Python Q & A


What is REPL and how to use it in Python?

A REPL stands for Read-Eval-Print Loop. It’s an interactive environment that takes user inputs (Read), evaluates (Eval) them, displays the result to the user (Print), and then loops back to wait for another input. The Python REPL is a tool that allows developers to execute Python code interactively, which makes it an excellent utility for quick prototyping, learning, and debugging.

The default Python REPL can be accessed simply by running the `python` or `python3` command in your terminal or command prompt, without any script arguments. Once inside, you’re presented with the `>>>` prompt, indicating that it’s ready to accept Python code. You can start typing Python statements and expressions, and they will be executed immediately, with the results printed right below.

For example:


>>> 2 + 3


>>> print("Hello, World!")

Hello, World!



A few points to remember while using the Python REPL:

  1. Multiline Constructs: For multiline constructs like defining functions or loops, pressing `Enter` will change the prompt to `…`, indicating that the REPL expects more input for the current construct. To run the construct, simply press `Enter` on a new line.


  1. Built-in Help: You can access built-in documentation by typing `help()`. If you need information about a specific function or module, pass its name as an argument, e.g., `help(print)`.


  1. Exiting: To exit the REPL, you can use the `exit()` command or press `Ctrl+D` (or `Ctrl+Z` on Windows, followed by `Enter`).


  1. Enhanced REPLs: While the default REPL is great for simple tasks, there are enhanced versions available, such as `IPython`, that offer advanced features like auto-completion, syntax highlighting, and magic commands.


The Python REPL is a powerful interactive tool that offers an immediate feedback loop for Python code, making it indispensable for testing, learning, and debugging. Whether you’re a beginner trying out new concepts or an expert debugging a complex problem, the REPL is a valuable asset in the Python developer’s toolkit.

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Senior Software Engineer with 7+ yrs Python experience. Improved Kafka-S3 ingestion, GCP Pub/Sub metrics. Proficient in Flask, FastAPI, AWS, GCP, Kafka, Git