"""
Tests for src/data_pbdb.py.

Two categories:
  1. Pure-function tests (occurrences_to_field, schema validation) — run
     with hand-built record lists, no network needed at all.
  2. Mocked-HTTP tests (fetch_occurrences, discover_schema, caching,
     retries). These verify the actual pagination/retry/hard-fail
     LOGIC is correct; they do not prove PBDB's real schema matches
     REQUIRED_FIELDS — that must be confirmed by running
     `python -m src.data_pbdb --discover` against the live API.
"""
from __future__ import annotations
import json
import os
import shutil
import sys
import tempfile
from pathlib import Path
from unittest.mock import patch, MagicMock

import pytest
import torch

sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from src.data_pbdb import (
    occurrences_to_field,
    _validate_record_schema,
    _cache_key,
    fetch_occurrences,
    discover_schema,
    get_pbdb_dataset,
    PBDBFieldDataset,
    PBDBFetchError,
    REQUIRED_FIELDS,
)
from src.provenance import SchemaValidationError, DataLoadError


@pytest.fixture
def tmpdir():
    d = tempfile.mkdtemp()
    yield d
    shutil.rmtree(d, ignore_errors=True)


def make_record(max_ma, min_ma, lng, lat, genus="Testgenus"):
    return {
        "lng": lng, "lat": lat, "max_ma": max_ma, "min_ma": min_ma,
        "genus": genus,
    }


# --------------------------------------------------------------------- #
# occurrences_to_field — pure function, no network
# --------------------------------------------------------------------- #

def test_occurrences_to_field_shape():
    records = [make_record(65, 60, 10, 20), make_record(50, 45, -30, -10)]
    field = occurrences_to_field(records, n_time_bins=4, height=8, width=8)
    assert field.shape == (4, 2, 8, 8)


def test_occurrences_to_field_places_occurrence_in_correct_cell():
    records = [make_record(max_ma=100, min_ma=100, lng=0.0, lat=0.0)]
    field = occurrences_to_field(records, n_time_bins=1, height=2, width=2,
                                  age_min=0, age_max=100)
    assert field[:, 0].sum().item() == 1.0  # exactly one occurrence counted
    assert field[:, 1].sum().item() == 1.0  # exactly one distinct genus counted


def test_occurrences_to_field_raises_on_no_usable_records():
    bad_records = [{"lng": "not-a-number", "lat": 1, "max_ma": 1, "min_ma": 1}]
    with pytest.raises(SchemaValidationError) as exc_info:
        occurrences_to_field(bad_records)
    assert exc_info.value.outcome_code == "NO_USABLE_RECORDS"


def test_occurrences_to_field_raises_on_degenerate_age_range():
    records = [make_record(50, 50, 0, 0)] * 3  # all identical age
    with pytest.raises(SchemaValidationError) as exc_info:
        occurrences_to_field(records, age_min=50, age_max=50)
    assert exc_info.value.outcome_code == "DEGENERATE_AGE_RANGE"


def test_occurrences_to_field_never_fabricates_data_in_empty_cells():
    records = [make_record(max_ma=100, min_ma=100, lng=0.0, lat=0.0)]
    field = occurrences_to_field(records, n_time_bins=5, height=10, width=10,
                                  age_min=0, age_max=100)
    nonzero_cells = (field[:, 0] > 0).sum().item()
    assert nonzero_cells == 1  # only the one real occurrence's cell is nonzero


# --------------------------------------------------------------------- #
# Schema validation
# --------------------------------------------------------------------- #

def test_validate_record_schema_raises_on_missing_fields():
    records = [{"lng": 1, "lat": 2}]  # missing max_ma, min_ma, genus
    with pytest.raises(SchemaValidationError) as exc_info:
        _validate_record_schema(records)
    assert exc_info.value.outcome_code == "PBDB_SCHEMA_MISMATCH"
    assert "max_ma" in str(exc_info.value)


def test_validate_record_schema_raises_on_empty_result():
    with pytest.raises(SchemaValidationError) as exc_info:
        _validate_record_schema([])
    assert exc_info.value.outcome_code == "EMPTY_PBDB_RESULT"


def test_validate_record_schema_passes_with_all_required_fields():
    records = [make_record(65, 60, 10, 20)]
    _validate_record_schema(records)  # should not raise


def test_validate_record_schema_passes_when_field_missing_only_from_first_record():
    records = [
        {"lng": 1, "lat": 2, "max_ma": 10, "min_ma": 5},  # genus MISSING here
        {"lng": 3, "lat": 4, "max_ma": 8, "min_ma": 4, "genus": "Canis"},
    ]
    _validate_record_schema(records)  # must NOT raise


def test_validate_record_schema_still_fails_when_field_absent_from_entire_sample():
    records = [{"lng": 1, "lat": 2, "max_ma": 10, "min_ma": 5} for _ in range(10)]
    with pytest.raises(SchemaValidationError) as exc_info:
        _validate_record_schema(records)  # genus absent from all 10
    assert exc_info.value.outcome_code == "PBDB_SCHEMA_MISMATCH"


def test_validate_record_schema_only_samples_first_50_records():
    records = [{"lng": 1, "lat": 2, "max_ma": 10, "min_ma": 5} for _ in range(60)]
    records[55]["genus"] = "Canis"  # only appears past the 50-record sample window
    with pytest.raises(SchemaValidationError):
        _validate_record_schema(records)


# --------------------------------------------------------------------- #
# Cache key determinism
# --------------------------------------------------------------------- #

def test_cache_key_is_order_independent():
    k1 = _cache_key({"base_name": "Dinosauria", "show": "full"})
    k2 = _cache_key({"show": "full", "base_name": "Dinosauria"})
    assert k1 == k2


def test_cache_key_differs_for_different_params():
    k1 = _cache_key({"base_name": "Dinosauria"})
    k2 = _cache_key({"base_name": "Mammalia"})
    assert k1 != k2


# --------------------------------------------------------------------- #
# fetch_occurrences — mocked HTTP (real network blocked in this sandbox
# by paleobiodb.org's robots.txt; these verify the LOGIC, not the live
# schema — see module docstring)
# --------------------------------------------------------------------- #

def _mock_response(records, status_code=200):
    resp = MagicMock()
    resp.status_code = status_code
    resp.json.return_value = {"records": records}
    resp.text = json.dumps({"records": records})[:200]
    return resp


def test_fetch_occurrences_paginates_until_short_page(tmpdir):
    page1 = [make_record(65, 60, i, i, genus=f"g{i}") for i in range(3)]
    page2 = [make_record(50, 45, i, i, genus=f"g{i}") for i in range(2)]  # short page

    call_count = {"n": 0}
    def fake_get(url, params=None, headers=None, timeout=None):
        call_count["n"] += 1
        if params["offset"] == 0:
            return _mock_response(page1)
        return _mock_response(page2)

    with patch("requests.get", side_effect=fake_get):
        records = fetch_occurrences(
            base_name="Testtaxon", max_records=100, page_size=3,
            cache_dir=os.path.join(tmpdir, "cache"),
        )
    assert len(records) == 5  # 3 + 2, stopped because page2 was short
    assert call_count["n"] == 2


def test_fetch_occurrences_stops_at_max_records(tmpdir):
    full_page = [make_record(65, 60, i, i, genus=f"g{i}") for i in range(5)]

    def fake_get(url, params=None, headers=None, timeout=None):
        return _mock_response(full_page[: params["limit"]])

    with patch("requests.get", side_effect=fake_get):
        records = fetch_occurrences(
            base_name="Testtaxon", max_records=7, page_size=5,
            cache_dir=os.path.join(tmpdir, "cache"),
        )
    assert len(records) <= 7


def test_fetch_occurrences_hard_fails_after_retries_exhausted(tmpdir):
    def fake_get(url, params=None, headers=None, timeout=None):
        return _mock_response([], status_code=500)

    with patch("requests.get", side_effect=fake_get), \
         patch("time.sleep", return_value=None):  # skip real backoff delays in test
        with pytest.raises(PBDBFetchError) as exc_info:
            fetch_occurrences(base_name="Testtaxon", cache_dir=os.path.join(tmpdir, "cache"))
    assert exc_info.value.outcome_code == "PBDB_HTTP_ERROR"


def test_fetch_occurrences_hard_fails_on_schema_mismatch(tmpdir):
    bad_records = [{"lng": 1, "lat": 2}]  # missing max_ma/min_ma/genus

    def fake_get(url, params=None, headers=None, timeout=None):
        return _mock_response(bad_records)

    with patch("requests.get", side_effect=fake_get):
        with pytest.raises(SchemaValidationError) as exc_info:
            fetch_occurrences(base_name="Testtaxon", cache_dir=os.path.join(tmpdir, "cache"))
    assert exc_info.value.outcome_code == "PBDB_SCHEMA_MISMATCH"


def test_fetch_occurrences_uses_cache_on_second_call(tmpdir):
    records = [make_record(65, 60, 1, 1, genus="g1")]
    call_count = {"n": 0}

    def fake_get(url, params=None, headers=None, timeout=None):
        call_count["n"] += 1
        return _mock_response(records)

    cache_dir = os.path.join(tmpdir, "cache")
    with patch("requests.get", side_effect=fake_get):
        r1 = fetch_occurrences(base_name="Testtaxon", cache_dir=cache_dir)
        r2 = fetch_occurrences(base_name="Testtaxon", cache_dir=cache_dir)

    assert r1 == r2
    assert call_count["n"] == 1  # second call hit the cache, not the network


def test_discover_schema_reports_missing_fields(tmpdir):
    incomplete_records = [{"lng": 1, "lat": 2, "genus": "g1"}]  # no max_ma/min_ma

    def fake_get(url, params=None, headers=None, timeout=None):
        return _mock_response(incomplete_records)

    with patch("requests.get", side_effect=fake_get):
        result = discover_schema(base_name="Testtaxon", limit=1)

    assert "max_ma" in result["required_fields_missing"]
    assert "genus" in result["required_fields_present"]


def test_discover_schema_hard_fails_on_empty_result(tmpdir):
    def fake_get(url, params=None, headers=None, timeout=None):
        return _mock_response([])

    with patch("requests.get", side_effect=fake_get):
        with pytest.raises(PBDBFetchError) as exc_info:
            discover_schema(base_name="Nonexistenttaxon")
    assert exc_info.value.outcome_code == "PBDB_EMPTY_RESPONSE"


# --------------------------------------------------------------------- #
# End-to-end (mocked): PBDBFieldDataset / get_pbdb_dataset
# --------------------------------------------------------------------- #

def test_pbdb_field_dataset_one_trajectory_per_taxon_group(tmpdir):
    records = [make_record(max_ma=100 - i * 10, min_ma=95 - i * 10,
                            lng=i, lat=i, genus=f"g{i}") for i in range(4)]

    def fake_get(url, params=None, headers=None, timeout=None):
        return _mock_response(records)

    with patch("requests.get", side_effect=fake_get):
        ds = PBDBFieldDataset(
            taxon_groups=["TaxonA", "TaxonB", "TaxonC"],
            n_time_bins=4, height=8, width=8,
            cache_dir=os.path.join(tmpdir, "cache"),
        )
    assert len(ds) == 3
    item = ds[0]
    assert item["fields"].shape == (4, 2, 8, 8)
    assert item["taxon_group"] == "TaxonA"


def test_get_pbdb_dataset_provenance_is_real_pbdb(tmpdir):
    records = [make_record(max_ma=100 - i * 10, min_ma=95 - i * 10,
                            lng=i, lat=i, genus=f"g{i}") for i in range(4)]

    def fake_get(url, params=None, headers=None, timeout=None):
        return _mock_response(records)

    with patch("requests.get", side_effect=fake_get):
        ds, provenance = get_pbdb_dataset(
            taxon_groups=["TaxonA"], cache_dir=os.path.join(tmpdir, "cache"),
        )
    assert provenance == "REAL_PBDB"
    assert len(ds) == 1


if __name__ == "__main__":
    sys.exit(pytest.main([__file__, "-v"]))