Why does assertFalse succeed on None?
import unittest
class TestNoneIsFalse(unittest.TestCase):
def test_none_is_false(self):
self.assertFalse(None)
Results:
> python -m unittest temp
.
----------------------------------------------------------------------
Ran 1 test in 0.001s
OK
It seems as if this behaviour invites errors where a function does not always return a value. For example:
def is_lower_than_5(x):
if x < 5:
return True
elif x > 5:
return False
....
def test_5_is_not_lower_than_5(self):
self.assertFalse(is_lower_than_5(5))
The above test would pass even though it should fail. It is missing an error in the code that should be caught.
How should we assert that the value is literally False and not merely false in a boolean context? e.g.
self.assertEquals(False, None) # assert fails. good!
None is falsy, as well as 0, "", [], ...
assertFalse does not check whether the given value is False by identity. This behavior is consistent with the if statement:
if not None:
print('falsy value!')
Similarly, assertTrue does not check whether a value is True, and as such values like 1, "abc", [1, 2, 3] pass the test. See Truth Value Testing for more information.
This behavior is also explicitly documented:
assertTrue(expr, msg=None)
assertFalse(expr, msg=None)
Test that expr is true (or false).
Note that this is equivalent to bool(expr) is True and not to expr is True
If you really want to be sure that a value is True or False, use assertIs.
Your case is actually pointed out in the documentation:
Note that this is equivalent to bool(expr) is True and not to expr is
True (use assertIs(expr, True) for the latter).
Source: https://docs.python.org/2/library/unittest.html#unittest.TestCase.assertFalse
Python default return value for functions is None.
Python also implements Duck typing, so some values are threated as falsey, those are
empty string
integer zero
boolean False
empty list
empty tuple
So yes, you should implement it as self.assertEquals(False, None) if you want to explicitly check the False boolean value. This is not a good idea, in python you can just do
if my_value:
print 'truthy value'
else:
print 'falsey value'
You could design your test cases using boundary-value analysis to check your corner cases.
Related
I just learned there are truthy and falsy values in python which are different from the normal True and False.
Can someone please explain in depth what truthy and falsy values are? Where should I use them? What is the difference between truthy and True values and falsy and False values?
We use "truthy" and "falsy" to differentiate from the bool values True and False. A "truthy" value will satisfy the check performed by if or while statements. As explained in the documentation, all values are considered "truthy" except for the following, which are "falsy":
None
False
Numbers that are numerically equal to zero, including:
0
0.0
0j
decimal.Decimal(0)
fraction.Fraction(0, 1)
Empty sequences and collections, including:
[] - an empty list
{} - an empty dict
() - an empty tuple
set() - an empty set
'' - an empty str
b'' - an empty bytes
bytearray(b'') - an empty bytearray
memoryview(b'') - an empty memoryview
an empty range, like range(0)
objects for which
obj.__bool__() returns False
obj.__len__() returns 0, given that obj.__bool__ is undefined
As the comments described, it just refers to values which are evaluated to True or False.
For instance, to see if a list is not empty, instead of checking like this:
if len(my_list) != 0:
print("Not empty!")
You can simply do this:
if my_list:
print("Not empty!")
This is because some values, such as empty lists, are considered False when evaluated for a boolean value. Non-empty lists are True.
Similarly for the integer 0, the empty string "", and so on, for False, and non-zero integers, non-empty strings, and so on, for True.
The idea of terms like "truthy" and "falsy" simply refer to those values which are considered True in cases like those described above, and those which are considered False.
For example, an empty list ([]) is considered "falsy", and a non-empty list (for example, [1]) is considered "truthy".
See also this section of the documentation.
Python determines the truthiness by applying bool() to the type, which returns True or False which is used in an expression like if or while.
Here is an example for a custom class Vector2dand it's instance returning False when the magnitude (lenght of a vector) is 0, otherwise True.
import math
class Vector2d(object):
def __init__(self, x, y):
self.x = float(x)
self.y = float(y)
def __abs__(self):
return math.hypot(self.x, self.y)
def __bool__(self):
return bool(abs(self))
a = Vector2d(0,0)
print(bool(a)) #False
b = Vector2d(10,0)
print(bool(b)) #True
Note: If we wouldn't have defined __bool__ it would always return True, as instances of a user-defined class are considered truthy by default.
Example from the book: "Fluent in Python, clear, concise and effective programming"
Truthy values refer to the objects used in a boolean context and not so much the boolean value that returns true or false.Take these as an example:
>>> bool([])
False
>>> bool([1])
True
>>> bool('')
False
>>> bool('hello')
True
Where should you use Truthy or Falsy values ?
These are syntactic sugar, so you can always avoid them, but using them can make your code more readable and make you more efficient.
Moreover, you will find them in many code examples, whether in python or not, because it is considered good practice.
As mentioned in the other answers, you can use them in if tests and while loops. Here are two other examples in python 3 with default values combined with or, s being a string variable. You will extend to similar situations as well.
Without truthy
if len(s) > 0:
print(s)
else:
print('Default value')
with truthy it is more concise:
print(s or 'Default value')
In python 3.8, we can take advantage of the assignment expression :=
without truthy
if len(s) == 0:
s = 'Default value'
do_something(s)
with truthy it is shorter too
s or (s := 'Default value')
do_something(s)
or even shorter,
do_something(s or (s := 'Default value'))
Without the assignment expression, one can do
s = s or 'Default value'
do_something(s)
but not shorter. Some people find the s =... line unsatisfactory because it corresponds to
if len(s)>0:
s = s # HERE is an extra useless assignment
else:
s = "Default value"
nevertheless you can adhere to this coding style if you feel comfortable with it.
Any object in Python can be tested for its truth value. It can be used in an if or while condition or as operand of the Boolean operations.
The following values are considered False:
None
False
zero of any numeric type, for example, 0, 0L, 0.0, 0j.
any empty sequence, for example, '', (), [].
any empty mapping, for example, {}.
instances of user-defined classes, if the class defines a __nonzero__() or __len__() method, when that method returns the integer zero or bool value False.
All other values are considered True -- thus objects of many types are always true.
Operations and built-in functions that have a Boolean result always return 0 or False for false and 1 or True for true, unless otherwise stated.
In case of if (!id) {}
!expr returns false if its single operand can be converted to true; otherwise, returns true.
If a value can be converted to true, the value is so-called truthy. If a value can be converted to false, the value is so-called falsy.
Examples of expressions that can be converted to false are:
null;
NaN;
0;
empty string ("" or '' or ``);
undefined.
Even though the ! operator can be used with operands that are not Boolean values, it can still be considered a boolean operator since its return value can always be converted to a boolean primitive. To explicitly convert its return value (or any expression in general) to the corresponding boolean value, use a double NOT operator or the Boolean constructor.
Example:
n1 = !null // !t returns true
n2 = !NaN // !f returns true
n3 = !'' // !f returns true
n4 = !'Cat' // !t returns false
While in case of if (id != null) {} it will only check if the value in id is not equal to null
reference https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Logical_NOT
Falsy means something empty like empty list,tuple, as any datatype having empty values or None.
Truthy means :
Except are Truthy
Apologies if this has been asked before, but I have searched in vain for an answer to my exact question. Basically, with Python 2.7, I have a program running a series of geoprocessing tools, depended on what is reqested via a series of True/False variables that the user adjusts in the script e.g.
x = True
if x:
run function
However, I have now discovered that x does not need to be literally "True" for the function to run. For example:
In: x = True
if x:
print True
Out: True
In: x = 123
if x:
print True
Out: True
In: x = 'False'
if x:
print True
Out: True
In: x = False
if x:
print True
Out:
So any value other than False appears to evaluate to True, which would not be the case for if x == True or if x is True. Seeing as PEP 8 strongly recommends only using the if x: variant, can anybody explain why this behaviour occurs? It seems that if x: is more a test for "if x is not False" or "if x exists". With that in mind, I believe I should be using if x is True: in this case, despite what PEP 8 has to say.
The following values in Python are false in the context of if and other logical contexts:
False
None
numeric values equal to 0, such as 0, 0.0, -0.0
empty strings: '' and u''
empty containers (such as lists, tuples and dictionaries)
anything that implements __bool__ (in Python3) to return False, or __nonzero__ (in Python2) to return False or 0.
anything that doesn't implement __bool__ (in Python3) or __nonzero__ (in Python2), but does implement __len__ to return a value equal to 0
An object is considered "false" if any of those applies, and "true" otherwise, regardless of whether it's actually equal to or identical with False or True
Now, if you've arranged that x is necessarily one of the objects True or False, then you can safely write if x. If you've arranged that the "trueness" of x indicates whether or not to perform the operation, regardless of type, then you can safely write if x. Where you can write that you should prefer to do so, since it's cleaner to read.
Normally, if it is allowed for x to take the value True then you're in one of those two cases, and so you would not write if x is True. The important thing is to correctly document the meaning of x, so that it reflects the test used in the code.
Python programmers are expected to know what's considered true, so if you just document, "runs the function if x is true", then that expresses what your original code does. Documenting it, "runs the function if x is True" would have a different meaning, and is less commonly used precisely because of the style rule in PEP8 that says to test for trueness rather than the specific value True.
However, if you wanted the code to behave differently in the case where x is an empty container from the case where it is None, then you would write something like if x is not None.
I'd like to add a short example where those 3 tests differ:
def test(x):
print(x, ":", bool(x), x == True, x is True)
test("something")
test(1)
test(True)
The output (pretty formatted):
# "something" : True False False
# 1 : True True False
# True : True True True
x = 'False'
x = 123
Are both True
Other truth values.
The document explains other values.
As far as the PEP8 reason, its far more semantic to read if this_file_is_green
Other falsey values include 0, '', []. You should just use the if x: version.
It goes without saying that you should write code that does what you need. But in most cases, you simply don't need to say == True or is True, because you don't need to distinguish True from other "truthy" values. So it's recommended to leave that out for simplicity.
The case where you definitely should use == True or is True is when you do need to distinguish True from other truthy values.
In your example, do you care about the difference between True and 123? That would tell you which way to code it.
One thing about coding == True or is True: it will raise a minor red flag when other developers read your code. They won't think it's wrong, they will just wonder why it's there and will want to know why it's important to treat True differently from other truthy values in this particular case.
In other words, if you don't need it, it's best not to use it.
The ability to say
if x:
...
is considered a feature. You can also specify when the test should be considered to pass or not for user defined classes (just define the method __nonzero__ in Python 2.x or __bool__ in Python 3).
For example for strings and containers like lists, dictionaries or sets the test if x ... means "if x is not empty".
Note that the rationale is not that this allows less code to write, but that resulting code is easier to read and to understand.
If you like instead to write if x is True ... have you considered to go farther down that path to if (x is True) is True ... or if ((x is True) is True) is True ... ? :-)
In Python 2.7, if a: and if a==True are not giving the same output for values different to 1. Here are some snippets of code to demonstrate the different behaviors:
with a=1
a=1
if a==True:
print (a,"True")
else:
print (a,"Not True")
output> (1,True)
a=1
if a:
print (a,"True")
else:
print (a,"Not True")
output> (1, True)
with a=2
a=2
if a:
print (a,"True")
else:
print (a,"Not True")
output> (2, True)
a=2
if a==True:
print (a,"True")
else:
print (a,"Not True")
output> (2, Not True)
if you use if x ,it means it has to evaluate x for its truth value.But when you use x ==True or x is True.It means checking whether type(x)==bool and whether x is True.
attention : x is True is no equal to bool(x)==True
when you use x is True , you are checking the id of x and True.
I just learned there are truthy and falsy values in python which are different from the normal True and False.
Can someone please explain in depth what truthy and falsy values are? Where should I use them? What is the difference between truthy and True values and falsy and False values?
We use "truthy" and "falsy" to differentiate from the bool values True and False. A "truthy" value will satisfy the check performed by if or while statements. As explained in the documentation, all values are considered "truthy" except for the following, which are "falsy":
None
False
Numbers that are numerically equal to zero, including:
0
0.0
0j
decimal.Decimal(0)
fraction.Fraction(0, 1)
Empty sequences and collections, including:
[] - an empty list
{} - an empty dict
() - an empty tuple
set() - an empty set
'' - an empty str
b'' - an empty bytes
bytearray(b'') - an empty bytearray
memoryview(b'') - an empty memoryview
an empty range, like range(0)
objects for which
obj.__bool__() returns False
obj.__len__() returns 0, given that obj.__bool__ is undefined
As the comments described, it just refers to values which are evaluated to True or False.
For instance, to see if a list is not empty, instead of checking like this:
if len(my_list) != 0:
print("Not empty!")
You can simply do this:
if my_list:
print("Not empty!")
This is because some values, such as empty lists, are considered False when evaluated for a boolean value. Non-empty lists are True.
Similarly for the integer 0, the empty string "", and so on, for False, and non-zero integers, non-empty strings, and so on, for True.
The idea of terms like "truthy" and "falsy" simply refer to those values which are considered True in cases like those described above, and those which are considered False.
For example, an empty list ([]) is considered "falsy", and a non-empty list (for example, [1]) is considered "truthy".
See also this section of the documentation.
Python determines the truthiness by applying bool() to the type, which returns True or False which is used in an expression like if or while.
Here is an example for a custom class Vector2dand it's instance returning False when the magnitude (lenght of a vector) is 0, otherwise True.
import math
class Vector2d(object):
def __init__(self, x, y):
self.x = float(x)
self.y = float(y)
def __abs__(self):
return math.hypot(self.x, self.y)
def __bool__(self):
return bool(abs(self))
a = Vector2d(0,0)
print(bool(a)) #False
b = Vector2d(10,0)
print(bool(b)) #True
Note: If we wouldn't have defined __bool__ it would always return True, as instances of a user-defined class are considered truthy by default.
Example from the book: "Fluent in Python, clear, concise and effective programming"
Truthy values refer to the objects used in a boolean context and not so much the boolean value that returns true or false.Take these as an example:
>>> bool([])
False
>>> bool([1])
True
>>> bool('')
False
>>> bool('hello')
True
Where should you use Truthy or Falsy values ?
These are syntactic sugar, so you can always avoid them, but using them can make your code more readable and make you more efficient.
Moreover, you will find them in many code examples, whether in python or not, because it is considered good practice.
As mentioned in the other answers, you can use them in if tests and while loops. Here are two other examples in python 3 with default values combined with or, s being a string variable. You will extend to similar situations as well.
Without truthy
if len(s) > 0:
print(s)
else:
print('Default value')
with truthy it is more concise:
print(s or 'Default value')
In python 3.8, we can take advantage of the assignment expression :=
without truthy
if len(s) == 0:
s = 'Default value'
do_something(s)
with truthy it is shorter too
s or (s := 'Default value')
do_something(s)
or even shorter,
do_something(s or (s := 'Default value'))
Without the assignment expression, one can do
s = s or 'Default value'
do_something(s)
but not shorter. Some people find the s =... line unsatisfactory because it corresponds to
if len(s)>0:
s = s # HERE is an extra useless assignment
else:
s = "Default value"
nevertheless you can adhere to this coding style if you feel comfortable with it.
Any object in Python can be tested for its truth value. It can be used in an if or while condition or as operand of the Boolean operations.
The following values are considered False:
None
False
zero of any numeric type, for example, 0, 0L, 0.0, 0j.
any empty sequence, for example, '', (), [].
any empty mapping, for example, {}.
instances of user-defined classes, if the class defines a __nonzero__() or __len__() method, when that method returns the integer zero or bool value False.
All other values are considered True -- thus objects of many types are always true.
Operations and built-in functions that have a Boolean result always return 0 or False for false and 1 or True for true, unless otherwise stated.
In case of if (!id) {}
!expr returns false if its single operand can be converted to true; otherwise, returns true.
If a value can be converted to true, the value is so-called truthy. If a value can be converted to false, the value is so-called falsy.
Examples of expressions that can be converted to false are:
null;
NaN;
0;
empty string ("" or '' or ``);
undefined.
Even though the ! operator can be used with operands that are not Boolean values, it can still be considered a boolean operator since its return value can always be converted to a boolean primitive. To explicitly convert its return value (or any expression in general) to the corresponding boolean value, use a double NOT operator or the Boolean constructor.
Example:
n1 = !null // !t returns true
n2 = !NaN // !f returns true
n3 = !'' // !f returns true
n4 = !'Cat' // !t returns false
While in case of if (id != null) {} it will only check if the value in id is not equal to null
reference https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Logical_NOT
Falsy means something empty like empty list,tuple, as any datatype having empty values or None.
Truthy means :
Except are Truthy
>>> if '' is not None:
... print'23333'
...
23333
I think (not None) is True and ('') is False so why it running print?
is and is not test for object identity, i.e., will test if '' and None are the same object, which they are not, so the test returns True in your case.
From the Python documentation:
The operators is and is not test for object identity: x is y is true
if and only if x and y are the same object. x is not y yields the
inverse truth value.
To put it another way, although '' and None have the same "truthiness", that is they both evaluate to False if you do bool(None) or bool(''), they to do not refer to the same object.
is not is a single operator, equal to the negation of is. Since '' is None is false, '' is not None is true.
But since is tests identity, not equality, '' is (not None) still won't do what you want.
I feel very confused about some code like this[not written by me]:
version = any(func1(), func2()) # wrong, should be any([func1(), func2()])
def func1():
if something:
return 1
else:
return None
def func2():
if something:
return 2
else:
return 3
version must be a num. when [func1(), func2()] is [1, None], should return 1, when is [None, 2], should return 2, when [1, 2], should return 1.
so I think it's wrong to use any() in this code, because any() just return True or False. If I rewirte this logic using another way, I can not find a graceful way as a pythoner.
I want to know whether any() can achieve the logic, if not, how to achieve it gracefully?
You can simply use or here.
version = func1() or func2()
Make sure the functions are defined before trying to call them.
This works because or returns the first True-like value or the last value (if no value is True-like) . And 'None' is considered False-like in Boolean context.
#AnandSKumar's answer is optimal. But just to give you some information on any if you are interested:
Take this example:
>>> def foo():
... return 2
...
>>> def boo():
... return 3
...
>>> def doo():
... return 4
...
>>> f = [foo, boo, doo]
>>> any(i() < 3 for i in f)
True
Ultimately what is happening inside the any is, iterate over the array of methods j, and indicate whether each item is less than 3, what the "any" will do in this case is return "ANY" condition that matches that. So even if you find one that is False, it will still return True.
There is another similar method to this called "all", that will ensure that ALL conditions are met based on your condition you are checking. Here is the example:
>>> all(i() < 3 for i in f)
False
So, as you can see, because one condition failed, it will return False.
For the arbitrary length case (where explicitly chaining or doesn't make sense), you can make a version of any that returns the first truthy value or a given value when all results are falsy with:
# If on Py2, you'll want to do this to get shortcircuiting behavior
from future_builtins import filter
result = next(filter(None, iterable_to_check), False) # False can be replaced with a chosen default
The filter only produces "truthy" values, and the two arg next gets the first "truthy" value, or the default value if filter finds no "truthy" values.
If the iterable_to_check is a non-empty Sequence (rather than merely Iterable), you can exactly match the behavior of chained ors (the "falsy" result is the last value, not a specific value like False or None) with:
result = next(filter(None, sequence_to_check), sequence_to_check[-1])
to use the final element ("truthy" or "falsy") as the result when all elements were "falsy".
To be clear, if the set of things to test is fixed and smallish, explicit or per Anand's answer is the better way to go.