Use your knowledge of **character classes** and **quantifiers** to extract all email addresses from a block of text. Email addresses follow specific patterns, making them ideal candidates for **regular expression** matching. Your goal is to write a function that scans a given string and returns every email address it finds.

- Identify the pattern of a typical email address (for example, `username@example.com`);
- Use Python's `re` module to construct a regular expression that matches email addresses;
- Write a function that returns a list of all email addresses found in the input string.


import unittest
import user_code
import ast
import re   
import unittest
import importlib
import io
from contextlib import redirect_stdout

class TestTask(unittest.TestCase):
    def test_basic_emails(self):
        import user_code
        importlib.reload(user_code)
        text = "Contact us at support@example.com or sales@company.org for details."
        result = user_code.extract_emails(text)
        expected = ["support@example.com", "sales@company.org"]
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Correctly extracts multiple emails in order",
            f"Expected {expected}, got {result}",
        )

    def test_no_emails(self):
        import user_code
        importlib.reload(user_code)
        text = "No email addresses here!"
        result = user_code.extract_emails(text)
        expected = []
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Returns an empty list when no emails are present",
            f"Expected empty list, got {result}",
        )

    def test_varied_emails(self):
        import user_code
        importlib.reload(user_code)
        text = "Emails: first.last@domain.co.uk, foo_bar-123@sub.domain.com, x@y.io."
        result = user_code.extract_emails(text)
        expected = ["first.last@domain.co.uk", "foo_bar-123@sub.domain.com", "x@y.io"]
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Correctly extracts emails with subdomains and country TLDs",
            f"Expected {expected}, got {result}",
        )

    def test_emails_with_extra_characters(self):
        import user_code
        importlib.reload(user_code)
        text = "Contact: <admin@website.com>, (info@web.org)!"
        result = user_code.extract_emails(text)
        expected = ["admin@website.com", "info@web.org"]
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Ignores punctuation around emails",
            f"Expected {expected}, got {result}",
        )

    def test_case_sensitivity(self):
        import user_code
        importlib.reload(user_code)
        text = "Write to John.DOE@Example.Com for info."
        result = user_code.extract_emails(text)
        expected = ["John.DOE@Example.Com"]
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Preserves original case of email addresses",
            f"Expected {expected}, got {result}",
        )

    def test_repeated_emails(self):
        import user_code
        importlib.reload(user_code)
        text = "Repeat: a@b.com a@b.com"
        result = user_code.extract_emails(text)
        expected = ["a@b.com", "a@b.com"]
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Returns all occurrences, including duplicates, in order",
            f"Expected {expected}, got {result}",
        )

def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message
        test_case.assertTrue(True, success_message)
    else:
        test_case._testMethodName = failure_message
        test_case.fail(failure_message)

def normalize_text(text):
    text = text.lower()
    text = re.sub(r"\s{2,}", " ", text)
    text = re.sub(r"\s*([,:?])\s*", r"\1 ", text)
    return text.strip()

def change_var(code: str, var_name: str, value: str) -> str:
    tree = ast.parse(code)
    lines = code.splitlines()
    for i, node in enumerate(tree.body):
        if isinstance(node, ast.Assign):
            for target in node.targets:
                if isinstance(target, ast.Name) and target.id == var_name:
                    start_line = node.lineno - 1
                    line = lines[start_line]
                    indent = ' ' * (len(line) - len(line.lstrip()))
                    lines[start_line] = f"{indent}{var_name} = {value}"
                    next_line = len(lines)
                    for next_node in tree.body[i+1:]:
                        if hasattr(next_node, 'lineno'):
                            next_line = next_node.lineno - 1
                            break
                    if next_line > start_line + 1:
                        lines[start_line+1:next_line] = []
                    
                    return '\\n'.join(lines)
    return code

if __name__ == "__main__":
    unittest.main()


test_main.py

A comprehensive course on Python regular expressions, designed for learners with basic Python knowledge. This course covers regex syntax, pattern matching, advanced features, and practical applications through theory and hands-on tasks.

Learn the fundamentals of regular expressions in Python, including basic syntax, pattern matching, and essential regex functions.

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Master advanced regex features such as lookahead/lookbehind, non-greedy matching, and apply regex to real-world text processing problems.

Challenge: Extract Email Addresses

Solución

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Challenge: Extract Email Addresses

Solución