus operation and assigns the result to the left operand.</li> <li>The ‘//=’ operator performs floor division and assigns the result to the left operand.</li> <li>The ‘**=’ operator performs exponential calculation and assigns the result to the left operand.</li> </ul> <p>======</p> <h5 id="584-logical-operators">5.8.4 Logical Operators</h5> <ul> <li>The ‘AND’ operator returns true if both operands are true. For example, <code>True and True</code> returns true.</li> <li>The ‘OR’ operator returns true if at least one of the operands is true. For example, <code>True or False</code> returns true.</li> <li>The ‘NOT’ operator returns true when the operand is false and vice versa. For example, <code>not True</code> returns false.</li> <li>In logical operations, numbers are first converted to boolean values. Zero is considered false, and all other numbers are considered true.</li> <li>In Python, the <code>bool()</code> function can be used to get the boolean value of an expression or variable.</li> </ul> <p>======</p> <h5 id="585-identity-operators">5.8.5 Identity Operators</h5> <ul> <li>The “is” operator in Python evaluates to True if the variables on either side of the operator point to the same memory location, and False otherwise.</li> <li>For example, if num1 $= 5$, then type(num1) is int and num1 is num2 will evaluate to True.</li> <li>The id() function returns the memory location of the object. In this case, id(num1) and id(num2) are the same, indicating that num1 and num2 point to the same memory location.</li> <li>The “is not” operator in Python evaluates to True if the variables on either side of the operator do not point to the same memory location, and False otherwise.</li> <li>For example, if num1 is not num2 will evaluate to False, since num1 and num2 point to the same memory location.</li> </ul> <p>======</p> <h5 id="586-membership-operators">5.8.6 Membership Operators</h5> <ul> <li>The ‘in’ keyword returns True if a variable/value is found in the specified sequence and False otherwise. For example, ‘1’ is in the list [1,2,3], so in a returns True, while ‘10’ is not in the list, so 10 not in a also returns True.</li> <li>The ’not in’ keyword returns True if a variable/value is not found in the specified sequence and False otherwise. For example, ‘1’ is not in the list [2,3,4], so 1 not in a returns True, while ‘10’ is not in the list [1,2,3], so 10 not in a returns False.</li> <li>In the above examples, ‘a’ is a list, and ‘1’, ‘2’, ‘3’, and ‘10’ are integers.</li> <li>The ‘in’ and ’not in’ keywords are used to check membership in a sequence.</li> <li>The ‘in’ and ’not in’ keywords can be used with various types of sequences, such as lists, strings, and dictionaries.</li> </ul> <p>======</p> <h5 id="59-expressions">5.9 EXPRESSIONS</h5> <ul> <li>An expression is a combination of constants, variables, and operators.</li> <li>It always evaluates to a value.</li> <li>A value or a standalone variable is also considered an expression.</li> <li>A standalone operator is not an expression.</li> <li>Examples of valid expressions include 100, 3.0 + 3.14, 23/3 -5 * 7 (14 -2), and “Global” + “Citizen”.</li> </ul> <p>======</p> <h5 id="591-precedence-of-operators">5.9.1 Precedence of Operators</h5> <ul> <li>Exponentiation, multiplication, division, modulo, floor division, addition, subtraction, and unary minus are the different types of operators in Python.</li> <li>The precedence of operators determines the order in which operations are performed. For example, multiplication is performed before addition.</li> <li>Parentheses can be used to override the precedence of operators. The expression within parentheses is evaluated first.</li> <li>For operators with equal precedence, the expression is evaluated from left to right.</li> <li>Examples are provided to illustrate the order of operation based on precedence and the use of parentheses.</li> </ul> <p>======</p> <h5 id="510-statement">5.10 STATEMENT</h5> <ul> <li>In Python, a statement is a unit of code that the Python interpreter can execute.</li> <li>Examples of statements include assignment statements and print statements.</li> <li>An assignment statement assigns a value to a variable. For example, <code>x = 4</code> and <code>cube = x ** 3</code> are assignment statements.</li> <li>The print statement prints a value or message to the console. For example, <code>print (x, cube)</code> is a print statement that prints the values of <code>x</code> and <code>cube</code>.</li> <li>The <code>#</code> symbol is used to add comments to a Python program. Comments are not executed by the interpreter and are used to explain the code.</li> </ul> <p>======</p> <h5 id="511-input-and-output">5.11 INPUT AND OUTPUT</h5> <ul> <li>The “print” function in Python is used to output specific text, equations, or variable values.</li> <li>To concatenate strings in Python, you can use the “+” operator or commas when using the “print” function.</li> <li>When using commas to separate multiple arguments in the “print” function, each argument’s data type is preserved.</li> <li>If different data types are used with the “+” operator, an error will occur due to implicit type conversion issues.</li> <li>Example: <code>print("I’m", 16, "years old")</code> will output “I’m 16 years old” preserving the integer value of 16.</li> </ul> <p>======</p> <h5 id="512-type-conversion">5.12 TYPE CONVERSION</h5> <ul> <li>In Python, the input function returns a string by default. Therefore, in the statement <code>num1 = num1 * 2</code>, <code>num1</code> is treated as a string, and the multiplication operator <code>*</code> acts as a repetition operator, leading to unexpected results.</li> <li>To obtain the correct output, it is necessary to convert the string input to an integer using the <code>int()</code> function.</li> <li>Type conversion in Python can be explicit or implicit.</li> <li>Explicit type conversion occurs when the programmer specifies the conversion from one data type to another.</li> <li>Implicit type conversion occurs when the interpreter automatically converts the data type based on the context, without the need for explicit instructions from the programmer.</li> </ul> <p>======</p> <h5 id="5121-explicit-conversion">5.12.1 Explicit Conversion</h5> <ul> <li> <p>In Python, explicit type conversion includes:</p> </li> <li> <p><code>int(x)</code>: Converts x to an integer</p> </li> <li> <p><code>float(x)</code>: Converts x to a floating-point number</p> </li> <li> <p><code>str(x)</code>: Converts x to a string representation</p> </li> <li> <p><code>chr(x)</code>: Converts ASCII value of x to character</p> </li> <li> <p><code>ord(x)</code>: Returns the character associated with the ASCII code x</p> </li> <li> <p>Examples of explicit type conversion from int to float and vice versa:</p> <ul> <li>Program 5-5: Converts integer values to float</li> <li>Program 5-6: Converts float to integer, resulting in loss of decimal part</li> </ul> </li> <li> <p>Explicit type casting is needed for converting integers or floats to strings:</p> <ul> <li>Program 5-7: Attempts to concatenate integer and string, resulting in an error</li> <li>Program 5-8: Uses explicit typecasting to concatenate strings</li> <li>Program 5-9: Demonstrates explicit type conversion from string to integer</li> </ul> </li> <li> <p>Explicit type conversion is necessary as implicit conversion may lead to loss of information.</p> </li> </ul> <p>======</p> <h5 id="5122-implicit-conversion">5.12.2 Implicit Conversion</h5> <ul> <li>Implicit conversion, also known as coercion, is an automatic data type conversion done by Python without programmer’s instruction.</li> <li>An example of implicit conversion from int to float is shown in Program 5-10.</li> <li>In this program, an integer value stored in variable num1 is added to a float value stored in variable num2.</li> <li>The result is automatically converted to a float value stored in variable sum1 without explicitly telling the interpreter.</li> <li>This implicit conversion occurs due to type promotion that allows performing operations by converting data into a wider-sized data type without any loss of information.</li> </ul> <p>======</p> <h5 id="513-debugging">5.13 DEBUGGING</h5> <ul> <li>Debugging is the process of identifying and removing errors or bugs in a program.</li> <li>Errors in programming can be categorized into three types: i) Syntax errors: These are mistakes in using the programming language’s syntax or grammar. ii) Logical errors: These are errors in the program’s logic or algorithm, resulting in incorrect output. iii) Runtime errors: These are errors that occur while the program is running, such as division by zero or array index out of bounds.</li> <li>Syntax errors are usually caught by the compiler, while logical and runtime errors might require manual debugging.</li> <li>Effective debugging techniques include using debugging tools, step-by-step execution, and print statements to monitor variable values.</li> </ul> <p>======</p> <h5 id="5131-syntax-errors">5.13.1 Syntax Errors</h5> <ul> <li>Python has its own syntax rules that the interpreter follows for interpretation.</li> <li>If the syntax is not as per Python’s rules, the interpreter shows error messages and stops execution.</li> <li>An example of syntax error is unmatched parentheses, like $(7+11$ which is missing a closing parenthesis.</li> <li>Such syntax errors must be corrected before the program can be executed.</li> <li>The interpreter expects statements to be syntactically correct for interpretation.</li> </ul> <p>======</p> <h5 id="5132-logical-errors">5.13.2 Logical Errors</h5> <ul> <li>A logical error is a type of bug in a program that results in incorrect behavior or output.</li> <li>Unlike syntax errors, logical errors allow the program to run without terminating abruptly.</li> <li>The only evidence of a logical error is often the incorrect output produced by the program.</li> <li>To identify logical errors, one must work backwards from the output to determine what went wrong.</li> <li>Logical errors are also known as semantic errors, as they occur when the meaning or semantics of the program are incorrect.</li> </ul> <p>======</p> <h5 id="5133-runtime-error">5.13.3 Runtime Error</h5> <ul> <li>A runtime error is a type of error that occurs while a program is running or being executed.</li> <li>It is different from a syntax error, which is caught during the compilation stage.</li> <li>Runtime errors are caused when a statement is syntactically correct but the interpreter encounters a problem during execution.</li> <li>For example, a “division by zero” error is a runtime error that occurs when a program attempts to divide a number by zero.</li> <li>Program 5-11 is an example of a program that can generate runtime errors. It produces a runtime error when the user inputs a non-integer value or zero for the variable num2.</li> </ul> <p>======</p>