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/melt_test.py

@@ -0,0 +1,49 @@
+"""Tests para melt."""
+
+import sys
+import os
+sys.path.insert(0, os.path.dirname(__file__))
+
+from melt import melt
+
+
+def test_melt_basico():
+    """Melt basico."""
+    rows = [{"region": "US", "q1": 10, "q2": 20}]
+    result = melt(rows, id_vars=["region"], value_vars=["q1", "q2"])
+    assert len(result) == 2
+    assert result[0] == {"region": "US", "variable": "q1", "value": 10}
+    assert result[1] == {"region": "US", "variable": "q2", "value": 20}
+
+
+def test_melt_multiples_id_vars():
+    """Multiples id_vars."""
+    rows = [{"region": "US", "year": 2023, "q1": 10, "q2": 20}]
+    result = melt(rows, id_vars=["region", "year"], value_vars=["q1", "q2"])
+    assert len(result) == 2
+    assert result[0]["region"] == "US"
+    assert result[0]["year"] == 2023
+    assert result[0]["variable"] == "q1"
+    assert result[0]["value"] == 10
+    assert result[1]["variable"] == "q2"
+    assert result[1]["value"] == 20
+
+
+def test_melt_value_vars_none_derrite_todas_las_columnas_no_id():
+    """value_vars None derrite todas las columnas no-id."""
+    rows = [{"id": 1, "a": 10, "b": 20, "c": 30}]
+    result = melt(rows, id_vars=["id"])
+    assert len(result) == 3
+    vars_found = {r["variable"] for r in result}
+    assert vars_found == {"a", "b", "c"}
+    values_found = {r["value"] for r in result}
+    assert values_found == {10, 20, 30}
+
+
+def test_melt_fila_con_campo_faltante_en_value_vars():
+    """Fila con campo faltante en value_vars."""
+    rows = [{"region": "US", "q1": 10}]  # q2 no existe
+    result = melt(rows, id_vars=["region"], value_vars=["q1", "q2"])
+    assert len(result) == 2
+    q2_row = next(r for r in result if r["variable"] == "q2")
+    assert q2_row["value"] is None