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Python Set Operations Explained: From Theory to Real-Time Applications

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A  set  in Python is an unordered collection of unique elements. It is useful when storing distinct values and performing operations like union, intersection, or difference. Real-Time Example: Removing Duplicate Customer Emails in a Marketing Campaign Imagine you are working on an email marketing campaign for your company. You have a list of customer emails, but some are duplicated. Using a set , you can remove duplicates efficiently before sending emails. Code Example: # List of customer emails (some duplicates) customer_emails = [ "alice@example.com" , "bob@example.com" , "charlie@example.com" , "alice@example.com" , "david@example.com" , "bob@example.com" ] # Convert list to a set to remove duplicates unique_emails = set (customer_emails) # Convert back to a list (if needed) unique_email_list = list (unique_emails) # Print the unique emails print ( "Unique customer emails:" , unique_email_list) Ou...

Sets Vs Lists Python Programmer Tips

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Sets are only useful when trying to ensure unique items are preserved. Before sets were available, it was common to process items and check if they exist in a list (or dictionary) before adding them. List example Here unique is an empty list. Every time I compare with this list, and if it is not duplicated then the input item will append to the unique list.  >>> unique = []  >>> for name in ['srini', 'srini', 'rao', 'srini']:  ... if name not in unique:  ... unique.append(name)  ... >>> unique ['srini', 'rao'] There is no need to do this when using sets. Instead of appending you add to a set: Set example >>> for name in ['srini', 'srini', 'rao', 'srini']: ... unique.add(name)  ...  >>> unique {'srini', 'rao'} Just like tuples and lists, interacting with sets have some differences on how to access their items. You can't index them like lists an...