feat: funciones Python datascience, finance, cybersecurity y pipelines

Datascience: aggregate_by_group, deduplicate_entities/relations, detect_drift,
diff_entities/relations, extract_entities/relations_llm, hotness_score, melt,
merge_graphs, pivot, build_entity/relation_schema_prompt.
Finance: avellaneda_stoikov_quotes, generate_gbm_prices, generate_taker_order,
hawkes_intensity + módulo finance.py.
Cybersecurity: envelope_encrypt/decrypt + módulo cybersecurity.py.
Pipelines: extraction_pipeline, monte_carlo_market, run_market_sim.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

python/functions/datascience/diff_relations.md

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+---
+name: diff_relations
+kind: function
+lang: py
+domain: datascience
+version: "1.0.0"
+purity: pure
+signature: "def diff_relations(before: list[dict], after: list[dict], key: tuple[str, str, str] = ('source_id', 'target_id', 'relation_type'), ignore_fields: list[str] | None = None, compare_fields: list[str] | None = None) -> dict"
+description: "Compara relaciones entre dos snapshots usando key compuesta (source_id, target_id, relation_type). Detecta relaciones añadidas, eliminadas y modificadas con detalle campo a campo."
+tags: [diff, relations, graph, snapshot, operations, comparison, datascience]
+uses_functions: []
+uses_types: []
+returns: []
+returns_optional: false
+error_type: ""
+imports: []
+tested: true
+tests:
+  - "relacion añadida"
+  - "relacion eliminada"
+  - "relacion con metadata modificada (mismo source/target/type, distinto weight)"
+  - "key compuesta funciona correctamente"
+test_file_path: "python/functions/datascience/diff_relations_test.py"
+file_path: "python/functions/datascience/diff_relations.py"
+---
+
+## Ejemplo
+
+```python
+before = [
+    {"source_id": "A", "target_id": "B", "relation_type": "knows", "weight": 1.0},
+    {"source_id": "B", "target_id": "C", "relation_type": "owns", "weight": 0.5},
+]
+after = [
+    {"source_id": "A", "target_id": "B", "relation_type": "knows", "weight": 2.0},
+    {"source_id": "C", "target_id": "D", "relation_type": "knows", "weight": 1.0},
+]
+
+result = diff_relations(before, after)
+# result["added"]    -> [{"source_id": "C", "target_id": "D", ...}]
+# result["removed"]  -> [{"source_id": "B", "target_id": "C", ...}]
+# result["modified"] -> [{"key": "A|B|knows", "changes": {"weight": {"old": 1.0, "new": 2.0}}}]
+# result["unchanged"] -> 0
+```
+
+## Notas
+
+La key compuesta se serializa como `source_id|target_id|relation_type`. Si alguno de los campos clave no existe en la relacion, se usa string vacio.
+
+Misma semantica que `diff_entities_py_datascience` pero adaptada para relaciones donde no hay un ID unico — la identidad se define por los tres campos de la key.
+
+Complemento natural de `diff_entities_py_datascience` para comparar grafos completos entre ejecuciones de pipelines.