Pyramid architecture

What is Pyramid?

Pyramid is a Python web framework from the Pylons Project. It aims to be usable for a single-file application and still hold together once that application becomes large, which is why so much of it is built around explicit configuration rather than convention.

That philosophy shows up as architecture. How does the configurator assemble an application at startup, and what does it register? How are URLs matched — by route or by traversal — and where does the framework decide between them? Where do authentication and session handling attach to a request? Reading the source, those answers are spread across the configuration system and the request pipeline.

The map on this page is JigsawML's read of the Pyramid repository. It groups the source into the nine areas below, draws the dependencies between them, and lets you open any one to see the code behind it.

Key components in the Pyramid architecture

JigsawML identified and labelled these components automatically by analysing the Pyramid repository. Open the interactive map to expand any of them and read the underlying code.

• Framework

  The request pipeline and router that every Pyramid application runs on.

• Configuration System

  The configurator and registry that assemble an application before it serves traffic.

• Security Sessions

  Authentication, authorization policies, and the session machinery around a request.

• Rendering Static

  Template renderers and static-asset handling that produce a response body.

• CLI Scripts

  Command-line entry points for serving, shell access, and route inspection.

• Test Suite

  The tests covering the framework's own behaviour.

• Documentation

  Narrative documentation and API reference maintained inside the repository.

• Build Project

  Packaging and the scaffolding used to start a new Pyramid project.

• External Services

  Dependencies and outside systems referenced from the framework's edges.

How this map was generated

JigsawML ingested the public repository, resolved its dependencies, and grouped the code into architectural components using AI agents and a knowledge graph. Nothing here was drawn by hand. The same process runs against private repositories and cloud accounts, and re-runs on every commit so the map never goes stale.

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