Harmonize the Gmail labeling automation (gmail_labeler.py) with the comprehensive rules defined in the iCloud Filtering Guide.
- Gap Analysis: Compare
LABEL_RULESingmail_labeler.pyagainst categories in the iCloud Guide.- Identified Gap: "Travel & Bookings" category is present in the Guide but missing in the Python script.
- Identified Gap: "Research & Learning" in the Guide maps to "Professional/Jobs" or "Marketing" in the script, but deserves a distinct
Education/Researchcategory.
- Rule Translation: Convert specific email addresses and subject keywords from the Guide into Python
repatterns.
- Refactor
gmail_labeler.py:- Add
Travelcategory with patterns from the Guide (Airlines, Hotels, Booking sites). - Add
Education/Researchcategory (Universities, MOOCs, ResearchGate). - Enhance
FinanceandShoppingwith specific sender domains to improve precision.
- Add
- Validation: Verify Python syntax and regex validity.
- Execution: Run the updated labeler against the inbox.
- Monitoring: Review
gmail_labeler.logfor categorization distribution and errors.
- Source Code:
/Users/4jp/Workspace/mail_automation/gmail_labeler.py - Reference Data:
/Users/4jp/Workspace/mail_automation/iCloud Mail Filtering Rules - Complete Guide.md - Data Source: Live Gmail Inbox (via API)
- Code Artifact: Updated
gmail_labeler.py(v2.0) - Operational State: Emails in Gmail organized into labels.
- Logs: Execution logs detailing the number of emails processed per category.
| Metric | Definition | Target |
|---|---|---|
| Uncategorized Reduction | Decrease in the volume of "Uncategorized" emails | -15% relative to baseline |
| Rule Specificity | Count of distinct regex patterns in LABEL_RULES |
Increase by ~20 patterns |
| Processing Efficiency | Time to process a batch of 500 emails | Maintain < 60s |
| New Category Volume | Number of emails caught by new Travel & Education rules |
> 0 |