从你的描述中，我认为你需要把表达式放在“析取范式”（DNF）中，它看起来像Or（And（v1，v2），And（v1，v4），...）。下面的代码将使用一个额外的包来完成这一点（DNF在电子设计自动化中很常见）。要安装软件包，请执行pip3 install pyeda。
将表达式拆分为相应的And表达式的代码如下所示。
备注：

• 如果过滤器中有超过数字/字母（如问号等），则匹配过滤器的正则表达式可能需要调整。
• 你没有例子来说明如何否定一个独立变量。我用的是“不是（A）”
• 如果没有独立变量（只有比较变量），代码会简单得多
• 如果你有更多的操作符（比如小于，等等），代码会稍微复杂一些

总体思路：

• 将你的表达式转换成布尔表达式（x & y）|这是通过使所有比较成为变量来完成的。
• 将布尔表达式转换为DNF
• 用原始比较替换回变量。

from pyeda.inter import *
import re
import pandas as pd
dataex = {'Component': [123, 
                        456, 
                        789], 
          'Constraint': ["A and (B or C)", 
                         "((MIRROR='ELECTRIC' and MIRRORCAMERA!='NO') or (MIRROR='MANUAL' and (MIRROR_RIGHT!='NO' or MIRROR_LEFT!='NO'))) and STEERWHEEL_LOCK='NO'", 
                         "LENGTH='122' or (LENGTH='135' and BATTERY='551') or LENGTH='149' or (LENGTH='181' and (BATTERY='674' or (BATTERY='551' and CHARGER!='NO')))"]}
df_example = pd.DataFrame(data=dataex)

def transform_expr(input_expression):

    def move_not_before(x):
        if '!=' in x.group(1):
            return '~'+x.group(1).replace("!=","=")
        else:
            return x.group(1)

    expr1 = (re.sub("([a-zA-Z0-9'_]*!=[a-zA-Z0-9'_]*)", move_not_before,input_expression))

    variables = {}
    values = {}
    current_key = 0
    expr2 = ""
    last_idx = 0
    # Make transformations to reach a boolean form
    for idx in re.finditer("([a-zA-Z0-9'_]*=[a-zA-Z0-9'_]*)", expr1):
        expr2 += expr1[last_idx:idx.span(1)[0]]
        if idx[1] in values:
            expr2 += values[idx[1]]
        else:
            expr2 += f'v{current_key}'
            variables[f'v{current_key}']=idx[1]
            values[idx[1]] = f'v{current_key}'
            current_key+=1
        last_idx = idx.span(1)[1]
    expr2 += expr1[last_idx:]

    expr3 = re.sub("and", "&", expr2)
    expr4 = re.sub("or", "|", expr3)
    expr5 = expr(expr4).to_dnf()

    result = []
    # We know expr5 is like Or(And(...),And(...)...), xs has the children
    for v in expr5.xs:
        # We remove the And(...)
        if "," in str(v):
            arr = str(v)[4:-1].replace(" ","").split(",")
        else:
            # For cases in which you have only one variable
            arr = [str(v)]
        r = []
        for x in arr:
            if x[0]=="~":
                variable_name = x[1:]
            else:
                variable_name = x

            if variable_name not in variables:
                # How do we negate a standalone variable?
                if x[0]=="~":
                    variable_value = f"not({variable_name})"
                else:
                    variable_value = variable_name
            else:
                variable_value = variables[variable_name]

            if x[0]=="~":
                r.append(variable_value.replace("=","!="))
            else:
                r.append(variable_value)

        result.append(" and ".join(r))

    return result

df_example['Constraint'] = df_example['Constraint'].map(transform_expr)

df_result = df_example.explode('Constraint')

pd.set_option("max_colwidth", None)
print(df_result)

它将打印：

Component                                                         Constraint
0        123                                                            A and B
0        123                                                            A and C
1        456  MIRROR='ELECTRIC' and MIRRORCAMERA!='NO' and STEERWHEEL_LOCK='NO'
1        456    MIRROR='MANUAL' and MIRROR_RIGHT!='NO' and STEERWHEEL_LOCK='NO'
1        456     MIRROR='MANUAL' and MIRROR_LEFT!='NO' and STEERWHEEL_LOCK='NO'
2        789                                                       LENGTH='122'
2        789                                                       LENGTH='149'
2        789                                     LENGTH='135' and BATTERY='551'
2        789                                     LENGTH='181' and BATTERY='674'
2        789                   BATTERY='551' and LENGTH='181' and CHARGER!='NO'