Introduction to Python Programming

Introduction to Python Programming

• Lecture 1 covers introductory Python programming concepts.
• Chapter objectives include describing algorithm features, understanding computer programs, variables, and assignment in Python, and coding/running simple Python programs.
• Algorithms are sets of steps to complete a task, forming the building blocks of programming and enabling decision-making in computers.
• A concrete example is a method for subtracting two numbers, involving column-aligned digits, proceeding through columns from right to left, and borrowing.
• Algorithms generally consist of a finite number of instructions, where each instruction is clearly defined.
• These actions are performed by a computing agent, eventually leading to a problem solution.
• Algorithms serve as blueprints for completing tasks.

Computer Programming

• This involves a computing agent (often a computer) following an algorithm's instructions, manipulating information, starting with input, transforming it according to rules, and generating output.
• Algorithms and computer programs are interchangeable concepts in the processing of information.
• Programming is essentially instructing a computer, as computers are not inherently intelligent and require explicit instructions.
• A programming language is used to communicate with computers and write programs.

Python Programming Language

• Python is a high-level general-purpose programming language.
• Python syntax is similar to English, enhancing readability and ease of learning.
• Python provides programmers with useful tools like libraries and built-in functions, simplifying development.
• Python has efficient high-level data structures and a simple yet effective object-oriented programming style.
• Python is a free, open-source language; source code is freely readable, modifiable, and distributable.
• Python works as an interpreter, reading one line at a time instead of compiling and then executing.
• Python is beginner-friendly, widely used in machine learning, and possesses mature libraries for various applications like web development, machine learning, data analysis, etc.

Installing Python

• Many computers and Macs already have Python pre-installed.
• To check if Python is installed, use the command prompt (or equivalent) and type "Python."
• Alternative installers include downloading official distributions, using package managers (e.g., Anaconda), or installing specialized versions for numerical computation, Internet of Things (IoT) purposes, or embedded systems.
• The current latest version is frequently updated, so check the Python website to ensure you have the current installer.

Installing Python Using Anaconda Navigator

• For a desktop GUI, Anaconda Navigator can simplify tasks in launching programs, managing packages, and controlling environments, without the need for command lines.
• After downloading from the website, you need to follow simple steps to install the program in your system.

Jupyter Notebook

• Python code can be compiled and run using Jupyter.
• Open Jupyter notebook, creating a new notebook, inputting code for desired tasks, saving data as ".ipynb" files.
• Running code involves using Jupyter's built-in functionalities (e.g. Run, arrow button).

Python Keywords

• Each programming language uses specific keywords (reserved words) with precise meanings.
• Python keywords, which cannot be used in other contexts, comprise 35 different words for use in programming.
• These keywords are different from built-in functions and data types within Python itself.

Python Statements

• Statements are explicit commands to execute by the Python interpreter.
• A statement like y=10 sends the value of 10 to the variable y.
• Python statements, such as if, while, etc. come in a variety of forms, each having a specific purpose in Python programming.
• Continuation characters (/) enable extending statements across multiple lines.
• Brackets ((), {}, []) can be used to define multi-line statements, simplifying complex programming tasks.

Indentation

• Indentation is crucial to Python programming.
• Whitespace at the beginning of a line dictates the block-structuring of code.
• Using consistent whitespace and indentation is required as tab or space combined are not allowed, causing Python to misunderstand the coding structure.
• Correct indentation is essential for unambiguous code interpretation.

Output Variables

• Python's print() function serves to display the results of expressions or statements directly to the console/terminal.
• Python's print command can also show multiple variables separated by commas, providing flexibility in outputting multiple values in one command.
• The + character can also be used to join strings and other values for display via the print() function.
• Combining strings and numbers in the print() function using the + operator can result in errors; instead, use commas for separating different data types.
• The combination must be valid within Python programming syntax to avoid errors.

Global Variables

• Variables declared outside functions are considered global, accessible anywhere inside or outside of the function.
• Variables defined within a function are local, used only inside that function.
• The global keyword makes a variable local, accessible within the function where defined.

Variable Names

• Variable names in Python can be short (e.g., x) or descriptive (e.g., student_name).
• Variable names begin with a letter (A-Z, a-z) or an underscore (_).
• Python variables must contain only alpha-numeric characters or underscores (A-Z, a-z, 0-9, and _).
• Python keywords (e.g., if, while) cannot be used as variable names.
• Variable names are case-sensitive (e.g., name, Name, NAME represent different variables).

Comments in Python

• Comments in Python explain sections of the code (e.g., for documentation).
• Comments are added using the # symbol, enabling programmers to include notes for clarity, understanding, and reference.
• Comments are ignored at runtime but essential for readability and maintainability, especially for large-scale programs or for others reviewing your Python code.

Error Detection

• Programmers frequently make typographical errors or mistakes in syntax during programming (called syntax errors), which lead to program execution errors.
• Understanding syntax, the structure of statements in a programming language, is crucial for correctness.
• Errors are displayed as SyntaxError or NameError, helping programmers locate and correct issues in their code.