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A simplified API to PLY (Python Lex & Yacc).

Project description

Ox is simple “compiler of compilers” framework based on the excellent PLY library.

Why Ox?

PLY is a great library which is a reasonably efficient pure Python implementation of Yacc/Bison. We think, however, its API is a little bit awkward and does a lot of strange magic under the hood. Ox wraps main PLY functionality into a more functional and straightforward API that aims to be more explicit while still being easier to use.

PLY was designed to be a Python replacement for Yacc/Bison and does not offer any functionality to work as a general framework for building compilers. Ox is a minimalistic framework and provides a few extra bells and whistles (but it will never be nowhere near a Python replacement for, say, LLVM).

Ox is mature enough to be useful for production code, but just like PLY, it was created as a tool for a introductory compilers course. One explicit pedagogical goal of Ox is to make the boundaries of the different compilation phases very explicit and easily pluggable into each other. This approach is good for teaching, but it does not lead to the most efficient or robust implementations of real compilers. Ox, as most compiler generators, is good for quick experimentation but it is limited in terms of performance and, more importantly, Ox parsers generally fail to provide nice error messages for syntax errors.

What about the name?

PLY is a Pythonic implementation/interpretation of Yacc. The most widespread Yacc implementation is of course GNU Bison. We decided to keep the bovine theme alive and call it Ox.

Concepts

Compilation is usually broken in a few steps:

  1. Tokenization/lexical analysis: a string of source code is broken into a list of tokens. Ox lexers are any function that receives a string of source code and return a list (or any iterable) of tokens.
  2. Parsing: the list of tokens is converted into a syntax tree. In Ox, the parser is derived from a grammar in BNF form. It receives a list of tokens and outputs an arbitrary parse tree.
  3. Semantic analysis: the parse tree is scanned for semantic errors (e.g. invalid variable names, invalid type signatures, etc). The parse tree may be converted to different representations in this process.
  4. Code optimization: many optimizations are applied in order to generate efficient internal representations. This is highly dependent on the target language and runtime and it tends to be the largest part of a real compiler.
  5. Code generation: the intermediate representation is used to emit code in the target language. The target language is often a low level language such as assembly or machine code. Nothing prevents us from emmiting Python or Javascript, however.

Ox is mostly concerned with steps 1 and 2. The library has very limited support steps 3 onwards, but in general they tend to be very application specific and a general tool such as Ox can offer little help.

Usage

Ox can build a lexer function by simply providing a list of token names associated with their corresponding regular expressions:

import ox

lexer = ox.make_lexer([
    ('NUMBER', r'\d+(\.\d*)?'),
    ('PLUS', r'\+'),
    ('MINUS', r'\-'),
    ('MUL', r'\*'),
    ('DIV', r'\/'),
])

This declares a tokenizer function that receives a string of source code and returns a list of tokens:

>>> lexer('21 + 21')
[NUMBER('21'), PLUS('+'), NUMBER('21')]

The next step, of course, is to pass this list of tokens to a parser in order to generate the parse tree. We can easily declare a parser in Ox from a mapping of grammar rules to handler functions.

Each handler function receives a number of inputs from its corresponding grammar rule and return an AST node. In the example bellow, we return tuples to build our AST as a LISP-like S-expressions.

binop = lambda x, op, y: (op, x, y)
identity = lambda x: x

Now the rules:

parser = ox.make_parser([
    ('expr : expr PLUS term', binop),
    ('expr : expr MINUS term', binop),
    ('expr : term', identity),
    ('term : term MUL atom', binop),
    ('term : term DIV atom', binop),
    ('term : atom', identity),
    ('atom : NUMBER', float),
])

The parser takes a list of tokens and convert it to an AST:

>>> parser(lexer('2 + 2 * 20'))
('+', 2.0, ('*', 2.0, 20.0))

The AST makes it easy to analyze and evaluate an expression. We can write a simple evaluator as follows:

import operator as op

operations = {'+': op.add, '-': op.sub, '*': op.mul, '/': op.truediv}

def eval(node):
    if isinstance(node, tuple):
        head, *tail = node
        func = operations[head]
        args = (eval(x) for x in tail)
        return func(*args)
    else:
        return node

The eval function receives an AST, but we can easily compose it with the other functions in order to accept string inputs. (Ox functions understand sidekick’s pipeline operators. The arrow operator >> composes two functions by passing the output of each function to the function in the pipeline following the arrow direction).

>>> eval_input = lexer >> parser >> eval
>>> eval_input('2 + 2 * 20')
42.0

We can call this function in a loop to have a nice calculator written with only a few lines of Python code!

def eval_loop():
    expr = input('expr: ')
    print('result:', eval_input(expr))

Project details


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