==========
Compynator
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Introduction
Compynator is a tiny (~400 SLOCs), pure Python implementation of parser combinators <https://en.wikipedia.org/wiki/Parser_combinator>_. With this
library, one can build up a complex parser from primitive parsers such as "get
one token" (the One parser), or compose parsers together such as "if this
parser fails, try that parser" (the Or combinator), etc. The mental model is
a binary tree of execution nodes through which a sequence of input tokens flows.
The implementation in this package supports optional memoization and curtailment
as described in [Frost2007]_. This allows a memoized parser to achieve
asymptotically best performance, and support ambiguous grammars.
Compynator is not an official Google product.
Examples
An example that solves
https://leetcode.com/problems/parsing-a-boolean-expression:
.. code-block:: python
t = Terminal('t').value(True)
f = Terminal('f').value(False)
e = Forward()
n = Terminal('!(').then(e).value(lambda x: not x).skip(')')
a_empty = Succeed(True)
a_e_tail = Forward()
a_e_tail.is_(
Terminal(',').then(e).then(
a_e_tail, lambda x, y: x and y) | a_empty)
a = Terminal('&(').then(e).then(
a_e_tail, lambda x, y: x and y).skip(')')
o_empty = Succeed(False)
o_e_tail = Forward()
o_e_tail.is_(
Terminal(',').then(e).then(
o_e_tail, lambda x, y: x or y) | o_empty)
o = Terminal('|(').then(e).then(
o_e_tail, lambda x, y: x or y).skip(')')
e.is_(t | f | n | a | o)
self.assertEqual(e('!(f)'), {Result(True, '')})
self.assertEqual(e('|(f,t)'), {Result(True, '')})
self.assertEqual(e('&(t,f)'), {Result(False, '')})
self.assertEqual(e('|(&(t,f,t),!(t))'), {Result(False, '')})
See test_benchmark.py <tests/test_benchmark.py>_ for a literal translation of
the ABNF rules for URI parsing as given in [RFC3986]_ into a structured tree::
Uri
Scheme http
HierPart
Authority
UserInfo None
Host www.ics.uci.edu
Port None
Path /pub/ietf/uri/
Query query
Fragment fragment
There are more examples in the tests <tests>_ directory.
Translating Augmented Backus-Naur Form (ABNF)
Care should be taken to ensure that repeat takes all possible results
instead of greedily parsing for the most. For example, the ABNF *3"a" "aa"
cannot be simply translated as Terminal('a').repeat(0, 3) + 'aa'. This
translation will fail to parse aaaa because it greedily matches the first
3 a's, then fails to find the remaining 2 a's. The correct translation
should be Terminal('a').repeat(0, 3, take_all=True) + 'aa'.
=================== ====================================
ABNF Compynator
=================== ====================================
Terminal Terminal
Rule Parser
Concatenation p1 + p2
Alternative p1 | p2
Sequence group Normal use of parentheses
Variable repetition p.repeat(lower, upper, take_all)
Specific repetition p.repeat(x, x)
Optional p.repeat(0, 1, take_all)
=================== ====================================
Translating Parsing Expression Grammar (PEG)
Unlike ABNF, PEG operators are always greedy. When translating PEG, we do not
need to worry about backtracking the repetitions with take_all.
============== ===============================
PEG Compynator
============== ===============================
Terminal Terminal
Nonterminal Parser
Epsilon Empty
Sequence p1 + p2
Ordered choice p1 | p2
Zero or more p.repeat()
One or more p.repeat(1)
Optional p.repeat(0, 1)
And predicate Lookahead(p)
Not predicate Lookahead(p, take_if=False)
============== ===============================
Combinator vs Generator
Advantages
Advantages of parser combinators versus parser generators are:
#. Readability. A grammar can be expressed in a very similar form as its BNF.
The code can be considered an executable specification of the grammar.
#. Simple setup. The code is the grammar. There is no need to run a generator to
regenerate code when the grammar changes.
#. Understandability. Each parser is generally short and simple that its
correctness can be easily verified. There is no need to look into generated
code, or the code of the parser generator.
#. Parser combinators support context-sensitive grammars. For example, to parse
an XML body, assuming start parses a start tag, body parses the body,
and end parses a specified end tag:
.. code-block:: python
xml_tag = start.then(lambda tag_name: body.skip(end(tag_name)))
#. Combination of lexing and parsing. Most parser generators perform their
lexing and parsing phases separately. Parser combinators combine these phases
together. Hence they are not limited to string inputs. The example (in
test_core.py <tests/test_core.py>_) below takes a tokenized sequence.
.. code-block:: python
NUM, OP, TERMINAL = 0, 1, 2
tokens = [(NUM, 2), (OP, operator.add), (NUM, 10),
(OP, operator.mul), (NUM, 4)]
num = One.where(lambda c: c[0] == NUM)
op = One.where(lambda c: c[0] == OP).value(lambda c: c[1])
mult_div = op.where(lambda c: c in (operator.mul, operator.truediv))
add_sub = op.where(lambda c: c in (operator.add, operator.sub))
left_paren = One.where(lambda c: c[0] == TERMINAL and c[1] == '(')
right_paren = One.where(lambda c: c[0] == TERMINAL and c[1] == ')')
expr = Forward()
factor = (
num.value(lambda t: t[1]) |
left_paren.then(expr).skip(right_paren)
)
def do_op(left, op, right):
return op(left, right)
term = Forward()
term.is_((
Collect(term, mult_div, factor).value(lambda v: do_op(*v)) ^
factor
).memoize())
expr.is_((
Collect(expr, add_sub, term).value(lambda v: do_op(*v)) ^
term
).memoize())
calc = expr.filter(lambda r: not r.remain)
self.assertEqual(
set(expr(tokens)),
{
Result(value=42, remain=[]),
Result(value=12, remain=tokens[3:]),
Result(value=2, remain=tokens[1:]),
})
self.assertEqual(calc(tokens), Succeed(42)([]))
Disadvantages
Disadvantages of parser combinators are:
#. Familiarity. Most textbooks write about parser generators and traditional
parsing techniques such as LL, LR, etc. Parser combinators are more common
in functional and logic programming communities, as popularized by
[Wadler1985]_ and [Hutton1992].
#. Coupling of code and grammar. The downside of simple setup is a tight
coupling of code and grammar, which might make it difficult to understand.
#. As it is implemented here, performance might be impacted due to composition
overhead. See test_benchmark.py <tests/test_benchmark.py> for details. On
the same machine, the result for URI parsing could be ~70 times slower::
t.test_parse_uri() 903.5961110000001 usec per run
t.test_urlparse() 13.704007000000074 usec per run
#. All the advantages and disadvantages of scannerless parsing apply too.
Limitations
Currently, this library does not implement:
#. Source context such as line and column number of the token.
#. "Greedy" matching in the same sense as in regular expression (i.e. longest
match). The greedy operation in this library is in the "greedy algorithm"
sense, i.e. the first rule that matches will be taken.
#. Space treatments. Spaces have to be explicitly taken care of in grammars.
References
.. [Wadler1985] Wadler, Philip. (1985). "How to replace failure by a list of
successes". Proc. conference on functional programming and computer
architecture. Springer–Verlag.
.. [Hutton1992] Hutton, Graham. (1992). "Higher-order functions for parsing".
Journal of functional programming, 2(3), 323–343.
.. [Frost2007] Frost R.A., Hafiz R., Callaghan P. (2007) "Parser Combinators for
Ambiguous Left-Recursive Grammars". In: Hudak P., Warren D.S. (eds)
"Practical Aspects of Declarative Languages". PADL 2008. Lecture Notes in
Computer Science, vol 4902. Springer, Berlin, Heidelberg
.. [RFC3986] Berners-Lee, T., Fielding, R., and L. Masinter, "Uniform Resource
Identifier (URI): Generic Syntax", STD 66, RFC 3986, January 2005.