⚡ Bolt: Optimize get_email_settings query

[Woschj]

💡 What: Optimized the get_email_settings function in app/services/admin_email_service.py by replacing a Python-level iteration and filtering logic with a MongoDB database-level query using the $regex operator ^email_.

🎯 Why: Previously, the get_email_settings function was doing an unconditional mongodb.find('settings', {}) which fetched all settings from the database and loaded them into memory. It then iterated through all the rows using Python and filtered them by checking if the key started with email_. As the number of settings grows, fetching everything into memory and looping in python introduces unnecessary I/O overhead and memory waste. Pushing this filter directly to MongoDB leverages the database engine, only returning the data that is actually needed.

📊 Impact:
This optimization eliminates a full table scan and replaces it with an efficient database-level string matching query. Network bandwidth between the application and the database is significantly reduced because only the matched rows are transferred, and CPU/memory overhead inside the python process is eliminated.

🧪 Measurement:
A benchmark script was created using mongomock that populated the database with 10,000 non-email settings and 100 email settings.
The benchmark results showed:
Baseline Time: ~2.46s
Optimized Time: ~0.08s
Improvement: ~96.5%

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PR created automatically by Jules for task 4922470496782343825 started by @Woschj

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