PyPy

Compiling Dynamic Language Implementations

The Python Situation

The Python Situation

• lots of implementationso CPython - Posixo Jython - JVM o IronPython - .NET

• specialized projectso Stackless Pythono unladen-swallowo Psyco

What PyPy is

1.Python Implementation2.Translation Framework

What PyPy is

1. Python implemented in Python 

What PyPy is

1. Python implemented in Python 

• looks like this:

$> python py.py

What PyPy is

1. Python implemented in Python 

• looks like this:

• runs on top of CPython

$> python py.py

What PyPy is

1. Python implemented in Python 

• looks like this:

• runs on top of CPython• about 2000 times slower than CPython 

$> python py.py

What PyPy is

2.  Translation Framework 

$> python py.py

$> ./pypy-c $> ./pypy-jvm$> ./pypy-cli

some PyPy facts

• founded in 2003 by Holger Krekel and Armin Rigo• 2004 - 2007 EU Project - Sixth Framework• since 2007 Open Source Project• occasional Funding by Google• Sprint-Driven Development

PyPy Components

1.Architecture2.RPython3.Interpreter 4.Translation Framework

PyPy componentsArchitektur

PyPy componentsRPython• RPython = Restricted/Reduced Python 

PyPy componentsRPython• RPython = Restricted/Reduced Python 

o Restricted = most possible static subset of Python  

PyPy componentsRPython• RPython = Restricted/Reduced Python 

o Restricted = most possible static subset of Python  o required to perform Type Inference 

PyPy componentsRPython• RPython = Restricted/Reduced Python 

o Restricted = most possible static subset of Python  o required to perform Type Inference o input to the Translation Framework

PyPy componentsRPython• RPython = Restricted/Reduced Python 

o Restricted = most possible static subset of Python  o required to perform Type Inference o input to the Translation Frameworko no real specification - just some hints

PyPy componentsRPython• RPython = Restricted/Reduced Python 

o Restricted = most possible static subset of Python  o required to perform Type Inference o input to the Translation Frameworko no real specification - just some hintso used for writing interpreters

PyPy componentsRPython• RPython = Restricted/Reduced Python 

o Restricted = most possible static subset of Python  o required to perform Type Inference o input to the Translation Frameworko no real specification - just some hintso used for writing interpreterso can be used for writing extensions as well

PyPy componentsInterpreter

PyPy componentsInterpreter• written in RPython

PyPy componentsInterpreter• written in RPython• Internals:

o bytecode compiler -> generates bytecode

PyPy componentsInterpreter• written in RPython• Internals:

o bytecode compiler -> generates bytecodeo bytecode evaluator -> interprets bytecode 

PyPy componentsInterpreter• written in RPython• Internals:

o bytecode compiler -> generates bytecodeo bytecode evaluator -> interprets bytecode o object space -> handles operations on objects

Python Interpreter

PyPy componentsTranslation Framework

PyPy componentsTranslation Framework

PyPy componentsTranslation Framework

PyPy componentsTranslation Framework

PyPy > CPython

1.High Level Language Implementation

2.JIT Generation3.Object Spaces4.Stackless

PyPy > CPythonHigh Level Language Implementation• easy to experiment with 

PyPy > CPythonHigh Level Language Implementation• easy to experiment with • easy to implement new features

PyPy > CPythonHigh Level Language Implementation• easy to experiment with • easy to implement new features

o lazily computed objects and functions

PyPy > CPythonHigh Level Language Implementation• easy to experiment with • easy to implement new features

o lazily computed objects and functionso plug-able  garbage-collection 

PyPy > CPythonHigh Level Language Implementation• easy to experiment with • easy to implement new features

o lazily computed objects and functionso plug-able  garbage-collection o runtime replacement of live-objects 

PyPy > CPythonHigh Level Language Implementation• easy to experiment with • easy to implement new features

o lazily computed objects and functionso plug-able  garbage-collection o runtime replacement of live-objectso stackless concurrency 

PyPy > CPythonJIT Generation• based on Partial Evaluation via

Yoshihiko Futamura (1971). "Partial Evaluation of Computation Process – An Approach to a Compiler-Compiler" 

PyPy > CPythonJIT Generation• based on Partial Evaluation via

Yoshihiko Futamura (1971). "Partial Evaluation of Computation Process – An Approach to a Compiler-Compiler"

• says: it's possible to take an interpreter and transform it into a compiler

PyPy > CPythonJIT Generation• based on Partial Evaluation via

Yoshihiko Futamura (1971). "Partial Evaluation of Computation Process – An Approach to a Compiler-Compiler"

• says: it's possible to take an interpreter and transform it into a compiler

• means:having such a thing is pretty cool because writing interpreters is a lot easier than writing compilers. 

PyPy > CPythonJIT Generation

PyPy > CPythonObject Spaces• Flow ObjSpace• Thunk ObjSpace• Taint ObjSpace• Dump ObjSpace• Transparent Proxies

Thunk Object Space

• provides:1.lazily computed objects • lazily computed functions• globally replaceable objects

Thunk Object Space

• provides:1.lazily computed objects • lazily computed functions• globally replaceable objects

• is implemented in about 200 lines of code

Thunk Object Space

• provides:1.lazily computed objects • lazily computed functions• globally replaceable objects

• is implemented in about 200 lines of code

• Example:

>>>> a = "hello">>>> b = "world">>>> a + b'helloworld'

>>>> become(a,b)>>>> a + b'worldworld'

Taint Object Space

• provides protection for:o sensitive data that should not leak

Taint Object Space

• provides protection for:o sensitive data that should not leak

• provides protection from:o untrusted data that needs to be validated

Taint Object Space

• provides protection for:o sensitive data that should not leak

• provides protection from:o untrusted data that needs to be validated

• Example:>>>> password = "secret">>>> password'secret'

>>>> password = taint("secret")>>>> passwordTraceback (application-level):  File "<inline>", line 1 in <interactive>    passwordTaintError

PyPy > CPythonStackless• infinite Recursion

o CPython limited to depth=1000o regular PyPy limited to depth=5000

PyPy > CPythonStackless• infinite Recursion

o CPython limited to depth=1000o regular PyPy limited to depth=5000

• Microthreadso Coroutineso Tasklets and Channelso Greenlets

PyPy > CPythonStackless• infinite Recursion

o CPython limited to depth=1000o regular PyPy limited to depth=5000

• Microthreadso Coroutineso Tasklets and Channelso Greenlets

• Coroutine Pickling• Coroutine Cloning 

Demo

Lazy functions and objectsTainted objectsTranslator Shell