redis-om-python/redis_developer/orm/model.py

import abc
import dataclasses
import decimal
import json
import logging
import operator
from copy import deepcopy
from enum import Enum
from functools import reduce
from typing import (
    AbstractSet,
    Any,
    Callable,
    Dict,
    Mapping,
    Optional,
    Set,
    Tuple,
    TypeVar,
    Union,
    Sequence,
    no_type_check,
    Protocol,
    List,
    get_origin,
    get_args, Type
)

import redis
from pydantic import BaseModel, validator
from pydantic.fields import FieldInfo as PydanticFieldInfo
from pydantic.fields import ModelField, Undefined, UndefinedType
from pydantic.main import ModelMetaclass
from pydantic.typing import NoArgAnyCallable, resolve_annotations
from pydantic.utils import Representation
from ulid import ULID

from .encoders import jsonable_encoder
from .render_tree import render_tree
from .token_escaper import TokenEscaper

model_registry = {}
_T = TypeVar("_T")
log = logging.getLogger(__name__)
escaper = TokenEscaper()

# For basic exact-match field types like an indexed string, we create a TAG
# field in the RediSearch index. TAG is designed for multi-value fields
# separated by a "separator" character. We're using the field for single values
# (multi-value TAGs will be exposed as a separate field type), and we use the
# pipe character (|) as the separator. There is no way to escape this character
# in hash fields or JSON objects, so if someone indexes a value that includes
# the pipe, we'll warn but allow, and then warn again if they try to query for
# values that contain this separator.
SINGLE_VALUE_TAG_FIELD_SEPARATOR = "|"

# This is the default field separator in RediSearch. We need it to determine if
# someone has accidentally passed in the field separator with string value of a
# multi-value field lookup, like a IN or NOT_IN.
DEFAULT_REDISEARCH_FIELD_SEPARATOR = ","


class RedisModelError(Exception):
    """Raised when a problem exists in the definition of a RedisModel."""


class QuerySyntaxError(Exception):
    """Raised when a query is constructed improperly."""


class NotFoundError(Exception):
    """Raised when a query found no results."""


class Operators(Enum):
    EQ = 1
    NE = 2
    LT = 3
    LE = 4
    GT = 5
    GE = 6
    OR = 7
    AND = 8
    NOT = 9
    IN = 10
    NOT_IN = 11
    LIKE = 12
    ALL = 13

    def __str__(self):
        return str(self.name)


ExpressionOrModelField = Union['Expression', 'NegatedExpression', ModelField]


def embedded(cls):
    """
    Mark a model as embedded to avoid creating multiple indexes if the model is
    only ever used embedded within other models.
    """
    setattr(cls.Meta, 'embedded', True)


class ExpressionProtocol(Protocol):
    op: Operators
    left: ExpressionOrModelField
    right: ExpressionOrModelField

    def __invert__(self) -> 'Expression':
        pass

    def __and__(self, other: ExpressionOrModelField):
        pass

    def __or__(self, other: ExpressionOrModelField):
        pass

    @property
    def name(self) -> str:
        raise NotImplementedError

    @property
    def tree(self) -> str:
        raise NotImplementedError


@dataclasses.dataclass
class NegatedExpression:
    """A negated Expression object.

    For now, this is a separate dataclass from Expression that acts as a facade
    around an Expression, indicating to model code (specifically, code
    responsible for querying) to negate the logic in the wrapped Expression. A
    better design is probably possible, maybe at least an ExpressionProtocol?
    """
    expression: 'Expression'

    def __invert__(self):
        return self.expression

    def __and__(self, other):
        return Expression(left=self, op=Operators.AND, right=other, parents=self.expression.parents)

    def __or__(self, other):
        return Expression(left=self, op=Operators.OR, right=other, parents=self.expression.parents)

    @property
    def left(self):
        return self.expression.left

    @property
    def right(self):
        return self.expression.right

    @property
    def op(self):
        return self.expression.op

    @property
    def name(self):
        if self.expression.op is Operators.EQ:
            return f"NOT {self.expression.name}"
        else:
            return f"{self.expression.name} NOT"

    @property
    def tree(self):
        return render_tree(self)


@dataclasses.dataclass
class Expression:
    op: Operators
    left: ExpressionOrModelField
    right: ExpressionOrModelField
    parents: List[Tuple[str, 'RedisModel']]

    def __invert__(self):
        return NegatedExpression(self)

    def __and__(self, other: ExpressionOrModelField):
        return Expression(left=self, op=Operators.AND, right=other, parents=self.parents)

    def __or__(self, other: ExpressionOrModelField):
        return Expression(left=self, op=Operators.OR, right=other, parents=self.parents)

    @property
    def name(self):
        return str(self.op)

    @property
    def tree(self):
        return render_tree(self)


ExpressionOrNegated = Union[Expression, NegatedExpression]


class ExpressionProxy:
    def __init__(self, field: ModelField, parents: List[Tuple[str, 'RedisModel']]):
        self.field = field
        self.parents = parents

    def __eq__(self, other: Any) -> Expression:  # type: ignore[override]
        return Expression(left=self.field, op=Operators.EQ, right=other, parents=self.parents)

    def __ne__(self, other: Any) -> Expression:  # type: ignore[override]
        return Expression(left=self.field, op=Operators.NE, right=other, parents=self.parents)

    def __lt__(self, other: Any) -> Expression:  # type: ignore[override]
        return Expression(left=self.field, op=Operators.LT, right=other, parents=self.parents)

    def __le__(self, other: Any) -> Expression:  # type: ignore[override]
        return Expression(left=self.field, op=Operators.LE, right=other, parents=self.parents)

    def __gt__(self, other: Any) -> Expression:  # type: ignore[override]
        return Expression(left=self.field, op=Operators.GT, right=other, parents=self.parents)

    def __ge__(self, other: Any) -> Expression:  # type: ignore[override]
        return Expression(left=self.field, op=Operators.GE, right=other, parents=self.parents)

    def __mod__(self, other: Any) -> Expression:  # type: ignore[override]
        return Expression(left=self.field, op=Operators.LIKE, right=other, parents=self.parents)

    def __getattr__(self, item):
        if get_origin(self.field.outer_type_) == list:
            embedded_cls = get_args(self.field.outer_type_)
            if not embedded_cls:
                # TODO: Is this even possible?
                raise QuerySyntaxError("In order to query on a list field, you must define "
                                       "the contents of the list with a type annotation, like: "
                                       "orders: List[Order]. Docs: TODO")
            embedded_cls = embedded_cls[0]
            attr = getattr(embedded_cls, item)
        else:
            attr = getattr(self.field.outer_type_, item)
        if isinstance(attr, self.__class__):
            new_parent = (self.field.name, self.field.outer_type_)
            if not new_parent in attr.parents:
                attr.parents.append(new_parent)
            new_parents = list(set(self.parents) - set(attr.parents))
            if new_parents:
                attr.parents = new_parents + attr.parents
        return attr


class QueryNotSupportedError(Exception):
    """The attempted query is not supported."""


class RediSearchFieldTypes(Enum):
    TEXT = 'TEXT'
    TAG = 'TAG'
    NUMERIC = 'NUMERIC'
    GEO = 'GEO'


# TODO: How to handle Geo fields?
NUMERIC_TYPES = (float, int, decimal.Decimal)
DEFAULT_PAGE_SIZE = 10


class FindQuery:
    def __init__(self,
                 expressions: Sequence[ExpressionOrNegated],
                 model: Type['RedisModel'],
                 offset: int = 0,
                 limit: int = DEFAULT_PAGE_SIZE,
                 page_size: int = DEFAULT_PAGE_SIZE,
                 sort_fields: Optional[List[str]] = None):
        self.expressions = expressions
        self.model = model
        self.offset = offset
        self.limit = limit
        self.page_size = page_size

        if sort_fields:
            self.sort_fields = self.validate_sort_fields(sort_fields)
        else:
            self.sort_fields = []

        self._expression = None
        self._query: Optional[str] = None
        self._pagination: list[str] = []
        self._model_cache: list[RedisModel] = []

    @property
    def pagination(self):
        if self._pagination:
            return self._pagination
        self._pagination = self.resolve_redisearch_pagination()
        return self._pagination

    @property
    def expression(self):
        if self._expression:
            return self._expression
        if self.expressions:
            self._expression = reduce(operator.and_, self.expressions)
        else:
            # TODO: Is there a better way to support the "give me all records" query?
            # Also -- if we do it this way, we need different type annotations.
            self._expression = Expression(left=None, right=None, op=Operators.ALL,
                                          parents=[])
        return self._expression

    @property
    def query(self):
        return self.resolve_redisearch_query(self.expression)

    def validate_sort_fields(self, sort_fields):
        for sort_field in sort_fields:
            field_name = sort_field.lstrip("-")
            if field_name not in self.model.__fields__:
                raise QueryNotSupportedError(f"You tried sort by {field_name}, but that field "
                                             f"does not exist on the model {self.model}")
            field_proxy = getattr(self.model, field_name)
            if not getattr(field_proxy.field.field_info, 'sortable', False):
                raise QueryNotSupportedError(f"You tried sort by {field_name}, but {self.model} does "
                                             "not define that field as sortable. See docs: XXX")
        return sort_fields

    @staticmethod
    def resolve_field_type(field: ModelField, operator: Operators) -> RediSearchFieldTypes:
        if getattr(field.field_info, 'primary_key', None) is True:
            return RediSearchFieldTypes.TAG
        elif operator is Operators.LIKE:
            fts = getattr(field.field_info, 'full_text_search', None)
            if fts is not True:  # Could be PydanticUndefined
                raise QuerySyntaxError(f"You tried to do a full-text search on the field '{field.name}', "
                                       f"but the field is not indexed for full-text search. Use the "
                                       f"full_text_search=True option. Docs: TODO")
            return RediSearchFieldTypes.TEXT

        field_type = field.outer_type_

        # TODO: GEO
        if any(issubclass(field_type, t) for t in NUMERIC_TYPES):
            return RediSearchFieldTypes.NUMERIC
        else:
            # TAG fields are the default field type.
            # TODO: A ListField or ArrayField that supports multiple values
            #  and contains logic should allow IN and NOT_IN queries.
            return RediSearchFieldTypes.TAG

    @staticmethod
    def expand_tag_value(value):
        if isinstance(str, value):
            return value
        try:
            expanded_value = "|".join([escaper.escape(v) for v in value])
        except TypeError:
            raise QuerySyntaxError("Values passed to an IN query must be iterables,"
                                   "like a list of strings. For more information, see:"
                                   "TODO: doc.")
        return expanded_value

    @classmethod
    def resolve_value(cls, field_name: str, field_type: RediSearchFieldTypes,
                      field_info: PydanticFieldInfo, op: Operators, value: Any,
                      parents: List[Tuple[str, 'RedisModel']]) -> str:
        if parents:
            prefix = "_".join([p[0] for p in parents])
            field_name = f"{prefix}_{field_name}"
        result = ""
        if field_type is RediSearchFieldTypes.TEXT:
            result = f"@{field_name}_fts:"
            if op is Operators.EQ:
                result += f'"{value}"'
            elif op is Operators.NE:
                result = f'-({result}"{value}")'
            elif op is Operators.LIKE:
                result += value
            else:
                raise QueryNotSupportedError("Only equals (=), not-equals (!=), and like() "
                                             "comparisons are supported for TEXT fields. See "
                                             "docs: TODO.")
        elif field_type is RediSearchFieldTypes.NUMERIC:
            if op is Operators.EQ:
                result += f"@{field_name}:[{value} {value}]"
            elif op is Operators.NE:
                # TODO: Is this enough or do we also need a clause for all values
                #  ([-inf +inf]) from which we then subtract the undesirable value?
                result += f"-(@{field_name}:[{value} {value}])"
            elif op is Operators.GT:
                result += f"@{field_name}:[({value} +inf]"
            elif op is Operators.LT:
                result += f"@{field_name}:[-inf ({value}]"
            elif op is Operators.GE:
                result += f"@{field_name}:[{value} +inf]"
            elif op is Operators.LE:
                result += f"@{field_name}:[-inf {value}]"
        # TODO: How will we know the difference between a multi-value use of a TAG
        #  field and our hidden use of TAG for exact-match queries?
        elif field_type is RediSearchFieldTypes.TAG:
            if op is Operators.EQ:
                separator_char = getattr(field_info, 'separator',
                                         SINGLE_VALUE_TAG_FIELD_SEPARATOR)
                if value == separator_char:
                    # The value is ONLY the TAG field separator character --
                    # this is not going to work.
                    log.warning("Your query against the field %s is for a single character, %s, "
                                "that is used internally by redis-developer-python. We must ignore "
                                "this portion of the query. Please review your query to find "
                                "an alternative query that uses a string containing more than "
                                "just the character %s.", field_name, separator_char, separator_char)
                    return ""
                if separator_char in value:
                    # The value contains the TAG field separator. We can work
                    # around this by breaking apart the values and unioning them
                    # with multiple field:{} queries.
                    values = filter(None, value.split(separator_char))
                    for value in values:
                        value = escaper.escape(value)
                        result += f"@{field_name}:{{{value}}}"
                else:
                    value = escaper.escape(value)
                    result += f"@{field_name}:{{{value}}}"
            elif op is Operators.NE:
                value = escaper.escape(value)
                result += f"-(@{field_name}:{{{value}}})"
            elif op is Operators.IN:
                # TODO: Implement IN, test this...
                expanded_value = cls.expand_tag_value(value)
                result += f"(@{field_name}:{{{expanded_value}}})"
            elif op is Operators.NOT_IN:
                # TODO: Implement NOT_IN, test this...
                expanded_value = cls.expand_tag_value(value)
                result += f"-(@{field_name}:{{{expanded_value}}})"

        return result

    def resolve_redisearch_pagination(self):
        """Resolve pagination options for a query."""
        return ["LIMIT", self.offset, self.limit]

    def resolve_redisearch_sort_fields(self):
        """Resolve sort options for a query."""
        if not self.sort_fields:
            return
        fields = []
        for f in self.sort_fields:
            direction = "desc" if f.startswith('-') else 'asc'
            fields.extend([f.lstrip('-'), direction])
        if self.sort_fields:
            return ["SORTBY", *fields]

    @classmethod
    def resolve_redisearch_query(cls, expression: ExpressionOrNegated) -> str:
        """Resolve an expression to a string RediSearch query."""
        field_type = None
        field_name = None
        field_info = None
        encompassing_expression_is_negated = False
        result = ""

        if isinstance(expression, NegatedExpression):
            encompassing_expression_is_negated = True
            expression = expression.expression

        if expression.op is Operators.ALL:
            if encompassing_expression_is_negated:
                # TODO: Is there a use case for this, perhaps for dynamic
                #  scoring purposes?
                raise QueryNotSupportedError("You cannot negate a query for all results.")
            return "*"

        if isinstance(expression.left, Expression) or \
                isinstance(expression.left, NegatedExpression):
            result += f"({cls.resolve_redisearch_query(expression.left)})"
        elif isinstance(expression.left, ModelField):
            field_type = cls.resolve_field_type(expression.left, expression.op)
            field_name = expression.left.name
            field_info = expression.left.field_info
            if not field_info or not getattr(field_info, "index", None):
                raise QueryNotSupportedError(f"You tried to query by a field ({field_name}) "
                                             f"that isn't indexed. See docs: TODO")
        else:
            raise QueryNotSupportedError(f"A query expression should start with either a field "
                                         f"or an expression enclosed in parenthesis. See docs: "
                                         f"TODO")

        right = expression.right

        if isinstance(right, Expression) or isinstance(right, NegatedExpression):
            if expression.op == Operators.AND:
                result += " "
            elif expression.op == Operators.OR:
                result += "| "
            else:
                raise QueryNotSupportedError("You can only combine two query expressions with"
                                             "AND (&) or OR (|). See docs: TODO")

            if isinstance(right, NegatedExpression):
                result += "-"
                # We're handling the RediSearch operator in this call ("-"), so resolve the
                # inner expression instead of the NegatedExpression.
                right = right.expression

            result += f"({cls.resolve_redisearch_query(right)})"
        else:
            if isinstance(right, ModelField):
                raise QueryNotSupportedError("Comparing fields is not supported. See docs: TODO")
            else:
                result += cls.resolve_value(field_name, field_type, field_info,
                                            expression.op, right, expression.parents)

        if encompassing_expression_is_negated:
            result = f"-({result})"

        return result

    def execute(self, exhaust_results=True):
        args = ["ft.search", self.model.Meta.index_name, self.query, *self.pagination]
        if self.sort_fields:
            args += self.resolve_redisearch_sort_fields()

        # Reset the cache if we're executing from offset 0.
        if self.offset == 0:
            self._model_cache.clear()

        # If the offset is greater than 0, we're paginating through a result set,
        # so append the new results to results already in the cache.
        raw_result = self.model.db().execute_command(*args)
        count = raw_result[0]
        results = self.model.from_redis(raw_result)
        self._model_cache += results

        if not exhaust_results:
            return self._model_cache

        # The query returned all results, so we have no more work to do.
        if count <= len(results):
            return self._model_cache

        # Transparently (to the user) make subsequent requests to paginate
        # through the results and finally return them all.
        query = self
        while True:
            # Make a query for each pass of the loop, with a new offset equal to the
            # current offset plus `page_size`, until we stop getting results back.
            query = FindQuery(expressions=query.expressions,
                              model=query.model,
                              offset=query.offset + query.page_size,
                              page_size=query.page_size,
                              limit=query.limit)
            _results = query.execute(exhaust_results=False)
            if not _results:
                break
            self._model_cache += _results
        return self._model_cache

    def first(self):
        query = FindQuery(expressions=self.expressions, model=self.model,
                          offset=0, limit=1, sort_fields=self.sort_fields)
        results = query.execute()
        if not results:
            raise NotFoundError()
        return results[0]

    def all(self, batch_size=10):
        if batch_size != self.page_size:
            # TODO: There's probably a copy-with-change mechanism in Pydantic,
            #  or can we use one from dataclasses?
            query = FindQuery(expressions=self.expressions,
                              model=self.model,
                              offset=self.offset,
                              page_size=batch_size,
                              limit=batch_size,
                              sort_fields=self.sort_fields)
            return query.execute()
        return self.execute()

    def sort_by(self, *fields: str):
        if not fields:
            return self
        return FindQuery(expressions=self.expressions,
                         model=self.model,
                         offset=self.offset,
                         page_size=self.page_size,
                         limit=self.limit,
                         sort_fields=list(fields))

    def update(self, **kwargs):
        """Update all matching records in this query."""
        # TODO

    def delete(cls, **field_values):
        """Delete all matching records in this query."""
        for field_name, value in field_values:
            valid_attr = hasattr(cls.model, field_name)
            if not valid_attr:
                raise RedisModelError(f"Can't update field {field_name} because "
                                      f"the field does not exist on the model {cls}")

        return cls

    def __iter__(self):
        if self._model_cache:
            for m in self._model_cache:
                yield m
        else:
            for m in self.execute():
                yield m

    def __getitem__(self, item: int):
        """
        Given this code:
            Model.find()[1000]

        We should return only the 1000th result.

            1. If the result is loaded in the query cache for this query,
               we can return it directly from the cache.

            2. If the query cache does not have enough elements to return
               that result, then we should clone the current query and
               give it a new offset and limit: offset=n, limit=1.
        """
        if self._model_cache and len(self._model_cache) >= item:
            return self._model_cache[item]

        query = FindQuery(expressions=self.expressions,
                          model=self.model,
                          offset=item,
                          sort_fields=self.sort_fields,
                          limit=1)

        return query.execute()[0]


class PrimaryKeyCreator(Protocol):
    def create_pk(self, *args, **kwargs) -> str:
        """Create a new primary key"""


class UlidPrimaryKey:
    """A client-side generated primary key that follows the ULID spec.
        https://github.com/ulid/javascript#specification
    """
    @staticmethod
    def create_pk(*args, **kwargs) -> str:
        return str(ULID())


def __dataclass_transform__(
    *,
    eq_default: bool = True,
    order_default: bool = False,
    kw_only_default: bool = False,
    field_descriptors: Tuple[Union[type, Callable[..., Any]], ...] = (()),
) -> Callable[[_T], _T]:
    return lambda a: a


class FieldInfo(PydanticFieldInfo):
    def __init__(self, default: Any = Undefined, **kwargs: Any) -> None:
        primary_key = kwargs.pop("primary_key", False)
        sortable = kwargs.pop("sortable", Undefined)
        index = kwargs.pop("index", Undefined)
        full_text_search = kwargs.pop("full_text_search", Undefined)
        super().__init__(default=default, **kwargs)
        self.primary_key = primary_key
        self.sortable = sortable
        self.index = index
        self.full_text_search = full_text_search


class RelationshipInfo(Representation):
    def __init__(
        self,
        *,
        back_populates: Optional[str] = None,
        link_model: Optional[Any] = None,
    ) -> None:
        self.back_populates = back_populates
        self.link_model = link_model


def Field(
    default: Any = Undefined,
    *,
    default_factory: Optional[NoArgAnyCallable] = None,
    alias: str = None,
    title: str = None,
    description: str = None,
    exclude: Union[
        AbstractSet[Union[int, str]], Mapping[Union[int, str], Any], Any
    ] = None,
    include: Union[
        AbstractSet[Union[int, str]], Mapping[Union[int, str], Any], Any
    ] = None,
    const: bool = None,
    gt: float = None,
    ge: float = None,
    lt: float = None,
    le: float = None,
    multiple_of: float = None,
    min_items: int = None,
    max_items: int = None,
    min_length: int = None,
    max_length: int = None,
    allow_mutation: bool = True,
    regex: str = None,
    primary_key: bool = False,
    sortable: Union[bool, UndefinedType] = Undefined,
    index: Union[bool, UndefinedType] = Undefined,
    full_text_search: Union[bool, UndefinedType] = Undefined,
    schema_extra: Optional[Dict[str, Any]] = None,
) -> Any:
    current_schema_extra = schema_extra or {}
    field_info = FieldInfo(
        default,
        default_factory=default_factory,
        alias=alias,
        title=title,
        description=description,
        exclude=exclude,
        include=include,
        const=const,
        gt=gt,
        ge=ge,
        lt=lt,
        le=le,
        multiple_of=multiple_of,
        min_items=min_items,
        max_items=max_items,
        min_length=min_length,
        max_length=max_length,
        allow_mutation=allow_mutation,
        regex=regex,
        primary_key=primary_key,
        sortable=sortable,
        index=index,
        full_text_search=full_text_search,
        **current_schema_extra,
    )
    field_info._validate()
    return field_info


@dataclasses.dataclass
class PrimaryKey:
    name: str
    field: ModelField


class MetaProtocol(Protocol):
    global_key_prefix: str
    model_key_prefix: str
    primary_key_pattern: str
    database: redis.Redis
    primary_key: PrimaryKey
    primary_key_creator_cls: Type[PrimaryKeyCreator]
    index_name: str
    abstract: bool
    embedded: bool


@dataclasses.dataclass
class DefaultMeta:
    """A default placeholder Meta object.

    TODO: Revisit whether this is really necessary, and whether making
     these all optional here is the right choice.
    """
    global_key_prefix: Optional[str] = None
    model_key_prefix: Optional[str] = None
    primary_key_pattern: Optional[str] = None
    database: Optional[redis.Redis] = None
    primary_key: Optional[PrimaryKey] = None
    primary_key_creator_cls: Optional[Type[PrimaryKeyCreator]] = None
    index_name: Optional[str] = None
    abstract: Optional[bool] = False
    embedded: Optional[bool] = False


class ModelMeta(ModelMetaclass):
    _meta: MetaProtocol

    def __new__(cls, name, bases, attrs, **kwargs):  # noqa C901
        meta = attrs.pop('Meta', None)
        new_class = super().__new__(cls, name, bases, attrs, **kwargs)

        # The fact that there is a Meta field and _meta field is important: a
        # user may have given us a Meta object with their configuration, while
        # we might have inherited _meta from a parent class, and should
        # therefore use some of the inherited fields.
        meta = meta or getattr(new_class, 'Meta', None)
        base_meta = getattr(new_class, '_meta', None)

        if meta and meta != DefaultMeta and meta != base_meta:
            new_class.Meta = meta
            new_class._meta = meta
        elif base_meta:
            new_class._meta = deepcopy(base_meta)
            new_class.Meta = new_class._meta
            # Unset inherited values we don't want to reuse (typically based on
            # the model name).
            new_class._meta.embedded = False
            new_class._meta.model_key_prefix = None
            new_class._meta.index_name = None
        else:
            new_class._meta = deepcopy(DefaultMeta)
            new_class.Meta = new_class._meta

        # Create proxies for each model field so that we can use the field
        # in queries, like Model.get(Model.field_name == 1)
        for field_name, field in new_class.__fields__.items():
            setattr(new_class, field_name, ExpressionProxy(field, []))
            # Check if this is our FieldInfo version with extended ORM metadata.
            if isinstance(field.field_info, FieldInfo):
                if field.field_info.primary_key:
                    new_class._meta.primary_key = PrimaryKey(name=field_name, field=field)

        if not getattr(new_class._meta, 'global_key_prefix', None):
            new_class._meta.global_key_prefix = getattr(base_meta, "global_key_prefix", "")
        if not getattr(new_class._meta, 'model_key_prefix', None):
            # Don't look at the base class for this.
            new_class._meta.model_key_prefix = f"{new_class.__module__}.{new_class.__name__}"
        if not getattr(new_class._meta, 'primary_key_pattern', None):
            new_class._meta.primary_key_pattern = getattr(base_meta, "primary_key_pattern",
                                                          "{pk}")
        if not getattr(new_class._meta, 'database', None):
            new_class._meta.database = getattr(base_meta, "database",
                                               redis.Redis(decode_responses=True))
        if not getattr(new_class._meta, 'primary_key_creator_cls', None):
            new_class._meta.primary_key_creator_cls = getattr(base_meta, "primary_key_creator_cls",
                                                              UlidPrimaryKey)
        if not getattr(new_class._meta, 'index_name', None):
            new_class._meta.index_name = f"{new_class._meta.global_key_prefix}:" \
                                         f"{new_class._meta.model_key_prefix}:index"

        # Not an abstract model class or embedded model, so we should let the
        # Migrator create indexes for it.
        if abc.ABC not in bases and not new_class._meta.embedded:
            key = f"{new_class.__module__}.{new_class.__qualname__}"
            model_registry[key] = new_class

        return new_class


class RedisModel(BaseModel, abc.ABC, metaclass=ModelMeta):
    pk: Optional[str] = Field(default=None, primary_key=True)

    Meta = DefaultMeta
    # TODO: Missing _meta here is causing IDE warnings.

    class Config:
        orm_mode = True
        arbitrary_types_allowed = True
        extra = 'allow'

    def __init__(__pydantic_self__, **data: Any) -> None:
        super().__init__(**data)
        __pydantic_self__.validate_primary_key()

    def __lt__(self, other):
        """Default sort: compare primary key of models."""
        return self.pk < other.pk

    @validator("pk", always=True)
    def validate_pk(cls, v):
        if not v:
            v = cls._meta.primary_key_creator_cls().create_pk()
        return v

    @classmethod
    def validate_primary_key(cls):
        """Check for a primary key. We need one (and only one)."""
        primary_keys = 0
        for name, field in cls.__fields__.items():
            if getattr(field.field_info, 'primary_key', None):
                primary_keys += 1
        if primary_keys == 0:
            raise RedisModelError("You must define a primary key for the model")
        elif primary_keys > 1:
            raise RedisModelError("You must define only one primary key for a model")

    @classmethod
    def make_key(cls, part: str):
        global_prefix = getattr(cls._meta, 'global_key_prefix', '').strip(":")
        model_prefix = getattr(cls._meta, 'model_key_prefix', '').strip(":")
        return f"{global_prefix}:{model_prefix}:{part}"

    @classmethod
    def make_primary_key(cls, pk: Any):
        """Return the Redis key for this model."""
        return cls.make_key(cls._meta.primary_key_pattern.format(pk=pk))

    def key(self):
        """Return the Redis key for this model."""
        pk = getattr(self, self._meta.primary_key.field.name)
        return self.make_primary_key(pk)

    @classmethod
    def db(cls):
        return cls._meta.database

    @classmethod
    def find(cls, *expressions: Union[Any, Expression]) -> FindQuery:  # TODO: How to type annotate this?
        return FindQuery(expressions=expressions, model=cls)

    @classmethod
    def from_redis(cls, res: Any):
        # TODO: Parsing logic borrowed from redisearch-py. Evaluate.
        import six
        from six.moves import xrange, zip as izip

        def to_string(s):
            if isinstance(s, six.string_types):
                return s
            elif isinstance(s, six.binary_type):
                return s.decode('utf-8', 'ignore')
            else:
                return s  # Not a string we care about

        docs = []
        step = 2  # Because the result has content
        offset = 1  # The first item is the count of total matches.

        for i in xrange(1, len(res), step):
            fields_offset = offset

            fields = dict(
                dict(izip(map(to_string, res[i + fields_offset][::2]),
                          map(to_string, res[i + fields_offset][1::2])))
            )

            try:
                del fields['id']
            except KeyError:
                pass

            try:
                fields['json'] = fields['$']
                del fields['$']
            except KeyError:
                pass

            if 'json' in fields:
                json_fields = json.loads(fields['json'])
                doc = cls(**json_fields)
            else:
                doc = cls(**fields)
            docs.append(doc)
        return docs


    @classmethod
    def add(cls, models: Sequence['RedisModel']) -> Sequence['RedisModel']:
        return [model.save() for model in models]

    @classmethod
    def update(cls, **field_values):
        """Update this model instance."""
        return cls

    @classmethod
    def values(cls):
        """Return raw values from Redis instead of model instances."""
        return cls

    def delete(self):
        return self.db().delete(self.key())

    def save(self, *args, **kwargs) -> 'RedisModel':
        raise NotImplementedError

    @classmethod
    def redisearch_schema(cls):
        raise NotImplementedError


class HashModel(RedisModel, abc.ABC):
    def __init_subclass__(cls, **kwargs):
        super().__init_subclass__(**kwargs)

        for name, field in cls.__fields__.items():
            if issubclass(field.outer_type_, RedisModel):
                raise RedisModelError(f"HashModels cannot have embedded model "
                                      f"fields. Field: {name}")

            for typ in (Set, Mapping, List):
                if issubclass(field.outer_type_, typ):
                    raise RedisModelError(f"HashModels cannot have set, list,"
                                          f" or mapping fields. Field: {name}")

    def save(self, *args, **kwargs) -> 'HashModel':
        document = jsonable_encoder(self.dict())
        success = self.db().hset(self.key(), mapping=document)

        return success

    @classmethod
    def get(cls, pk: Any) -> 'HashModel':
        document = cls.db().hgetall(cls.make_primary_key(pk))
        if not document:
            raise NotFoundError
        return cls.parse_obj(document)

    @classmethod
    @no_type_check
    def _get_value(cls, *args, **kwargs) -> Any:
        """
        Always send None as an empty string.

        TODO: We do this because redis-py's hset() method requires non-null
        values. Is there a better way?
        """
        val = super()._get_value(*args, **kwargs)
        if val is None:
            return ""
        return val

    @classmethod
    def redisearch_schema(cls):
        hash_prefix = cls.make_key(cls._meta.primary_key_pattern.format(pk=""))
        schema_prefix = f"ON HASH PREFIX 1 {hash_prefix} SCHEMA"
        schema_parts = [schema_prefix] + cls.schema_for_fields()
        return " ".join(schema_parts)

    @classmethod
    def schema_for_fields(cls):
        schema_parts = []

        for name, field in cls.__fields__.items():
            # TODO: Merge this code with schema_for_type()?
            _type = field.outer_type_
            if getattr(field.field_info, 'primary_key', None):
                if issubclass(_type, str):
                    redisearch_field = f"{name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR}"
                else:
                    redisearch_field = cls.schema_for_type(name, _type, field.field_info)
                schema_parts.append(redisearch_field)
            elif getattr(field.field_info, 'index', None) is True:
                schema_parts.append(cls.schema_for_type(name, _type, field.field_info))
                # TODO: Raise error if user embeds a model field or list and makes it
                #  sortable. Instead, the embedded model should mark individual fields
                #  as sortable.
                if getattr(field.field_info, 'sortable', False) is True:
                    schema_parts.append("SORTABLE")
            elif get_origin(_type) == list:
                embedded_cls = get_args(_type)
                if not embedded_cls:
                    # TODO: Test if this can really happen.
                    log.warning("Model %s defined an empty list field: %s", cls, name)
                    continue
                embedded_cls = embedded_cls[0]
                schema_parts.append(cls.schema_for_type(name, embedded_cls,
                                                        field.field_info))
            elif issubclass(_type, RedisModel):
                schema_parts.append(cls.schema_for_type(name, _type, field.field_info))
        return schema_parts

    @classmethod
    def schema_for_type(cls, name, typ: Any, field_info: PydanticFieldInfo):
        if get_origin(typ) == list:
            embedded_cls = get_args(typ)
            if not embedded_cls:
                # TODO: Test if this can really happen.
                log.warning("Model %s defined an empty list field: %s", cls, name)
                return ""
            embedded_cls = embedded_cls[0]
            return cls.schema_for_type(name, embedded_cls, field_info)
        elif any(issubclass(typ, t) for t in NUMERIC_TYPES):
            return f"{name} NUMERIC"
        elif issubclass(typ, str):
            if getattr(field_info, 'full_text_search', False) is True:
                return f"{name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR} " \
                       f"{name}_fts TEXT"
            else:
                return f"{name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR}"
        elif issubclass(typ, RedisModel):
            sub_fields = []
            for embedded_name, field in typ.__fields__.items():
                sub_fields.append(cls.schema_for_type(f"{name}_{embedded_name}", field.outer_type_,
                                                      field.field_info))
            return " ".join(sub_fields)
        else:
            return f"{name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR}"


class JsonModel(RedisModel, abc.ABC):
    def save(self, *args, **kwargs) -> 'JsonModel':
        success = self.db().execute_command('JSON.SET', self.key(), ".", self.json())
        return success

    @classmethod
    def get(cls, pk: Any) -> 'JsonModel':
        document = cls.db().execute_command("JSON.GET", cls.make_primary_key(pk))
        if not document:
            raise NotFoundError
        return cls.parse_raw(document)

    @classmethod
    def redisearch_schema(cls):
        key_prefix = cls.make_key(cls._meta.primary_key_pattern.format(pk=""))
        schema_prefix = f"ON JSON PREFIX 1 {key_prefix} SCHEMA"
        schema_parts = [schema_prefix] + cls.schema_for_fields()
        return " ".join(schema_parts)

    @classmethod
    def schema_for_fields(cls):
        schema_parts = []
        json_path = "$"

        for name, field in cls.__fields__.items():
            _type = field.outer_type_
            schema_parts.append(cls.schema_for_type(
                json_path, name, "", _type, field.field_info))
        return schema_parts

    @classmethod
    def schema_for_type(cls, json_path: str, name: str, name_prefix: str, typ: Any,
                        field_info: PydanticFieldInfo,
                        parent_type: Optional[Any] = None) -> str:
        should_index = getattr(field_info, 'index', False)
        field_type = get_origin(typ)
        try:
            field_is_model = issubclass(typ, RedisModel)
        except TypeError:
            # Not a class, probably a type annotation
            field_is_model = False

        # When we encounter a list or model field, we need to descend
        # into the values of the list or the fields of the model to
        # find any values marked as indexed.
        if field_type == list:
            embedded_cls = get_args(typ)
            if not embedded_cls:
                log.warning("Model %s defined an empty list field: %s", cls, name)
                return ""
            embedded_cls = embedded_cls[0]
            return cls.schema_for_type(f"{json_path}.{name}[*]", name, name_prefix,
                                       embedded_cls, field_info, parent_type=field_type)
        elif field_is_model:
            name_prefix = f"{name_prefix}_{name}" if name_prefix else name
            sub_fields = []
            for embedded_name, field in typ.__fields__.items():
                if parent_type == list or isinstance(parent_type, RedisModel):
                    # This is a list, so the correct JSONPath expression is to
                    # refer directly to attribute names after the list notation,
                    # e.g. orders[*].created_date.
                    path = json_path
                else:
                    # All other fields should use dot notation with both the
                    # current field name and "embedded" field name, e.g.,
                    # order.address.street_line_1.
                    path = f"{json_path}.{name}"
                sub_fields.append(cls.schema_for_type(path,
                                                      embedded_name,
                                                      name_prefix,
                                                      field.outer_type_,
                                                      field.field_info,
                                                      parent_type=field_type))
            return " ".join(filter(None, sub_fields))
        elif should_index:
            index_field_name = f"{name_prefix}_{name}" if name_prefix else name
            path = f"{json_path}.{name}"
            if any(issubclass(typ, t) for t in NUMERIC_TYPES):
                schema_part = f"{path} AS {index_field_name} NUMERIC"
            elif issubclass(typ, str):
                if getattr(field_info, 'full_text_search', False) is True:
                    schema_part = f"{path} AS {index_field_name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR} " \
                           f"{path} AS {index_field_name}_fts TEXT"
                else:
                    schema_part = f"{path} AS {index_field_name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR}"
            else:
                schema_part = f"{path} AS {index_field_name} TAG"
            # TODO: GEO field
            schema_part += " SORTABLE"
            return schema_part

        return ""