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redis-om-python/redis_om/model/model.py
Andrew Brookins 2b1994b98b Disable features without required Redis modules 
Some features, like querying and embedded models, require
either the RediSearch or RedisJSON modules running in Redis.
Without these modules, using these features would result
in inscrutable errors.

We now disable some tests if the Redis module required for the
test is not found in the Redis instance the tests are using,
and raise errors or log messages if the same is true during
execution of HashModel and JsonModel.
2021-11-03 12:37:12 -07:00

1551 lines
55 KiB
Python
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import abc
import dataclasses
import decimal
import json
import logging
import operator
from copy import copy
from enum import Enum
from functools import reduce
from typing import (
AbstractSet,
Any,
Callable,
Dict,
List,
Mapping,
Optional,
Protocol,
Sequence,
Set,
Tuple,
Type,
TypeVar,
Union,
get_args,
get_origin,
no_type_check,
)
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, validate_model
from pydantic.typing import NoArgAnyCallable
from pydantic.utils import Representation
from redis.client import Pipeline
from ulid import ULID
from ..checks import has_redis_json, has_redisearch
from ..connections import get_redis_connection
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)
def is_supported_container_type(typ: Optional[type]) -> bool:
if typ == list or typ == tuple:
return True
unwrapped = get_origin(typ)
return unwrapped == list or unwrapped == tuple
def validate_model_fields(model: Type["RedisModel"], field_values: Dict[str, Any]):
for field_name in field_values.keys():
if field_name not in model.__fields__:
raise QuerySyntaxError(
f"The field {field_name} does not exist on the model {model.__name__}"
)
def decode_redis_value(
obj: Union[List[bytes], Dict[bytes, bytes], bytes], encoding: str
) -> Union[List[str], Dict[str, str], str]:
"""Decode a binary-encoded Redis hash into the specified encoding."""
if isinstance(obj, list):
return [v.decode(encoding) for v in obj]
if isinstance(obj, dict):
return {
key.decode(encoding): value.decode(encoding) for key, value in obj.items()
}
elif isinstance(obj, bytes):
return obj.decode(encoding)
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: Optional[ExpressionOrModelField]
right: Optional[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:
return Expression(
left=self.field, op=Operators.LT, right=other, parents=self.parents
)
def __le__(self, other: Any) -> Expression:
return Expression(
left=self.field, op=Operators.LE, right=other, parents=self.parents
)
def __gt__(self, other: Any) -> Expression:
return Expression(
left=self.field, op=Operators.GT, right=other, parents=self.parents
)
def __ge__(self, other: Any) -> Expression:
return Expression(
left=self.field, op=Operators.GE, right=other, parents=self.parents
)
def __mod__(self, other: Any) -> Expression:
return Expression(
left=self.field, op=Operators.LIKE, right=other, parents=self.parents
)
def __lshift__(self, other: Any) -> Expression:
return Expression(
left=self.field, op=Operators.IN, right=other, parents=self.parents
)
def __getattr__(self, item):
if is_supported_container_type(self.field.outer_type_):
embedded_cls = get_args(self.field.outer_type_)
if not embedded_cls:
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 new_parent not 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,
):
if not has_redisearch(model.db()):
raise RedisModelError("Your Redis instance does not have either the RediSearch module "
"or RedisJSON module installed. Querying requires that your Redis "
"instance has one of these modules installed.")
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] = []
def dict(self) -> Dict[str, Any]:
return dict(
model=self.model,
offset=self.offset,
page_size=self.page_size,
limit=self.limit,
expressions=copy(self.expressions),
sort_fields=copy(self.sort_fields),
)
def copy(self, **kwargs):
original = self.dict()
original.update(**kwargs)
return FindQuery(**original)
@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:
self._expression = Expression(
left=None, right=None, op=Operators.ALL, parents=[]
)
return self._expression
@property
def query(self):
"""
Resolve and return the RediSearch query for this FindQuery.
NOTE: We cache the resolved query string after generating it. This should be OK
because all mutations of FindQuery through public APIs return a new FindQuery instance.
"""
if self._query:
return self._query
self._query = self.resolve_redisearch_query(self.expression)
return self._query
def validate_sort_fields(self, sort_fields: List[str]):
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, op: Operators) -> RediSearchFieldTypes:
if getattr(field.field_info, "primary_key", None) is True:
return RediSearchFieldTypes.TAG
elif op 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 fields
container_type = get_origin(field_type)
if is_supported_container_type(container_type):
# NOTE: A list of strings, like:
#
# tarot_cards: List[str] = field(index=True)
#
# becomes a TAG field, which means that users can run equality and
# membership queries on values.
#
# Meanwhile, a list of RedisModels, like:
#
# friends: List[Friend] = field(index=True)
#
# is not itself directly indexed, but instead, we index any fields
# within the model inside the list marked as `index=True`.
return RediSearchFieldTypes.TAG
elif container_type is not None:
raise QuerySyntaxError(
"Only lists and tuples are supported for multi-value fields. "
"See docs: TODO"
)
elif any(issubclass(field_type, t) for t in NUMERIC_TYPES):
# Index numeric Python types as NUMERIC fields, so we can support
# range queries.
return RediSearchFieldTypes.NUMERIC
else:
# TAG fields are the default field type and support equality and
# membership queries, though membership (and the multi-value nature
# of the field) are hidden from users unless they explicitly index
# multiple values, with either a list or tuple,
# e.g.,
# favorite_foods: List[str] = field(index=True)
return RediSearchFieldTypes.TAG
@staticmethod
def expand_tag_value(value):
if isinstance(value, str):
return escaper.escape(value)
if isinstance(value, bytes):
# TODO: We don't decode and then escape bytes objects passed as input.
# Should we?
# TODO: TAG indexes fail on JSON arrays of numbers -- only strings
# are allowed -- what happens if we save an array of bytes?
return value
try:
return "|".join([escaper.escape(str(v)) for v in value])
except TypeError:
log.debug(
"Escaping single non-iterable value used for an IN or "
"NOT_IN query: %s",
value,
)
return escaper.escape(str(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:
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-om-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 = 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 arbitrarily deep expression into a single RediSearch query string.
This method is complex. Note the following:
1. This method makes a recursive call to itself when it finds that
either the left or right operand contains another expression.
2. An expression might be in a "negated" form, which means that the user
gave us an expression like ~(Member.age == 30), or in other words,
"Members whose age is NOT 30." Thus, a negated expression is one in
which the meaning of an expression is inverted. If we find a negated
expression, we need to add the appropriate "NOT" syntax but can
otherwise use the resolved RediSearch query for the expression as-is.
3. The final resolution of an expression should be a left operand that's
a ModelField, an operator, and a right operand that's NOT a ModelField.
With an IN or NOT_IN operator, the right operand can be a sequence
type, but otherwise, sequence types are converted to strings.
TODO: When the operator is not IN or NOT_IN, detect a sequence type (other
than strings, which are allowed) and raise an exception.
"""
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 with full-text search?
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(
"A query expression should start with either a field "
"or an expression enclosed in parenthesis. See docs: "
"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 not field_name:
raise QuerySyntaxError("Could not resolve field name. See docs: TODO")
elif not field_type:
raise QuerySyntaxError("Could not resolve field type. See docs: TODO")
elif not field_info:
raise QuerySyntaxError("Could not resolve field info. See docs: TODO")
elif 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 = query.copy(offset=query.offset + query.page_size)
_results = query.execute(exhaust_results=False)
if not _results:
break
self._model_cache += _results
return self._model_cache
def first(self):
query = self.copy(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:
query = self.copy(page_size=batch_size, limit=batch_size)
return query.execute()
return self.execute()
def sort_by(self, *fields: str):
if not fields:
return self
return self.copy(sort_fields=list(fields))
def update(self, use_transaction=True, **field_values):
"""
Update models that match this query to the given field-value pairs.
Keys and values given as keyword arguments are interpreted as fields
on the target model and the values as the values to which to set the
given fields.
"""
validate_model_fields(self.model, field_values)
pipeline = self.model.db().pipeline() if use_transaction else None
for model in self.all():
for field, value in field_values.items():
setattr(model, field, value)
# TODO: In the non-transaction case, can we do more to detect
# failure responses from Redis?
model.save(pipeline=pipeline)
if pipeline:
# TODO: Response type?
# TODO: Better error detection for transactions.
pipeline.execute()
def delete(self):
"""Delete all matching records in this query."""
# TODO: Better response type, error detection
return self.model.db().delete(*[m.key() for m in self.all()])
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 = self.copy(offset=item, 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
encoding: str
@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
encoding: Optional[str] = "utf-8"
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 = type(
f"{new_class.__name__}Meta", (base_meta,), dict(base_meta.__dict__)
)
new_class.Meta = new_class._meta
# Unset inherited values we don't want to reuse (typically based on
# the model name).
new_class._meta.model_key_prefix = None
new_class._meta.index_name = None
else:
new_class._meta = type(
f"{new_class.__name__}Meta", (DefaultMeta,), dict(DefaultMeta.__dict__)
)
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, []))
annotation = new_class.get_annotations().get(field_name)
if annotation:
new_class.__annotations__[field_name] = Union[
annotation, ExpressionProxy
]
else:
new_class.__annotations__[field_name] = ExpressionProxy
# 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", get_redis_connection()
)
if not getattr(new_class._meta, "encoding", None):
new_class._meta.encoding = getattr(base_meta, "encoding")
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 getattr(new_class._meta, "embedded", False):
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
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
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)
def delete(self):
return self.db().delete(self.key())
def update(self, **field_values):
"""Update this model instance with the specified key-value pairs."""
raise NotImplementedError
def save(self, pipeline: Optional[Pipeline] = None) -> "RedisModel":
raise NotImplementedError
@validator("pk", always=True, allow_reuse=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))
@classmethod
def db(cls):
return cls._meta.database
@classmethod
def find(cls, *expressions: Union[Any, Expression]) -> FindQuery:
return FindQuery(expressions=expressions, model=cls)
@classmethod
def from_redis(cls, res: Any):
# TODO: Parsing logic copied from redisearch-py. Evaluate.
import six
from six.moves import xrange
from six.moves import 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 get_annotations(cls):
d = {}
for c in cls.mro():
try:
d.update(**c.__annotations__)
except AttributeError:
# object, at least, has no __annotations__ attribute.
pass
return d
@classmethod
def add(cls, models: Sequence["RedisModel"]) -> Sequence["RedisModel"]:
# TODO: Add transaction support
return [model.save() for model in models]
@classmethod
def redisearch_schema(cls):
raise NotImplementedError
def check(self):
"""Run all validations."""
*_, validation_error = validate_model(self.__class__, self.__dict__)
if validation_error:
raise validation_error
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, pipeline: Optional[Pipeline] = None) -> "HashModel":
self.check()
if pipeline is None:
db = self.db()
else:
db = pipeline
document = jsonable_encoder(self.dict())
db.hset(self.key(), mapping=document)
return self
@classmethod
def get(cls, pk: Any) -> "HashModel":
document = cls.db().hgetall(cls.make_primary_key(pk))
if not document:
raise NotFoundError
try:
result = cls.parse_obj(document)
except TypeError as e:
log.warning(
f'Could not parse Redis response. Error was: "{e}". Probably, the '
"connection is not set to decode responses from bytes. "
"Attempting to decode response using the encoding set on "
f"model class ({cls.__class__}. Encoding: {cls.Meta.encoding}."
)
document = decode_redis_value(document, cls.Meta.encoding)
result = cls.parse_obj(document)
return result
@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)
def update(self, **field_values):
validate_model_fields(self.__class__, field_values)
for field, value in field_values.items():
setattr(self, field, value)
self.save()
@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))
elif is_supported_container_type(_type):
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):
# TODO: Import parent logic from JsonModel to deal with lists, so that
# a List[int] gets indexed as TAG instead of NUMERICAL.
# 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.
# TODO: Abstract string-building logic for each type (TAG, etc.) into
# classes that take a field name.
sortable = getattr(field_info, "sortable", False)
if is_supported_container_type(typ):
embedded_cls = get_args(typ)
if not embedded_cls:
# TODO: Test if this can really happen.
log.warning(
"Model %s defined an empty list or tuple field: %s", cls, name
)
return ""
embedded_cls = embedded_cls[0]
schema = cls.schema_for_type(name, embedded_cls, field_info)
elif any(issubclass(typ, t) for t in NUMERIC_TYPES):
schema = f"{name} NUMERIC"
elif issubclass(typ, str):
if getattr(field_info, "full_text_search", False) is True:
schema = (
f"{name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR} "
f"{name}_fts TEXT"
)
else:
schema = 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
)
)
schema = " ".join(sub_fields)
else:
schema = f"{name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR}"
if schema and sortable is True:
schema += " SORTABLE"
return schema
class JsonModel(RedisModel, abc.ABC):
def __init_subclass__(cls, **kwargs):
if not has_redis_json(cls.db()):
log.error("Your Redis instance does not have the RedisJson module "
"loaded. JsonModel depends on RedisJson.")
# Generate the RediSearch schema once to validate fields.
cls.redisearch_schema()
def save(self, pipeline: Optional[Pipeline] = None) -> "JsonModel":
self.check()
if pipeline is None:
db = self.db()
else:
db = pipeline
db.execute_command("JSON.SET", self.key(), ".", self.json())
return self
def update(self, **field_values):
# TODO: Better support for embedded field models.
validate_model_fields(self.__class__, field_values)
for field, value in field_values.items():
setattr(self, field, value)
self.save()
@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)
is_container_type = is_supported_container_type(typ)
parent_is_container_type = is_supported_container_type(parent_type)
parent_is_model = False
if parent_type:
try:
parent_is_model = issubclass(parent_type, RedisModel)
except TypeError:
pass
# TODO: We need a better way to know that we're indexing a value
# discovered in a model within an array.
#
# E.g., say we have a field like `orders: List[Order]`, and we're
# indexing the "name" field from the Order model (because it's marked
# index=True in the Order model). The JSONPath for this field is
# $.orders[*].name, but the "parent" type at this point is Order, not
# List. For now, we'll discover that Orders are stored in a list by
# checking if the JSONPath contains the expression for all items in
# an array.
parent_is_model_in_container = parent_is_model and json_path.endswith("[*]")
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 is_container_type:
field_type = get_origin(typ)
embedded_cls = get_args(typ)
if not embedded_cls:
log.warning(
"Model %s defined an empty list or tuple 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_is_container_type:
# We'll store this value either as a JavaScript array, so
# the correct JSONPath expression is to refer directly to
# attribute names after the container 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=typ,
)
)
return " ".join(filter(None, sub_fields))
# NOTE: This is the termination point for recursion. We've descended
# into models and lists until we found an actual value to index.
elif should_index:
index_field_name = f"{name_prefix}_{name}" if name_prefix else name
if parent_is_container_type:
# If we're indexing the this field as a JavaScript array, then
# the currently built-up JSONPath expression will be
# "field_name[*]", which is what we want to use.
path = json_path
else:
path = f"{json_path}.{name}"
sortable = getattr(field_info, "sortable", False)
full_text_search = getattr(field_info, "full_text_search", False)
sortable_tag_error = RedisModelError(
"In this Preview release, TAG fields cannot "
f"be marked as sortable. Problem field: {name}. "
"See docs: TODO"
)
# TODO: GEO field
if parent_is_container_type or parent_is_model_in_container:
if typ is not str:
raise RedisModelError(
"In this Preview release, list and tuple fields can only "
f"contain strings. Problem field: {name}. See docs: TODO"
)
if full_text_search is True:
raise RedisModelError(
"List and tuple fields cannot be indexed for full-text "
f"search. Problem field: {name}. See docs: TODO"
)
schema = f"{path} AS {index_field_name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR}"
if sortable is True:
raise sortable_tag_error
elif any(issubclass(typ, t) for t in NUMERIC_TYPES):
schema = f"{path} AS {index_field_name} NUMERIC"
elif issubclass(typ, str):
if full_text_search is True:
schema = (
f"{path} AS {index_field_name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR} "
f"{path} AS {index_field_name}_fts TEXT"
)
if sortable is True:
# NOTE: With the current preview release, making a field
# full-text searchable and sortable only makes the TEXT
# field sortable. This means that results for full-text
# search queries can be sorted, but not exact match
# queries.
schema += " SORTABLE"
else:
schema = f"{path} AS {index_field_name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR}"
if sortable is True:
raise sortable_tag_error
else:
schema = f"{path} AS {index_field_name} TAG SEPARATOR {SINGLE_VALUE_TAG_FIELD_SEPARATOR}"
if sortable is True:
raise sortable_tag_error
return schema
return ""
class EmbeddedJsonModel(JsonModel, abc.ABC):
class Meta:
embedded = True
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