What does assert
mean? How is it used?
The assert
statement exists in almost every programming language. It has two main uses:
It helps detect problems early in your program, where the cause is clear, rather than later when some other operation fails. A type error in Python, for example, can go through several layers of code before actually raising an Exception if not caught early on. It works as documentation for other developers reading the code, who see the assert and can confidently say that its condition holds from now on.
When you do...
assert condition
... you're telling the program to test that condition, and immediately trigger an error if the condition is false.
In Python, it's roughly equivalent to this:
if not condition:
raise AssertionError()
Try it in the Python shell:
>>> assert True # nothing happens
>>> assert False
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AssertionError
Assertions can include an optional message, and you can disable them when running the interpreter.
To print a message if the assertion fails:
assert False, "Oh no! This assertion failed!"
Do not use parenthesis to call assert
like a function. It is a statement. If you do assert(condition, message)
you'll be running the assert
with a (condition, message)
tuple as first parameter.
As for disabling them, when running python
in optimized mode, where __debug__
is False
, assert statements will be ignored. Just pass the -O
flag:
python -O script.py
See here for the relevant documentation.
Watch out for the parentheses. As has been pointed out in other answers, in Python 3, assert
is still a statement, so by analogy with print(..)
, one may extrapolate the same to assert(..)
or raise(..)
but you shouldn't.
This is wrong:
assert(2 + 2 == 5, "Houston we've got a problem")
This is correct:
assert 2 + 2 == 5, "Houston we've got a problem"
The reason the first one will not work is that bool( (False, "Houston we've got a problem") )
evaluates to True
.
In the statement assert(False)
, these are just redundant parentheses around False
, which evaluate to their contents. But with assert(False,)
the parentheses are now a tuple, and a non-empty tuple evaluates to True
in a boolean context.
assert (2 + 2 = 5), "Houston we've got a problem"
should be ok, yes?
assert (2 + 2 = 5), "Houston we've got a problem"
won't work... but it has nothing to do with the assert statement, which is fine. Your condition won't work because it isn't a condition. Missing a second =
.
assert (2+2==5), “Houston we’ve got a problem
will evaluate to assert False, “Houston we’ve got a problem
, and will thus raise the assertion error. This is regardless of whether you have a space between assert
and (2+2==5)
. What the other commenters are talking about is when you pass (2+2==5, “Houston we’ve got a problem”)
as a input the assert function. So the input is really a tuple consisting of 2 terms 2+2==5
and “Houston we’ve got a problem`.
As other answers have noted, assert
is similar to throwing an exception if a given condition isn't true. An important difference is that assert statements get ignored if you compile your code with the optimization option -O
. The documentation says that assert expression
can better be described as being equivalent to
if __debug__:
if not expression: raise AssertionError
This can be useful if you want to thoroughly test your code, then release an optimized version when you're happy that none of your assertion cases fail - when optimization is on, the __debug__
variable becomes False and the conditions will stop getting evaluated. This feature can also catch you out if you're relying on the asserts and don't realize they've disappeared.
if Not Error: raise Exception(“ this is a error”)
? That way, the program will still show the source of the error, when the user runs it..
assert
statement? The assumption here is that when the program is released to the end user, you are using the -O flag, thus assuming that all the bugs have been removed. Hence, any error or program crash is due to input to the program which is valid as per the contract, but cant be handled by the program. So it should alert the user as such.
The goal of an assertion in Python is to inform developers about unrecoverable errors in a program.
Assertions are not intended to signal expected error conditions, like “file not found”, where a user can take corrective action (or just try again).
Another way to look at it is to say that assertions are internal self-checks in your code. They work by declaring some conditions as impossible in your code. If these conditions don’t hold that means there’s a bug in the program.
If your program is bug-free, these conditions will never occur. But if one of them does occur the program will crash with an assertion error telling you exactly which “impossible” condition was triggered. This makes it much easier to track down and fix bugs in your programs.
Here’s a summary from a tutorial on Python’s assertions I wrote:
Python’s assert statement is a debugging aid, not a mechanism for handling run-time errors. The goal of using assertions is to let developers find the likely root cause of a bug more quickly. An assertion error should never be raised unless there’s a bug in your program.
assert
statement and when to use this. I am trying to understand a number of terms that you introduced in the article.
assert statement
, cant price
also be considered a user input? Why do you consider assert user.is_admin()
as data validation but not assert price
?
Others have already given you links to documentation.
You can try the following in a interactive shell:
>>> assert 5 > 2
>>> assert 2 > 5
Traceback (most recent call last):
File "<string>", line 1, in <fragment>
builtins.AssertionError:
The first statement does nothing, while the second raises an exception. This is the first hint: asserts are useful to check conditions that should be true in a given position of your code (usually, the beginning (preconditions) and the end of a function (postconditions)).
Asserts are actually highly tied to programming by contract, which is a very useful engineering practice:
http://en.wikipedia.org/wiki/Design_by_contract.
From docs:
Assert statements are a convenient way to insert debugging assertions into a program
You can read more here: http://docs.python.org/release/2.5.2/ref/assert.html
The assert statement has two forms.
The simple form, assert <expression>
, is equivalent to
if __debug__:
if not <expression>: raise AssertionError
The extended form, assert <expression1>, <expression2>
, is equivalent to
if __debug__:
if not <expression1>: raise AssertionError(<expression2>)
Assertions are a systematic way to check that the internal state of a program is as the programmer expected, with the goal of catching bugs. See the example below.
>>> number = input('Enter a positive number:')
Enter a positive number:-1
>>> assert (number > 0), 'Only positive numbers are allowed!'
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AssertionError: Only positive numbers are allowed!
>>>
assert math.pow(number, 2) >= 0
because you can guarantee that for any number this is true unless there is an error in the math.pow() code.
Here is a simple example, save this in file (let's say b.py)
def chkassert(num):
assert type(num) == int
chkassert('a')
and the result when $python b.py
Traceback (most recent call last):
File "b.py", line 5, in <module>
chkassert('a')
File "b.py", line 2, in chkassert
assert type(num) == int
AssertionError
As summarized concisely on the C2 Wiki:
An assertion is a boolean expression at a specific point in a program which will be true unless there is a bug in the program.
You can use an assert
statement to document your understanding of the code at a particular program point. For example, you can document assumptions or guarantees about inputs (preconditions), program state (invariants), or outputs (postconditions).
Should your assertion ever fail, this is an alert for you (or your successor) that your understanding of the program was wrong when you wrote it, and that it likely contains a bug.
For more information, John Regehr has a wonderful blog post on the Use of Assertions, which applies to the Python assert
statement as well.
assert
statement is useful for documenting the programmer‘s understanding of the code.
The assert
statement exists in almost every programming language. It helps detect problems early in your program, where the cause is clear, rather than later as a side-effect of some other operation. They always expect a True
condition.
When you do something like:
assert condition
You're telling the program to test that condition and immediately trigger an error if it is false.
In Python, assert
expression, is equivalent to:
if __debug__:
if not <expression>: raise AssertionError
You can use the extended expression to pass an optional message:
if __debug__:
if not (expression_1): raise AssertionError(expression_2)
Try it in the Python interpreter:
>>> assert True # Nothing happens because the condition returns a True value.
>>> assert False # A traceback is triggered because this evaluation did not yield an expected value.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AssertionError
There are some caveats to seen before using them mainly for those who deem to toggles between the assert
and if
statements. The aim to use assert
is on occasions when the program verifies a condition and return a value that should stop the program immediately instead of taking some alternative way to bypass the error:
1. Parentheses
As you may have noticed, the assert
statement uses two conditions. Hence, do not use parentheses to englobe them as one for obvious advice. If you do such as:
assert (condition, message)
Example:
>>> assert (1==2, 1==1)
<stdin>:1: SyntaxWarning: assertion is always true, perhaps remove parentheses?
You will be running the assert
with a (condition, message)
which represents a tuple as the first parameter, and this happens cause non-empty tuple in Python is always True
. However, you can do separately without problem:
assert (condition), "message"
Example:
>>> assert (1==2), ("This condition returns a %s value.") % "False"
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AssertionError: This condition returns a False value.
2. Debug purpose
If you are wondering regarding when use assert
statement. Take an example used in real life:
* When your program tends to control each parameter entered by the user or whatever else:
def loremipsum(**kwargs):
kwargs.pop('bar') # return 0 if "bar" isn't in parameter
kwargs.setdefault('foo', type(self)) # returns `type(self)` value by default
assert (len(kwargs) == 0), "unrecognized parameter passed in %s" % ', '.join(kwargs.keys())
* Another case is on math when 0 or non-positive as a coefficient or constant on a certain equation:
def discount(item, percent):
price = int(item['price'] * (1.0 - percent))
print(price)
assert (0 <= price <= item['price']),\
"Discounted prices cannot be lower than 0 "\
"and they cannot be higher than the original price."
return price
* or even a simple example of a boolean implementation:
def true(a, b):
assert (a == b), "False"
return 1
def false(a, b):
assert (a != b), "True"
return 0
3. Data processing or data validation
The utmost importance is to not rely on the assert
statement to execute data processing or data validation because this statement can be turned off on the Python initialization with -O
or -OO
flag – meaning value 1, 2, and 0 (as default), respectively – or PYTHONOPTIMIZE
environment variable.
Value 1:
* asserts are disabled;
* bytecode files are generated using .pyo
extension instead of .pyc
;
* sys.flags.optimize
is set to 1 (True
);
* and, __debug__
is set to False
;
Value 2: disables one more stuff
* docstrings are disabled;
Therefore, using the assert
statement to validate a sort of expected data is extremely dangerous, implying even to some security issues. Then, if you need to validate some permission I recommend you raise AuthError
instead. As a preconditional effective, an assert
is commonly used by programmers on libraries or modules that do not have a user interact directly.
if the statement after assert is true then the program continues , but if the statement after assert is false then the program gives an error. Simple as that.
e.g.:
assert 1>0 #normal execution
assert 0>1 #Traceback (most recent call last):
#File "<pyshell#11>", line 1, in <module>
#assert 0>1
#AssertionError
In Pycharm, if you use assert
along with isinstance
to declare an object's type, it will let you access the methods and attributes of the parent object while you are coding, it will auto-complete automatically.
For example, let's say self.object1.object2
is a MyClass
object.
import MyClasss
def code_it(self):
testObject = self.object1.object2 # at this point, program doesn't know that testObject is a MyClass object yet
assert isinstance(testObject , MyClasss) # now the program knows testObject is a MyClass object
testObject.do_it() # from this point on, PyCharm will be able to auto-complete when you are working on testObject
If you ever want to know exactly what a reserved function does in python, type in help(enter_keyword)
Make sure if you are entering a reserved keyword that you enter it as a string.
Python assert is basically a debugging aid which test condition for internal self-check of your code. Assert makes debugging really easy when your code gets into impossible edge cases. Assert check those impossible cases.
Let's say there is a function to calculate price of item after discount :
def calculate_discount(price, discount):
discounted_price = price - [discount*price]
assert 0 <= discounted_price <= price
return discounted_price
here, discounted_price can never be less than 0 and greater than actual price. So, in case the above condition is violated assert raises an Assertion Error, which helps the developer to identify that something impossible had happened.
Hope it helps :)
assert
is useful in a debugging context, but should not be relied outside of a debugging context.
My short explanation is:
assert raises AssertionError if expression is false, otherwise just continues the code, and if there's a comma whatever it is it will be AssertionError: whatever after comma, and to code is like: raise AssertionError(whatever after comma)
A related tutorial about this:
https://www.tutorialspoint.com/python/assertions_in_python.htm
assert
, but not when to use (or not use) an assert
; also noting that an assert
can be disabled if __debug__
is False
would be useful.
As written in other answers, assert
statements are used to check the state of the program at a given point.
I won't repeat what was said about associated message, parentheses, or -O
option and __debug__
constant. Check also the doc for first hand information. I will focus on your question: what is the use of assert
? More precisely, when (and when not) should one use assert
?
The assert
statements are useful to debug a program, but discouraged to check user input. I use the following rule of thumb: keep assertions to detect a this should not happen situation. A user input may be incorrect, e.g. a password too short, but this is not a this should not happen case. If the diameter of a circle is not twice as large as its radius, you are in a this should not happen case.
The most interesting, in my mind, use of assert
is inspired by the programming by contract as described by B. Meyer in [Object-Oriented Software Construction]( https://www.eiffel.org/doc/eiffel/Object-Oriented_Software_Construction%2C_2nd_Edition ) and implemented in the [Eiffel programming language]( https://en.wikipedia.org/wiki/Eiffel_(programming_language)). You can't fully emulate programming by contract using the assert
statement, but it's interesting to keep the intent.
Here's an example. Imagine you have to write a head
function (like the [head
function in Haskell]( http://www.zvon.org/other/haskell/Outputprelude/head_f.html)). The specification you are given is: "if the list is not empty, return the first item of a list". Look at the following implementations:
>>> def head1(xs): return xs[0]
And
>>> def head2(xs):
... if len(xs) > 0:
... return xs[0]
... else:
... return None
(Yes, this can be written as return xs[0] if xs else None
, but that's not the point).
If the list is not empty, both functions have the same result and this result is correct:
>>> head1([1, 2, 3]) == head2([1, 2, 3]) == 1
True
Hence, both implementations are (I hope) correct. They differ when you try to take the head item of an empty list:
>>> head1([])
Traceback (most recent call last):
...
IndexError: list index out of range
But:
>>> head2([]) is None
True
Again, both implementations are correct, because no one should pass an empty list to these functions (we are out of the specification). That's an incorrect call, but if you do such a call, anything can happen. One function raises an exception, the other returns a special value. The most important is: we can't rely on this behavior. If xs
is empty, this will work:
print(head2(xs))
But this will crash the program:
print(head1(xs))
To avoid some surprises, I would like to know when I'm passing some unexpected argument to a function. In other words: I would like to know when the observable behavior is not reliable, because it depends on the implementation, not on the specification. Of course, I can read the specification, but programmers do not always read carefully the docs.
Imagine if I had a way to insert the specification into the code to get the following effect: when I violate the specification, e.g by passing an empty list to head
, I get a warning. That would be a great help to write a correct (i.e. compliant with the specification) program. And that's where assert
enters on the scene:
>>> def head1(xs):
... assert len(xs) > 0, "The list must not be empty"
... return xs[0]
And
>>> def head2(xs):
... assert len(xs) > 0, "The list must not be empty"
... if len(xs) > 0:
... return xs[0]
... else:
... return None
Now, we have:
>>> head1([])
Traceback (most recent call last):
...
AssertionError: The list must not be empty
And:
>>> head2([])
Traceback (most recent call last):
...
AssertionError: The list must not be empty
Note that head1
throws an AssertionError
, not an IndexError
. That's important because an AssertionError
is not any runtime error: it signals a violation of the specification. I wanted a warning, but I get an error. Fortunately, I can disable the check (using the -O
option), but at my own risks. I will do it a crash is really expensive, and hope for the best. Imagine my program is embedded in a spaceship that travels through a black hole. I will disable assertions and hope the program is robust enough to not crash as long as possible.
This example was only about preconditions, be you can use assert
to check postconditions (the return value and/or the state) and invariants (state of a class). Note that checking postconditions and invariants with assert
can be cumbersome:
for postconditions, you need to assign the return value to a variable, and maybe to store the iniial state of the object if you are dealing with a method;
for invariants, you have to check the state before and after a method call.
You won't have something as sophisticated as Eiffel, but you can however improve the overall quality of a program.
To summarize, the assert
statement is a convenient way to detect a this should not happen situation. Violations of the specification (e.g. passing an empty list to head
) are first class this should not happen situations. Hence, while the assert
statement may be used to detect any unexpected situation, it is a privilegied way to ensure that the specification is fulfilled. Once you have inserted assert
statements into the code to represent the specification, we can hope you have improved the quality of the program because incorrect arguments, incorrect return values, incorrect states of a class..., will be reported.
Assertions are statements that state a fact confidently in our program.
Syntax : assert <condition>
or assert <condition>,<error message>
It has a condition/expression which is supposed to be always true. If the condition is false, the assert
statement will halt the program and throw an error message saying AssertionError
. So your assertion expression will be something that you don't want in your program.
e.g.
assert
Key Points :
It is used as a debugging tool. It takes an expression and an optional message. It exists in almost every programming language
+
for the description, but -
for then using assert
for input validation. Net score: nothing.
The assert
keyword in Python raises an AssertionError
if the code following the assert
keyword is False
. If not, it continues as nothing happened.
Example 1:
a = 5
b = 6
assert a == b
OUTPUT:
AssertionError
This is because, obviously, a
does not equal b
. This is particularly useful if you want to raise an Exception
in your code.
def get_dict_key(d, k):
try:
assert k in d
return d[k]
except Exception:
print("Key must be in dict.")
The above example is practically useless, but remember, it is mostly used for debugging purposes, so you can track down your bugs.
assert
, but does not answer when to use (or not use) an assert
.
format : assert Expression[,arguments] When assert encounters a statement,Python evaluates the expression.If the statement is not true,an exception is raised(assertionError). If the assertion fails, Python uses ArgumentExpression as the argument for the AssertionError. AssertionError exceptions can be caught and handled like any other exception using the try-except statement, but if not handled, they will terminate the program and produce a traceback. Example:
def KelvinToFahrenheit(Temperature):
assert (Temperature >= 0),"Colder than absolute zero!"
return ((Temperature-273)*1.8)+32
print KelvinToFahrenheit(273)
print int(KelvinToFahrenheit(505.78))
print KelvinToFahrenheit(-5)
When the above code is executed, it produces the following result:
32.0
451
Traceback (most recent call last):
File "test.py", line 9, in <module>
print KelvinToFahrenheit(-5)
File "test.py", line 4, in KelvinToFahrenheit
assert (Temperature >= 0),"Colder than absolute zero!"
AssertionError: Colder than absolute zero!
def getUser(self, id, Email):
user_key = id and id or Email
assert user_key
Can be used to ensure parameters are passed in the function call.
if not user_key: raise ValueError()
Check last 2 paragraphs here: wiki.python.org/moin/UsingAssertionsEffectively
assert
should not be used for input validation because either the validation will be stripped out if __debug__
is False
. Also using assertions for non-debug purposes can cause people to catch the resulting AssertionError
s, which can make debugging more difficult instead of less.
>>>this_is_very_complex_function_result = 9
>>>c = this_is_very_complex_function_result
>>>test_us = (c < 4)
>>> #first we try without assert
>>>if test_us == True:
print("YES! I am right!")
else:
print("I am Wrong, but the program still RUNS!")
I am Wrong, but the program still RUNS!
>>> #now we try with assert
>>> assert test_us
Traceback (most recent call last):
File "<pyshell#52>", line 1, in <module>
assert test_us
AssertionError
>>>
Success story sharing
if not condition: raise AssertError()
, why should I use assert? Are there any conditions under which assert is better other than just being a shorter form ofif not condition
statement?assert
, but after reading all answers, i totally got nothing i want!