"""Tests para profile_table — pipeline EDA one-shot del grupo `eda`.

Crea una DuckDB temporal con tres columnas representativas:
  - id_str: enteros guardados como VARCHAR ('10','20',...) -> debe promocionarse
    a inferred_type "numeric" y recibir un bloque col["numeric"].
  - precio: numerica nativa (DOUBLE).
  - categoria: categorica textual.
Luego corre profile_table(write_report=False) y verifica el contrato.
"""

import os
import tempfile

import duckdb

from pipelines.profile_table import profile_table


def _make_db() -> str:
    """Crea una DuckDB temporal con la tabla de prueba y devuelve su path."""
    tmp_dir = tempfile.mkdtemp(prefix="profile_table_test_")
    db_path = os.path.join(tmp_dir, "t.duckdb")
    con = duckdb.connect(db_path)
    con.execute(
        "CREATE TABLE items ("
        "  id_str VARCHAR,"   # enteros guardados como texto
        "  precio DOUBLE,"    # numerica nativa
        "  categoria VARCHAR" # categorica
        ")"
    )
    rows = [
        ("10", 9.5, "alfa"),
        ("20", 12.0, "beta"),
        ("30", 7.25, "alfa"),
        ("40", 15.75, "gamma"),
        ("50", 3.0, "beta"),
        ("60", 22.4, "alfa"),
    ]
    con.executemany("INSERT INTO items VALUES (?, ?, ?)", rows)
    con.close()
    return db_path


def _col(profile: dict, name: str) -> dict:
    return next(c for c in profile["columns"] if c["name"] == name)


def test_varchar_integer_promotes_to_numeric():
    db_path = _make_db()
    r = profile_table(db_path, "items", sample=5000, write_report=False)

    # status ok y sin tocar disco.
    assert r["status"] == "ok", r
    assert r["report_md_path"] is None
    assert r["report_json_path"] is None

    prof = r["profile"]

    # La columna VARCHAR-entera se promociono a numeric con bloque numeric.
    id_col = _col(prof, "id_str")
    assert id_col["inferred_type"] == "numeric", id_col["inferred_type"]
    assert id_col["numeric"] is not None
    assert id_col["numeric"]["min"] == 10.0
    assert id_col["numeric"]["max"] == 60.0

    # La numerica nativa sigue siendo numeric con su bloque.
    precio_col = _col(prof, "precio")
    assert precio_col["inferred_type"] == "numeric"
    assert precio_col["numeric"] is not None

    # La categorica recibe su bloque categorical.
    cat_col = _col(prof, "categoria")
    assert cat_col["inferred_type"] in ("categorical", "text")
    assert cat_col["categorical"] is not None
    assert cat_col["categorical"]["mode"] == "alfa"

    # key_candidates es una lista; quality_score existe (tabla y columnas).
    assert isinstance(prof["key_candidates"], list)
    assert prof["quality_score"] is not None
    assert id_col["quality_score"] is not None

    # type_breakdown recalculado refleja la promocion (>=2 numeric).
    assert prof["type_breakdown"]["numeric"] >= 2