from abc import ABCMeta
from abc import abstractmethod

from collections import OrderedDict
from copy import deepcopy
import math
from datetime import datetime
from typing import Any, Dict, List, Optional

from moto.core import BaseBackend, BackendDict, BaseModel
from moto.core.utils import underscores_to_camelcase
from moto.core.utils import camelcase_to_pascal

from moto.utilities.paginator import paginate

from .exceptions import (
    AlreadyExistsException,
    ConflictException,
    ValidationException,
    RulesetAlreadyExistsException,
    RulesetNotFoundException,
    ResourceNotFoundException,
)


class DataBrewBackend(BaseBackend):
    PAGINATION_MODEL = {
        "list_recipes": {
            "input_token": "next_token",
            "limit_key": "max_results",
            "limit_default": 100,
            "unique_attribute": "name",
        },
        "list_recipe_versions": {
            "input_token": "next_token",
            "limit_key": "max_results",
            "limit_default": 100,
            "unique_attribute": "name",
        },
        "list_rulesets": {
            "input_token": "next_token",
            "limit_key": "max_results",
            "limit_default": 100,
            "unique_attribute": "name",
        },
        "list_datasets": {
            "input_token": "next_token",
            "limit_key": "max_results",
            "limit_default": 100,
            "unique_attribute": "name",
        },
        "list_jobs": {
            "input_token": "next_token",
            "limit_key": "max_results",
            "limit_default": 100,
            "unique_attribute": "name",
        },
    }

    def __init__(self, region_name: str, account_id: str):
        super().__init__(region_name, account_id)
        self.recipes: Dict[str, FakeRecipe] = OrderedDict()
        self.rulesets: Dict[str, FakeRuleset] = OrderedDict()
        self.datasets: Dict[str, FakeDataset] = OrderedDict()
        self.jobs: Dict[str, FakeJob] = OrderedDict()

    @staticmethod
    def validate_length(param: str, param_name: str, max_length: int) -> None:
        if len(param) > max_length:
            raise ValidationException(
                f"1 validation error detected: Value '{param}' at '{param_name}' failed to "
                f"satisfy constraint: Member must have length less than or equal to {max_length}"
            )

    def create_recipe(
        self,
        recipe_name: str,
        recipe_description: str,
        recipe_steps: List[Dict[str, Any]],
        tags: Dict[str, str],
    ) -> "FakeRecipeVersion":
        # https://docs.aws.amazon.com/databrew/latest/dg/API_CreateRecipe.html
        if recipe_name in self.recipes:
            raise ConflictException(f"The recipe {recipe_name} already exists")

        recipe = FakeRecipe(
            self.region_name, recipe_name, recipe_description, recipe_steps, tags
        )
        self.recipes[recipe_name] = recipe
        return recipe.latest_working

    def delete_recipe_version(self, recipe_name: str, recipe_version: str) -> None:
        if not FakeRecipe.version_is_valid(recipe_version, latest_published=False):
            raise ValidationException(
                f"Recipe {recipe_name} version {recipe_version} is invalid."
            )

        try:
            recipe = self.recipes[recipe_name]
        except KeyError:
            raise ResourceNotFoundException(f"The recipe {recipe_name} wasn't found")

        if (
            recipe_version != FakeRecipe.LATEST_WORKING
            and float(recipe_version) not in recipe.versions
        ):
            raise ResourceNotFoundException(
                f"The recipe {recipe_name} version {recipe_version } wasn't found."
            )

        if recipe_version in (
            FakeRecipe.LATEST_WORKING,
            str(recipe.latest_working.version),
        ):
            if recipe.latest_published is not None:
                # Can only delete latest working version when there are no others
                raise ValidationException(
                    f"Recipe version {recipe_version} is not allowed to be deleted"
                )
            else:
                del self.recipes[recipe_name]
        else:
            recipe.delete_published_version(recipe_version)

    def update_recipe(
        self,
        recipe_name: str,
        recipe_description: str,
        recipe_steps: List[Dict[str, Any]],
    ) -> None:
        if recipe_name not in self.recipes:
            raise ResourceNotFoundException(f"The recipe {recipe_name} wasn't found")

        recipe = self.recipes[recipe_name]
        recipe.update(recipe_description, recipe_steps)

    @paginate(pagination_model=PAGINATION_MODEL)  # type: ignore[misc]
    def list_recipes(
        self, recipe_version: Optional[str] = None
    ) -> List["FakeRecipeVersion"]:
        # https://docs.aws.amazon.com/databrew/latest/dg/API_ListRecipes.html
        if recipe_version == FakeRecipe.LATEST_WORKING:
            version = "latest_working"
        elif recipe_version in (None, FakeRecipe.LATEST_PUBLISHED):
            version = "latest_published"
        else:
            raise ValidationException(
                f"Invalid version {recipe_version}. "
                "Valid versions are LATEST_PUBLISHED and LATEST_WORKING."
            )
        recipes = [getattr(self.recipes[key], version) for key in self.recipes]
        return [r for r in recipes if r is not None]

    @paginate(pagination_model=PAGINATION_MODEL)  # type: ignore[misc]
    def list_recipe_versions(self, recipe_name: str) -> List["FakeRecipeVersion"]:
        # https://docs.aws.amazon.com/databrew/latest/dg/API_ListRecipeVersions.html
        self.validate_length(recipe_name, "name", 255)

        recipe = self.recipes.get(recipe_name)
        if recipe is None:
            return []

        latest_working = recipe.latest_working

        recipe_versions = [
            recipe_version
            for recipe_version in recipe.versions.values()
            if recipe_version is not latest_working
        ]
        return [r for r in recipe_versions if r is not None]

    def describe_recipe(
        self, recipe_name: str, recipe_version: Optional[str] = None
    ) -> "FakeRecipeVersion":
        # https://docs.aws.amazon.com/databrew/latest/dg/API_DescribeRecipe.html
        self.validate_length(recipe_name, "name", 255)

        if recipe_version is None:
            recipe_version = FakeRecipe.LATEST_PUBLISHED
        else:
            self.validate_length(recipe_version, "recipeVersion", 16)
            if not FakeRecipe.version_is_valid(recipe_version):
                raise ValidationException(
                    f"Recipe {recipe_name} version {recipe_version} isn't valid."
                )

        recipe = None
        if recipe_name in self.recipes:
            if recipe_version == FakeRecipe.LATEST_PUBLISHED:
                recipe = self.recipes[recipe_name].latest_published
            elif recipe_version == FakeRecipe.LATEST_WORKING:
                recipe = self.recipes[recipe_name].latest_working
            else:
                recipe = self.recipes[recipe_name].versions.get(float(recipe_version))
        if recipe is None:
            raise ResourceNotFoundException(
                f"The recipe {recipe_name} for version {recipe_version} wasn't found."
            )
        return recipe

    def publish_recipe(
        self, recipe_name: str, description: Optional[str] = None
    ) -> None:
        # https://docs.aws.amazon.com/databrew/latest/dg/API_PublishRecipe.html
        self.validate_length(recipe_name, "name", 255)
        try:
            self.recipes[recipe_name].publish(description)
        except KeyError:
            raise ResourceNotFoundException(f"Recipe {recipe_name} wasn't found")

    def create_ruleset(
        self,
        ruleset_name: str,
        ruleset_description: str,
        ruleset_rules: List[Dict[str, Any]],
        ruleset_target_arn: str,
        tags: Dict[str, str],
    ) -> "FakeRuleset":
        if ruleset_name in self.rulesets:
            raise RulesetAlreadyExistsException()

        ruleset = FakeRuleset(
            self.region_name,
            ruleset_name,
            ruleset_description,
            ruleset_rules,
            ruleset_target_arn,
            tags,
        )
        self.rulesets[ruleset_name] = ruleset
        return ruleset

    def update_ruleset(
        self,
        ruleset_name: str,
        ruleset_description: str,
        ruleset_rules: List[Dict[str, Any]],
        tags: Dict[str, str],
    ) -> "FakeRuleset":
        if ruleset_name not in self.rulesets:
            raise RulesetNotFoundException(ruleset_name)

        ruleset = self.rulesets[ruleset_name]
        if ruleset_description is not None:
            ruleset.description = ruleset_description
        if ruleset_rules is not None:
            ruleset.rules = ruleset_rules
        if tags is not None:
            ruleset.tags = tags

        return ruleset

    def describe_ruleset(self, ruleset_name: str) -> "FakeRuleset":
        if ruleset_name not in self.rulesets:
            raise RulesetNotFoundException(ruleset_name)
        return self.rulesets[ruleset_name]

    @paginate(pagination_model=PAGINATION_MODEL)  # type: ignore[misc]
    def list_rulesets(self) -> List["FakeRuleset"]:
        return list(self.rulesets.values())

    def delete_ruleset(self, ruleset_name: str) -> None:
        if ruleset_name not in self.rulesets:
            raise RulesetNotFoundException(ruleset_name)

        del self.rulesets[ruleset_name]

    def create_dataset(
        self,
        dataset_name: str,
        dataset_format: str,
        dataset_format_options: Dict[str, Any],
        dataset_input: Dict[str, Any],
        dataset_path_options: Dict[str, Any],
        tags: Dict[str, str],
    ) -> "FakeDataset":
        if dataset_name in self.datasets:
            raise AlreadyExistsException(dataset_name)

        dataset = FakeDataset(
            self.region_name,
            self.account_id,
            dataset_name,
            dataset_format,
            dataset_format_options,
            dataset_input,
            dataset_path_options,
            tags,
        )
        self.datasets[dataset_name] = dataset
        return dataset

    @paginate(pagination_model=PAGINATION_MODEL)  # type: ignore[misc]
    def list_datasets(self) -> List["FakeDataset"]:
        return list(self.datasets.values())

    def update_dataset(
        self,
        dataset_name: str,
        dataset_format: str,
        dataset_format_options: Dict[str, Any],
        dataset_input: Dict[str, Any],
        dataset_path_options: Dict[str, Any],
        tags: Dict[str, str],
    ) -> "FakeDataset":

        if dataset_name not in self.datasets:
            raise ResourceNotFoundException("One or more resources can't be found.")

        dataset = self.datasets[dataset_name]

        if dataset_format is not None:
            dataset.format = dataset_format
        if dataset_format_options is not None:
            dataset.format_options = dataset_format_options
        if dataset_input is not None:
            dataset.input = dataset_input
        if dataset_path_options is not None:
            dataset.path_options = dataset_path_options
        if tags is not None:
            dataset.tags = tags

        return dataset

    def delete_dataset(self, dataset_name: str) -> None:
        if dataset_name not in self.datasets:
            raise ResourceNotFoundException("One or more resources can't be found.")

        del self.datasets[dataset_name]

    def describe_dataset(self, dataset_name: str) -> "FakeDataset":
        if dataset_name not in self.datasets:
            raise ResourceNotFoundException("One or more resources can't be found.")

        return self.datasets[dataset_name]

    def describe_job(self, job_name: str) -> "FakeJob":
        # https://docs.aws.amazon.com/databrew/latest/dg/API_DescribeJob.html
        self.validate_length(job_name, "name", 240)

        if job_name not in self.jobs:
            raise ResourceNotFoundException(f"Job {job_name} wasn't found.")

        return self.jobs[job_name]

    def delete_job(self, job_name: str) -> None:
        # https://docs.aws.amazon.com/databrew/latest/dg/API_DeleteJob.html
        self.validate_length(job_name, "name", 240)

        if job_name not in self.jobs:
            raise ResourceNotFoundException(f"The job {job_name} wasn't found.")

        del self.jobs[job_name]

    def create_profile_job(self, **kwargs: Any) -> "FakeProfileJob":
        # https://docs.aws.amazon.com/databrew/latest/dg/API_CreateProfileJob.html
        job_name = kwargs["name"]
        self.validate_length(job_name, "name", 240)

        if job_name in self.jobs:
            raise ConflictException(
                f"The job {job_name} {self.jobs[job_name].job_type.lower()} job already exists."
            )

        job = FakeProfileJob(
            account_id=self.account_id, region_name=self.region_name, **kwargs
        )

        self.jobs[job_name] = job
        return job

    def create_recipe_job(self, **kwargs: Any) -> "FakeRecipeJob":
        # https://docs.aws.amazon.com/databrew/latest/dg/API_CreateRecipeJob.html
        job_name = kwargs["name"]
        self.validate_length(job_name, "name", 240)

        if job_name in self.jobs:
            raise ConflictException(
                f"The job {job_name} {self.jobs[job_name].job_type.lower()} job already exists."
            )

        job = FakeRecipeJob(
            account_id=self.account_id, region_name=self.region_name, **kwargs
        )

        self.jobs[job_name] = job
        return job

    def update_job(self, **kwargs: Any) -> "FakeJob":
        job_name = kwargs["name"]
        self.validate_length(job_name, "name", 240)

        if job_name not in self.jobs:
            raise ResourceNotFoundException(f"The job {job_name} wasn't found")

        job = self.jobs[job_name]

        for param, value in kwargs.items():
            setattr(job, param, value)
        return job

    def update_recipe_job(self, **kwargs: Any) -> "FakeJob":
        # https://docs.aws.amazon.com/databrew/latest/dg/API_UpdateRecipeJob.html
        return self.update_job(**kwargs)

    def update_profile_job(self, **kwargs: Any) -> "FakeJob":
        # https://docs.aws.amazon.com/databrew/latest/dg/API_UpdateProfileJob.html
        return self.update_job(**kwargs)

    @paginate(pagination_model=PAGINATION_MODEL)  # type: ignore[misc]
    def list_jobs(
        self, dataset_name: Optional[str] = None, project_name: Optional[str] = None
    ) -> List["FakeJob"]:
        # https://docs.aws.amazon.com/databrew/latest/dg/API_ListJobs.html
        if dataset_name is not None:
            self.validate_length(dataset_name, "datasetName", 255)
        if project_name is not None:
            self.validate_length(project_name, "projectName", 255)

        def filter_jobs(job: FakeJob) -> bool:
            if dataset_name is not None and job.dataset_name != dataset_name:
                return False
            if (
                project_name is not None
                and getattr(job, "project_name", None) != project_name
            ):
                return False
            return True

        return list(filter(filter_jobs, self.jobs.values()))


class FakeRecipe(BaseModel):
    INITIAL_VERSION = 0.1
    LATEST_WORKING = "LATEST_WORKING"
    LATEST_PUBLISHED = "LATEST_PUBLISHED"

    @classmethod
    def version_is_valid(
        cls, version: str, latest_working: bool = True, latest_published: bool = True
    ) -> bool:
        validity = True

        if len(version) < 1 or len(version) > 16:
            validity = False
        else:
            try:
                float(version)
            except ValueError:
                if not (
                    (version == cls.LATEST_WORKING and latest_working)
                    or (version == cls.LATEST_PUBLISHED and latest_published)
                ):
                    validity = False
        return validity

    def __init__(
        self,
        region_name: str,
        recipe_name: str,
        recipe_description: str,
        recipe_steps: List[Dict[str, Any]],
        tags: Dict[str, str],
    ):
        self.versions: Dict[float, FakeRecipeVersion] = OrderedDict()
        self.versions[self.INITIAL_VERSION] = FakeRecipeVersion(
            region_name,
            recipe_name,
            recipe_description,
            recipe_steps,
            tags,
            version=self.INITIAL_VERSION,
        )
        self.latest_working = self.versions[self.INITIAL_VERSION]
        self.latest_published: Optional[FakeRecipeVersion] = None

    def publish(self, description: Optional[str] = None) -> None:
        self.latest_published = self.latest_working
        self.latest_working = deepcopy(self.latest_working)
        self.latest_published.publish(description)
        del self.versions[self.latest_working.version]
        self.versions[self.latest_published.version] = self.latest_published
        self.latest_working.version = self.latest_published.version + 0.1
        self.versions[self.latest_working.version] = self.latest_working

    def update(
        self, description: Optional[str], steps: Optional[List[Dict[str, Any]]]
    ) -> None:
        if description is not None:
            self.latest_working.description = description
        if steps is not None:
            self.latest_working.steps = steps

    def delete_published_version(self, version: str) -> None:
        float_version = float(version)
        assert float_version.is_integer()
        if float_version == self.latest_published.version:  # type: ignore[union-attr]
            prev_version = float_version - 1.0
            # Iterate back through the published versions until we find one that exists
            while prev_version >= 1.0:
                if prev_version in self.versions:
                    self.latest_published = self.versions[prev_version]
                    break
                prev_version -= 1.0
            else:
                # Didn't find an earlier published version
                self.latest_published = None
        del self.versions[float_version]


class FakeRecipeVersion(BaseModel):
    def __init__(
        self,
        region_name: str,
        recipe_name: str,
        recipe_description: str,
        recipe_steps: List[Dict[str, Any]],
        tags: Dict[str, str],
        version: float,
    ):
        self.region_name = region_name
        self.name = recipe_name
        self.description = recipe_description
        self.steps = recipe_steps
        self.created_time = datetime.now()
        self.tags = tags
        self.published_date: Optional[datetime] = None
        self.version = version

    def as_dict(self) -> Dict[str, Any]:
        dict_recipe = {
            "Name": self.name,
            "Steps": self.steps,
            "Description": self.description,
            "CreateDate": f"{self.created_time.timestamp():.3f}",
            "Tags": self.tags or dict(),
            "RecipeVersion": str(self.version),
        }
        if self.published_date is not None:
            dict_recipe["PublishedDate"] = f"{self.published_date.timestamp():.3f}"

        return dict_recipe

    def publish(self, description: Optional[str]) -> None:
        self.version = float(math.ceil(self.version))
        self.published_date = datetime.now()
        if description is not None:
            self.description = description


class FakeRuleset(BaseModel):
    def __init__(
        self,
        region_name: str,
        ruleset_name: str,
        ruleset_description: str,
        ruleset_rules: List[Dict[str, Any]],
        ruleset_target_arn: str,
        tags: Dict[str, str],
    ):
        self.region_name = region_name
        self.name = ruleset_name
        self.description = ruleset_description
        self.rules = ruleset_rules
        self.target_arn = ruleset_target_arn
        self.created_time = datetime.now()

        self.tags = tags

    def as_dict(self) -> Dict[str, Any]:
        return {
            "Name": self.name,
            "Rules": self.rules,
            "Description": self.description,
            "TargetArn": self.target_arn,
            "CreateDate": f"{self.created_time.timestamp():.3f}",
            "Tags": self.tags or dict(),
        }


class FakeDataset(BaseModel):
    def __init__(
        self,
        region_name: str,
        account_id: str,
        dataset_name: str,
        dataset_format: str,
        dataset_format_options: Dict[str, Any],
        dataset_input: Dict[str, Any],
        dataset_path_options: Dict[str, Any],
        tags: Dict[str, str],
    ):
        self.region_name = region_name
        self.account_id = account_id
        self.name = dataset_name
        self.format = dataset_format
        self.format_options = dataset_format_options
        self.input = dataset_input
        self.path_options = dataset_path_options
        self.created_time = datetime.now()
        self.tags = tags

    @property
    def resource_arn(self) -> str:
        return (
            f"arn:aws:databrew:{self.region_name}:{self.account_id}:dataset/{self.name}"
        )

    def as_dict(self) -> Dict[str, Any]:
        return {
            "Name": self.name,
            "Format": self.format,
            "FormatOptions": self.format_options,
            "Input": self.input,
            "PathOptions": self.path_options,
            "CreateDate": f"{self.created_time.timestamp():.3f}",
            "Tags": self.tags or dict(),
            "ResourceArn": self.resource_arn,
        }


class BaseModelABCMeta(ABCMeta, type(BaseModel)):  # type: ignore[misc]
    pass


class FakeJob(BaseModel, metaclass=BaseModelABCMeta):  # type: ignore[misc]

    ENCRYPTION_MODES = ("SSE-S3", "SSE-KMS")
    LOG_SUBSCRIPTION_VALUES = ("ENABLE", "DISABLE")

    @property
    @abstractmethod
    def local_attrs(self) -> List[str]:
        raise NotImplementedError

    def __init__(self, account_id: str, region_name: str, **kwargs: Any):
        self.account_id = account_id
        self.region_name = region_name
        self.name = kwargs.get("name")
        self.created_time = datetime.now()
        self.dataset_name = kwargs.get("dataset_name")
        self.encryption_mode = kwargs.get("encryption_mode")
        self.log_subscription = kwargs.get("log_subscription")
        self.max_capacity = kwargs.get("max_capacity")
        self.max_retries = kwargs.get("max_retries")
        self.role_arn = kwargs.get("role_arn")
        self.tags = kwargs.get("tags")
        self.validate()
        # Set attributes specific to subclass
        for k in self.local_attrs:
            setattr(self, k, kwargs.get(k))

    def validate(self) -> None:
        if self.encryption_mode is not None:
            if self.encryption_mode not in FakeJob.ENCRYPTION_MODES:
                raise ValidationException(
                    f"1 validation error detected: Value '{self.encryption_mode}' at 'encryptionMode' failed to satisfy constraint: Member must satisfy enum value set: [{', '.join(self.ENCRYPTION_MODES)}]"
                )
        if self.log_subscription is not None:
            if self.log_subscription not in FakeJob.LOG_SUBSCRIPTION_VALUES:
                raise ValidationException(
                    f"1 validation error detected: Value '{self.log_subscription}' at 'logSubscription' failed to satisfy constraint: Member must satisfy enum value set: [{', '.join(self.LOG_SUBSCRIPTION_VALUES)}]"
                )

    @property
    @abstractmethod
    def job_type(self) -> str:
        pass

    @property
    def resource_arn(self) -> str:
        return f"arn:aws:databrew:{self.region_name}:{self.account_id}:job/{self.name}"

    def as_dict(self) -> Dict[str, Any]:
        rtn_dict = {
            "Name": self.name,
            "AccountId": self.account_id,
            "CreateDate": f"{self.created_time.timestamp():.3f}",
            "DatasetName": self.dataset_name,
            "EncryptionMode": self.encryption_mode,
            "Tags": self.tags or dict(),
            "LogSubscription": self.log_subscription,
            "MaxCapacity": self.max_capacity,
            "MaxRetries": self.max_retries,
            "ResourceArn": self.resource_arn,
            "RoleArn": self.role_arn,
            "Type": self.job_type,
        }

        # Add in subclass attributes
        for k in self.local_attrs:
            rtn_dict[camelcase_to_pascal(underscores_to_camelcase(k))] = getattr(
                self, k
            )

        # Remove items that have a value of None
        rtn_dict = {k: v for k, v in rtn_dict.items() if v is not None}

        return rtn_dict


class FakeProfileJob(FakeJob):  # type: ignore[misc]
    job_type = "PROFILE"
    local_attrs = ["output_location", "configuration", "validation_configurations"]


class FakeRecipeJob(FakeJob):  # type: ignore[misc]
    local_attrs = [
        "database_outputs",
        "data_catalog_outputs",
        "outputs",
        "project_name",
        "recipe_reference",
    ]
    job_type = "RECIPE"


databrew_backends = BackendDict(DataBrewBackend, "databrew")
