Thun Dialects of Joy in Python. v0.4.2 -------------------------------------------------- Copyright © 2014-2020 Simon Forman This file is part of Thun Thun is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. Thun 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 General Public License for more details. You should have received a copy of the GNU General Public License along with Thun. If not see . -------------------------------------------------- §.1 Introduction Joy is a programming language created by Manfred von Thun that is easy to use and understand and has many other nice properties. This project implements Python and Prolog interpreters for dialects that attempts to stay very close to the spirit of Joy but does not precisely match the behaviour of the original version written in C. The best source (no pun intended) for learning about Joy is the information made available at the website of La Trobe University (see the references section below for the URL) which contains source code for the original C interpreter, Joy language source code for various functions, and a great deal of fascinating material mostly written by Von Thun on Joy and its deeper facets as well as how to program in it and several interesting aspects. It's quite a treasure trove. §.2 Installation From PyPI in the usual way, e.g.: pip install Thun Or if you have downloaded the source, from the top directory: python ./setup.py install Or you can run the package directly from the top directory. To start a crude REPL: python -m joy There is a "quiet" mode for e.g. using joy from a shell script: python -m joy -q This supresses the initial banner output and the prompt text. §.3 Documentation §.3.1 Jupyter Notebooks The docs/ folder contains Jupyter notebooks, ... TODO §.3.2 Sphinx Docs Some of the documentation is in the form of ReST files §.3.3 Building the Docs Building the documentation is a little tricky at the moment. It involves a makefile that uses nbconvert to generate ReST files from some of the notebooks, copies those to the sphinx source dir, then builds the HTML output using sphinx. Get the dependencies for (re)building the docs: pip install Thun[build-docs] make docs §.4 Basics of Joy Joy is stack-based. There is a main stack that holds data items: integers, floats, strings, functions, and sequences or quotes which hold data items themselves. 23 1.8 'a string' "another" dup [21 18 /] [1 [2 [3]]] A Joy expression is just a sequence (a.k.a. "list") of items. Sequences intended as programs are called "quoted programs". Evaluation proceeds by iterating through the terms in the expression, putting all literals onto the main stack and executing functions as they are encountered. Functions receive the current stack and return the next stack. §.4.1 Python Semantics In general, where otherwise unspecified, the semantics of Thun are that of the underlying Python. That means, for example, that integers are unbounded (whatever your machine can handle), strings cannot be added to integers but can be multiplied, Boolean True and False are effectively identical to ints 1 and 0, empty sequences are considered False, etc. Nothing is done about Python exceptions currently, although it would be possible to capture the stack and expression just before the exception and build a robust and flexible error handler. Because they are both just datastructures, you could immediately retry them under a debugger, or edit either or both of the stack and expression. All state is in one or the other. §.4.2 Literals and Simple Functions joy? 1 2 3 . 1 2 3 1 . 2 3 1 2 . 3 1 2 3 . 1 2 3 <-top joy? + + 1 2 3 . + + 1 5 . + 6 . 6 <-top joy? 7 * 6 . 7 * 6 7 . * 42 . 42 <-top joy? §.4.3 Combinators The main loop is very simple as most of the action happens through what are called "combinators": functions which accept quoted programs on the stack and run them in various ways. These combinators factor specific patterns that provide the effect of control-flow in other languages (such as ifte which is like if..then..else..) Combinators receive the current expession in addition to the stack and return the next expression. They work by changing the pending expression the interpreter is about to execute. The combinators could work by making recursive calls to the interpreter and all intermediate state would be held in the call stack of the implementation language, in this joy implementation they work instead by changing the pending expression and intermediate state is put there. joy? 23 [0 >] [dup --] while ... -> 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 TODO: §.4.4 Definitions and More Elaborate Functions §.4.5 Programming and Metaprogramming §.4.6 Refactoring §.5 This Implementation Run with: python -m joy Thun |-- COPYING - license |-- README - this file | |-- archive - info on Joy | |-- Joy-Programming.zip | `-- README | |-- docs - Various Examples and Demos | |-- * - Jupyter Notebooks on Thun and supporting modules | `-- README - Table of Contents | |-- joy | |-- joy.py - main loop, REPL | |-- library.py - Functions, Combinators, Definitions | |-- parser.py - convert text to Joy datastructures | | | `-- utils | |-- pretty_print.py - convert Joy datastructures to text | `-- stack.py - work with stacks | |-- thun - Experimental Prolog Code | |-- compiler.pl - A start on a compiler for Prof. Wirth's RISC CPU | `-- thun.pl - An interpreter in the Logical Paradigm, compiler. | `-- setup.py §.6 References & Further Reading Wikipedia entry for Joy: https://en.wikipedia.org/wiki/Joy_%28programming_language%29 Homepage at La Trobe University: http://www.latrobe.edu.au/humanities/research/research-projects/past-projects/joy-programming-language -------------------------------------------------- Misc... Stack based - literals (as functions) - functions - combinators - Refactoring and making new definitions - traces and comparing performance - metaprogramming as programming, even the lowly integer range function can be expressed in two phases: building a specialized program and then executing it with a combinator - ?Partial evaluation? - ?memoized dynamic dependency graphs? - algebra