Python's "object-based" subset is roughly equivalent to JavaScript. Like JavaScript (and unlike Java), Python supports a programming style that uses simple functions and variables without engaging in class definitions. However, for JavaScript, that's all there is.
https://wiki.python.org/moin/TimeComplexity. In C++ you can use std::find to determine whether or not an item is contained in a std::vector .
The 'not' is a Logical operator in Python that will return True if the expression is False. The 'not' operator is used in the if statements. For example: if not x. If x is True, then not will evaluate as false, otherwise, True.
You would want and
instead of &&
.
Python uses and
and or
conditionals.
i.e.
if foo == 'abc' and bar == 'bac' or zoo == '123':
# do something
I'm getting an error in the IF conditional. What am I doing wrong?
There reason that you get a SyntaxError
is that there is no &&
operator in Python. Likewise ||
and !
are not valid Python operators.
Some of the operators you may know from other languages have a different name in Python.
The logical operators &&
and ||
are actually called and
and or
.
Likewise the logical negation operator !
is called not
.
So you could just write:
if len(a) % 2 == 0 and len(b) % 2 == 0:
or even:
if not (len(a) % 2 or len(b) % 2):
I summarized the operator "equivalents" in this table:
+------------------------------+---------------------+
| Operator (other languages) | Operator (Python) |
+==============================+=====================+
| && | and |
+------------------------------+---------------------+
| || | or |
+------------------------------+---------------------+
| ! | not |
+------------------------------+---------------------+
See also Python documentation: 6.11. Boolean operations.
Besides the logical operators Python also has bitwise/binary operators:
+--------------------+--------------------+
| Logical operator | Bitwise operator |
+====================+====================+
| and | & |
+--------------------+--------------------+
| or | | |
+--------------------+--------------------+
There is no bitwise negation in Python (just the bitwise inverse operator ~
- but that is not equivalent to not
).
See also 6.6. Unary arithmetic and bitwise/binary operations and 6.7. Binary arithmetic operations.
The logical operators (like in many other languages) have the advantage that these are short-circuited. That means if the first operand already defines the result, then the second operator isn't evaluated at all.
To show this I use a function that simply takes a value, prints it and returns it again. This is handy to see what is actually evaluated because of the print statements:
>>> def print_and_return(value):
... print(value)
... return value
>>> res = print_and_return(False) and print_and_return(True)
False
As you can see only one print statement is executed, so Python really didn't even look at the right operand.
This is not the case for the binary operators. Those always evaluate both operands:
>>> res = print_and_return(False) & print_and_return(True);
False
True
But if the first operand isn't enough then, of course, the second operator is evaluated:
>>> res = print_and_return(True) and print_and_return(False);
True
False
To summarize this here is another Table:
+-----------------+-------------------------+
| Expression | Right side evaluated? |
+=================+=========================+
| `True` and ... | Yes |
+-----------------+-------------------------+
| `False` and ... | No |
+-----------------+-------------------------+
| `True` or ... | No |
+-----------------+-------------------------+
| `False` or ... | Yes |
+-----------------+-------------------------+
The True
and False
represent what bool(left-hand-side)
returns, they don't have to be True
or False
, they just need to return True
or False
when bool
is called on them (1).
So in Pseudo-Code(!) the and
and or
functions work like these:
def and(expr1, expr2):
left = evaluate(expr1)
if bool(left):
return evaluate(expr2)
else:
return left
def or(expr1, expr2):
left = evaluate(expr1)
if bool(left):
return left
else:
return evaluate(expr2)
Note that this is pseudo-code not Python code. In Python you cannot create functions called and
or or
because these are keywords.
Also you should never use "evaluate" or if bool(...)
.
This implicit bool
call can be used to customize how your classes behave with and
, or
and not
.
To show how this can be customized I use this class which again print
s something to track what is happening:
class Test(object):
def __init__(self, value):
self.value = value
def __bool__(self):
print('__bool__ called on {!r}'.format(self))
return bool(self.value)
__nonzero__ = __bool__ # Python 2 compatibility
def __repr__(self):
return "{self.__class__.__name__}({self.value})".format(self=self)
So let's see what happens with that class in combination with these operators:
>>> if Test(True) and Test(False):
... pass
__bool__ called on Test(True)
__bool__ called on Test(False)
>>> if Test(False) or Test(False):
... pass
__bool__ called on Test(False)
__bool__ called on Test(False)
>>> if not Test(True):
... pass
__bool__ called on Test(True)
If you don't have a __bool__
method then Python also checks if the object has a __len__
method and if it returns a value greater than zero.
That might be useful to know in case you create a sequence container.
See also 4.1. Truth Value Testing.
Probably a bit beyond the scope of the original question but in case you're dealing with NumPy arrays or subclasses (like Pandas Series or DataFrames) then the implicit bool
call
will raise the dreaded ValueError
:
>>> import numpy as np
>>> arr = np.array([1,2,3])
>>> bool(arr)
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
>>> arr and arr
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
>>> import pandas as pd
>>> s = pd.Series([1,2,3])
>>> bool(s)
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
>>> s and s
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
In these cases you can use the logical and function from NumPy which performs an element-wise and
(or or
):
>>> np.logical_and(np.array([False,False,True,True]), np.array([True, False, True, False]))
array([False, False, True, False])
>>> np.logical_or(np.array([False,False,True,True]), np.array([True, False, True, False]))
array([ True, False, True, True])
If you're dealing just with boolean arrays you could also use the binary operators with NumPy, these do perform element-wise (but also binary) comparisons:
>>> np.array([False,False,True,True]) & np.array([True, False, True, False])
array([False, False, True, False])
>>> np.array([False,False,True,True]) | np.array([True, False, True, False])
array([ True, False, True, True])
(1)
That the bool
call on the operands has to return True
or False
isn't completely correct. It's just the first operand that needs to return a boolean in it's __bool__
method:
class Test(object):
def __init__(self, value):
self.value = value
def __bool__(self):
return self.value
__nonzero__ = __bool__ # Python 2 compatibility
def __repr__(self):
return "{self.__class__.__name__}({self.value})".format(self=self)
>>> x = Test(10) and Test(10)
TypeError: __bool__ should return bool, returned int
>>> x1 = Test(True) and Test(10)
>>> x2 = Test(False) and Test(10)
That's because and
actually returns the first operand if the first operand evaluates to False
and if it evaluates to True
then it returns the second operand:
>>> x1
Test(10)
>>> x2
Test(False)
Similarly for or
but just the other way around:
>>> Test(True) or Test(10)
Test(True)
>>> Test(False) or Test(10)
Test(10)
However if you use them in an if
statement the if
will also implicitly call bool
on the result. So these finer points may not be relevant for you.
Two comments:
and
and or
for logical operations in Python.If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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