"""/api/la-averages serves DfE's own LA averages (fact_ks4_la_averages).

It used to average the dataframe: every school with an Attainment 8,
independent and special schools included. Kensington and Chelsea came out at
35.2 against DfE's 54.5, and most LAs about 7 points low (audit H2).
"""

import numpy as np
import pandas as pd
import pytest
from fastapi.testclient import TestClient

LATEST = 202425


def _df():
    return pd.DataFrame([
        # A state school and an independent: their mean, 37.65, is not DfE's figure.
        dict(year=LATEST, local_authority="Kensington and Chelsea", local_authority_code=207, attainment_8_score=54.9),
        dict(year=LATEST, local_authority="Kensington and Chelsea", local_authority_code=207, attainment_8_score=20.4),
        dict(year=LATEST, local_authority="Bristol, City of", local_authority_code=801, attainment_8_score=45.0),
        dict(year=LATEST, local_authority="West Sussex", local_authority_code=938, attainment_8_score=48.0),
        # DfE publishes no LA figure for City of London.
        dict(year=LATEST, local_authority="City of London", local_authority_code=201, attainment_8_score=30.0),
        # A newer year with primary results only.
        dict(year=202526, local_authority="Kensington and Chelsea", local_authority_code=207, attainment_8_score=np.nan),
    ])


class _Row:
    def __init__(self, year, la_code, la_name, attainment_8_score):
        self.year = year
        self.la_code = la_code
        self.la_name = la_name
        self.attainment_8_score = attainment_8_score


class _StubSession:
    rows = [
        _Row(LATEST, 207, "Kensington and Chelsea", 54.5),
        _Row(LATEST, 801, "Bristol City", 46.3),   # DfE's spelling, not ours
        _Row(LATEST, 938, "West Sussex", None),    # suppressed
        _Row(LATEST, 330, "Birmingham", 44.0),     # no school of ours there
        _Row(202324, 207, "Kensington and Chelsea", 54.5),
    ]

    def query(self, model):
        assert model.__name__ == "Ks4LaAverage"
        return self

    def filter(self, condition):
        # The payload filters on year == <year>; apply it as Postgres would.
        self._year = condition.right.value
        return self

    def all(self):
        return [r for r in self.rows if r.year == self._year]

    def rollback(self):
        pass

    def close(self):
        pass


class _OldYearOnly(_StubSession):
    rows = [_Row(202324, 207, "Kensington and Chelsea", 54.5)]


class _NoMart(_StubSession):
    def all(self):
        raise RuntimeError('relation "marts.fact_ks4_la_averages" does not exist')


@pytest.fixture()
def payload(monkeypatch):
    from backend import app as app_module
    from backend import database as database_module

    def _run(session_cls):
        monkeypatch.setattr(database_module, "SessionLocal", session_cls)
        return app_module._la_averages_payload(_df())

    return _run


def test_serves_dfe_figures_keyed_by_our_la_names(payload):
    out = payload(_StubSession)
    assert out["year"] == LATEST
    assert out["secondary"]["attainment_8_by_la"] == {
        "Kensington and Chelsea": 54.5,
        "Bristol, City of": 46.3,
    }


def test_an_la_without_a_dfe_figure_is_absent(payload):
    by_la = payload(_StubSession)["secondary"]["attainment_8_by_la"]
    assert "City of London" not in by_la
    assert "West Sussex" not in by_la
    assert None not in by_la.values()


def test_no_dfe_figures_for_the_year_give_an_empty_map(payload):
    assert payload(_OldYearOnly) == {"year": LATEST, "secondary": {"attainment_8_by_la": {}}}


def test_a_missing_mart_gives_an_empty_map(payload):
    assert payload(_NoMart)["secondary"]["attainment_8_by_la"] == {}


def test_the_endpoint_serves_dfe_figures(monkeypatch):
    from backend import app as app_module
    from backend import database as database_module

    monkeypatch.setattr(app_module, "load_school_data", _df)
    monkeypatch.setattr(database_module, "SessionLocal", _StubSession)
    resp = TestClient(app_module.app).get("/api/la-averages")
    assert resp.status_code == 200, resp.text
    assert resp.json()["secondary"]["attainment_8_by_la"]["Kensington and Chelsea"] == 54.5