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The Adventures of a Pythonista in Schemeland/19
by Michele Simionato
April 21, 2009
Summary
This is the first of six episodes concerning the R6RS module system. The module system is quite new and it is the result of several compromises. As a consequence, it has some rough edge and writing portable code - specially for macro writers - is not always trivial.

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The R6RS module system

For nearly 30 years Scheme lived without a standard module system. The consequences of this omission were the proliferation of dozens of incompatible module systems and neverending debates. The situation changed with the R6RS report: nowadays Scheme has an official module system, finally.

Unfortunately the official module system is not used by all Scheme implementations, and it is quite possible that some implementation will never support it. For instance Chicken, a major implementation, just released version 4, which includes a brand new module system not compatible with the R6RS system. You should be aware that the module system (and actually the whole of the R6RS standard) is controversial, and there are good reasons why it is so.

I cannot do anything about the political issues, but I can do something about the technical issues, by explaining the subtle points and by documenting the most common pitfalls. It will take me six full episodes to explain the module system and its trickiness, especially for macro writers who want to write portable code.

http://www.phyast.pitt.edu/~micheles/scheme/Jigsaw.png

Modules are not first class objects

Since the title of this series is The Adventures of a Pythonista in Schemeland let me begin my excursion about the R6RS module system by contrasting it with the Python module system.

The major difference between Python modules and Scheme modules is that Python modules are first class runtime objects which can be passed and returned from functions, as well as modified and introspected freely; Scheme modules, instead, are compile time entities which cannot be imported at runtime, nor passed to functions or returned from functions; moreover they cannot be modified and cannot be introspected.

Python modules are so flexible because they are basically dictionaries. It would not be difficult to implement a Python-like module system in Scheme, by making use of hash-tables, the equivalent of dictionaries. However, the standard module system does not follow this route, because Scheme modules may contain macros which are not first class objects, therefore modules cannot be first class objects themselves [some may argue that having macros which are not first class objects is the root of all evil, and look for alternative routes with macro-like constructs which are however first class objects; however, I do not want to open this particular can of worms here].

Since Scheme modules are not first class objects it is impossible to add names dynamically to a module, or to replace a binding with another, as in Python. It is also impossible to get the list of names exported by a module: the only way is to look at the export list in the source code. It is also impossible to export all the names from a module automatically: one has to list them all explicitly.

In general Scheme is not too strong at introspection, and that it is really disturbing to me since it is an issue that could be easily solved. For instance, my sweet-macros library provides introspection features, so that you can ask at runtime, for instance from the REPL, what are the patterns and the literals accepted by a macro, its source code and its associated transformer, even if the macro is a purely compile time entity. It would be perfectly possible to give an introspection API to every imported module. For instance, every module could automagically define a variable - defined both at runtime and compile time - containing the full list of exported names and there could be some builtin syntax to query the list.

But introspection has been completely neglected by the current standard. One wonders how Schemers cope with large libraries/frameworks like the ones we use every day in the enterprise world, which export thounsands and thousands of names in hundreds and hundreds of modules. Let's hope for something better in the future.

I also want to point out a thing that should be obvious: if you have a Scheme library lib.sls which defines a variable x, and you import it with a prefix lib., you can access the variable with the Python-like syntax lib.x. However, lib.x in Scheme means something completely different from lib.x in Python: lib.x in Scheme is just a name with a prefix, whereas lib.x in Python means "take the attribute x of the object lib" and that involves a function call. In other words, Python must perform an hash table lookup everytime you use the syntax lib.x, whereas Scheme does not need to do so.

I should also points out that usually (and unfortunately) in the Scheme world people do not use prefixes; by default all exported names are imported, just as it is the case for Python when the (discouraged) style from lib import * is used.

Compiling Scheme modules vs compiling Python modules

Let me continue my comparison between Python modules and Scheme modules, by comparing the compilation/execution mechanism in the two languages. I will begin from Python, by giving a simplified description which is however not far from the truth.

When you run a script script.py depending on some library lib.py, the Python interpreter searches fo a bytecode-compiled file lib.pyc, updated with respect to the the source file lib.py; if it finds it, it imports it, otherwise it compiles the source file on-the-fly, generates a lib.pyc file and imports it. A bytecompiled file is updated with respect to the source file if it has been generated after the source file; if you modify the source file, the lib.pyc file becomes outdated: the Python interpreter is smart enough to recognize the issue and to seamlessly recompile lib.pyc.

In Scheme the compilation process is very much implementation-dependent. Here I will give some example of how things work in three representative R6RS-conforming implementations, Ikarus, Ypsilon and PLT Scheme/mzscheme.

Ikarus has two modes of operation; by default it just compiles everything from scratch, without using any intermediate file. This is possible since the Ikarus compiler is very fast. However, this mechanism does not scale; if you have very large libraries, it does not make sense to recompile everything every time you add a little script. Therefore Ikarus (in the latest development version) added a mechanism similar to the Python one; if you have a file script.ss which depends on a library lib.sls and run the command

$ ikarus --compile-dependencies script.ss
Serializing "./lib.sls.ikarus-fasl" ...

the compiler will automatically (re)generate a precompiled file lib.sls.ikarus-fasl from the source file lib.sls as needed, by looking at the time stamps. Exactly the same as in Python. The only difference is that Python compiles to bytecode, whereas Ikarus compile to native code.

Notice that whereas in theory Ikarus should always be much faster of Python, in practice this is not guaranteed: a lot of Python programs are actually calling underlying C libraries, so that Python can be pretty fast in some cases (for instance in numeric computations using numpy).

All I said for Ikarus, can be said from Ypsilon, with minor differences. Ypsilon compiles to bytecode, like Python. Precompiled files are automatically generated without the need to specify any flag, as in Python; however they are stored in a so called auto-compile-cache directory, which by default is situated in $HOME/.ypsilon. The location can be changed by setting the environment variable YPSILON_ACC or by passing the --acc=dir argument to the Ypsilon interpreter. It is possible to disable the cache and to clear the cache; if you are curious about the details you should look at the Ypsilon manual (man ypsilon).

PLT Scheme/mzscheme works in a slightly different way. The command

$ plt-r6rs script.ss

interprets the script and its dependencies on the fly. The command

$ plt-r6rs --compile script.ss

compiles the script and its dependencies, and stores the compiled file in the collects directory, which on my system is in $HOME/.plt-scheme/4.1.2/collects. Each library has its own directory of compiled files.

Compiling is not the same than executing

There are other similarities between a Python (bytecode) compiler and a Scheme compiler. For instance, they are both very permissive, in the sense that they flag very few errors at compile time. Consider for instance the following Python module:

$ cat lib.py
x = 1/0

The module contains an obvious error, that in principle should be visible to the (bytecode) compiler. However, the compiler only checks that the module contains syntactically correct Python code, it does not evaluate it, and generates a lib.pyc file without complaining:

$ python -m py_compile lib.py # generates lib.pyc without errors

The error will be flagged at runtime, only when you import the module:

$ python -c"import lib"
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "lib.py", line 1, in <module>
    x = 1/0
ZeroDivisionError: integer division or modulo by zero

R6RS Scheme uses a similar model. Consider for instance the library

$ echo lib.sls
#!r6rs
(library (lib)
 (export x)
 (import (rnrs))
 (define x (/ 1 0)))

and the script

$ echo script.ss
(import (rnrs) (lib))

You can compile the script and the library without seeing any error:

$ plt-r6rs --compile script.ss
 [Compiling ./script.ss]
 [Compiling ./.plt-scheme/4.1.2/collects/lib/main.sls]

Running the script however raises an error:

$  plt-r6rs  script.ss
/: division by zero

Like in Python, the error is raised when the module is imported (the technical name in Scheme is instantiated).

However, there is a gray area of the R6RS module system here, and implementations are free to not import unused modules. To my knowledge, Ikarus is the only implementation making using of this freedom. If you run

$ ikarus --r6rs-script script.ss

no error is raised. Ikarus is just visiting the module, i.e. taking notes of the names exported by it and of the dependencies, but the module is not evaluated, because it is not used. However, if you use it, for instance if you try to access the x variable, you will get the division error at runtime:

$ echo script.ss
(import (rnrs) (prefix (lib) lib:))
(begin
  (display "running ...\n")
  (display lib:x))
$  ikarus --r6rs-script script.ss
Unhandled exception:
 Condition components:
   1. &assertion
   2. &who: /
   3. &message: "division by 0"
   4. &irritants: ()

Here I have used an import prefix lib:, just to be more explicit. Another difference between Ikarus and PLT is that in PLT both the script and the library are compiled, whereas in Ikarus only the library is compiled. In the next episodes we will see many other examples of differences between R6RS-conforming implementations.


Acknowledgments

All the Adventures have my name at the top and I take full responsibility for the opinions and the mistakes. But for the parts which are correct, I deserve little credit, since most of the time I am just reporting advice which I have received from the Scheme community, mostly from comp.lang.scheme and ikarus-users, as well from private emails. This is true for all of my Adventures, but especially for the six episodes about the module system you are about to read. I was very ignorant about the module system when I started this project, and this work would not have been possible without the help of Abdulaziz Ghuloum, Derick Eddington, Will Clinger, Eli Barzilay, Matthew Flatt, André van Tolder and many others. Thank you guys, you rock!

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About the Blogger

Michele Simionato started his career as a Theoretical Physicist, working in Italy, France and the U.S. He turned to programming in 2003; since then he has been working professionally as a Python developer and now he lives in Milan, Italy. Michele is well known in the Python community for his posts in the newsgroup(s), his articles and his Open Source libraries and recipes. His interests include object oriented programming, functional programming, and in general programming metodologies that enable us to manage the complexity of modern software developement.

This weblog entry is Copyright © 2009 Michele Simionato. All rights reserved.

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