Run: 2026-04-24-01KQ01J2MWTMN3NWQF8C0T66X0

To extract the valid email addresses from the provided text, we can use a regular expression that matches valid email formats while excluding invalid entries. The valid emails are: 1. `john.doe@example.com` 2. `jane@smith-family.net` 3. `support@company.co.uk` 4. `info@subdomain.example.org` The invalid entries (`not.an.email.com` and `@missing-username.com`) are skipped as they either lack an `@` symbol or have no local part before it. ### Solution Code: ```python import re text = """Contact information: 1. John Doe - john.doe@example.com 2. Jane Smith - jane@smith-family.net 3. support@company.co.uk 4. info@subdomain.example.org 5. Invalid email: not.an.email.com 6. Another invalid: @missing-username.com""" # Regular expression to match valid email addresses email_pattern = r'[\w\.-]+@(?:[\w-]+\.)+[\w-]+' # Find all matches in the text emails = re.findall(email_pattern, text) # Join the emails into a comma-separated list without spaces result = ','.join(emails) print(result) ``` ### Output: ``` john.doe@example.com,jane@smith-family.net,support@company.co.uk,info@subdomain.example.org ``` ### Explanation: - **Regular Expression**: `r'[\w\.-]+@(?:[\w-]+\.)+[\w-]+'` matches: - **Local part**: `[\w\.-]+` (letters, digits, underscores, dots, hyphens). - **Domain**: `(?:[\w-]+\.)+` (one or more subdomains ending with a dot). - **Top-level domain**: `[\w-]+` (letters, digits, hyphens). - **Exclusion of Invalid Entries**: The regex naturally skips entries without `@` or lacking a local part. - **Result Construction**: Valid emails are joined into a single string, separated by commas without spaces.