Recurisve descent parsing library for Python based on functional combinators.
Parser combinators are just higher-order functions that take parsers as their arguments and return them as result values. Parser combinators are:
- First-class values
- Extremely composable
- Tend to make the code quite compact
- Resemble the readable notation of xBNF grammars
Parsers made with funcparserlib
are pure-Python LL(*) parsers. It means that it's very easy to write them without thinking about look-aheads and all that hardcore parsing stuff. But the recursive descent parsing is a rather slow method compared to LL(k) or LR(k) algorithms.
So the primary domain for funcparserlib
is parsing little languages or external DSLs (domain specific languages).
The library itself is very small. Its source code is only 0.5 KLOC, with lots of comments included. It features the longest parsed prefix error reporting, as well as a tiny lexer generator for token position tracking.
This is an excerpt from a JSON parser (RFC
4627) written using funcparserlib
. This
full example as well as others can be found here.
def parse(seq):
'Sequence(Token) -> object'
...
n = lambda s: a(Token('Name', s)) >> tokval
def make_array(n):
if n is None:
return []
else:
return [n[0]] + n[1]
...
null = n('null') >> const(None)
true = n('true') >> const(True)
false = n('false') >> const(False)
number = toktype('Number') >> make_number
string = toktype('String') >> make_string
value = forward_decl()
member = string + op_(':') + value >> tuple
object = (
op_('{') +
maybe(member + many(op_(',') + member)) +
op_('}')
>> make_object)
array = (
op_('[') +
maybe(value + many(op_(',') + value)) +
op_(']')
>> make_array)
value.define(
null
| true
| false
| object
| array
| number
| string)
json_text = object | array
json_file = json_text + skip(finished)
return json_file.parse(seq)
You can install the funcparserlib
library from PyPI via pip
:
$ pip install funcparserlib
There are no dependencies on other libraries.
A short intro to funcparserlib
can be found in the Nested Brackets
Mini-HOWTO.
The comprehensive funcparserlib Tutorial is also available.
See also comments inside the modules funcparserlib.parser
and
funcparserlib.lexer
or generate the API docs from the modules using pydoc
.
There a couple of examples available in the funcparserlib/tests directory:
See also the changelog and FAQ.
Despite being an LL(*
) parser, funcparserlib
has a reasonable performance. For example, a JSON parser written using funcparserlib
is 3 times faster than a parser using the popular pyparsing
library and only 5 times slower than the specialized JSON library simplejson
that uses ad hoc parsing. Here are some stats1:
File Size | cjson | simplejson | funcparserlib | json-ply | pyparsing |
---|---|---|---|---|---|
6 KB | 0 ms | 45 ms | 228 ms | n/a | 802 ms |
11 KB | 0 ms | 80 ms | 395 ms | 367 ms | 1355 ms |
100 KB | 4 ms | 148 ms | 855 ms | 1071 ms | 2611 ms |
134 KB | 11 ms | 957 ms | 4775 ms | n/a | 16534 ms |
1009 KB | 87 ms | 6904 ms | 36826 ms | n/a | 116510 ms |
User Code | 0.9 KLOC | 0.8 KLOC | 0.1 KLOC | 0.5 KLOC | 0.1 KLOC |
Library Code | 0 KLOC | 0 KLOC | 0.5 KLOC | 5.3 KLOC | 3.7 KLOC |
funcparserlib
and pyparsing
both have the smallest user code size (that is a common feature of parsing libraries compared to ad hoc parsers). The library code of funcparserlib
is 7 times smaller (and much more cleaner) than pyparsing
. The json-ply
uses a LALR parser ply
(similar to Yacc) and performs like funcparserlib
. cjson
is a C library, hence the incredible performance :)
- LEPL. A recursive descent parsing library that uses two-way generators for backtracking. Its source code is rather large: 17 KLOC
- pyparsing. A recursive descent parsing library. Probably the most popular Python parsing library. Nevertheless its source code is quite dirty (though 4 KLOC only)
- Monadic Parsing in Python. A series of blog entries on monadic parsing
- Pysec (aka Parsec in Python). A blog entry on monadic parsing, with nice syntax for Python
1 Testing hardware: Pentium III, 1 GHz, 512 MB. JSON files were taken from a real project, in a normalized encoding, i. e. they contained no extra separators. The version 0.3.2 of the library was used.