Boost Python Readability with the Powerful PrettyPrinter Library

PrettyPrinter is a powerful Python 3.6+ package for descriptive, syntax‑highlighted pretty‑printing, built on an improved Wadler‑Leijen layout algorithm and inspired by Haskell's prettyprinter, JavaScript's Prettier, Ruby's prettypreinter.rb, and IPython's pretty module.

Why does Python still need an extra pretty‑printing package? While IDEs and manual prints are the basic interface for developer‑data interaction, built‑in tools have limitations:

__repr__ and __str__ return plain strings; __repr__ aims for valid Python expressions but offers no formatting.

The standard pprint module formats built‑in containers but uses a greedy layout algorithm that often produces sub‑optimal output and cannot handle custom types beyond __repr__.

The third‑party pprintpp improves on pprint but still inherits its __repr__‑based constraints.

IPython’s IPython.lib.pretty provides a more advanced alternative with better algorithms and custom‑type support, yet it pushes data directly to a layout buffer and can have side effects.

To overcome these shortcomings, the author implemented three key improvements:

An algorithm that maximizes pretty‑printing quality, even at a modest performance cost—spending a tenth of a second to format output saves seconds when searching results.

A super‑simple, descriptive API that lets users register custom pretty‑printing functions without rewriting __repr__.

Robust syntax highlighting that gracefully handles invalid Python syntax without breaking.

The new package delivers impressive performance and an easy way to define custom pretty‑printing rules using two descriptive functions: register_pretty and pretty_call. Syntax highlighting looks polished and never aborts on malformed code, dramatically improving developer experience.

Simple, Descriptive API

PrettyPrinter defines output formatting through function calls. All non‑string Python values are represented by function results. The core function pretty_call describes the type of call to render. An example invocation is shown below:

The layout processing resembles the following diagram:

Using pretty_call, one can then define custom types. For example, registering a pretty printer for a MyClass:

Applying the register_pretty decorator creates a formatted output for MyClass instances:

The resulting output looks like:

Stateful Instance Representation

Function‑call based formatting struggles with stateful objects. PrettyPrinter solves this by inserting explanatory comments into the layout, which appear in the output. For a Connection class with "connected" and "disconnected" states, the following definitions produce annotated output:

In conclusion, the author highly recommends integrating PrettyPrinter into development workflows, especially within IPython, where all interactive results automatically benefit from the enhanced formatting. The package also includes ready‑made definitions for Django models, QuerySets, and attrs‑based classes, making it a valuable tool for Python developers.