Python 3: Fundamentals

Aimed at beginner Python developers, this course will provide you a fundamental understanding of how to program in Python. Your journey will take you from a total Python beginner to an intermediate level Python developer more than ready to tackle your own professional projects. Although not technically required, limited prior experience in any coding language, and a basic understanding of concepts such as looping, branching, etc will prove useful. This course will provide you the solid foundation you will need to continue moving forward in your Python development endeavors. This course is not a "here's how I do it, just type along please" type of course - its goal is to make you understand each and every line of code we are going to write together, why we write it and why it works, giving you the knowledge to apply the same coding techniques to your own situation and problems. Like any good college level course, this course is fairly lengthy and will require time, not only for watching the videos, but also working on your own to explore the various topics, trying things out, and at the end of each section working on increasingly complex problems. It takes a certain amount of time to master a programming language, and this course is no exception. If you are looking for a quick and superficial intro to Python, then this course is probably not for you. VERY IMPORTANT: Before attempting this course you must have a basic knowledge of how to use the DOS prompt (Windows) or shell (Linux/Mac). This means how to open a prompt/shell on your computer, navigating the file structure using cd, creating and deleting directories, copying files/directories from one location to another, listing files in the current directory, etc. There are plenty of 20-30 minute tutorials available online that will teach you those simple basics.

9 flashcards · Programming Languages · by mervanpolat

  1. Introduction to Types What are types in programming?

    Types are classifications for entities in programming, analogous to real-world categories like people, places, or things. They define the nature of data, such as numbers, text, or Boolean values, and determine how data can be manipulated.

  2. Integers in Python What is an integer in Python, and how is it used?

    An integer in Python, denoted as int, represents whole numbers, both positive and negative, including zero. They can be of any size, limited only by memory, and can be used directly in code as literals or as results of expressions

  3. Floating-Point Numbers Define floating-point numbers in Python.

    Floating-point numbers, or float in Python, represent real numbers with a decimal point, such as 3.14 or -2.75. They include a decimal even if it's zero (e.g., 5.0) and are used for calculations requiring fractional values.

  4. Imprecision of Floats Why are floating-point numbers imprecise in Python?

    Floating-point numbers can be imprecise due to the binary representation used by computers. Not all decimal numbers can be represented exactly in binary, leading to small inaccuracies in calculations and comparisons.

  5. Decimal Type What is the Decimal type in Python, and when should it be used?

    The Decimal type in Python provides exact representations of decimal numbers, avoiding the imprecision of floats. It's less efficient but should be used when precise decimal representation is crucial, such as in financial calculations.

  6. Literal Integers and Floats How are literal integers and floats defined in Python?

    Literal integers are directly typed into the code (e.g., 5, -3), whereas floats are defined by including a decimal point (e.g., 5.0). The presence of a decimal, even with a zero, categorizes a number as a float.

  7. Booleans in Python What are Boolean values in Python, and how are they represented?

    Boolean values represent truth values and are denoted in Python by True and False, with capitalization. They are used in conditional statements and logical operations.

  8. Formatting Floats for Precision How can you format floats in Python to reveal their true stored value?

    Use the format function with a float to display its precise stored value, e.g., format(0.1, '.25f'). This reveals the exact representation of the float in memory, which can differ slightly from its perceived value.

  9. Comparing Floats with Tolerance How should floats be compared in Python to account for their imprecision?

    Instead of direct equality checks, compare floats by their absolute difference and a small tolerance value, e.g., abs(float1 - float2) < tolerance, to account for potential imprecision.