235 lines
6.5 KiB
Plaintext
235 lines
6.5 KiB
Plaintext
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Thun
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Dialects of Joy in Python and Prolog.
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v0.3.0
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--------------------------------------------------
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Copyright © 2014-2020 Simon Forman
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This file is part of Thun
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Thun is free software: you can redistribute it and/or modify it under the
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terms of the GNU General Public License as published by the Free Software
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Foundation, either version 3 of the License, or (at your option) any
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later version.
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Thun is distributed in the hope that it will be useful, but WITHOUT ANY
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WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
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details.
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You should have received a copy of the GNU General Public License along
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with Thun. If not see <http://www.gnu.org/licenses/>.
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--------------------------------------------------
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§.1 Introduction
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Joy is a programming language created by Manfred von Thun that is easy to
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use and understand and has many other nice properties. This project
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implements Python and Prolog interpreters for dialects that attempts to
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stay very close to the spirit of Joy but does not precisely match the
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behaviour of the original version written in C.
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The best source (no pun intended) for learning about Joy is the
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information made available at the website of La Trobe University (see the
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references section below for the URL) which contains source code for the
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original C interpreter, Joy language source code for various functions,
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and a great deal of fascinating material mostly written by Von Thun on
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Joy and its deeper facets as well as how to program in it and several
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interesting aspects. It's quite a treasure trove.
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§.2 Installation
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From PyPI in the usual way, e.g.:
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pip install Thun
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Or if you have downloaded the source, from the top directory:
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python ./setup.py install
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Or you can run the package directly from the top directory.
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To start a crude REPL:
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python -m joy
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§.3 Documentation
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§.3.1 Jupyter Notebooks
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The docs/ folder contains Jupyter notebooks, ... TODO
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§.3.2 Sphinx Docs
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Some of the documentation is in the form of ReST files
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§.3.3 Building the Docs
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Building the documentation is a little tricky at the moment. It involves
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a makefile that uses nbconvert to generate ReST files from some of the
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notebooks, copies those to the sphinx source dir, then builds the HTML
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output using sphinx.
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Get the dependencies for (re)building the docs:
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pip install Thun[build-docs]
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make docs
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§.4 Basics of Joy
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Joy is stack-based. There is a main stack that holds data items:
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integers, floats, strings, functions, and sequences or quotes which hold
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data items themselves.
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23 1.8 'a string' "another" dup [21 18 /] [1 [2 [3]]]
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A Joy expression is just a sequence (a.k.a. "list") of items. Sequences
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intended as programs are called "quoted programs". Evaluation proceeds
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by iterating through the terms in the expression, putting all literals
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onto the main stack and executing functions as they are encountered.
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Functions receive the current stack and return the next stack.
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§.4.1 Python Semantics
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In general, where otherwise unspecified, the semantics of Thun are that
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of the underlying Python. That means, for example, that integers are
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unbounded (whatever your machine can handle), strings cannot be added to
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integers but can be multiplied, Boolean True and False are effectively
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identical to ints 1 and 0, empty sequences are considered False, etc.
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Nothing is done about Python exceptions currently, although it would be
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possible to capture the stack and expression just before the exception
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and build a robust and flexible error handler. Because they are both
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just datastructures, you could immediately retry them under a debugger,
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or edit either or both of the stack and expression. All state is in one
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or the other.
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§.4.2 Literals and Simple Functions
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joy? 1 2 3
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. 1 2 3
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1 . 2 3
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1 2 . 3
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1 2 3 .
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1 2 3 <-top
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joy? + +
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1 2 3 . + +
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1 5 . +
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6 .
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6 <-top
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joy? 7 *
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6 . 7 *
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6 7 . *
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42 .
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42 <-top
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joy?
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§.4.3 Combinators
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The main loop is very simple as most of the action happens through what
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are called "combinators": functions which accept quoted programs on the
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stack and run them in various ways. These combinators factor specific
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patterns that provide the effect of control-flow in other languages (such
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as ifte which is like if..then..else..) Combinators receive the current
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expession in addition to the stack and return the next expression. They
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work by changing the pending expression the interpreter is about to
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execute. The combinators could work by making recursive calls to the
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interpreter and all intermediate state would be held in the call stack of
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the implementation language, in this joy implementation they work instead
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by changing the pending expression and intermediate state is put there.
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joy? 23 [0 >] [dup --] while
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...
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-> 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
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TODO:
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§.4.4 Definitions and More Elaborate Functions
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§.4.5 Programming and Metaprogramming
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§.4.6 Refactoring
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§.5 This Implementation
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Run with:
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python -m joy
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Thun
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|-- COPYING - license
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|-- README - this file
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|-- archive - info on Joy
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| |-- Joy-Programming.zip
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| `-- README
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|-- docs - Various Examples and Demos
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| |-- * - Jupyter Notebooks on Thun and supporting modules
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| `-- README - Table of Contents
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|-- joy
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| |-- joy.py - main loop, REPL
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| |-- library.py - Functions, Combinators, Definitions
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| |-- parser.py - convert text to Joy datastructures
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| `-- utils
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| |-- pretty_print.py - convert Joy datastructures to text
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| `-- stack.py - work with stacks
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|-- thun - Experimental Prolog Code
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| |-- compiler.pl - A start on a compiler for Prof. Wirth's RISC CPU
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| `-- thun.pl - An interpreter in the Logical Paradigm, compiler.
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`-- setup.py
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§.6 References & Further Reading
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Wikipedia entry for Joy:
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https://en.wikipedia.org/wiki/Joy_%28programming_language%29
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Homepage at La Trobe University:
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http://www.latrobe.edu.au/humanities/research/research-projects/past-projects/joy-programming-language
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--------------------------------------------------
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Misc...
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Stack based - literals (as functions) - functions - combinators -
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Refactoring and making new definitions - traces and comparing
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performance - metaprogramming as programming, even the lowly integer
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range function can be expressed in two phases: building a specialized
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program and then executing it with a combinator - ?Partial evaluation?
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- ?memoized dynamic dependency graphs? - algebra
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