Python Introduction and Tutorial

Here is a Python tutorial designed for intelligent individuals new to programming, focusing on the core concepts needed to understand the example scripts later in this book.

Follow one of these links to set up Python on your computer:

• Windows: https://docs.python.org/3/using/windows.html
• MacOS: https://docs.python.org/3/using/mac.html
• Linux: https://docs.python.org/3/using/unix.html#getting-and-installing-the-latest-version-of-python

Welcome to the world of Python! Think of Python not just as a programming language, but as a precise way to give instructions to a computer. Its popularity stems from its readability – Python code often looks surprisingly like plain English. This makes it an excellent starting point for programming and particularly well-suited for interacting with complex systems like AI models. At its heart, programming is about manipulating data and controlling the flow of execution, and Python provides elegant tools for both.

Let’s start with the absolute basics: variables. A variable is simply a named container for storing information. You might have a variable called prompt to hold the text you want to send to Gemini, or temperature_setting to store a numerical value controlling the AI’s creativity. You create a variable by assigning a value to a name using the equals sign (=), like my_name = "Alex". Here, my_name is the variable, and it now holds the text string "Alex". Python automatically figures out the type of data – text (called a string), whole numbers (integers), decimal numbers (floats), or true/false values (Booleans).

Often, you’ll work with collections of data. Two fundamental ways Python organizes data are lists and dictionaries. A list is an ordered sequence of items, enclosed in square brackets []. For example, prompts = ["What is the capital of France?", "Summarize the theory of relativity."] creates a list containing two strings. You can access items by their position (starting from 0). A dictionary, enclosed in curly braces {}, stores key-value pairs. Think of it like a real dictionary: you look up a word (the key) to find its definition (the value). For instance, config = {"model": "gemini-pro", "max_tokens": 500} stores configuration settings. You access values using their keys, like config["model"].

Computers excel at repetition and decision-making. Python uses control flow statements for this. The if statement lets your program make decisions. You provide a condition, and if it’s true, a block of code runs: if user_age >= 18: print("Access granted"). You can add an else block for what to do if the condition is false. For repetition, the for loop is invaluable. It iterates over a sequence (like a list). For example, for p in prompts: print(p) would print each prompt stored in our prompts list, one by one.

As programs grow, repeating the same sequence of instructions becomes tedious and error-prone. Functions solve this by letting you package a block of code under a specific name. You define a function using def, give it a name, specify any inputs (parameters or arguments) it needs, and write the code it should execute. Later, you can call the function by its name whenever you need that task performed, potentially passing in different arguments each time. Functions can also return a result. For instance, you might define a function send_to_gemini(prompt_text) that takes a prompt, interacts with the API, and returns the AI’s response.

Python’s power is greatly extended by modules (sometimes called libraries or packages). These are collections of pre-written code, often providing specialized functionality. Your scripts interacting with Gemini will rely heavily on Google’s specific Gemini library. To use code from a module, you first need to bring it into your script using the import statement. For example, import google.generativeai as genai makes the functions and objects defined within the google.generativeai module available for use in your code, often giving it a shorter alias (genai in this case) for convenience.

So, how does this all fit together when interacting with something like the Gemini API? Typically, a script might start with import statements to bring in necessary libraries (like the Gemini library). It might then define variables to store things like your API key or configuration settings (perhaps using a dictionary). You might define one or more functions, for instance, one to format your prompt and another to handle the actual communication with the API, taking the prompt as input and returning the response. The main part of your script could then use a loop (maybe a for loop) to iterate through a list of prompts, calling your functions for each one, and perhaps using if statements to check the responses or handle potential errors.

When you look at the Python example scripts later in this book, don’t feel pressured to understand every single character immediately. Instead, focus on identifying these core building blocks: Where are variables being defined? What data (strings, lists, dictionaries) are they holding? Can you spot the loops (for) and decisions (if)? Which parts are reusable functions (def), and where are they being called? Which external libraries are being brought in (import)? Recognizing these patterns is the key to deciphering the script’s purpose and logic. Python’s readability is your ally here; often, the variable and function names themselves will give you strong clues about what the code is trying to achieve. Programming is fundamentally about breaking down problems into logical steps, and Python provides a clear syntax for expressing those steps.

Dear reader, this short chapter is not sufficient to introduce you to Python programming but it will enable you to understand the Python examples in the following chapters. Furthermore, the Gemini mobile apps or web interface can be used to guide you through the use of Python.