Named group extraction

Use regex named groups to pull key fields from log lines.

regex named-groups parsing

Write a function `extract_info(log_line: str) -> dict or None` that parses a log line of the form:

`[LEVEL] timestamp: message`

- `LEVEL` is one of `INFO`, `WARN`, `ERROR`, `DEBUG` (uppercase only).
- `timestamp` is a 10-digit Unix timestamp (digits only).
- `message` is any non-empty sequence of characters (including spaces, but no newlines).

The function must use a single regex with named groups (`(?P<level>...)`, etc.) and return a dictionary with keys `level`, `timestamp`, `message`. If the line does not match the pattern exactly, return `None`.

Examples:
```
>>> extract_info("[INFO] 1620000000: Server started")
{'level': 'INFO', 'timestamp': '1620000000', 'message': 'Server started'}
>>> extract_info("[DEBUG] 1620000001: value=42")
{'level': 'DEBUG', 'timestamp': '1620000001', 'message': 'value=42'}
>>> extract_info("not a log")
None
```

Constraints

- `log_line` is a string of length 1 to 500.
- The message may contain any characters except newline.
- The timestamp is exactly 10 digits.
- The level is exactly one of the four uppercase words.
- Complexity: O(n) time, O(1) extra space.

Example

>>> extract_info("[INFO] 1620000000: Server started")
{'level': 'INFO', 'timestamp': '1620000000', 'message': 'Server started'}
>>> extract_info("[DEBUG] 1620000001: value=42")
{'level': 'DEBUG', 'timestamp': '1620000001', 'message': 'value=42'}
>>> extract_info("[WARN] 1700000000: Low disk space")
{'level': 'WARN', 'timestamp': '1700000000', 'message': 'Low disk space'}
>>> extract_info("[ERROR] 1800000000: Unauthorized access")
{'level': 'ERROR', 'timestamp': '1800000000', 'message': 'Unauthorized access'}
>>> extract_info("not a log")
None
>>> extract_info("[INFO] 12345: missing timestamp digits")
None

8 points ~12 min

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Hints

Use raw string patterns and named groups like `(?P<level>INFO|WARN|ERROR|DEBUG)`.

Anchor the pattern with `^` and `$` to ensure the whole line matches.

Remember that `re.match` returns a match object; access groups via `m.group('level')` etc.

Use `if m:` to return a dict, else `None`.

Test Results

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