⚡ Bolt: [performance improvement] Optimize pandas iteration and cache FAQ loading

[alinelena]

💡 What:

1. Replaced iterrows() with itertuples(index=False, name=None) in calc_solvMPCONF196.py and calc_MPCONF196.py.
2. Replaced iterrows() with to_dict('records') in gscdb138.py and calc_elasticity.py.
3. Extracted and cached yaml.safe_load for faqs.yml in build_components.py using @lru_cache(maxsize=1) and deepcopy().

🎯 Why:

1. iterrows() is a known performance bottleneck in Pandas as it boxes every row into a Series. itertuples() and to_dict('records') provide a 10x-100x speedup for row iteration.
2. yaml.safe_load is extremely slow compared to native Python parsing. Repeatedly parsing the same static configuration file (faqs.yml) on every component render adds unnecessary overhead. Caching it eliminates this bottleneck.

📊 Impact:

• Iteration over large DataFrames in these critical calculation scripts is now significantly faster.
• Rendering the FAQ component in the Dash application no longer incurs the expensive YAML parsing penalty.

🔬 Measurement:
Verified correctness with:

• Isolated script runs uv run pytest ml_peg/calcs/...
• Full test suite PYTHONPATH=. pytest tests/
• uv run ruff check passed with no issues.
  Removed stray binary artifacts generated during testing before committing.

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PR created automatically by Jules for task 14934560429555836660 started by @alinelena

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