import pathlib
import unittest.mock
from datetime import datetime, timedelta, timezone

import jsonpickle
import pydantic
import pytest
from freezegun import freeze_time

from datahub.ingestion.api.common import PipelineContext
from datahub.ingestion.run.pipeline import Pipeline
from datahub.ingestion.source.usage.bigquery_usage import (
    BigQueryTableRef,
    BigQueryUsageConfig,
    BigQueryUsageSource,
)
from tests.test_helpers import mce_helpers

WRITE_REFERENCE_FILE = False


FROZEN_TIME = "2021-07-20 00:00:00"


@freeze_time(FROZEN_TIME)
def test_bq_usage_config():
    config = BigQueryUsageConfig.parse_obj(
        dict(
            project_id="sample-bigquery-project-name-1234",
            bucket_duration="HOUR",
            end_time="2021-07-20T00:00:00Z",
            table_pattern={"allow": ["test-regex", "test-regex-1"], "deny": []},
        )
    )
    assert config.get_allow_pattern_string() == "test-regex|test-regex-1"
    assert config.get_deny_pattern_string() == ""
    assert (config.end_time - config.start_time) == timedelta(hours=1)
    assert config.projects == ["sample-bigquery-project-name-1234"]


@freeze_time(FROZEN_TIME)
def test_bq_timezone_validation():
    with pytest.raises(pydantic.ValidationError, match="UTC"):
        BigQueryUsageConfig.parse_obj(
            dict(
                project_id="sample-bigquery-project-name-1234",
                start_time="2021-07-20T00:00:00",
            )
        )


@freeze_time(FROZEN_TIME)
def test_bq_usage_source(pytestconfig, tmp_path):
    # from google.cloud.logging_v2 import ProtobufEntry

    test_resources_dir: pathlib.Path = (
        pytestconfig.rootpath / "tests/integration/bigquery-usage"
    )
    bigquery_reference_logs_path = test_resources_dir / "bigquery_logs.json"

    if WRITE_REFERENCE_FILE:
        source = BigQueryUsageSource.create(
            dict(
                projects=[
                    "harshal-playground-306419",
                ],
                start_time=datetime.now(tz=timezone.utc) - timedelta(days=25),
            ),
            PipelineContext(run_id="bq-usage-test"),
        )
        entries = list(
            source._get_bigquery_log_entries_via_gcp_logging(
                source._make_bigquery_logging_clients()
            )
        )

        entries = [entry._replace(logger=None) for entry in entries]
        log_entries = jsonpickle.encode(entries, indent=4)
        with bigquery_reference_logs_path.open("w") as logs:
            logs.write(log_entries)

    with unittest.mock.patch(
        "datahub.ingestion.source.usage.bigquery_usage.GCPLoggingClient", autospec=True
    ) as MockClient:
        # Add mock BigQuery API responses.
        with bigquery_reference_logs_path.open() as logs:
            reference_logs = jsonpickle.decode(logs.read())
        MockClient().list_entries.return_value = reference_logs

        # Run a BigQuery usage ingestion run.
        pipeline = Pipeline.create(
            {
                "run_id": "test-bigquery-usage",
                "source": {
                    "type": "bigquery-usage-legacy",
                    "config": {
                        "projects": ["sample-bigquery-project-1234"],
                        "start_time": "2021-01-01T00:00Z",
                        "end_time": "2021-07-01T00:00Z",
                    },
                },
                "sink": {
                    "type": "file",
                    "config": {
                        "filename": f"{tmp_path}/bigquery_usages.json",
                    },
                },
            }
        )
        pipeline.run()
        pipeline.raise_from_status()

    mce_helpers.check_golden_file(
        pytestconfig,
        output_path=tmp_path / "bigquery_usages.json",
        golden_path=test_resources_dir / "bigquery_usages_golden.json",
    )


@freeze_time(FROZEN_TIME)
def test_bq_usage_source_with_read_events(pytestconfig, tmp_path):
    # from google.cloud.logging_v2 import ProtobufEntry

    test_resources_dir: pathlib.Path = (
        pytestconfig.rootpath / "tests/integration/bigquery-usage"
    )
    bigquery_reference_logs_path = test_resources_dir / "bigquery_logs.json"

    if WRITE_REFERENCE_FILE:
        source = BigQueryUsageSource.create(
            dict(
                projects=[
                    "harshal-playground-306419",
                ],
                start_time=datetime.now(tz=timezone.utc) - timedelta(days=25),
            ),
            PipelineContext(run_id="bq-usage-test"),
        )
        entries = list(
            source._get_bigquery_log_entries_via_gcp_logging(
                source._make_bigquery_logging_clients()
            )
        )

        entries = [entry._replace(logger=None) for entry in entries]
        log_entries = jsonpickle.encode(entries, indent=4)
        with bigquery_reference_logs_path.open("w") as logs:
            logs.write(log_entries)

    with unittest.mock.patch(
        "datahub.ingestion.source.usage.bigquery_usage.GCPLoggingClient", autospec=True
    ) as MockClient:
        # Add mock BigQuery API responses.
        with bigquery_reference_logs_path.open() as logs:
            reference_logs = jsonpickle.decode(logs.read())
        MockClient().list_entries.return_value = reference_logs

        # Run a BigQuery usage ingestion run.
        pipeline = Pipeline.create(
            {
                "run_id": "test-bigquery-usage",
                "source": {
                    "type": "bigquery-usage-legacy",
                    "config": {
                        "projects": ["sample-bigquery-project-1234"],
                        "start_time": "2021-01-01T00:00Z",
                        "end_time": "2021-07-01T00:00Z",
                        "include_read_operational_stats": True,
                    },
                },
                "sink": {
                    "type": "file",
                    "config": {
                        "filename": f"{tmp_path}/bigquery_usages_with_read_events.json",
                    },
                },
            }
        )
        pipeline.run()
        pipeline.raise_from_status()

    mce_helpers.check_golden_file(
        pytestconfig,
        output_path=tmp_path / "bigquery_usages_with_read_events.json",
        golden_path=test_resources_dir / "bigquery_usages_with_read_events_golden.json",
    )


@pytest.mark.parametrize(
    "test_input,expected",
    [
        ("test_table$20220101", "test_table"),
        ("test_table$__PARTITIONS_SUMMARY__", "test_table"),
        ("test_table_20220101", "test_table"),
        ("20220101", "test_dataset"),
        ("test_table", "test_table"),
    ],
)
def test_remove_extras(test_input, expected):
    config = BigQueryUsageConfig.parse_obj(
        dict(
            project_id="sample-bigquery-project-name-1234",
        )
    )

    table_ref = BigQueryTableRef("test_project", "test_dataset", test_input)
    assert table_ref.remove_extras(config.sharded_table_pattern).table == expected