Adventures in Machine Learning

Python REPL: Mastering the Standard and Customizing with Alternative Options

Getting to Know the Python Standard REPL

Python has become one of the most popular programming languages in the world today. Its rich set of features and ease of use makes it an attractive option for both new and experienced programmers.

Knowing how to use Python’s interactive shell, or REPL (Read-Eval-Print-Loop), is a crucial skill that every Python programmer should possess. In this article, we will explore the benefits of using a Python REPL and guide you through the various aspects of working with the Python standard REPL.

What is Python’s Interactive Shell or REPL? Python’s interactive shell, also known as REPL, is a command-line interface that allows you to test your Python code line-by-line.

The REPL is a way of interacting with Python in real-time, which means you can execute Python code and see the results immediately. The shell prompts you for input and executes the code you enter, returning the output to the screen.

Why Use a Python REPL? Using the Python REPL provides many benefits for Python programmers.

The primary benefit is the ability to work in interactive mode, which provides a quick and easy way to test code. When working with a REPL, you don’t need to write complete programs, save them to a file, and then run them to see the output.

Instead, you can execute individual lines of code within the shell and see the results immediately. This makes it much easier to experiment with code and try out different solutions.

Starting and Ending REPL Interactive Sessions

To start your Python REPL session, you need to open a command-line interface and type “python”. This will launch the Python interpreter.

Once you’re in the shell, you can start typing Python commands and seeing the results immediately. To end the REPL session, you can type “exit()” or “quit()” in the shell.

Running Code in a REPL Session

Evaluating Expressions and Simple Statements

The simplest way to use the REPL is to evaluate expressions and simple statements. In Python, expressions are pieces of code that produce a value.

You can type an expression into the shell and see the result immediately. For example, you can type “3+4” in the shell and see the result “7” on the screen.

Running Compound Statements

Compound statements in Python are statements that contain other statements. Examples of compound statements include if-else statements, loops, and functions.

Compound statements are executed over multiple lines, and the Python interpreter will continue to prompt the user for input until the entire block of code has been entered.

Dealing With Explicit and Implicit Line Continuations

When working with multiple lines of code in a REPL session, you may need to use explicit or implicit line continuations. When using explicit line continuations, you use the backslash () character at the end of the line to indicate that the statement continues onto the next line.

When using implicit line continuations, the statement continues onto the next line without using any special characters.

Printing vs Evaluating

When working with a Python REPL, you can choose to either print output to the screen or evaluate the output. By default, Python will automatically evaluate expressions and print the result to the screen.

However, you can use the print() function to explicitly print output to the screen.

Flagging and Understanding Errors

When working with Python code in a REPL session, it’s important to know how to flag and understand errors. Python errors can be divided into two broad categories: syntax errors and exceptions.

Syntax errors occur when the Python interpreter encounters code that does not follow the Python syntax rules. Exceptions are raised when the Python interpreter encounters an error during the execution of a Python program.

Using the _ Special Variable

The _ special variable in Python is a way to access the last value that was printed or calculated in the shell. You can use the _ variable to perform calculations on the last result or to retrieve the last value for use in a subsequent calculation.

Reloading Imported Modules

If you’re working with modules in a Python REPL, you may need to reload the module each time you make changes to it. You can do this by using the reload() function from the importlib module.

Editing Code in the Standard REPL

In addition to executing code, you can also edit code within the Python REPL. To do this, you can use the Ctrl+E command to launch the editor.

The editor provides features such as multicursor editing and syntax highlighting to make it easier to edit your code.

Code History

The code history feature in the Python REPL allows you to recall previously executed commands. To recall a previous command, you can use the up and down arrow keys to scroll through your command history.

Code Completion

Code completion is a feature in the Python REPL that allows you to automatically complete code as you type. This can save you time when writing code, as you don’t have to remember the exact spelling of a function or variable name.

Useful Keyboard Shortcuts

There are many useful keyboard shortcuts in the Python REPL that can help you work more efficiently. These include shortcuts for repeating the last command, clearing the screen, and navigating through your code history.

Using Python’s Built-in Help System

Python’s built-in help system is a valuable resource when working with Python code. The help() function provides a detailed explanation of how to use a specific Python function or module.

Introspecting Your Code Dynamically

Introspection is the ability to examine and modify code dynamically during runtime. In Python, you can use functions such as type(), dir(), and help() to introspect your code and retrieve information about objects, functions, and modules.

Customizing the Standard REPL

You can customize the Python standard REPL to meet your specific needs by providing a startup file, colorizing output with the Rich library, or using an alternative REPL such as



bpython, or



In conclusion, the Python standard REPL is a powerful tool that provides many benefits for Python programmers. By knowing how to use the REPL effectively, you can become a more efficient and productive Python developer.

Whether you’re evaluating expressions, running compound statements, editing code, or using Python’s built-in help system, the Python REPL is a valuable resource that can help you get the job done.

Customizing the Python Standard REPL – Making it Your Own

Python has a standard interactive shell or REPL that comes with the Python distribution. Its convenience and accessibility make it an indispensable tool for both novice and seasoned Python programmers.

In the previous sections, we explored the basics of using the Python standard REPL, as well as how to use it to our advantage. In this expansion, we will venture further into customizing Python’s REPL, making it more flexible to fit our individual needs.

In this section, we will cover providing a startup file, colorizing output with the Rich library, as well as using an alternative REPL such as



bpython, or


Providing a Startup File

When you launch Python’s interactive shell, it uses the default settings and modules that are compiled into the interpreter. However, you can customize it to your liking by providing a startup file, which contains instructions that Python reads and executes before the shell starts.

This way, you can automatically change some settings to match your preferences, such as importing frequently used modules, setting the prompt string, or defining utility functions. You can create a startup file and set the PYTHONSTARTUP environment variable to point to its path.

On Unix-like systems, you can add the following line to your .bashrc or .bash_profile file in your home directory:




Then create a file named in your home directory, and add any Python code you want to execute when the shell starts. For example, you can add the following lines to import the math and numpy modules and define the prompt string:


import math

import numpy as np

# set the prompt string

sys.ps1 = “>>>”


Now when you launch Python’s interactive shell, you’ll notice that it has imported the math and numpy modules and that the prompt string has been changed.

Colorizing Output with the Rich Library

The Rich library is a Python package that can add color and styling to the output of command-line interfaces, including Python’s standard REPL. With Rich, you can customize the output of the REPL by highlighting specific text, adding colors, and using styles.

This can make the output more readable and easier to understand. To install Rich, you can run the following command:


pip install rich


Then, you can create a Python script or startup file to customize your REPL’s output using Rich. Here’s an example:


from rich.console import Console

from rich.theme import Theme

# create a custom theme

custom_theme = Theme({

“keyword”: “bold yellow”,

“name”: “red”,

“literal”: “green”,

“string”: “purple”,


# create a Console instance with the custom theme

console = Console(theme=custom_theme)

# some Python code to execute

name = “Python”

age = 30

# output using the Console object

console.print(f”Hello, [name]! You are [age] years old.”)


This will produce output in the following format, with the text in square brackets highlighted according to the custom theme:


Hello, [Python]! You are [30] years old.


Uncovering Missing Features in the Standard REPL

The standard Python REPL is a useful tool, but it has some limitations. There are feature-rich REPLs that offer additional features and functionalities that standard Python doesn’t provide.

These may be particularly beneficial for those who are working on larger projects. Let’s take a look at some of the most popular alternative REPLs in the Python ecosystem.


IPython is one of the most popular and mature alternative REPLs for Python. It offers a rich set of features, including advanced tab-completion, object introspection, and integrating with other interactive tools.

For example,

IPython allows you to use system commands as if you were in a shell, multiple sessions at once, and it even lets you embed multimedia content.


bpython, like

IPython, is an alternative REPL that provides some additional features compared to the standard REPL. What sets

bpython apart is its modern interface and the powerful auto-completion that it offers.

bpython makes programming in Python an exciting and fluid experience.


ptpython is another full-featured REPL for Python that enables you to build richer user experiences. It provides features such as syntax highlighting, auto-completion, and a more modern and intuitive interface.


IDLE comes with the standard Python distribution and provides a basic, out-of-the-box Python REPL.

IDLE has a few additional features that Python’s REPL lacks, such as syntax highlighting, and it also includes an editor to write and test Python files.

It is often used as a learning tool for novice programmers.


Customization is key when it comes to using the Python standard REPL. By modifying settings, importing frequently used modules, and defining utility functions, you can make quick work of most Python-related tasks.

Furthermore, extensions like Rich can add color and style to your terminal and make the REPL output more elegant. When it comes to alternative REPLs, both beginners and professionals have a lot of options to choose from.


bpython provides a smoother experience with its superior auto-completion,

IPython’s superior debugging provides advanced introspection views and the capability for code snippets from previous sessions.

IDLE is the go-to for beginners, offering more features than the standard REPL without overwhelming the programmer with too many additional functions.

In conclusion, customizing Python’s interactive shell or REPL enhances the productivity of both novice and more experienced Python programmers. By providing a startup file, users can customize settings, import modules, and define utility functions.

Furthermore, the Rich package can add color and style to the output of the REPL, making it more readable for the user. Alternative REPLs like


IPython, and

IDLE provide additional features and an intuitive interface, depending on the programmer’s needs.

Overall, customizing Python’s REPL makes the programming experience more personalized and efficient, as well as provides a clearer insight into the code being written, resulting in a successful and rewarding outcome.