Read named regex captures as a dictionary.
How It Works
Match.groupdict(default=None) returns {name: value} for named capture groups. Missing optional captures use None or your specified default. Unnamed captures are not included.
Step-by-Step Example
import re
matched_entry = re.fullmatch(r'(?P<letter>[A-Z])(?P<number>\d+)', 'Q17')
print(matched_entry.groupdict())Understanding the Example
- The expression "re.fullmatch(r'(?P<letter>[A-Z])(?P<number>\\d+)', 'Q17')" supplies the value stored as 'matched_entry'. This value is then used or checked by the later statements.
- The print() call exposes the result so you can compare it with the behavior described above. Check the value and its type when experimenting.
A successful run of this example prints the following output:
{'letter': 'Q', 'number': '17'}Where This Fits in a Real Program
Start by writing down examples that should match and examples that must fail. Check whether you need to locate a substring, match a prefix or validate an entire field; these are different operations. Unicode and escape sequences can also change which characters are matched, so test accented text and empty input.
Practice: Try It Yourself
Named groups reduce fragile numeric indices in larger parsing patterns.
For this exercise, predict the result before running the changed code. Then explain the difference between the original and modified cases using the actual values, not just whether the program completed.
Further Reading
Read the official Python documentation for complete parameters, return types and exceptions.
Common Beginner Mistakes
- Expecting unnamed groups to appear in groupdict() or assuming a failed match still has groups.
- Extract named area and local number fields from a test code.
Key Takeaways
- Read named regex captures as a dictionary.
- Match.groupdict(default=None) returns {name: value} for named capture groups.
- Apply the demonstrated operation to the practice input and verify its result before depending on it in a larger program.