解析文本文件一般方法

Question

看过一些解析文本或者源代码文件程序的代码，在写lexer的时候好像一个一个字符读进去再收集token然后分析是keyword\identifier\number...之类的方法比较多，是不是用正则表达式会比较慢？还是有部分用正则表达式无法实现？用正则表达式将文本切开再从中析下keyword\identifier\number...有什么不同？

Answer 1

现在的lexer也是用正则了。

# http://www.evanfosmark.com/2009/02/sexy-lexing-with-python/

import re
 
 
class UnknownTokenError(Exception):
    """ This exception is for use to be thrown when an unknown token is
        encountered in the token stream. It hols the line number and the
        offending token.
    """
    def __init__(self, token, lineno):
        self.token = token
        self.lineno = lineno
 
    def __str__(self):
        return "Line #%s, Found token: %s" % (self.lineno, self.token)
 
 
class _InputScanner(object):
    """ This class manages the scanning of a specific input. An instance of it is
        returned when scan() is called. It is built to be great for iteration. This is
        mainly to be used by the Lexer and ideally not directly.
    """
 
    def __init__(self, lexer, input):
        """ Put the lexer into this instance so the callbacks can reference it 
            if needed.
        """
        self._position = 0
        self.lexer = lexer
        self.input = input
 
    def __iter__(self):
        """ All of the code for iteration is controlled by the class itself.
            This and next() (or __next__() in Python 3.0) are so syntax
            like `for token in Lexer(...):` is valid and works.
        """
        return self
 
    def __next__(self):
        """ Used for iteration. It returns token after token until there
            are no more tokens. (change this to __next__(self) if using Py3.0)
        """
        if not self.done_scanning():
            return self.scan_next()
        raise StopIteration
 
    def done_scanning(self):
        """ A simple boolean function that returns true if scanning is
            complete and false if it isn't.
        """
        return self._position >= len(self.input)
 
    def scan_next(self):
        """ Retreive the next token from the input. If the
            flag `omit_whitespace` is set to True, then it will
            skip over the whitespace characters present.
        """
        if self.done_scanning():
            return None
        if self.lexer.omit_whitespace:
            match = self.lexer.ws_regexc.match(self.input, self._position)
            if match:
                self._position = match.end()
        match = self.lexer.regexc.match(self.input, self._position)
        if match is None:
            lineno = self.input[:self._position].count("\n") + 1
            raise UnknownTokenError(self.input[self._position], lineno)
        self._position = match.end()
        value = match.group(match.lastgroup)
        if match.lastgroup in self.lexer._callbacks:
            value = self.lexer._callbacks[match.lastgroup](self, value)
        return match.lastgroup, value
 
 
class Lexer(object):
    """ A lexical scanner. It takes in an input and a set of rules based
        on reqular expressions. It then scans the input and returns the
        tokens one-by-one. It is meant to be used through iterating.
    """
 
    def __init__(self, rules, case_sensitive=True, omit_whitespace=True):
        """ Set up the lexical scanner. Build and compile the regular expression
            and prepare the whitespace searcher.
        """
        self._callbacks = {}
        self.omit_whitespace = omit_whitespace
        self.case_sensitive = case_sensitive
        parts = []
        for name, rule in rules:
            if not isinstance(rule, str):
                rule, callback = rule
                self._callbacks[name] = callback
            parts.append("(?P<%s>%s)" % (name, rule))
        if self.case_sensitive:
            flags = re.M
        else:
            flags = re.M|re.I
        self.regexc = re.compile("|".join(parts), flags)
        self.ws_regexc = re.compile("\s*", re.MULTILINE)
 
    def scan(self, input):
        """ Return a scanner built for matching through the `input` field. 
            The scanner that it returns is built well for iterating.
        """
        return _InputScanner(self, input)


if __name__ == '__main__':
    def stmnt_callback(scanner, token):
        """ This is just an example of providing a function to run the
        token through.
        """
        return ""
 
    rules = [
        ("IDENTIFIER", r"[a-zA-Z_]\w*"),
        ("OPERATOR",   r"\+|\-|\\|\*|\="),
        ("DIGIT",      r"[0-9]+(\.[0-9]+)?"),
        ("END_STMNT",  (";", stmnt_callback)), 
        ]
 
    lex = Lexer(rules, case_sensitive=True)
    for token in lex.scan("foo = 5 * 30; bar = bar - 60;"):
        print(token)

Answer 2

一般来说编程语言的正则表达式实现都是调用了第三方引擎的，这里有很详细的比较说明：

http://en.wikipedia.org/wiki/Comparis...

所以对比语言内置的文本处理函数来说，一个正则表达式就需要调用一次引擎，无论是内存占用、效率都要下降很多。你可以很简单运行同一个替换10W次，比较开启和不开启正则的时间和内存占用。

所以高效的文本解析应该尽可能少的使用正则表达式。