App Dev Notes PDF

Input and Output: - **Software Development Process**: Consists of five key stages: Understanding the Problem, Defining Specifications, Planning the Solution, Writing the Code, and Testing & Debugging. - **Understanding the Problem**: Clarify what the program needs to accomp...

Input and Output: - **Software Development Process**: Consists of five key stages: Understanding the Problem, Defining Specifications, Planning the Solution, Writing the Code, and Testing & Debugging. - **Understanding the Problem**: Clarify what the program needs to accomplish and identify the target audience. A thorough grasp of the problem sets the foundation for a successful program. - **Defining Specifications**: Outline the features and functions required for the program. This acts as a blueprint, detailing inputs, processing needs, and expected outputs. - **Planning the Solution**: Map out how the program will work. Choose appropriate algorithms and data structures to ensure efficiency and clarity in the program's design. - **Writing the Code**: Convert the plan into actual code using a programming language like Python. Focus on readability and maintainability to facilitate future modifications. - **Testing and Debugging**: Rigorously test the program under various conditions to identify and fix bugs. Continuous testing ensures the software performs as intended. - **Input, Processing, and Output**: The three main actions of any program. Input gathers data, manipulates it according to specified rules, and output presents results to users. - **Variables**: Serve as named references for storing data, enabling easier management and manipulation. Python's naming conventions, case sensitivity, and reserved keywords are crucial for clarity and functionality. - **Expressions**: Allow for the creation and manipulation of data values through operations. They can be simple (like literals) or complex (involving multiple operations). - **Output Statements**: The print() function is essential for displaying information. It can be customized using parameters like sep and end to format output effectively. - **Assignment Statements**: Assign values to variables, allowing for updates and references. Understanding how assignment works helps in managing data flow in programs. - **User Input**: The input() function collects user data as strings, which can be converted to the desired type for further processing. - **Multiple Assignment**: Enables assigning values to multiple variables simultaneously, improving code efficiency and readability, especially when swapping values. - Rules for creating variable names -- - **A variable name must begin with a letter or an underscore (\_).** - **A variable name cannot start with a number.** - **A variable name can only contain letters, numbers, and**\ **underscores (A-Z, a-z, 0-9, and \_).** - **Variable names are case-sensitive, meaning height, Height,**\ **and HEIGHT are all different variables.** - **Variable names cannot be Python keywords.** - Python keywords are case sensitive (True or False). **False** - Literal -- **Numeric and string literals represent specific values** - What is an expression? Give an example. **Expressions are snippets of code that generate or calculate new data values. Examples: 4.5, 1, 9, 32** - What are the Python operators? **Symbols that perform operations on variables and values** - Concatenation -- **Combining strings together** - print -- **Fundamental tool used to display information on screen** - sep -- **specifies the string inserted between each expression** - end -- **specifies the string appended at the end of the output** - assignment statement -- **allows you to assign values to variables** - input() -- **Used to get input from the user, and it always returns the input as a string** - All input values are returned as strings (True or False). **True** Variables and Data Types: - **Data Type**: Defines the nature of data a variable can hold. - **Numeric Types**: Includes integers, floats, and complex numbers. - **Text Types**: Refers to strings. - **Boolean Types**: Represents truth values (True or False). - **Type Conversion**: Changing one data type to another. - **Operators**: Symbols that perform operations on variables and values. 1. Numeric Data Types a. In programming, data types play a pivotal role, particularly in handling numerical data. Python categorizes numbers into three primary types: i. **Integers** (*int*): Whole numbers without decimals. ii. **Floats** (*float*): Numbers that contain decimal points, allowing for more precise representation. iii. **Complex Numbers**: These consist of a real part and an imaginary part, denoted with a suffix 'j'. b. Python offers a variety of operations for these number types, including arithmetic operations and type conversion. For example, the type() function is utilized to check the type of a variable. 2. Strings c. Strings in Python can be enclosed in **single** (' ') or **double** (\" ") quotation marks, which provides flexibility, particularly when dealing with quotes within strings. Multi-line strings can be created using triple quotes ("\"\" or '''). ### **String Operations** iv. **Slicing**: Allows extraction of a substring using indices. For instance, string \[2:5\] extracts characters from index 2 to 4. v. **Concatenation**: Combines strings using the + operator. vi. **String Formatting**: Achieved through f-strings (e.g., f\"Hello, {name}\") or the format() method. ### **Practical Application** vii. The chapter emphasizes the utility of string operations in real-world applications, such as formatting user output and handling text data. 3. Boolean d. The Boolean data type in Python is crucial for decision-making in programs. It has two possible values: **True** and **False**. Various **comparison operators** (e.g., \>, \ 4. Type Conversion g. Type conversion, or casting, is a critical skill in Python that allows the transformation of one data type to another using constructor functions like int(), float(), and str(). This is particularly useful when handling user input, which is typically in string format. h. ### **Example of Type Conversion** xi. user\_input = input(\"Enter a number: \") number = int(user\_input) print(f\"The number you entered is {number}\") xii. This example shows how to convert user input from a string to an integer, showcasing the necessity of type conversion in program functionality. 5. Operators i. Operators are fundamental in Python, facilitating a variety of operations on variables and values. The chapter categorizes operators into several types, including: xiii. **Arithmetic Operators**: Used for basic mathematical operations (e.g., +, -, \*, /). xiv. **Comparison Operators**: Compare values and return Boolean results. xv. **Logical Operators**: Combine conditional statements for more complex evaluations. j. ### Practical Use Cases xvi. Operators are integral to decision-making processes in programming, allowing for complex expressions and conditional statements that control the flow of execution. 6. Data type specifics\ 1. Str -- Text Type\ 2. Float -- Numeric Types 7. **Integers (int)** - Whole numbers without a fractional component (Ex: 1, -4, 8, 100, -32) 8. **Floating-point numbers (float)** - Numbers that contain a decimal point / Suitable for representing precise values (Ex: 12.345, 3.256, 2.1, 0.0036) 9. Text -- Keywords -- String of characters enclosed in quotes 10. **Boolean Types** - "bool" / Used to evaluate expressions and make decisions as same as in other programming languages / Two possible values (True/False) 11. **Casting or Conversion** -- Converting string-formatted numbers for calculations 12. **Arithmetic Operators** -- Operators for mathematical computations 13. **Slicing** -- Extract substrings from strings 14. **Concatenation** -- Combine strings using "+" operator 15. **import** -- Necessary to generate random numbers 16. **random** -- Generates random numbers 17. **f-strings** -- efficient way to format strings in Python / allowing embedding of variables 18. **Relational or Comparison Operators** -- Operators that compare two values 19. **Boolean or Logical Operators** -- True, False, comparison operators Conditional Structures: 1. **The if Statement** a. **Syntax**: if condition: b. **Comparison Operators**: i. Equals: a == b ii. Not Equals: a != b iii. Less Than: a \< b iv. Greater Than: a \ b c. **Example**: Check if b \> a and print accordingly. d. **Indentation** is crucial to define code blocks. 2. **The if-else Statement** e. **Syntax**:if condition: \# code if true else: \# code if false f. **Functionality**: Executes one block for true, another for false. g. **Example**: Check if a number is even or odd. 3. **The if-elif-else Statement** h. **Syntax**:if condition1: \# code if condition1 is true elif condition2: \# code if condition2 is true else: \# code if none are true i. **Example**: Categorize numerical grades into letter grades. 4. **The match-case Statement** j. Introduced in Python 3.10, it serves as an alternative to switch statements. k. **Syntax**:match value: case 1: \# code for case 1 case 2: \# code for case 2 case \_: \# default case l. **Example**: Match against various values with a default case. 5. **Control flow** -- Enhances decision -- making and automation / Improves code readability 6. **if statement** -- Allows program to execute certain code only if a specific condition is true. 7. **Relational or conditional operators** -- Operators that are used to compare values 8. **Indentation** -- Define the scope of code blocks. (Different from other programs that use curly braces {}) 9. **if -- else statement** -- Allows program to execute one block of code if a condition is true, and another block of code if the condition is false. 10. **if -- elif -- statement** -- Check multiple conditions one by one. Program executes the block of code under the first condition that is true. If no conditions are true, code block under the else statement is executed 11. **match -- case statement** -- Offers functionality like a switch statement in other languages. Allows for pattern matching and is more expressive than using other sequence data types.