Oliver Bestwalter

Automagic Configuration in Python

Stop writing configuration files. Learn a Python-native approach that makes configuration safe, testable, and nearly invisible for your team.

Automagic Configuration in Python
#1about 6 minutes

An introduction from an in-house developer's perspective

The speaker shares his background working in small, autonomous teams and how that experience shaped his approach to software configuration.

#2about 7 minutes

Adopting a philosophy of configuration without configuration files

The talk focuses on solving configuration for internal systems by leveraging Python's internals rather than focusing on performance or complex code.

#3about 5 minutes

Redefining the blurry line between configuration and constants

Configuration is defined not as a variable or a true constant, but as a value derived from the environment that remains fixed after startup.

#4about 4 minutes

Practical examples of using Python for configuration

Classic configuration files are often unnecessary for internal Python projects, as demonstrated by tools like Sphinx, Plotly, and Nox.

#5about 6 minutes

How Python's module execution and import model works

Code at the module level executes during import, and the execution path differs when running a file as a script versus importing it as a module.

#6about 10 minutes

Exploring the mutability of Python constants and attributes

Most "constants" in Python, including system attributes, can be modified at runtime, highlighting the need for patterns that enforce immutability.

#7about 6 minutes

Implementing a testable singleton with read-only properties

A singleton class using the @property decorator provides a sweet spot for creating dynamic, read-only configuration values that are easily testable.

#8about 6 minutes

Q&A on versioning, runtime changes, and common mistakes

The speaker answers audience questions about version handling in a monorepo, why configuration shouldn't change at runtime, and potential pitfalls of these patterns.

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