Background:
I mostly run python scripts from the command line in pipelines and so my arguments are always strings that need to be type casted to the appropriate type.  I make a lot of little scripts each day and type casting each parameter for every script takes more time than it should.  
Question:
Is there a canonical way to automatically type cast parameters for a function?
My Way:
I've developed a decorator to do what I want if there isn't a better way.  The decorator is the autocast fxn below.  The decorated fxn is fxn2 in the example.  Note that at the end of the code block I passed 1 and 2 as strings and if you run the script it will automatically add them.  Is this a good way to do this? 
def estimateType(var):
    #first test bools
    if var == 'True':
            return True
    elif var == 'False':
            return False
    else:
            #int
            try:
                    return int(var)
            except ValueError:
                    pass
            #float
            try:
                    return float(var)
            except ValueError:
                    pass
            #string
            try:
                    return str(var)
            except ValueError:
                    raise NameError('Something Messed Up Autocasting var %s (%s)' 
                                      % (var, type(var)))
def autocast(dFxn):
    '''Still need to figure out if you pass a variable with kw args!!!
    I guess I can just pass the dictionary to the fxn **args?'''
    def wrapped(*c, **d):
            print c, d
            t = [estimateType(x) for x in c]
            return dFxn(*t)
    return wrapped
@autocast
def fxn2(one, two):
   print one + two 
fxn2('1', '2')      
EDIT: For anyone that comes here and wants the updated and concise working version go here:
https://github.com/sequenceGeek/cgAutoCast
And here is also quick working version based on above:
def boolify(s):
    if s == 'True' or s == 'true':
            return True
    if s == 'False' or s == 'false':
            return False
    raise ValueError('Not Boolean Value!')
def estimateType(var):
    '''guesses the str representation of the variables type'''
    var = str(var) #important if the parameters aren't strings...
    for caster in (boolify, int, float):
            try:
                    return caster(var)
            except ValueError:
                    pass
    return var
def autocast(dFxn):
    def wrapped(*c, **d):
            cp = [estimateType(x) for x in c]
            dp = dict( (i, estimateType(j)) for (i,j) in d.items())
            return dFxn(*cp, **dp)
    return wrapped
######usage######
@autocast
def randomFunction(firstVar, secondVar):
    print firstVar + secondVar
randomFunction('1', '2')
                If you want to auto-convert values:
def boolify(s):
    if s == 'True':
        return True
    if s == 'False':
        return False
    raise ValueError("huh?")
def autoconvert(s):
    for fn in (boolify, int, float):
        try:
            return fn(s)
        except ValueError:
            pass
    return s
You can adjust boolify to accept other boolean values if you like.
You could just use plain eval to input string if you trust the source:
>>> eval("3.2", {}, {})
3.2
>>> eval("True", {}, {})
True
But if you don't trust the source, you could use literal_eval from ast module.
>>> ast.literal_eval("'hi'")
'hi'
>>> ast.literal_eval("(5, 3, ['a', 'b'])")
(5, 3, ['a', 'b'])
Edit: As Ned Batchelder's comment, it won't accept non-quoted strings, so I added a workaround, also an example about autocaste decorator with keyword arguments.
import ast
def my_eval(s):
    try:
        return ast.literal_eval(s)
    except ValueError: #maybe it's a string, eval failed, return anyway
        return s       #thanks gnibbler
def autocaste(func):
    def wrapped(*c, **d):
        cp = [my_eval(x) for x in c]
        dp = {i: my_eval(j) for i,j in d.items()} #for Python 2.6+
        #you can use dict((i, my_eval(j)) for i,j in d.items()) for older versions
        return func(*cp, **dp)
    return wrapped
@autocaste
def f(a, b):
    return a + b
print(f("3.4", "1")) # 4.4
print(f("s", "sd"))  # ssd
print(my_eval("True")) # True
print(my_eval("None")) # None
print(my_eval("[1, 2, (3, 4)]")) # [1, 2, (3, 4)]
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