To extract the valid email addresses from the given text, we can use regular expressions. Here's how we can do it: ```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 pattern to match valid email addresses pattern = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b' # Find all valid email addresses in the text valid_emails = re.findall(pattern, text) # Join the valid email addresses into a comma-separated list without spaces result = ','.join(valid_emails) print(result) ``` Output: ``` john.doe@example.com,jane@smith-family.net,support@company.co.uk,info@subdomain.example.org ``` The regular expression pattern `r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b'` is used to match valid email addresses. Here's a breakdown of the pattern: - `\b`: Word boundary to match the start and end of a word - `[A-Za-z0-9._%+-]+`: Matches one or more characters that are letters (uppercase or lowercase), digits, periods, underscores, percent signs, or plus or minus signs - `@`: Matches the @ symbol - `[A-Za-z0-9.-]+`: Matches one or more characters that are letters (uppercase or lowercase), digits, periods, or hyphens - `\.`: Matches a period (.) - `[A-Z|a-z]{2,}`: Matches two or more letters (uppercase or lowercase) - `\b`: Word boundary to match the end of the email address The `re.findall()` function is used to find all occurrences of valid email addresses in the text and return them as a list. Finally, the `join()` method is used to join the valid email addresses into a comma-separated list without spaces. So in summary, the code extracts all valid email addresses from the given text using a regular expression and returns them as a comma-separated list without spaces.