import pytest
from pydantic import ValidationError

from tht.evidence import (
    CuratedEvidence,
    dump_curated_markdown,
    load_curated_tree,
    parse_curated_markdown,
)

COMMON = {
    "schema_version": 1,
    "id": "evidence:fascia-pediatrica",
    "title": "Fascia pediatrica",
    "purposes": ["sql_generation"],
    "applies_to": {
        "concepts": ["fascia pediatrica"],
        "tables": ["clinical.patient"],
        "columns": ["clinical.patient.birth_date"],
    },
    "language": "it",
    "provenance": {
        "source_file": "source/domain/patient.md",
        "source_sha256": "sha256:" + "a" * 64,
        "supporting_excerpts": ["I pazienti sotto i 18 anni sono pediatrici."],
    },
    "review_items": [],
}


def test_formula_requires_its_typed_payload():
    with pytest.raises(ValidationError):
        CuratedEvidence.model_validate({
            **COMMON,
            "kind": "formula",
            "payload": {"concept": "fascia pediatrica"},
        })


def test_reference_rejects_formula_payload():
    with pytest.raises(ValidationError):
        CuratedEvidence.model_validate({
            **COMMON,
            "kind": "reference",
            "payload": {
                "concept": "fascia pediatrica",
                "columns": ["clinical.patient.birth_date"],
                "sql": "CASE WHEN true THEN 1 END",
            },
        })


@pytest.mark.parametrize(("kind", "payload"), [
    ("glossary", {
        "definition": "Un paziente con età inferiore a 18 anni.",
        "synonyms": ["minore"],
        "variants": ["pediatrico"],
    }),
    ("domain", {"rule": "L'età è calcolata alla data di ricovero."}),
    ("enum", {
        "column": "clinical.episode.discharge_status",
        "values": {"D": "dimesso"},
    }),
    ("example", {
        "question": "Come riconosco un paziente pediatrico?",
        "interpretation": "Applicare la formula della fascia pediatrica.",
    }),
    ("mapping", {
        "concept": "fascia pediatrica",
        "tables": ["clinical.patient"],
        "columns": ["clinical.patient.birth_date"],
    }),
    ("normalization", {
        "input": "PEDS",
        "output": "pediatrico",
        "rule": "Converte il codice abbreviato nella forma canonica.",
    }),
    ("formula", {
        "concept": "fascia pediatrica",
        "columns": ["clinical.patient.birth_date"],
        "sql": "CASE WHEN age < 18 THEN 'pediatrica' ELSE 'adulta' END",
    }),
    ("reference", {
        "url": "https://example.test/linea-guida",
        "label": "Linea guida",
        "description": "Criteri clinici di riferimento.",
    }),
])
def test_every_kind_requires_a_typed_payload(kind, payload):
    evidence = CuratedEvidence.model_validate({
        **COMMON,
        "kind": kind,
        "payload": payload,
    })

    assert evidence.kind == kind


def test_canonical_evidence_rejects_unknown_envelope_and_payload_fields():
    with pytest.raises(ValidationError):
        CuratedEvidence.model_validate({
            **COMMON,
            "kind": "domain",
            "payload": {"rule": "Una regola", "unknown": "no"},
            "unknown": "no",
        })


@pytest.mark.parametrize("purpose", ["disambiguation", "rewriting", "schema_linking", "sql_generation"])
def test_all_public_evidence_purposes_are_accepted(purpose):
    evidence = CuratedEvidence.model_validate({
        **COMMON,
        "kind": "domain",
        "purposes": [purpose],
        "payload": {"rule": "Una regola di dominio."},
    })

    assert evidence.purposes == (purpose,)


@pytest.mark.parametrize("field, value", [
    ("id", "formula:fascia-pediatrica"),
    ("purposes", ["memory"]),
    ("provenance", {
        **COMMON["provenance"],
        "source_sha256": "sha256:not-a-digest",
    }),
    ("provenance", {
        **COMMON["provenance"],
        "supporting_excerpts": [],
    }),
    ("provenance", {
        **COMMON["provenance"],
        "supporting_excerpts": ["x" * 1001],
    }),
])
def test_common_evidence_constraints_reject_invalid_values(field, value):
    with pytest.raises(ValidationError):
        CuratedEvidence.model_validate({
            **COMMON,
            field: value,
            "kind": "domain",
            "payload": {"rule": "Una regola di dominio."},
        })


def test_provenance_is_immutable_after_validation():
    evidence = CuratedEvidence.model_validate({
        **COMMON,
        "kind": "domain",
        "payload": {"rule": "Una regola di dominio."},
    })

    with pytest.raises(ValidationError):
        evidence.provenance.source_file = "source/other.md"


@pytest.mark.parametrize("sql", [
    "SELECT clinical.patient.birth_date FROM clinical.patient",
    "WITH patients AS (SELECT 1) SELECT * FROM patients",
    "DELETE FROM clinical.patient",
    "CREATE TABLE scratch (id integer)",
    "TRUNCATE TABLE clinical.patient",
    "GRANT SELECT ON clinical.patient TO reader",
    "VALUES (1)",
    "TABLE clinical.patient",
    "SET search_path = clinical",
    "CASE WHEN age < 18 THEN 'pediatrica' ELSE 'adulta' END; SELECT 1",
])
def test_formula_rejects_complete_sql_statements(sql):
    with pytest.raises(ValidationError):
        CuratedEvidence.model_validate({
            **COMMON,
            "kind": "formula",
            "payload": {
                "concept": "fascia pediatrica",
                "columns": ["clinical.patient.birth_date"],
                "sql": sql,
            },
        })


def test_formula_accepts_one_composable_postgresql_expression():
    evidence = CuratedEvidence.model_validate({
        **COMMON,
        "kind": "formula",
        "payload": {
            "concept": "fascia pediatrica",
            "columns": ["clinical.patient.birth_date"],
            "sql": "CASE WHEN age < 18 THEN 'pediatrica' ELSE 'adulta' END",
        },
    })

    assert evidence.payload.sql.startswith("CASE WHEN")


def _formula_evidence() -> CuratedEvidence:
    return CuratedEvidence.model_validate({
        **COMMON,
        "kind": "formula",
        "payload": {
            "concept": "fascia pediatrica",
            "columns": ["clinical.patient.birth_date"],
            "sql": "CASE WHEN age < 18 THEN 'pediatrica' ELSE 'adulta' END",
        },
    })


def _domain_evidence_v2() -> CuratedEvidence:
    return CuratedEvidence.model_validate({
        **COMMON,
        "schema_version": 2,
        "title": "Dominio Ablazione",
        "kind": "domain",
        "payload": {
            "rule": (
                "Il dominio Ablazione rappresenta la procedura transcatetere.\n\n"
                "La fact centrale è `clinical.fact_ablazione`."
            ),
        },
    })


def test_v2_curated_markdown_renders_domain_content_in_the_markdown_body(tmp_path):
    evidence = _domain_evidence_v2()
    path = tmp_path / "curated" / "domain" / "dominio-ablazione.md"

    text = dump_curated_markdown(evidence)
    frontmatter = text.split("---\n", 2)[1]
    parsed = parse_curated_markdown(text, path=path)

    assert "domain:" not in frontmatter
    assert "supporting_excerpts:" not in frontmatter
    assert "review_items:" not in frontmatter
    assert "# Dominio Ablazione\n" in text
    assert "## Regola\n\nIl dominio Ablazione" in text
    assert "## Estratti di supporto\n\n> I pazienti sotto i 18 anni sono pediatrici." in text
    assert parsed == evidence


@pytest.mark.parametrize(("kind", "payload", "rendered"), [
    ("glossary", {
        "definition": "Un paziente con età inferiore a 18 anni.",
        "synonyms": ["minore"],
        "variants": ["pediatrico"],
    }, "## Sinonimi\n\n- minore"),
    ("enum", {
        "column": "clinical.episode.discharge_status",
        "values": {"D": "dimesso", "T": "trasferito | altra struttura"},
    }, "| `D` | dimesso |"),
    ("example", {
        "question": "Come riconosco un paziente pediatrico?",
        "interpretation": "Applicare la formula della fascia pediatrica.",
    }, "## Domanda\n\nCome riconosco un paziente pediatrico?"),
    ("mapping", {
        "concept": "fascia pediatrica",
        "tables": ["clinical.patient"],
        "columns": ["clinical.patient.birth_date"],
    }, "## Tabelle\n\n- `clinical.patient`"),
    ("normalization", {
        "input": "PEDS",
        "output": "pediatrico",
        "rule": "Converte il codice abbreviato nella forma canonica.",
    }, "## Output\n\npediatrico"),
    ("formula", {
        "concept": "fascia pediatrica",
        "columns": ["clinical.patient.birth_date"],
        "sql": "CASE WHEN age < 18 THEN 'pediatrica' ELSE 'adulta' END",
    }, "```sql\nCASE WHEN age < 18"),
    ("reference", {
        "url": "https://example.test/linea-guida",
        "label": "Linea guida",
        "description": "Criteri clinici di riferimento.",
    }, "## URL\n\n<https://example.test/linea-guida>"),
])
def test_v2_curated_markdown_renders_and_round_trips_every_typed_payload(
    tmp_path, kind, payload, rendered,
):
    evidence = CuratedEvidence.model_validate({
        **COMMON,
        "schema_version": 2,
        "kind": kind,
        "payload": payload,
    })
    path = tmp_path / "curated" / kind / "fascia-pediatrica.md"

    text = dump_curated_markdown(evidence)

    assert rendered in text
    assert parse_curated_markdown(text, path=path) == evidence


def test_v2_curated_markdown_renders_review_items_as_readable_blocks(tmp_path):
    evidence = CuratedEvidence.model_validate({
        **COMMON,
        "schema_version": 2,
        "kind": "domain",
        "review_items": [{
            "code": "ambiguous_source_statement",
            "message": "Il sorgente non chiarisce la data di riferimento.",
            "field": "domain.rule",
        }],
        "payload": {"rule": "L'età è calcolata alla data di ricovero."},
    })
    path = tmp_path / "curated" / "domain" / "fascia-pediatrica.md"

    text = dump_curated_markdown(evidence)

    assert "## Elementi da rivedere" in text
    assert "### `ambiguous_source_statement`" in text
    assert "Il sorgente non chiarisce la data di riferimento." in text
    assert "**Campo:** `domain.rule`" in text
    assert parse_curated_markdown(text, path=path) == evidence


@pytest.mark.parametrize("legacy_field", [
    "review_items: []\n",
    "payload:\n  rule: should-not-be-ignored\n",
])
def test_v2_curated_markdown_rejects_body_owned_fields_in_frontmatter(legacy_field):
    text = dump_curated_markdown(_domain_evidence_v2()).replace(
        "kind: domain\n",
        f"kind: domain\n{legacy_field}",
    )

    with pytest.raises(ValueError, match="frontmatter"):
        parse_curated_markdown(text)


def test_v2_curated_markdown_rejects_unstructured_body_content():
    text = dump_curated_markdown(_domain_evidence_v2()) + "should-not-be-ignored\n"

    with pytest.raises(ValueError, match="unstructured"):
        parse_curated_markdown(text)


def test_v2_curated_markdown_round_trips_an_empty_enum_as_an_explicit_empty_state(tmp_path):
    evidence = CuratedEvidence.model_validate({
        **COMMON,
        "schema_version": 2,
        "kind": "enum",
        "payload": {
            "column": "clinical.episode.discharge_status",
            "values": {},
        },
    })

    text = dump_curated_markdown(evidence)

    assert "Nessun elemento" in text
    assert parse_curated_markdown(
        text,
        path=tmp_path / "curated" / "enum" / "discharge-status.md",
    ) == evidence


def test_curated_markdown_round_trip_uses_the_kind_specific_key(tmp_path):
    evidence = _formula_evidence()
    path = tmp_path / "curated" / "formula" / "fascia-pediatrica.md"

    text = dump_curated_markdown(evidence)
    parsed = parse_curated_markdown(text, path=path)

    assert "formula:" in text
    assert "payload:" not in text
    assert parsed == evidence


def test_curated_markdown_rejects_a_kind_that_disagrees_with_its_directory(tmp_path):
    text = dump_curated_markdown(_formula_evidence())

    with pytest.raises(ValueError, match="directory"):
        parse_curated_markdown(text, path=tmp_path / "curated" / "reference" / "guide.md")


def test_load_curated_tree_returns_documents_in_path_order_and_ignores_readmes(tmp_path):
    root = tmp_path / "curated"
    formula_path = root / "formula" / "fascia-pediatrica.md"
    domain_path = root / "domain" / "eta.md"
    formula_path.parent.mkdir(parents=True)
    domain_path.parent.mkdir(parents=True)
    formula_path.write_text(dump_curated_markdown(_formula_evidence()), encoding="utf-8")
    domain_path.write_text(dump_curated_markdown(CuratedEvidence.model_validate({
        **COMMON,
        "id": "evidence:eta-ricovero",
        "title": "Età al ricovero",
        "kind": "domain",
        "payload": {"rule": "L'età è calcolata al ricovero."},
    })), encoding="utf-8")
    (root / "README.md").write_text("solo navigazione", encoding="utf-8")

    loaded = load_curated_tree(root)

    assert [item.id for item in loaded] == [
        "evidence:eta-ricovero",
        "evidence:fascia-pediatrica",
    ]


@pytest.mark.parametrize(("source_file", "reference_url"), [
    ("source/domain/patient.pdf", "https://example.test/linea-guida"),
    ("../patient.md", "https://example.test/linea-guida"),
    ("source/domain/patient.md", "https://user:secret@example.test/linea-guida"),
    ("source/domain/patient.md", "https://example.test/linea-guida?access_token=secret"),
])
def test_canonical_evidence_rejects_unsafe_source_or_url(source_file, reference_url):
    with pytest.raises(ValidationError):
        CuratedEvidence.model_validate({
            **COMMON,
            "kind": "reference",
            "provenance": {**COMMON["provenance"], "source_file": source_file},
            "payload": {
                "url": reference_url,
                "label": "Linea guida",
                "description": "Criteri clinici.",
            },
        })


def test_curated_markdown_rejects_nonempty_body_instead_of_ignoring_it():
    text = dump_curated_markdown(_formula_evidence()) + "password: should-not-be-ignored\n"

    with pytest.raises(ValueError, match="body"):
        parse_curated_markdown(text)


@pytest.mark.parametrize(("scope", "payload"), [
    (
        {"tables": ["patient"], "columns": ["clinical.patient.birth_date"]},
        {"rule": "Una regola."},
    ),
    (
        {"tables": ["clinical.patient"], "columns": ["clinical.patient.date.of.birth"]},
        {"rule": "Una regola."},
    ),
    (
        {"tables": ["clinical.patient"], "columns": ["clinical.patient.birth_date"]},
        {
            "concept": "fascia pediatrica",
            "columns": ["clinical.patient"],
            "sql": "CASE WHEN age < 18 THEN 1 ELSE 0 END",
        },
    ),
])
def test_schema_identifiers_require_table_or_column_shape(scope, payload):
    with pytest.raises(ValidationError):
        CuratedEvidence.model_validate({
            **COMMON,
            "kind": "formula" if "sql" in payload else "domain",
            "applies_to": scope,
            "payload": payload,
        })


def test_load_curated_tree_rejects_non_utf8_and_oversized_files(tmp_path, monkeypatch):
    root = tmp_path / "curated"
    path = root / "domain" / "eta.md"
    path.parent.mkdir(parents=True)
    path.write_bytes(b"\xff")

    with pytest.raises(ValueError, match="UTF-8"):
        load_curated_tree(root)

    path.write_text(dump_curated_markdown(CuratedEvidence.model_validate({
        **COMMON,
        "kind": "domain",
        "payload": {"rule": "Una regola."},
    })), encoding="utf-8")
    monkeypatch.setattr("tht.evidence.canonical.MAX_CURATED_FILE_BYTES", 1)

    with pytest.raises(ValueError, match="size limit"):
        load_curated_tree(root)