Overview of python-sibilant
Sibilant is not done. It's still being organically grown in bars and coffee shops whenever I get a chance to sit alone. I will eventually get to the point where it seems like a 1.0.0 is sane. Until then, this is version 0.9.0 and every commit or pull-request could introduce dramatic changes.
Mostly "why not," and "I do what I want," with some "for myself," mixed in.
But also because I really love the idea of domain-specific languages. Every single time I wrote a block of configuration for optparse or argparse I yearned for defmacro. Whenever I created structured unpacking of data, I wanted to just define the shapes and let those be transformed into a parser and object model.
This was a project begun in 2007 and subsequently left abaondoned in early 2008.
I believe the concept grew out of my hacking with the absurdity that is Spexy. But while Spexy was mostly a joke and a puzzle, Sibilant had a goal to create a working and sane-ish LISP compiler.
I wasn't ready for such an undertaking, and a great deal of Real Life took up my time instead. The modest first passes as Sibilant sat mostly forgotten in a CVS repo.
Some time in January of 2014 I ran across my checkout. The upstream
cvsroot had disappeared -- it was on a host that had probably been
migrated, and I'd not bothered to bring along these repos, or I did a
really good job hiding it from myself. I imported what I had left to
GitHub for posterity, unsure of the fate of the project.
For the next few years I would idly poke at bits here and there. I toyed with different ideas for some of the basic data types, but never got anywhere serious.
Then suddenly in July of 2017 I went nuts and threw together the compiler in a week while drinking at a barcade.
It has been a fantastic learning experience, and excellent mental exercise. While the Sibilant user base might always number in just the single digits, I can never consider the project a failure. The sheer joy from when a particular feature comes to life for the first time, or the satisfaction of seeing the language develop are enough to merit declaring it a success. I am excited to continue hacking at it, what more is there?
Python Version Support
CPython 3.5, 3.6, and 3.7 are currently supported. CPython 3.8 has made some bytecode changes (removals) that impact sibilant's ability to target it.
Sibilant targets Python bytecode directly. I rely heavily on the
auto-generated documentation for the
dis module, and on its output
for seeing just what the default compiler would do for some cases.
Sibilant is slowly growing as more special forms and macros are added. Below are a few of the key features
Python 3 provides an extensible import system via
sibilant module is loaded, this system will be extended
to support treating sibilant source files (files found in
and ending in
.sibilant) as packages or modules.
In other words, to enable loading of sibilant code at runtime, you
just need to have
import sibilant at the beginning of your
From within a sibilant module the
import function allows fetching a
module from the importer.
def import and
def import-from will bind
modules or their contents.
Compile to File
Sibilant has the ability to compile a
.lspy file into a
can then be loaded by the default importer. Modules loaded in this
manner skip the parse and compile stages, but still execute in-order
during load. These modules have a hard dependency on sibilant -- they
are not stand-alone. All of the sibilant types are pulled in
A big advantage of sibilant over an interpreted lisp using a lambda emitter in Python is that the bytecode sibilant emits can have a line-number-table associated with it. This means that exceptions or tracebacks will interleave between python source code and sibilant source code, and correctly show the line that the raise came from.
The Sibilant compiler implements simple tail-call optimization via a
trampoline. The trampoline will bounce tail-calls out of the calling
frame where they will be evaluated, consuming no additional stack
space. This form of TCO does have the somewhat frustrating side-effect
of collapsing the call stack, which can make tracebacks difficult to
debug. Sibilant will only perform TCO on calls to functions written
with TCO enabled -- ie. Python function calls won't get bounced unless
they were explicitly created with the sibilant
Parse-time Macros: reader macros
Parse time macros defined via
set-macro-character can transform
the source stream before it becomes a source object
Compile-time Macros: defmacro
Compile time macros defined via
defmacro are the simple, low-level
variety, transforming the
cons list from the parsed source code and
emitting a new list representing the expanded form. An implementation
macroexpand-1 is included for macro debugging purposes.
Macros which expand from a
symbol rather than a
cons list can be
defalias. Alias macros take no arguments.
Compile-time optimized operators
The common Python operators and comparators are implemented such that they have both a compile-time and run-time representation. Where possible, operators will compile to direct bytecode operations, but can also be passed and called as runtime functions.
try special form can be used as an expression, evaluating to the
block that runs last.
the context manager interface
with special form can be used to enter a context manager and
bind the result locally, then clean up once execution of the inner
form ends. The expression evaluates to the last value of the body.
for-each forms can be used to repeatedly execute a
body of code. The
continue forms can be used from within
those blocks as well.
Sibilant can create generators from
forms, by using either the
Future Feature: Rewrite Sibilant in Sibilant
I'd like to get to the point where I can rewrite the compiler subpackage in sibilant itself. Then compile the new compiler in the old compiler, and finally re-compile the new compiler using itself.
The sibilant compiler will eventually become sibilantzero, to be relegated to a simple build dependency in producing sibilant proper.
Should You Use Sibilant?
Probably not. Instead you should almost certainly use a well-defined and maintained Lisp or Scheme from the beginning. Here's some really great ones:
- Chez Scheme - https://www.scheme.com/
- Guile - https://www.gnu.org/software/guile/
- Racket - https://racket-lang.org
- Clojure - https://clojure.org
However if you're really stuck to an existing Python environment, you just might enjoying giving Sibilant a shot. Let me know your cool use-case!
Sibilant needs to be installed as a wheel to function correctly:
pip3 install .
Author: Christopher O'Brien email@example.com
IRC Channel: #py-sibilant on Libera
Original Git Repository: https://github.com/obriencj/python-sibilant
This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License along with this library; if not, see http://www.gnu.org/licenses/.