Python

To debug Python code with AI you first read the traceback yourself, isolate the failing line, then paste the error and the surrounding code into an assistant with enough context for a precise answer. This chapter covers how tracebacks are structured, the eight error messages you will meet most often, the prompt that gets useful […]

Python sets are unordered collections of unique items, written in curly braces such as {“North”, “South”, “East”}. Add a value that is already present and nothing happens, which makes sets the fastest way to remove duplicates, test membership and compare two groups. This chapter covers creating Python sets, adding and removing items, and the union, […]

Python user input is read with the built-in input() function. It pauses the program, shows an optional prompt, waits for the person to type something and press Enter, and returns whatever they typed as a string. Because the result is always text, you must convert and validate it before using it in calculations, usually inside […]

Python regex (regular expressions) is pattern matching for text, provided by the built-in re module. Instead of checking for one fixed word, you describe a shape: “three letters, a dash, four digits” or “anything between angle brackets”. With search, findall, sub and fullmatch you can find, extract, replace and validate text in a few lines. […]

To automate Excel reports with Python and AI you let pandas do the calculations, openpyxl build a formatted workbook with a chart, and an AI API write the executive summary from the numbers you calculated. The result is a monthly report that takes one command instead of an afternoon, and a summary that is grounded […]

Python tuples are ordered collections that cannot be changed after they are created, written in parentheses such as (“Pune”, 411001, “India”). They hold records whose shape is fixed: a coordinate pair, a database row, the two values a function hands back. This chapter covers creating Python tuples, unpacking them, the few methods they have and […]

Python web scraping means downloading a web page with requests and pulling the data you need out of its HTML with BeautifulSoup. This chapter scrapes book titles, prices and ratings from a practice site, follows pagination, saves the result to CSV and explains the rules (robots.txt, terms of use, rate limits) that keep scraping legal […]

Python type casting means converting a value from one data type to another, for example turning the text “250” into the integer 250 so you can add to it. The main casting functions are int(), float(), str() and bool(), plus list(), tuple(), set() and dict() for collections. This chapter shows when each one is needed […]

Python try except is the mechanism for handling errors without crashing your program. Code that might fail goes in a try block; if an exception occurs, Python jumps to the matching except block instead of stopping. Optional else and finally clauses run when no error occurred and when the block finishes, respectively. Why exceptions matter […]

Python lists are ordered, changeable collections written in square brackets, such as [“Laptop”, “Monitor”, “Mouse”]. They are the workhorse data structure of the language: a column of sales figures, a queue of tasks, the rows read from a CSV file. This chapter shows how to create Python lists and how to access, add, remove, sort […]