# mypy: disable-error-code=name-defined
"""Amazon NeptuneClient Module."""

import json
import logging
from typing import Any, Dict, List, Optional, TypedDict, Union, cast

import boto3
from botocore.auth import SigV4Auth
from botocore.awsrequest import AWSPreparedRequest, AWSRequest
from typing_extensions import Literal, NotRequired

import awswrangler.neptune._gremlin_init as gremlin
from awswrangler import _utils, exceptions
from awswrangler.neptune._gremlin_parser import GremlinParser

gremlin_python = _utils.import_optional_dependency("gremlin_python")
opencypher = _utils.import_optional_dependency("requests")
sparql = _utils.import_optional_dependency("SPARQLWrapper")
if any((gremlin_python, opencypher, sparql)):
    import requests

_logger: logging.Logger = logging.getLogger(__name__)


DEFAULT_PORT = 8182
NEPTUNE_SERVICE_NAME = "neptune-db"
HTTP_PROTOCOL = "https"
WS_PROTOCOL = "wss"


class BulkLoadParserConfiguration(TypedDict):
    """Typed dictionary representing the additional parser configuration for the Neptune Bulk Loader."""

    namedGraphUri: NotRequired[str]
    """
    The default graph for all RDF formats when no graph is specified
    (for non-quads formats and NQUAD entries with no graph).
    """
    baseUri: NotRequired[str]
    """The base URI for RDF/XML and Turtle formats."""
    allowEmptyStrings: NotRequired[bool]
    """
    Gremlin users need to be able to pass empty string values("") as node
    and edge properties when loading CSV data.
    If ``allowEmptyStrings`` is set to ``false`` (the default),
    such empty strings are treated as nulls and are not loaded.

    If allowEmptyStrings is set to true, the loader treats empty strings
    as valid property values and loads them accordingly.
    """


class NeptuneClient:
    """Class representing a Neptune cluster connection."""

    def __init__(
        self,
        host: str,
        port: int = DEFAULT_PORT,
        iam_enabled: bool = False,
        boto3_session: Optional[boto3.Session] = None,
        region: Optional[str] = None,
    ):
        self.host = host
        self.port = port
        self.iam_enabled = iam_enabled
        self.boto3_session = self.__ensure_session(session=boto3_session)
        if region is None:
            self.region = self.__get_region_from_session()
        else:
            self.region = region
        self._http_session = requests.Session()
        self.gremlin_connection = None

    def __del__(self) -> None:
        """Close the Gremlin connection."""
        if isinstance(self.gremlin_connection, gremlin.Client):
            self.gremlin_connection.close()

    def __get_region_from_session(self) -> str:
        """Extract region from session."""
        region: Optional[str] = self.boto3_session.region_name
        if region is not None:
            return region
        raise exceptions.InvalidArgument("There is no region_name defined on boto3, please configure it.")

    @staticmethod
    def __ensure_session(session: Optional[boto3.Session] = None) -> boto3.Session:
        """Ensure that a valid boto3.Session will be returned."""
        if session is not None:
            return session
        if boto3.DEFAULT_SESSION:
            return boto3.DEFAULT_SESSION

        return boto3.Session()

    def _prepare_request(
        self,
        method: str,
        url: str,
        *,
        data: Any = None,
        params: Any = None,
        headers: Any = None,
        service: str = NEPTUNE_SERVICE_NAME,
    ) -> "requests.PreparedRequest":
        request = requests.Request(method=method, url=url, data=data, params=params, headers=headers)
        if self.boto3_session is not None:
            aws_request = self._get_aws_request(
                method=method, url=url, data=data, params=params, headers=headers, service=service
            )
            request.headers = dict(aws_request.headers)

        return request.prepare()

    def _get_aws_request(
        self,
        method: str,
        url: str,
        *,
        data: Any = None,
        params: Any = None,
        headers: Any = None,
        service: str = NEPTUNE_SERVICE_NAME,
    ) -> Union[AWSRequest, AWSPreparedRequest]:
        req = AWSRequest(method=method, url=url, data=data, params=params, headers=headers)
        if self.iam_enabled:
            credentials = self.boto3_session.get_credentials()
            try:
                frozen_creds = credentials.get_frozen_credentials()
            except AttributeError:
                _logger.warning("Could not find valid IAM credentials in any the following locations:\n")
                _logger.warning(
                    "env, assume-role, assume-role-with-web-identity, sso, shared-credential-file, custom-process, "
                    "config-file, ec2-credentials-file, boto-config, container-role, iam-role\n"
                )
                _logger.warning(
                    "Go to https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html for more "
                    "details on configuring your IAM credentials."
                )
                return req
            SigV4Auth(frozen_creds, service, self.region).add_auth(req)
            prepared_iam_req = req.prepare()
            return prepared_iam_req
        return req

    def read_opencypher(self, query: str, headers: Any = None) -> Any:
        """Execute the provided openCypher query.

        Parameters
        ----------
        query : str
            The query to execute
        headers : Any, optional
            Any additional headers that should be associated with the query. Defaults to None.

        Returns
        -------
        Any
            The result of the query.
        """
        if headers is None:
            headers = {}

        if "content-type" not in headers:
            headers["content-type"] = "application/x-www-form-urlencoded"

        url = f"{HTTP_PROTOCOL}://{self.host}:{self.port}/openCypher"
        data = {"query": query}

        req = self._prepare_request("POST", url, data=data, headers=headers)
        res = self._http_session.send(req)
        _logger.debug(res)
        if res.ok:
            return res.json()["results"]
        raise exceptions.QueryFailed(f"Status Code: {res.status_code} Reason: {res.reason} Message: {res.text}")

    def read_gremlin(self, query: str, headers: Any = None) -> List[Dict[str, Any]]:
        """Execute the provided Gremlin traversal and returns the results.

        Parameters
        ----------
        query : str
            The Gremlin query

        Returns
        -------
        Dict[str, Any]
            Dictionary with the results
        """
        return self._execute_gremlin(query, headers)

    def write_gremlin(self, query: str) -> bool:
        """Execute a Gremlin write query.

        Parameters
        ----------
            query (str): The query to execute

        Returns
        -------
        bool
            The success of the Gremlin write query
        """
        res = self._execute_gremlin(query)
        _logger.debug(res)
        return True

    def _execute_gremlin(self, query: str, headers: Any = None) -> List[Dict[str, Any]]:
        try:
            c = self._get_gremlin_connection(headers)
            result = c.submit(query)
            future_results = result.all()
            results = future_results.result()
            return GremlinParser.gremlin_results_to_dict(results)
        except Exception as e:
            if isinstance(self.gremlin_connection, gremlin.Client):
                self.gremlin_connection.close()
            self.gremlin_connection = None
            _logger.error(e)
            raise exceptions.QueryFailed(e)

    def _get_gremlin_connection(self, headers: Any = None) -> "gremlin.Client":
        if self.gremlin_connection is None:
            uri = f"{HTTP_PROTOCOL}://{self.host}:{self.port}/gremlin"
            request = self._prepare_request("GET", uri, headers=headers)
            ws_url = f"{WS_PROTOCOL}://{self.host}:{self.port}/gremlin"
            self.gremlin_connection = gremlin.Client(
                ws_url, "g", headers=dict(request.headers), call_from_event_loop=True
            )
        return self.gremlin_connection

    def read_sparql(self, query: str, headers: Any = None) -> Any:
        """Execute the given query and returns the results.

        Parameters
        ----------
        query : str
            The SPARQL query to execute
        headers : Any, optional
            Any additional headers to include with the request. Defaults to None.

        Returns
        -------
        Any
            [description]
        """
        res = self._execute_sparql(query, headers)
        _logger.debug(res)
        return res

    def write_sparql(self, query: str, headers: Any = None) -> bool:
        """Execute the specified SPARQL write statements.

        Parameters
        ----------
        query : str
            The SPARQL query to execute
        headers : Any, optional
            Any additional headers to include with the request. Defaults to None.

        Returns
        -------
        bool
            The success of the query
        """
        self._execute_sparql(query, headers)
        return True

    def _execute_sparql(self, query: str, headers: Any) -> Any:
        if headers is None:
            headers = {}

        s = sparql.SPARQLWrapper("")
        s.setQuery(query)
        query_type = str(s.queryType).upper()
        if query_type in ["SELECT", "CONSTRUCT", "ASK", "DESCRIBE"]:
            data = {"query": query}
        else:
            data = {"update": query}

        if "content-type" not in headers:
            headers["content-type"] = "application/x-www-form-urlencoded"

        uri = f"{HTTP_PROTOCOL}://{self.host}:{self.port}/sparql"
        req = self._prepare_request("POST", uri, data=data, headers=headers)
        res = self._http_session.send(req)
        _logger.debug(res)
        if res.ok:
            return res.json()
        raise exceptions.QueryFailed(f"Status Code: {res.status_code} Reason: {res.reason} Message: {res.text}")

    def status(self) -> Any:
        """Return the status of the Neptune cluster.

        Returns
        -------
        str
            The result of the call to the status API for the Neptune cluster
        """
        url = f"{HTTP_PROTOCOL}://{self.host}:{self.port}/status"
        req = self._prepare_request("GET", url, data="")
        res = self._http_session.send(req)
        return res.json()

    def load(
        self,
        s3_path: str,
        role_arn: str,
        parallelism: Literal["LOW", "MEDIUM", "HIGH", "OVERSUBSCRIBE"] = "HIGH",
        mode: Literal["RESUME", "NEW", "AUTO"] = "AUTO",
        format: str = "csv",
        parser_configuration: Optional[BulkLoadParserConfiguration] = None,
        update_single_cardinality_properties: Literal["TRUE", "FALSE"] = "FALSE",
        queue_request: Literal["TRUE", "FALSE"] = "FALSE",
        dependencies: Optional[List[str]] = None,
    ) -> str:
        """
        Start the Neptune Loader command for loading CSV data from external files on S3 into a Neptune DB cluster.

        Parameters
        ----------
        s3_path: str
            Amazon S3 URI that identifies a single file, multiple files, a folder, or multiple folders.
            Neptune loads every data file in any folder that is specified.
        role_arn: str
            The Amazon Resource Name (ARN) for an IAM role to be assumed by the Neptune DB instance for access to the S3 bucket.
            For information about creating a role that has access to Amazon S3 and then associating it with a Neptune cluster,
            see `Prerequisites: IAM Role and Amazon S3 Access <https://docs.aws.amazon.com/neptune/latest/userguide/bulk-load-tutorial-IAM.html>`_.
        parallelism: str
            Specifies the number of threads used by the bulk load process.
        mode: str
            The load job mode.

            In ```RESUME``` mode, the loader looks for a previous load from this source, and if it finds one, resumes that load job.
            If no previous load job is found, the loader stops.

            In ```NEW``` mode, the creates a new load request regardless of any previous loads.
            You can use this mode to reload all the data from a source after dropping previously loaded data from your Neptune cluster, or to load new data available at the same source.

            In ```AUTO``` mode, the loader looks for a previous load job from the same source, and if it finds one, resumes that job, just as in ```RESUME``` mode.
        format: str
            The format of the data. For more information about data formats for the Neptune Loader command,
            see `Using the Amazon Neptune Bulk Loader to Ingest Data <https://docs.aws.amazon.com/neptune/latest/userguide/load-api-reference-load.html#:~:text=The%20format%20of%20the%20data.%20For%20more%20information%20about%20data%20formats%20for%20the%20Neptune%20Loader%20command%2C%20see%20Using%20the%20Amazon%20Neptune%20Bulk%20Loader%20to%20Ingest%20Data.>`_.
        parser_configuration: dict[str, Any], optional
            An optional object with additional parser configuration values.
            Each of the child parameters is also optional: ``namedGraphUri``, ``baseUri`` and ``allowEmptyStrings``.
        update_single_cardinality_properties: str
            An optional parameter that controls how the bulk loader
            treats a new value for single-cardinality vertex or edge properties.
        queue_request: str
            An optional flag parameter that indicates whether the load request can be queued up or not.

            If omitted or set to ``"FALSE"``, the load request will fail if another load job is already running.
        dependencies: list[str], optional
            An optional parameter that can make a queued load request contingent on the successful completion of one or more previous jobs in the queue.

        Returns
        -------
        str
            ID of the load job
        """
        data: Dict[str, Any] = {
            "source": s3_path,
            "format": format,
            "iamRoleArn": role_arn,
            "mode": mode,
            "region": self.region,
            "failOnError": "TRUE",
            "parallelism": parallelism,
            "updateSingleCardinalityProperties": update_single_cardinality_properties,
            "queueRequest": queue_request,
        }
        if parser_configuration:
            data["parserConfiguration"] = parser_configuration
        if dependencies:
            data["dependencies"] = dependencies

        url = f"https://{self.host}:{self.port}/loader"

        req = self._prepare_request(
            method="POST",
            url=url,
            data=json.dumps(data),
            headers={"Content-Type": "application/json; charset=utf-8"},
        )
        res = self._http_session.send(req)

        _logger.debug(res)
        if res.ok:
            return cast(str, res.json()["payload"]["loadId"])

        raise exceptions.NeptuneLoadError(f"Status Code: {res.status_code} Reason: {res.reason} Message: {res.text}")

    def load_status(self, load_id: str) -> Any:
        """
        Return the status of the load job to the Neptune cluster.

        Parameters
        ----------
        load_id: str
            ID of the load job

        Returns
        -------
        dict[str, Any]
            The result of the call to the status API for the load job.
            See `Neptune Loader Get-Status Responses <https://docs.aws.amazon.com/neptune/latest/userguide/load-api-reference-status-response.html>_`
        """
        url = f"https://{self.host}:{self.port}/loader/{load_id}"

        req = self._prepare_request("GET", url, data="")
        res = self._http_session.send(req)

        if res.ok:
            return res.json()

        raise exceptions.NeptuneLoadError(f"Status Code: {res.status_code} Reason: {res.reason} Message: {res.text}")
