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Getting Started

Intro

In this guide, we will write a parser for a numeric expression calculator with a syntax similar to Python expressions. Writing a calculator is a common example in articles related to parsers and parsing techniques, so it is a good starting point in learning funcparserlib.

You will learn how to write a parser of numeric expressions using funcparserlib. Here are some expression strings we want to be able to parse:

0
1 + 2 + 3
-1 + 2 ** 32
3.1415926 * (2 + 7.18281828e-1) * 42

We will parse these strings into trees of objects like this one:

BinaryExpr('*')
|-- BinaryExpr('*')
|   |-- 3.1415926
|   `-- BinaryExpr('+')
|       |-- 2
|       `-- 0.718281828
`-- 42

Diving In

Here is the complete source code of the expression parser we are going to write.

You are not supposed to understand it now. Just look at its shape and try to get some feeling about its structure. By the end of this guide, you will fully understand this code and will be able to write parsers for your own needs.

>>> 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

Note

The code examples in this guide are actually executable. You can clone the funcparserlib repository from GitHub and run the examples from the document via doctest:

python3 -m doctest -v docs/getting-started/*.md

Test the expression parser:

>>> parse(tokenize("0"))
0

>>> parse(tokenize("1 + 2 + 3"))
BinaryExpr(op='+', left=BinaryExpr(op='+', left=1, right=2), right=3)

>>> parse(tokenize("-1 + 2 ** 32"))
BinaryExpr(op='+', left=-1, right=BinaryExpr(op='**', left=2, right=32))

>>> parse(tokenize("3.1415926 * (2 + 7.18281828e-1) * 42"))
BinaryExpr(op='*', left=BinaryExpr(op='*', left=3.1415926, right=BinaryExpr(op='+', left=2, right=0.718281828)), right=42)

Next

Now let's start learning how to write a numeric expression parser using funcparserlib.

In the next chapter you will learn about the first step in parsing: tokenizing the input. It means splitting your input string into a sequence of tokens that are easier to parse.