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https://github.com/vlasovskikh/funcparserlib
Recursive descent parsing library for Python based on functional combinators
https://github.com/vlasovskikh/funcparserlib
functional-programming parser-combinators parsing python
Last synced: about 2 months ago
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Recursive descent parsing library for Python based on functional combinators
- Host: GitHub
- URL: https://github.com/vlasovskikh/funcparserlib
- Owner: vlasovskikh
- License: mit
- Created: 2015-04-23T19:38:11.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2024-05-04T09:31:43.000Z (8 months ago)
- Last Synced: 2024-10-14T15:07:06.879Z (2 months ago)
- Topics: functional-programming, parser-combinators, parsing, python
- Language: Python
- Homepage: https://funcparserlib.pirx.ru
- Size: 2.08 MB
- Stars: 341
- Watchers: 20
- Forks: 38
- Open Issues: 11
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-combinator-parsers - funcparserlib
README
Funcparserlib
=============
Recursive descent parsing library for Python based on functional combinators.
[](https://pypi.org/project/funcparserlib/)
[](https://pypi.org/project/funcparserlib/)
Description
-----------
The primary focus of `funcparserlib` is **parsing little languages** or **external DSLs** (domain specific languages).
Parsers made with `funcparserlib` are pure-Python LL(\*) parsers. It means that it's **very easy to write parsers** without thinking about lookaheads and other hardcore parsing stuff. However, recursive descent parsing is a rather slow method compared to LL(k) or LR(k) algorithms. Still, parsing with `funcparserlib` is **at least twice faster than PyParsing**, a very popular library for Python.
The source code of `funcparserlib` is only 1.2K lines of code, with lots of comments. Its API is fully type hinted. It features the longest parsed prefix error reporting, as well as a tiny lexer generator for token position tracking.
The idea of parser combinators used in `funcparserlib` comes from the [Introduction to Functional Programming](https://www.cl.cam.ac.uk/teaching/Lectures/funprog-jrh-1996/) course. We have converted it from ML into Python.
Installation
------------
You can install `funcparserlib` from [PyPI](https://pypi.org/project/funcparserlib/):
```shell
$ pip install funcparserlib
```
There are no dependencies on other libraries.
Documentation
-------------
* [Getting Started](https://funcparserlib.pirx.ru/getting-started/)
* Your **starting point** with `funcparserlib`
* [API Reference](https://funcparserlib.pirx.ru/api/)
* Learn the details of the API
There are several examples available in the `tests/` directory:
* [GraphViz DOT parser](https://github.com/vlasovskikh/funcparserlib/blob/master/tests/dot.py)
* [JSON parser](https://github.com/vlasovskikh/funcparserlib/blob/master/tests/json.py)
See also [the changelog](https://funcparserlib.pirx.ru/changes/).
Example
-------
Let's consider a little language of **numeric expressions** with a syntax similar to Python expressions. Here are some expression strings in this language:
```
0
1 + 2 + 3
-1 + 2 ** 32
3.1415926 * (2 + 7.18281828e-1) * 42
```
Here is **the complete source code** of the tokenizer and the parser for this language written using `funcparserlib`:
```python
from typing import List, Tuple, Union
from dataclasses import dataclass
from funcparserlib.lexer import make_tokenizer, TokenSpec, Token
from funcparserlib.parser import tok, Parser, many, forward_decl, finished
@dataclass
class BinaryExpr:
op: str
left: "Expr"
right: "Expr"
Expr = Union[BinaryExpr, int, float]
def tokenize(s: str) -> List[Token]:
specs = [
TokenSpec("whitespace", r"\s+"),
TokenSpec("float", r"[+\-]?\d+\.\d*([Ee][+\-]?\d+)*"),
TokenSpec("int", r"[+\-]?\d+"),
TokenSpec("op", r"(\*\*)|[+\-*/()]"),
]
tokenizer = make_tokenizer(specs)
return [t for t in tokenizer(s) if t.type != "whitespace"]
def parse(tokens: List[Token]) -> Expr:
int_num = tok("int") >> int
float_num = tok("float") >> float
number = int_num | float_num
expr: Parser[Token, Expr] = forward_decl()
parenthesized = -op("(") + expr + -op(")")
primary = number | parenthesized
power = primary + many(op("**") + primary) >> to_expr
term = power + many((op("*") | op("/")) + power) >> to_expr
sum = term + many((op("+") | op("-")) + term) >> to_expr
expr.define(sum)
document = expr + -finished
return document.parse(tokens)
def op(name: str) -> Parser[Token, str]:
return tok("op", name)
def to_expr(args: Tuple[Expr, List[Tuple[str, Expr]]]) -> Expr:
first, rest = args
result = first
for op, expr in rest:
result = BinaryExpr(op, result, expr)
return result
```
Now, consider this numeric expression: `3.1415926 * (2 + 7.18281828e-1) * 42`.
Let's `tokenize()` it using the tokenizer we've created with `funcparserlib.lexer`:
```
[
Token('float', '3.1415926'),
Token('op', '*'),
Token('op', '('),
Token('int', '2'),
Token('op', '+'),
Token('float', '7.18281828e-1'),
Token('op', ')'),
Token('op', '*'),
Token('int', '42'),
]
```
Let's `parse()` these tokens into an expression tree using our parser created with `funcparserlib.parser`:
```
BinaryExpr(
op='*',
left=BinaryExpr(
op='*',
left=3.1415926,
right=BinaryExpr(op='+', left=2, right=0.718281828),
),
right=42,
)
```
Learn how to write this parser using `funcparserlib` in the [Getting Started](https://funcparserlib.pirx.ru/getting-started/) guide!
Used By
-------
Some open-source projects that use `funcparserlib` as an explicit dependency:
* [Hy](https://github.com/hylang/hy), a Lisp dialect that's embedded in Python
* 4.7K stars, version `~=1.0`, Python 3.8+
* [Splash](https://github.com/scrapinghub/splash), a JavaScript rendering service with HTTP API, by Scrapinghub
* 3.9K stars, version `*`. Python 3 in Docker
* [graphite-beacon](https://github.com/klen/graphite-beacon), a simple alerting system for Graphite metrics
* 453 stars, version `==0.3.6`, Python 2 and 3
* [blockdiag](https://github.com/blockdiag/blockdiag), generates block-diagram image file from spec-text file
* 194 stars, version `>= 1.0.0a0`, Python 3.7+
* [kll](https://github.com/kiibohd/kll), Keyboard Layout Language (KLL) compiler
* 113 stars, copied source code, Python 3.5+
Next
----
Read the [Getting Started](https://funcparserlib.pirx.ru/getting-started/) guide to start learning `funcparserlib`.