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Eradicating or Modifying the Exceptions throughout runtime

Modifying Exceptions Throughout Runtime: Suppose there’s a Registration Type. If you happen to obtained distinctive knowledge within the type like within the place of Title you bought cellphone numbers to take away that ambiguity from the info we use the next logical abstraction with none express coding(if-else ladder) not just for registration type may be utilized to DBMS Knowledge and in addition varied Datasets.

Distinctive Knowledge: The Knowledge is alleged to be distinctive when knowledge is wrong or doesn’t belong to the identical group. this knowledge can be known as ambiguous knowledge to take away this ambiguity within the knowledge some operations wanted to be carried out. eradicating distinctive knowledge from the listing reduces errors or exceptions whereas performing operations. 

Instance: String operations can’t be completed on the complete listing, as a result of it additionally has numerical. If we accomplish that exceptions can be raised. So, to keep away from exceptions, partition the info within the array into their respective knowledge kind.

Diagram for Distinctive knowledge

Convert parts of a listing to uppercase.

Enter: names[] = [‘geeks’, ‘for’, ‘geeks’, ‘is’, ‘best’, 9876543210, 3.142, 5 + 8j, True], convert strings within the listing to uppercase and take away undesirable knowledge.
Output: [‘GEEKS’, ‘FOR’, ‘GEEKS’, ‘IS’, ‘BEST’][9876543210, 3.142, 5 + 8j, True]

Recursive Strategy: By eradicating the distinctive knowledge from the listing utilizing exception dealing with.

Logic Skeleton:




     #replace/take away distinctive knowledge
     #replace args

return consequence


  •  Enter: Arr[]
  •  Intilize exceptional_data = [], Index = 0.
  • Iterate over arr and apply uppercase operation on the info in strive block to search out distinctive knowledge.

             i.e strive:

            whereas(index < len(names)):
                 names[index] = names[index].higher()
                 index += 1

  • If distinctive knowledge discovered, retailer it in exceptional_data listing and take away that knowledge from listing. and once more name perform with new listing and index

               i.e besides:
                        exception = names.pop(index)
                        case_changer(names, index)

Under is the Implementation of the above method:


# Python Program to take away Distinctive
# knowledge from an information container

# Contemplate names listing wanted to have solely
# string knowledge kind
names = ['geeks', 'for', 'geeks', 'is', 'best', 9876543210, 3.142, 5 + 8j, True]

# Checklist to catch distinctive knowledge.
exceptional_data = []

# Distinctive knowledge Exists i.e int,
# advanced and Boolean.
print('Distinctive knowledge:', names)

# Intilize index has worth to 0
index = 0

# case_changer converts string to
# uppercase strings

def case_changer(names, index):

    # Iterate over all parts to search out
    # distinctive knowledge index.
        whereas(index < len(names)):

            # Carry out operations on
            # non-exceptional knowledge.
            names[index] = names[index].higher()
            index += 1

# After discovering distinctive knowledge index
# attempt to change or take away it.
        exception = names.pop(index)

# After eradicating distinctive knowledge proceed
# operations on non-exceptional by
# calling the perform.
        case_changer(names, index)
    return names

print('Uppercase knowledge  :', case_changer(names, index))
print("Distinctive knowledge:", exceptional_data)

Distinctive knowledge: ['geeks', 'for', 'geeks', 'is', 'best', 9876543210, 3.142, (5+8j), True]
Uppercase knowledge  : ['GEEKS', 'FOR', 'GEEKS', 'IS', 'BEST']
Distinctive knowledge: [9876543210, 3.142, (5+8j), True]

Time Complexity: O(n), the place n is the size of the arr.
Auxiliary Area: O(1).

Benefits of Modifying the Exceptions throughout runtime:

  • Respective operations on the respective listing are completed simply with out express coding.
  • Knowledge is partitioned simply.
  • Exceptions are dealt with simply and in addition lowered.
  • The Time complexity can be environment friendly.
  • It additionally can be utilized to deal with bigger knowledge in datasets.


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