解析 python 中的嵌套函数

parsing nested functions in python

line = "add(multiply(add(2,3),add(4,5)),1)"

def readLine(line):
    countLeftBracket=0
    string = ""
    for char in line:
        if char !=")":
            string += char
        else:
            string +=char
            break

    for i in string:
        if i=="(":
            countLeftBracket+=1

    if countLeftBracket>1:
        cutString(string)
    else:
        return execute(string)

def cutString(string):
    countLeftBracket=0

    for char in string:
        if char!="(":
            string.replace(char,'')
        elif char=="(":
            string.replace(char,'')
            break

    for char in string:
        if char=="(":
            countLeftBracket+=1

    if countLeftBracket>1:
        cutString(string)
    elif countLeftBracket==1:
        return execute(string)

def add(num1,num2):
    return print(num1+num2)

def multiply(num1,num2):
    return print(num1*num2)

readLines(line)

我需要执行整行字符串。我试图一个一个地删除括号内的每个函数并用结果替换它们,但我有点迷路了。不确定如何继续,我的代码出现错误:

  File "main.py", line 26, in cutString                                                                                 
    if char!="(":                                                                                                       
RuntimeError: maximum recursion depth exceeded in comparison 

告诉我移动到哪里,使用哪种方法?

您可以使用生成器函数构建一个非常简单的解析器:

import re, operator
line, f = "add(multiply(add(2,3),add(4,5)),1)", {'add':operator.add, 'multiply':operator.mul}
def parse(d):
   n = next(d, None)
   if n is not None and n != ')':
     if n == '(':
       yield iter(parse(d))
     else:
       yield n
     yield from parse(d)

parsed = parse(iter(re.findall('\(|\)|\w+', line)))
def _eval(d):
   _r = []
   n = next(d, None)
   while n is not None:
      if n.isdigit():
        _r.append(int(n))
      else:
        _r.append(f[n](*_eval(next(d))))
      n = next(d, None)
   return _r

print(_eval(parsed)[0])

输出:

46

听起来这可以用正则表达式解决。

所以这是一个单一归约的例子

import re, operator
def apply(match):
   func_name = match.group(1) # what's outside the patentesis
   func_args = [int(x) for x in match.group(2).split(',')]
   func = {"add": operator.add, "multiply": operator.mul}
   return str(func[func_name](*func_args))
def single_step(line):
   return re.sub(r"([a-z]+)\(([^()]+)\)",apply,line)

例如:

line = "add(multiply(add(2,3),add(4,5)),1)"
print(single_step(line))

会输出:

add(multiply(5,9),1)

剩下要做的就是循环直到表达式是一个数字

while not line.isdigit():
   line = single_step(line)
print (line)

会显示

46

这是一个使用 pyparsing 的解决方案,因此更容易扩展:

from pyparsing import *

首先是一个方便的函数(使用第二个标记函数并打印解析树以查看原因)

def tag(name):
    """This version converts ["expr", 4] => 4
       comment in the version below to see the original parse tree
    """
    def tagfn(tokens):
        tklist = tokens.asList()
        if name == 'expr' and len(tklist) == 1:
            # LL1 artifact removal
            return tklist
        return tuple([name] + tklist)
    return tagfn

# def tag(name):
#     return lambda tokens: tuple([name] + tokens.asList())

我们的词法分析器需要识别左右括号、整数和名称。这就是你用 pyparsing 定义它们的方式:

LPAR = Suppress("(")
RPAR = Suppress(")")
integer = Word(nums).setParseAction(lambda s,l,t: [int(t[0])])
name = Word(alphas)

我们的解析器有函数调用,它以零个或多个表达式作为参数。一个函数调用也是一个表达式,所以为了处理循环我们必须转发声明 expr 和 fncall:

expr = Forward()
fncall = Forward()

expr << (integer | fncall).setParseAction(tag('expr'))
fnparams = delimitedList(expr)

fncall << (name + Group(LPAR + Optional(fnparams, default=[]) + RPAR)).setParseAction(tag('fncall'))

现在我们可以解析我们的字符串(我们也可以向函数添加空格和多于或少于两个参数):

line = "add(multiply(add(2,3),add(4,5)),1)"
res = fncall.parseString(line)

要查看返回的内容,您可以打印它,这称为解析树(或者,由于我们的标记函数对其进行了简化,因此称为抽象语法树):

import pprint
pprint.pprint(list(res))

输出:

[('fncall',
  'add',
  [('fncall',
    'multiply',
    [('fncall', 'add', [2, 3]), ('fncall', 'add', [4, 5])]),
   1])]

使用注释掉的标签函数(这只是为了处理更多的工作而没有额外的好处):

[('fncall',
  'add',
  [('expr',
    ('fncall',
     'multiply',
     [('expr', ('fncall', 'add', [('expr', 2), ('expr', 3)])),
      ('expr', ('fncall', 'add', [('expr', 4), ('expr', 5)]))])),
   ('expr', 1)])]

现在定义我们程序可用的函数:

FUNCTIONS = {
    'add': lambda *args: sum(args, 0),
    'multiply': lambda *args: reduce(lambda a, b: a*b, args, 1),
}

# print FUNCTIONS['multiply'](1,2,3,4)   # test that it works ;-)

我们的解析器现在写起来非常简单:

def parse(ast):
    if not ast:  # will not happen in our program, but it's good practice to exit early on no input
        return

    if isinstance(ast, tuple) and ast[0] == 'fncall':
        # ast is here ('fncall', <name-of-function>, [list-of-arguments])
        fn_name = ast[1]          # get the function name
        fn_args = parse(ast[2])   # parse each parameter (see elif below)
        return FUNCTIONS[fn_name](*fn_args)  # find and apply the function to its arguments
    elif isinstance(ast, list):
        # this is called when we hit a parameter list
        return [parse(item) for item in ast]
    elif isinstance(ast, int):
        return ast

现在根据词法分析阶段的结果调用解析器:

>>> print parse(res[0])  # the outermost item is an expression
46