dict(实际上是defaultdict)为你提供了一种非常简单的方法:

from collections import defaultdict
bool_mapping = defaultdict(bool) # Will give you False for non-found values
for val in ['True', 'yes', ...]:
    bool_mapping[val] = True

print(bool_mapping['True']) # True
print(bool_mapping['kitten']) # False

将这个方法定制为您想要的确切转换行为非常容易——您可以用允许的Truthy和Falsy值填充它，并在没有找到值时让它引发异常(或返回None)，或默认为True，或默认为False，或任何您想要的。

您可能已经有了一个解决方案，但对于其他人来说，他们正在寻找一种方法，将值转换为布尔值，使用“标准”假值，包括None，[]，{}和“”，除了false, no和0。

def toBoolean( val ):
    """ 
    Get the boolean value of the provided input.

        If the value is a boolean return the value.
        Otherwise check to see if the value is in 
        ["false", "f", "no", "n", "none", "0", "[]", "{}", "" ]
        and returns True if value is not in the list
    """

    if val is True or val is False:
        return val

    falseItems = ["false", "f", "no", "n", "none", "0", "[]", "{}", "" ]

    return not str( val ).strip().lower() in falseItems

def str2bool(v):
  return v.lower() in ("yes", "true", "t", "1")

然后像这样称呼它:

>>> str2bool("yes")
True
>>> str2bool("no")
False
>>> str2bool("stuff")
False
>>> str2bool("1")
True
>>> str2bool("0")
False

显式处理true和false:

您还可以使函数显式地检查True单词列表和False单词列表。然后，如果它不在两个列表中，则可以抛出异常。

从Python 2.6开始，你可以使用ast.literal_eval:

>>> import ast
>>> help(ast.literal_eval)
Help on function literal_eval in module ast:

literal_eval(node_or_string)
    Safely evaluate an expression node or a string containing a Python
    expression.  The string or node provided may only consist of the following
    Python literal structures: strings, numbers, tuples, lists, dicts, booleans,
    and None.

这似乎是可行的，只要你确定你的字符串将是“True”或“False”:

>>> ast.literal_eval("True")
True
>>> ast.literal_eval("False")
False
>>> ast.literal_eval("F")
Traceback (most recent call last):
  File "", line 1, in 
  File "/opt/Python-2.6.1/lib/python2.6/ast.py", line 68, in literal_eval
    return _convert(node_or_string)
  File "/opt/Python-2.6.1/lib/python2.6/ast.py", line 67, in _convert
    raise ValueError('malformed string')
ValueError: malformed string
>>> ast.literal_eval("'False'")
'False'

我通常不建议这样做，但它是完全内置的，可以根据您的需求来选择。

在有限的情况或情况下，您可以对正在处理的数据做出强有力的假设。然而，由于自定义对象可以覆盖Python中的__eq__相等性检查，因此存在一个重要的陷阱。看看下面这个刻意简化的玩具例子:

In [1]: class MyString: 
   ...:     def __init__(self, value): 
   ...:         self.value = value 
   ...:     def __eq__ (self, obj): 
   ...:         if hasattr(obj, 'value'): 
   ...:             return obj.value == self.value 
   ...:         return False 
   ...:                                                                                                                                           

In [2]: v = MyString("True")                                                                                                                      

In [3]: v == "True"                                                                                                                               
Out[3]: False

如果你想象有人继承了MyString的字符串类型，或者实现了各种原生字符串方法，repr等，这样MyString实例的行为就和字符串完全一样，但是在相等性检查中有特殊的额外值步骤，那么简单地使用== 'True'将会失败，而且从用户的角度来看，这很可能是一个无声的失败。

这就是为什么将type强制转换为您想要执行的相等性检查的确切性质，将其封装到一个helper函数中，并对依赖这种“已注册”的方式进行验证是一种很好的实践。例如，在MyString中，你可以这样写，

def validate(s):
    if isinstance(s, str):
        return s == 'True'
    elif isinstance(s, MyString):
        return s.value == 'True' # <-- business logic
    ...
    raise ValueError(f"Type {type(s)} not supported for validation.")

或者另一种常用的模式是反向透视图，其中您只为验证定义了一种行为，但是您有一个helper函数，它将强制转换为适合于该单一验证行为的类型，例如

def to_str(s):
    if isinstance(s, str):
        return s
    elif isinstance(s, MyString):
        return s.value
    ...
    raise ValueError(f"Unsupported type {type(s)}")

def validate(s):
    return to_str(s) == 'True'
    

It might look like we're adding a lot of boilerplate and verbosity. We could glibly express critique by saying, "why write all that if you can just write s == 'True'?" - But it misses the point that when you are validating something, you need to make sure all of your preconditions hold for the validation logic to be applied. If you can assume some data is a plain str type and you don't need to do any of that precondition (such as type) checking, great - but that's a very rare situation and it can be misleading to characterize the general situation for this question as being amenable to one super short and concise equality check.

该版本保留了int(value)等构造函数的语义，并提供了一种简单的方法来定义可接受的字符串值。

def to_bool(value):
    valid = {'true': True, 't': True, '1': True,
             'false': False, 'f': False, '0': False,
             }   

    if isinstance(value, bool):
        return value

    if not isinstance(value, basestring):
        raise ValueError('invalid literal for boolean. Not a string.')

    lower_value = value.lower()
    if lower_value in valid:
        return valid[lower_value]
    else:
        raise ValueError('invalid literal for boolean: "%s"' % value)


# Test cases
assert to_bool('true'), '"true" is True' 
assert to_bool('True'), '"True" is True' 
assert to_bool('TRue'), '"TRue" is True' 
assert to_bool('TRUE'), '"TRUE" is True' 
assert to_bool('T'), '"T" is True' 
assert to_bool('t'), '"t" is True' 
assert to_bool('1'), '"1" is True' 
assert to_bool(True), 'True is True' 
assert to_bool(u'true'), 'unicode "true" is True'

assert to_bool('false') is False, '"false" is False' 
assert to_bool('False') is False, '"False" is False' 
assert to_bool('FAlse') is False, '"FAlse" is False' 
assert to_bool('FALSE') is False, '"FALSE" is False' 
assert to_bool('F') is False, '"F" is False' 
assert to_bool('f') is False, '"f" is False' 
assert to_bool('0') is False, '"0" is False' 
assert to_bool(False) is False, 'False is False'
assert to_bool(u'false') is False, 'unicode "false" is False'

# Expect ValueError to be raised for invalid parameter...
try:
    to_bool('')
    to_bool(12)
    to_bool([])
    to_bool('yes')
    to_bool('FOObar')
except ValueError, e:
    pass