Python Assert: A Primer

The next piece is a high-level overview of Python’s Assert module. The Python language has specific debugging statements called “asserts” that allow for more lenient programme execution. They are also a sort of raise-if statement, being triggered when an associated expression evaluates to false. They provide a high-level type of sanity testing for the programme. Syntax:

The statement or expression referenced by an assert statement is evaluated during a Python program’s execution when an assert statement is encountered. An Assertion Error exception is thrown when the assertion is no longer true.

raised.

assert Expression[, Arguments]

The arguments are used as the Assertion error’s parameters. Exceptions of type Assertion Error may be handled normally, just like any other exception, by using the try-except statement, but if they are not, the programme will exit with a traceback.

Python, Why?

Assert?

- Help full in code debug.
- Help to find code bugs in a very short span of time.
- Allows checking parameter types and values.
- Allows to check invariants of data structure.
- Checking “can’t happen” situations.
- To ensure a function returns a reasonable outcome.
- Failed assertions can be reported by rewriting them before the failed instance. So a introspection information message is dropped by the rewritten message.

Python Assert Example

The following are some usages of Assert in Python:

The First Code Sample:

Here is the output of the

def radix_sort(Input_List, base=10):

if Input_List == [ ]:

return

```
``` def Input_factory(numeral , base):

def Input(Input_List , index_value):

return ((Input_List[index_value]//(base**numeral)) % base)

return Input

greatest = max( Input_List )

proponent = 0

while base**proponent <= greatest:

Input_List = sort_count(Input_List, base - 1, Input_factory(proponent, base))

proponent = proponent + 1

return Input_List

def sort_count(Input_List , greatest , Input):

count = [0]*(greatest + 1)ss="token keyword">for i in range(len( Input_List )):

count[Input(Input_List, i)] = count[Input(Input_List, i)] + 1

# to determine the last index_value for each of the element

count[0] = count[0] - 1

# zero-based index_valueing decrement

for i in range(1, greatest + 1):

count[i] = count[i] + count[ i - 1 ]

output_value = [None]*len(Input_List)

for i in range(len(Input_List) - 1, -1, -1):

output_value[count[Input(Input_List, i)]] = Input_List[i]

count[Input(Input_List, i)] = count[Input(Input_List, i)] - 1

return output_value

`Input_List = input('Enter the list of (nonnegative) numbers: ').split()`

:

for element in Input_List:

element = int(element)

assert element > 0,"!!! Negative number is entered !!!"

Input_List = [ int(x) for x in Input_List ]

sorted_list = radix_sort(Input_List)

print( ' Radix oriented sorted output : ' , end='')

print(sorted_list)

explanation@@@3 picture

Coding:

- Radix sort allows the keyed in input to be sorted without comparing the elements.
- For achieving this, a bucket has been generated. For elements with more than one digit involved, the technique is applied for all the digits in the element. It is also termed as bucket sort.
- Here the assert process is achieved by the below code block:

for element in Input_List:

element = int(element)

assert element > 0,"!!! Negative number is entered !!!"

- This assert check is used to verify whether any of the keyed in an element are a negative value. When a negative value is found, then the assertion error will be triggered, stating !!! A negative number is entered !!!.

Code Sample No. 2

result of

def heap_sort(Order_value, number, i):

Greatest = i # Initialize Greatest as root

left= 2 * i + 1 # left = 2*i + 1

right= 2 * i + 2 # right = 2*i + 2

```
``` # to verify the left child of root is greater than the root

if left< number and Order_value[i] < Order_value[left]:

Greatest = left

# to verify the right child of root is greater than the root

if right < number and Order_value[Greatest] < Order_value[right]:

Greatest = right

# swap roots on neccesity

if Greatest != i:

Order_value[i],Order_value[Greatest] = Order_value[Greatest],Order_value[i] # swap

# Heapify the root.

heap_sort(Order_value, number, Greatest)

# main function for Order_value sorting

def heapSort(Order_value):

number = len(Order_value)

# max heap build process.

for i in range(number, -1, -1):

heap_sort(Order_value , number , i)

# extract of all the constituents in the given heap

for i in range(number-1, 0, -1):

Order_value[i], Order_value[0] = Order_value[0], Order_value[i] # swap

heap_sort(Order_value , i , 0)

# main section of the code

Order_value = input('Enter the list of (nonnegative) numbers: ').split()

assert len(Order_value) > 0,"!!! List is empty !!!"

for constituent in Order_value:

constituent = int(constituent)

assert constituent > 0,"!!! Negative number is entered !!!"

`heapSort(Order_value)`

number = len(Order_value)

print ( "Sorted Order_value value is" )

for i in range( number):

print (Order_value[i])

rationale@@@5 picture

Code:

- Heap sort is also a type of selection sorting technique. It engages isolating the known input as non-sorted and sorted elements. The algorithm looping process is carried out in such a manner that for the unsorted region so that for every loop, the biggest value would be pressed. Across each and every element of the input list, the above process will be iterated.
- A maximum heap is produced at the agreed input list. After that, the final value is exchanged by means of the primary value constantly, and the value range is relatively diminished by one. The process will be repeated until the value range decreases to one.
- Here the assert process is achieved by the below code block:

assert len(Order_value) > 0,"!!! List is empty !!!"

for element in Input_List:

element = int(element)

assert element > 0,"!!! Negative number is entered !!!"

- Here two assert checks are maintained; one is to check whether the keyed in the input list is empty or not, and the other assert check is used to verify whether any of the keyed in the element are a negative value.
- When a negative value is found, then the assertion error will be triggered stating ” !!! A negative number is entered !!! ” . Similarly, when an empty list is keyed in by the user, then an assertion error stating ” !!! List is empty !!! ” is triggered.