What is Python?

Python is a high-level, interpreted programming language known for its clear syntax and readability. Think of it as a language that's closer to human language (like English) than it is to machine code (binary 1s and 0s). This makes it relatively easy to learn and use for a wide range of applications, from web development and data science to automation and artificial intelligence.

The Python Interpreter

When you write a Python script (a file ending in .py), your computer can't understand it directly. It needs a translator. This translator is the Python interpreter. You feed your code to the interpreter, and it executes it line by line.

There are several interpreters available, but the most common one is CPython, the official version written in the C programming language. Others include:

  • Jython: Compiles Python code to Java bytecode to run on the Java Virtual Machine (JVM).
  • IronPython: For running Python on the .NET framework.
  • PyPy: A fast alternative interpreter with a Just-In-Time (JIT) compiler.

For most beginners, CPython is all you'll need. You can download and install it from the official python.org website.

The REPL: Your Python Playground

REPL stands for Read-Eval-Print Loop. It's an interactive shell that allows you to type Python code one line at a time and see the result instantly. It's fantastic for testing small snippets of code without having to create a full .py file.

To access the REPL:

  1. Open your terminal or command prompt.
  2. Type python (or python3 on some systems) and press Enter.
  3. You'll see a prompt, usually >>>.

Python


# In your terminal
>>> print("Hello, Python world!")
Hello, Python world!
>>> 2 + 2
4
>>> exit() # To leave the REPL

The loop is:

  1. Read: It reads the line you typed (2 + 2).
  2. Eval: It evaluates (computes) the result (4).
  3. Print: It prints the result to the screen.
  4. Loop: It waits for your next command.

Jupyter Notebooks: The Next Level

While the REPL is great, it's not ideal for larger experiments. Jupyter Notebooks provide a web-based interactive environment where you can combine live code, explanatory text, equations, and visualizations in a single document. They are incredibly popular in data science and scientific computing. Each block of code, called a "cell," can be run independently.

To get started with Jupyter, you typically install it with Python's package manager: pip install notebook. Then run jupyter notebook in your terminal.