Project Documentation¶
architecture gives a complete view of PyPy’s basic design.
coding guide helps you to write code for PyPy (especially also describes coding in RPython a bit).
sprint reports lists reports written at most of our sprints, from 2003 to the present.
papers, talks and related projects lists presentations and related projects as well as our published papers.
PyPy video documentation is a page linking to the videos (e.g. of talks and introductions) that are available.
Technical reports is a page that contains links to the reports that we submitted to the European Union.
development methodology describes our sprint-driven approach.
LICENSE contains licensing details (basically a straight MIT-license).
Glossary of PyPy words to help you align your inner self with the PyPy universe.
Source Code Documentation¶
object spaces discusses the object space interface and several implementations.
bytecode interpreter explains the basic mechanisms of the bytecode interpreter and virtual machine.
interpreter optimizations describes our various strategies for improving the performance of our interpreter, including alternative object implementations (for strings, dictionaries and lists) in the standard object space.
translation is a detailed overview of our translation process. The rtyper_ is the largest component of our translation process.
dynamic-language translation is a paper that describes the translation process, especially the flow object space and the annotator in detail. (This document is one of the EU reports.)
low-level encapsulation describes how our approach hides away a lot of low level details. This document is also part of the EU reports.
translation aspects describes how we weave different properties into our interpreter during the translation process. This document is also part of the EU reports.
garbage collector strategies that can be used by the virtual machines produced by the translation process.
parser contains (outdated, unfinished) documentation about the parser.
rlib describes some modules that can be used when implementing programs in RPython.
configuration documentation describes the various configuration options that allow you to customize PyPy.
`JIT Generation in PyPy`_ describes how we produce the Python Just-in-time Compiler from our Python interpreter.