I Expect 'True' But Get 'None'

I expect 'True' but get 'None'

You don't ever return the return value of the recursive call:

if  x % n == 0:
    #print "passed {}".format(n)
    return recursive_factor_test(x,n-1)

When you omit the return statement there, your function ends without a return statement, thus falling back to the default None return value.

With the return there, it works:

>>> print recursive_factor_test(5040,7)
True

Use of True, False, and None as return values in Python functions

The advice isn't that you should never use True, False, or None. It's just that you shouldn't use if x == True.

if x == True is silly because == is just a binary operator! It has a return value of either True or False, depending on whether its arguments are equal or not. And if condition will proceed if condition is true. So when you write if x == True Python is going to first evaluate x == True, which will become True if x was True and False otherwise, and then proceed if the result of that is true. But if you're expecting x to be either True or False, why not just use if x directly!

Likewise, x == False can usually be replaced by not x.

There are some circumstances where you might want to use x == True. This is because an if statement condition is "evaluated in Boolean context" to see if it is "truthy" rather than testing exactly against True. For example, non-empty strings, lists, and dictionaries are all considered truthy by an if statement, as well as non-zero numeric values, but none of those are equal to True. So if you want to test whether an arbitrary value is exactly the value True, not just whether it is truthy, when you would use if x == True. But I almost never see a use for that. It's so rare that if you do ever need to write that, it's worth adding a comment so future developers (including possibly yourself) don't just assume the == True is superfluous and remove it.

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Using x is True instead is actually worse. You should never use is with basic built-in immutable types like Booleans (True, False), numbers, and strings. The reason is that for these types we care about values, not identity. == tests that values are the same for these types, while is always tests identities.

Testing identities rather than values is bad because an implementation could theoretically construct new Boolean values rather than go find existing ones, leading to you having two True values that have the same value, but they are stored in different places in memory and have different identities. In practice I'm pretty sure True and False are always reused by the Python interpreter so this won't happen, but that's really an implementation detail. This issue trips people up all the time with strings, because short strings and literal strings that appear directly in the program source are recycled by Python so 'foo' is 'foo' always returns True. But it's easy to construct the same string 2 different ways and have Python give them different identities. Observe the following:

>>> stars1 = ''.join('*' for _ in xrange(100))
>>> stars2 = '*' * 100
>>> stars1 is stars2
False
>>> stars1 == stars2
True

EDIT: So it turns out that Python's equality on Booleans is a little unexpected (at least to me):

>>> True is 1
False
>>> True == 1
True
>>> True == 2
False
>>> False is 0
False
>>> False == 0
True
>>> False == 0.0
True

The rationale for this, as explained in the notes when bools were introduced in Python 2.3.5, is that the old behaviour of using integers 1 and 0 to represent True and False was good, but we just wanted more descriptive names for numbers we intended to represent truth values.

One way to achieve that would have been to simply have True = 1 and False = 0 in the builtins; then 1 and True really would be indistinguishable (including by is). But that would also mean a function returning True would show 1 in the interactive interpreter, so what's been done instead is to create bool as a subtype of int. The only thing that's different about bool is str and repr; bool instances still have the same data as int instances, and still compare equality the same way, so True == 1.

So it's wrong to use x is True when x might have been set by some code that expects that "True is just another way to spell 1", because there are lots of ways to construct values that are equal to True but do not have the same identity as it:

>>> a = 1L
>>> b = 1L
>>> c = 1
>>> d = 1.0
>>> a == True, b == True, c == True, d == True
(True, True, True, True)
>>> a is b, a is c, a is d, c is d
(False, False, False, False)

And it's wrong to use x == True when x could be an arbitrary Python value and you only want to know whether it is the Boolean value True. The only certainty we have is that just using x is best when you just want to test "truthiness". Thankfully that is usually all that is required, at least in the code I write!

A more sure way would be x == True and type(x) is bool. But that's getting pretty verbose for a pretty obscure case. It also doesn't look very Pythonic by doing explicit type checking... but that really is what you're doing when you're trying to test precisely True rather than truthy; the duck typing way would be to accept truthy values and allow any user-defined class to declare itself to be truthy.

If you're dealing with this extremely precise notion of truth where you not only don't consider non-empty collections to be true but also don't consider 1 to be true, then just using x is True is probably okay, because presumably then you know that x didn't come from code that considers 1 to be true. I don't think there's any pure-python way to come up with another True that lives at a different memory address (although you could probably do it from C), so this shouldn't ever break despite being theoretically the "wrong" thing to do.

And I used to think Booleans were simple!

End Edit

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In the case of None, however, the idiom is to use if x is None. In many circumstances you can use if not x, because None is a "falsey" value to an if statement. But it's best to only do this if you're wanting to treat all falsey values (zero-valued numeric types, empty collections, and None) the same way. If you are dealing with a value that is either some possible other value or None to indicate "no value" (such as when a function returns None on failure), then it's much better to use if x is None so that you don't accidentally assume the function failed when it just happened to return an empty list, or the number 0.

My arguments for using == rather than is for immutable value types would suggest that you should use if x == None rather than if x is None. However, in the case of None Python does explicitly guarantee that there is exactly one None in the entire universe, and normal idiomatic Python code uses is.

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Regarding whether to return None or raise an exception, it depends on the context.

For something like your get_attr example I would expect it to raise an exception, because I'm going to be calling it like do_something_with(get_attr(file)). The normal expectation of the callers is that they'll get the attribute value, and having them get None and assume that was the attribute value is a much worse danger than forgetting to handle the exception when you can actually continue if the attribute can't be found. Plus, returning None to indicate failure means that None is not a valid value for the attribute. This can be a problem in some cases.

For an imaginary function like see_if_matching_file_exists, that we provide a pattern to and it checks several places to see if there's a match, it could return a match if it finds one or None if it doesn't. But alternatively it could return a list of matches; then no match is just the empty list (which is also "falsey"; this is one of those situations where I'd just use if x to see if I got anything back).

So when choosing between exceptions and None to indicate failure, you have to decide whether None is an expected non-failure value, and then look at the expectations of code calling the function. If the "normal" expectation is that there will be a valid value returned, and only occasionally will a caller be able to work fine whether or not a valid value is returned, then you should use exceptions to indicate failure. If it will be quite common for there to be no valid value, so callers will be expecting to handle both possibilities, then you can use None.

Defining a Function in python 3.6 and expecting True or False but returning None

In python every function returns None if you do not return anything. Check your if .. .elif ... else - where does the else return anything?

It does not - it just calls gender() (and then implicitly returns None)

Change it to return the return of that function call:

 if gener == '1':
    print('You selected Male')
    return True
elif gener == '2':
    print('You selected Female')
    return False
else:
    print('Invalid character')
    return gender()

This would fix your code, to make it better do not use recursion.

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Using unneded recursion will pack new data onto call stacks all the time. You can optimize it by using a loop instead of recursing:

def gender():
    """Choose Male or Femal, return True for Male and False for Female"""

    gener = ""   # prepare an invalid input
    while gener not in ['1','2']:  # loop until input gets valid
        gener = input('Choose "1" for Male or "2" for Female: ')

    if gener == '1':
        print('You selected Male')
        return True
    # elif gener == '2':
    #    print('You selected Female')
    #    return False
    else: # no need for explicit check, it can only be 1 or 2 
        print('You selected Female')
        return False

print(gender())

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Sidenote for political correctness:

• not all humans on earth term themself as male or female
• not all humans on earth wan't to make this decision known
• gender might change over a livetime

Python Returns none instead of True or False

Don't bother with strings at all; it's an order of magnitude faster to divide by 10 twice.

def isSiete(num):
    return num // 10 % 10 == 7

The arithmetic gets slower as the size of num increases, but this is still faster when num is a 17-digit number.

Why does my recursive function return None?

It is returning None because when you recursively call it:

if my_var != "a" and my_var != "b":
    print('You didn\'t type "a" or "b". Try again.')
    get_input()

..you don't return the value.

So while the recursion does happen, the return value gets discarded, and then you fall off the end of the function. Falling off the end of the function means that python implicitly returns None, just like this:

>>> def f(x):
...     pass
>>> print(f(20))
None

So, instead of just calling get_input() in your if statement, you need to return what the recursive call returns:

if my_var != "a" and my_var != "b":
    print('You didn\'t type "a" or "b". Try again.')
    return get_input()

Why does pandas None | True return False when Python None or True returns True?

Pandas | operator does not rely on Python or expression, and behaves differently.

If both operands are boolean, the result is mathematically defined, and the same for Python and Pandas.

But in your case series "buybox" is of type object, and "buybox_y" is bool. In this case Pandas | operator is not commutative:

• right operand is coerced to boolean
• then bitwise or is attempted
  
  • None | True is invalid operation, resulting in None
• and result is coerced to boolean

Thus,

>>> df['buybox'] | df['buybox_y']
0  False

>>> df['buybox_y'] | df['buybox']
0  True

For predictable results, you can clean up data, and cast to boolean type with Pandas astype before attempting boolean operations.

request.GET.get(' ') returns None

URL kwargs are not in request, but in class itself. Try self.kwargs.get('job_title'). If it's not in your ApplicationForm, you can pass them from get_form_kwargs method same as you passed Request

Getting asserting the value None error when unit testing with Pytest

I believe that this error occurs because of the function pandas.testing.assert_frame_equal returns None if frames are equal; if they're unequal it raises AssertionError. Therefore you're actually checking assert None.

So I think you should remove assert operator here and just write

testing.assert_frame_equal(expected, result)

Or write

assert testing.assert_frame_equal(expected, result) is None

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