Enterprise Hardening & Polars Lazy Engine Optimization

[Ali-datasmith]

This commit hardens and optimizes the Data-Quality-Auditor repository for enterprise production standards and recruiter review:

• Auth & Access Control: Refactored credentials.py to use argon2-cffi (PasswordHasher argon2id) and integrated a 1-click recruiter demo bypass in ui/login.py.
• Polars Lazy Engine: Upgraded profiling, duplicate detection, outlier calculation, and data cleaning routines to use zero-copy Polars lazy evaluation (pl.scan_csv, pl.LazyFrame, expressions).
• Mathematical Accuracy: Audited scoring formulas, outlier bounds (IQR), missing ratios, duplicate penalties, and edge case handling (boolean columns, zero division, empty frames).
• Testing & Quality Gates: Added unit test suite in tests/test_core.py (15 passing tests), strict Python 3.12+ type hints passing mypy without errors, and ruff linting compliance.
• CI/CD Infrastructure: Created .github/workflows/ci.yml combining Ruff, Mypy, Pytest, and CodeQL SAST analysis.
• B2B Documentation: Replaced README.md with dynamic badges, architecture diagram, features, testing instructions, and Streamlit Community Cloud deployment guide.

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PR created automatically by Jules for task 3431850846209552452 started by @Ali-datasmith

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