Sponsored
Sponsored
In this approach, we use regular expressions to check for valid emails. The regular expression will ensure that the email format adheres to the specified rules: the prefix starts with a letter and consists only of permitted characters, followed by '@leetcode.com'. This method efficiently checks the constraints by leveraging regular expressions, which are well-suited for pattern matching tasks.
The time complexity of this solution is O(n), where n is the number of users, as each email is scanned once. The space complexity is O(n) as we store all valid users in a list.
1import re
This Python solution utilizes the 're' module to define a regular expression pattern that matches valid emails. The pattern checks if the email starts with a letter and is followed by any combination of allowed characters before the fixed domain '@leetcode.com'. The function iterates through the list of users, filters valid emails using 're.match', and returns the filtered list.
This approach involves manually parsing the email to check the prefix and domain components. We split the email at the '@' character and validate both parts separately. This is an alternative to regex that provides a more step-by-step checking method.
The time complexity is O(n * m), where n is the number of users and m is the length of the largest email string due to manual character checking. The space complexity is O(n) for the result list.
1def find_valid_emails(users):
2 def is_valid_email(mail):
3 if '@leetcode.com' not in mail:
4 return False
5 prefix, domain = mail.split('@', 1)
6 if domain != 'leetcode.com':
7 return False
8 if not prefix or not prefix[0].isalpha():
9 return False
10 for char in prefix:
11 if not (char.isalnum() or char in '._-'):
12 return False
13 return True
14
15 valid_emails = [user for user in users if is_valid_email(user['mail'])]
16 return valid_emails
17
18# Example usage
19users = [
20 {'user_id': 1, 'name': 'Winston', 'mail': 'winston@leetcode.com'},
21 {'user_id': 2, 'name': 'Jonathan', 'mail': 'jonathanisgreat'},
22 {'user_id': 3, 'name': 'Annabelle', 'mail': 'bella-@leetcode.com'},
23 {'user_id': 4, 'name': 'Sally', 'mail': 'sally.come@leetcode.com'},
24 {'user_id': 5, 'name': 'Marwan', 'mail': 'quarz#2020@leetcode.com'},
25 {'user_id': 6, 'name': 'David', 'mail': 'david69@gmail.com'},
26 {'user_id': 7, 'name': 'Shapiro', 'mail': '.shapo@leetcode.com'}
27]
28
29valid_users = find_valid_emails(users)
30print(valid_users)
31This Python function manually splits the email at '@', checks if the domain is 'leetcode.com', and ensures that the prefix starts with a letter and contains only allowed characters. This approach is more granular and does not use regex, making it useful for understanding email validation through conditional checks.