Chapter 37. Managed Attributes

This chapter expands on the attribute interception techniques introduced earlier, introduces another, and employs them in a handful of larger examples. Like everything in this part of the book, this chapter is classified as an advanced topic and optional reading, because most applications programmers don’t need to care about the material discussed here—they can fetch and set attributes on objects without concern for attribute implementations. Especially for tools builders, though, managing attribute access can be an important part of flexible APIs.

Why Manage Attributes?

Object attributes are central to most Python programs—they are where we often store information about the entities our scripts process. Normally, attributes are simply names for objects; a person’s name attribute, for example, might be a simple string, fetched and set with basic attribute syntax:                 # Fetch attribute value = value         # Change attribute value

In most cases, the attribute lives in the object itself, or is inherited from a class from which it derives. That basic model suffices for most programs you will write in your Python career.

Sometimes, though, more flexibility is required. Suppose you’ve written a program to use a name attribute directly, but then your requirements change—for example, you decide that names should be validated with logic when set or mutated in some way when fetched. It’s straightforward to code methods to manage access to the attribute’s ...

Get Learning Python, 4th Edition now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.