"X Not In" VS. "Not X In"

x not in vs. not x in

The two forms make identical bytecode, as you can clearly verify:

>>> import dis
>>> dis.dis(compile('if x not in d: pass', '', 'exec'))
  1           0 LOAD_NAME                0 (x)
              3 LOAD_NAME                1 (d)
              6 COMPARE_OP               7 (not in)
              9 JUMP_IF_FALSE            4 (to 16)
             12 POP_TOP             
             13 JUMP_FORWARD             1 (to 17)
        >>   16 POP_TOP             
        >>   17 LOAD_CONST               0 (None)
             20 RETURN_VALUE        
>>> dis.dis(compile('if not x in d: pass', '', 'exec'))
  1           0 LOAD_NAME                0 (x)
              3 LOAD_NAME                1 (d)
              6 COMPARE_OP               7 (not in)
              9 JUMP_IF_FALSE            4 (to 16)
             12 POP_TOP             
             13 JUMP_FORWARD             1 (to 17)
        >>   16 POP_TOP             
        >>   17 LOAD_CONST               0 (None)
             20 RETURN_VALUE        

so obviously they're semantically identical.

As a matter of style, PEP 8 does not mention the issue.

Personally, I strongly prefer the if x not in y form -- that makes it immediately clear that not in is a single operator, and "reads like English". if not x in y may mislead some readers into thinking it means if (not x) in y, reads a bit less like English, and has absolutely no compensating advantages.

x not in y or not x in y

They always give the same result.

In fact, not 'ham' in 'spam and eggs' appears to be special cased to perform a single "not in" operation, rather than an "in" operation and then negating the result:

>>> import dis

>>> def notin():
    'ham' not in 'spam and eggs'
>>> dis.dis(notin)
  2           0 LOAD_CONST               1 ('ham')
              3 LOAD_CONST               2 ('spam and eggs')
              6 COMPARE_OP               7 (not in)
              9 POP_TOP             
             10 LOAD_CONST               0 (None)
             13 RETURN_VALUE    

>>> def not_in():
    not 'ham' in 'spam and eggs'
>>> dis.dis(not_in)
  2           0 LOAD_CONST               1 ('ham')
              3 LOAD_CONST               2 ('spam and eggs')
              6 COMPARE_OP               7 (not in)
              9 POP_TOP             
             10 LOAD_CONST               0 (None)
             13 RETURN_VALUE    

>>> def not__in():
    not ('ham' in 'spam and eggs')
>>> dis.dis(not__in)
  2           0 LOAD_CONST               1 ('ham')
              3 LOAD_CONST               2 ('spam and eggs')
              6 COMPARE_OP               7 (not in)
              9 POP_TOP             
             10 LOAD_CONST               0 (None)
             13 RETURN_VALUE        

>>> def noteq():
    not 'ham' == 'spam and eggs'
>>> dis.dis(noteq)
  2           0 LOAD_CONST               1 ('ham')
              3 LOAD_CONST               2 ('spam and eggs')
              6 COMPARE_OP               2 (==)
              9 UNARY_NOT           
             10 POP_TOP             
             11 LOAD_CONST               0 (None)
             14 RETURN_VALUE      

I had thought at first that they always gave the same result, but that not on its own was simply a low precedence logical negation operator, which could be applied to a in b just as easily as any other boolean expression, whereas not in was a separate operator for convenience and clarity.

The disassembly above was revealing! It seems that while not obviously is a logical negation operator, the form not a in b is special cased so that it's not actually using the general operator. This makes not a in b literally the same expression as a not in b, rather than merely an expression that results in the same value.

Which is faster? if not x in OR if x not in

They are exactly the same, and thus take the same amount of time. not in is just syntactic sugar. Using the dis module, we can see that both result in the same bytecode:

>>> dis.dis("not x in y")
  1           0 LOAD_NAME                0 (x)
              2 LOAD_NAME                1 (y)
              4 COMPARE_OP               7 (not in)
              6 RETURN_VALUE
>>> dis.dis("x not in y")
  1           0 LOAD_NAME                0 (x)
              2 LOAD_NAME                1 (y)
              4 COMPARE_OP               7 (not in)
              6 RETURN_VALUE

Even adding parentheses as not (x in y) does not change that, unless, of course, you add more to the parentheses:

>>> dis.dis("not (x in y)")
  1           0 LOAD_NAME                0 (x)
              2 LOAD_NAME                1 (y)
              4 COMPARE_OP               7 (not in)
              6 RETURN_VALUE
>>> dis.dis("not (x in y or z)")
  1           0 LOAD_NAME                0 (x)
              2 LOAD_NAME                1 (y)
              4 COMPARE_OP               6 (in)
              6 JUMP_IF_TRUE_OR_POP     10
              8 LOAD_NAME                2 (z)
        >>   10 UNARY_NOT
             12 RETURN_VALUE

Tested with both, Python 3.6.7 and 2.7.15.

Check if something is (not) in a list in Python

The bug is probably somewhere else in your code, because it should work fine:

>>> 3 not in [2, 3, 4]
False
>>> 3 not in [4, 5, 6]
True

Or with tuples:

>>> (2, 3) not in [(2, 3), (5, 6), (9, 1)]
False
>>> (2, 3) not in [(2, 7), (7, 3), "hi"]
True

Python `if x is not None` or `if not x is None`?

There's no performance difference, as they compile to the same bytecode:

>>> import dis
>>> dis.dis("not x is None")
  1           0 LOAD_NAME                0 (x)
              2 LOAD_CONST               0 (None)
              4 COMPARE_OP               9 (is not)
              6 RETURN_VALUE
>>> dis.dis("x is not None")
  1           0 LOAD_NAME                0 (x)
              2 LOAD_CONST               0 (None)
              4 COMPARE_OP               9 (is not)
              6 RETURN_VALUE

Stylistically, I try to avoid not x is y, a human reader might misunderstand it as (not x) is y. If I write x is not y then there is no ambiguity.

Is there a difference between if not x and if x is None?

not x will also return True for everything that evaluates to False in a boolean context. Some examples:

>>> x = ()
>>> not x
True
>>> x = []
>>> not x
True
>>> x = ''
>>> not x
True    
>>> x = 0
>>> not x
True    
>>> x is None
False

So if your code should act differently when x is None as opposed to x being an empty list, tuple, string, the number zero, ... then use x == None or x is None instead of not x.

python if (X not in Y) or (Z not in Y) condition unexpected result

Try this code :

files = ["f1", "f2", "f3", "f4", "f1.txt", "f3.pdf"]
for f in files: 
     if f+".txt" not in files and f+".pdf" not in files:
         print(f)

Python if not == vs if !=

Using dis to look at the bytecode generated for the two versions:

not ==

  4           0 LOAD_FAST                0 (foo)
              3 LOAD_FAST                1 (bar)
              6 COMPARE_OP               2 (==)
              9 UNARY_NOT           
             10 RETURN_VALUE   

!=

  4           0 LOAD_FAST                0 (foo)
              3 LOAD_FAST                1 (bar)
              6 COMPARE_OP               3 (!=)
              9 RETURN_VALUE   

The latter has fewer operations, and is therefore likely to be slightly more efficient.

---

It was pointed out in the commments (thanks, @Quincunx) that where you have if foo != bar vs. if not foo == bar the number of operations is exactly the same, it's just that the COMPARE_OP changes and POP_JUMP_IF_TRUE switches to POP_JUMP_IF_FALSE:

not ==:

  2           0 LOAD_FAST                0 (foo)
              3 LOAD_FAST                1 (bar)
              6 COMPARE_OP               2 (==)
              9 POP_JUMP_IF_TRUE        16

!=

  2           0 LOAD_FAST                0 (foo)
              3 LOAD_FAST                1 (bar)
              6 COMPARE_OP               3 (!=)
              9 POP_JUMP_IF_FALSE       16

In this case, unless there was a difference in the amount of work required for each comparison, it's unlikely you'd see any performance difference at all.

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However, note that the two versions won't always be logically identical, as it will depend on the implementations of __eq__ and __ne__ for the objects in question. Per the data model documentation:

There are no implied relationships among the comparison operators. The
truth of x==y does not imply that x!=y is false.

For example:

>>> class Dummy(object):
    def __eq__(self, other):
        return True
    def __ne__(self, other):
        return True

>>> not Dummy() == Dummy()
False
>>> Dummy() != Dummy()
True

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Finally, and perhaps most importantly: in general, where the two are logically identical, x != y is much more readable than not x == y.

Difference between 'not x' and 'x==None' in python

yes it can give different answers.

x == None

will call the __eq__() method to valuate the operator and give the result implemented compared to the None singleton.

not x

will call the __nonzero__() (__bool__() in python3) method to valuate the operator. The interpreter will convert x to a boolean (bool(x)) using the mentioned method and then inverse its returned value because of the not operator.

x is None

means that the reference x points to the None object, which is a singleton of type NoneType and will valuate false in comparaisons. The is operator tests object identity, and thus whether or not the two objects compared are the same instance of an object, and not similar objects.

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