Python REPL: A Hands-On Guide to Interactive Coding

You can also start an interactive session after running a script using the -i flag command. For example, python -i calc_tax.py will execute calc_tax.py and then drop you into the REPL environment with the script's variables still loaded in memory.

To exit the REPL, you can use one of several commands:

• Type quit() or exit()  then press Enter.

• On Unix/Linux/macOS, press Ctrl+D.

• On Windows, press Ctrl+Z and then press Enter.

Running Code in the REPL Environment

You can run code in Python’s REPL sessions in different ways depending on its complexity. Let’s look at the following type of code you can run in REPL.

Simple statements and expressions

The REPL environment can evaluate simple expressions and statements instantly. For example, you can perform arithmetic operations, assign variables, and evaluate Boolean expressions. The result of an expression is automatically printed. 

>>> 5 + 4
9
>>> name = "Allan"
>>> name
'Allan'
>>> 10 > 5
True

If a statement, like a variable assignment, doesn't produce an output, the REPL interpreter doesn't print anything. If you make a mistake, the REPL provides immediate feedback by raising an error.

Compound statements

Python REPL environment also handles multi-line compound statements like if statements and for loops. It automatically switches to the secondary prompt (...) after you type a line ending in a colon (:) and press Enter, indicating it's waiting for the indented block of code.

Take note that you'll need to indent your code manually; the REPL environment does not auto-indent. To signal the end of the compound statement, press Enter on an empty line.

Explicit and implicit line continuations

You can also write multi-line statements in Python REPL session using line continuations. An explicit line continuation uses a backslash \ at the end of a line to indicate the statement continues on the next line. 

Implicit line continuations occur automatically when the code is enclosed in parentheses (), brackets [], or braces {}.

Printing vs evaluating

The REPL's auto-printing feature only works on expressions with a return value. For example, if you have a list and append an item using temp.append(45), it will not produce any output. To see the new list, you need to explicitly evaluate the list variable on the next line. For the functions that return None. You need to use print() to see their output.

Useful REPL Features

The Python REPL environment has several built-in features that make it more productive to use and learn. I will discuss some of these features I have found useful.

Special variable _

The underscore (_) is a special variable in the REPL session that stores the result of the last expression. This is useful when you want to reuse results without retyping them.

In the example below, _ stores the value 30, which results from the expression 6*5.

Introspection tools

Python provides several built-in functions for interactively exploring objects and your environment. The table below summarizes the use of each function with examples.

Code history and tab completion

The REPL speeds up coding with the following history and auto-completion features:

• Code history: You can navigate through previously entered commands using the Up Arrow and Down Arrow keys. This allows you to quickly re-run, modify, or correct past lines.
• Tab completion: This helps complete variable names, module names, and object attributes. For example, typing impor then pressing Tab will autocomplete to import, or typing str.. followed by Tab will list string methods.

Keyboard shortcuts

The following are some common keyboard shortcuts that make navigating the REPL more efficient.

Customizing the REPL

The standard Python REPL can be customized to fit your workflow and preferences.

Startup file

Set the PYTHONSTARTUP environment variable to the path of a Python script that runs automatically whenever the REPL starts. This script can pre-import commonly used modules, define functions, or change prompt strings.

For example, create a file ~/.pystartup with the following content:

import sys, os, math, random
print("Custom REPL ready. Pre-imported: sys, os, math, random")

# Change the prompt strings
import sys
sys.ps1 = ">>> "
sys.ps2 = "... "

If you are using Windows, you can set up the environment using the following command:

setx PYTHONSTARTUP "C:\path\to\pystartup.py"

Rich output with rich

You can use the rich library to enhance and color the output in the REPL. You need to first install the rich module via pip.

pip install rich

Then enable rich using import and use in your Python REPL sessions. In the example below, I have used the library to print words in different font colors.

Example REPL Commands to Try

As you can see, Python’s REPL session is easy to use. Try out the following commands to practice your skills

Limitations of the Standard REPL Environment

While the standard Python’s REPL environment is great for quick tasks, it often feels limited compared to a modern IDE. You'll quickly notice a few missing features, including the following:

• No syntax highlighting: All your code appears in plain text. This makes it difficult to quickly distinguish keywords, strings, and comments visually, forcing you to read carefully.
• Minimal auto-indentation: While it handles the continuation prompt (...), you have to manually enter the correct indentation for compound statements, like if and for blocks.
• Basic code completion: The built-in tab completion is functional but doesn't offer the context-aware suggestions, inline documentation, or fuzzy matching found in advanced shells.
• Poor multi-line editing: Editing complex, multi-line blocks of code is cumbersome.
• Once a block is submitted, it cannot be easily edited or recalled from history.

Alternative REPLs

To overcome the above limitations of the standard interpreter, several enhanced REPLs and environments built on Python’s interactive model offer additional features that improve productivity and learning. I recommend trying out any of the following to find one that suits your needs.

• IDLE: A simple GUI-based Python environment bundled with Python itself. It offers syntax highlighting, an integrated editor, and a debugger, making it user-friendly for beginners.
• IPython: A powerful REPL with rich tab completion, syntax highlighting, magic commands (special commands starting with %), extensive history, and easy access to shell commands. Widely used in data science and scientific computing.
• bpython: This is a terminal-based REPL with inline syntax highlighting, auto-suggestions, and quick access to documentation. It’s lightweight but adds significant usability over the default REPL.
• ptpython: Designed for experienced users, this is an advanced REPL offering features like true multi-line editing, robust syntax highlighting, and even mouse support, giving you enhanced control in the terminal.
• Online REPLs: Browser-based environments like Python.org’s interactive shell and Python Morsels REPL are perfect for quick testing, sharing code, or practicing on the go.

Conclusion

The Python REPL session provides a fast, interactive environment for experimenting with code, making it invaluable for testing, learning, and exploring ideas. Mastering its built-in features gives you a powerful tool for everyday programming tasks. For more complex workflows or enhanced usability, experimenting with advanced REPL alternatives can further improve the interactive coding experience.

For a thorough understanding of Python, you can learn more from our Python Data Fundamentals and Python Programming Fundamentals skill tracks. The Python Cheat Sheet for Beginners also comes in handy when you want to have a glance at how to split a list in Python.