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WIP on basic non-relational model functionality

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Andrew Brookins 2021-08-30 18:08:07 -07:00
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# Redis Developer Python
redis-developer-python is a high-level library containing useful Redis
abstractions and tools, like an ORM and leaderboard.
## ORM/ODM
redis-developer-python includes an ORM/ODM.
### Declarative model classes
```pyhon
import decimal
import datetime
from typing import Optional
from redis import Redis
from redis_developer.orm import (
RedisModel,
Field,
Relationship
)
db = Redis()
# Declarative model classes
class BaseModel(RedisModel):
config:
database = db
class Address(BaseModel):
address_line_1: str
address_line_2: str
city: str
country: str
postal_code: str
class Order(BaseModel):
total: decimal.Decimal
currency: str
created_on: datetime.datetime
class Member(BaseModel):
# An auto-incrementing primary key is added by default if no primary key
# is specified.
id: Optional[int] = Field(default=None, primary_key=True)
first_name: str
last_name: str
email: str = Field(unique=True, index=True)
zipcode: Optional[int]
join_date: datetime.date
# Creates an embedded document: stored as hash fields or JSON document.
address: Address
# Creates a relationship to data in separate Hash or JSON documents.
orders: Relationship(Order, backref='recommended',
field_name='recommended_by')
# Creates a self-relationship.
recommended_by: Relationship('Member', backref='recommended',
field_name='recommended_by')
class Meta:
key_pattern = "member:{id}"
# Validation
# Raises ValidationError: last_name is required
Member(
first_name="Andrew",
zipcode="97086",
join_date=datetime.date.today()
)
# Passes validation
Member(
first_name="Andrew",
last_name="Brookins",
zipcode="97086",
join_date=datetime.date.today()
)
# Raises ValidationError: zipcode is not a number
Member(
first_name="Andrew",
last_name="Brookins",
zipcode="not a number",
join_date=datetime.date.today()
)
# Persist a model instance to Redis
member = Member(
first_name="Andrew",
last_name="Brookins",
zipcode="97086",
join_date=datetime.date.today()
)
# Assign the return value to get any auto-fields filled in,
# like the primary key (if an auto-incrementing integer).
member = member.save()
# Hydrate a model instance from Redis using the primary key.
member = Member.get(d=1)
# Hydrate a model instance from Redis using a secondary index on a unique field.
member = Member.get(email="a.m.brookins@gmail.com")
# What if the field wasn't unique and there were two "a.m.brookins@gmail.com"
# entries?
# This would raise a MultipleObjectsReturned error:
member = Member.get(Member.email == "a.m.brookins@gmail.com")
# What if you know there might be multiple results? Use filter():
members = Member.filter(Member.last_name == "Brookins")
# What if you want to only return values that don't match a query?
members = Member.exclude(last_name="Brookins")
# You can combine filer() and exclude():
members = Member.filter(last_name="Brookins").exclude(first_name="Andrew")
```
### Serialization and validation based on model classes
### Save a model instance to Redis
### Get a single model instance from Redis
### Update a model instance in Redis
### Batch/bulk insert and updates
### Declarative index creation and automatic index management
### Declarative “primary key”
### Declarative relationships (via Sorted Sets) or Embedded documents (JSON)
### Exact-value queries on indexed fields
### Ad-hoc numeric range and full-text queries (RediSearch)
### Aggregations (RediSearch)
### Unanswered Questions
What's the difference between these two forms?
```python
from redis_developer.orm import (
RedisModel,
indexed,
unique
)
class Member(RedisModel):
email: unique(str)
email: indexed(str)
# email: Indexed[str] <- Probably not possible?
# email: IndexedStr <- This is how constrained types work in Pydantic
class Meta:
primary_key = "id"
indexes = ["email"] # <- How about this?
```
It appears that Pydantic uses functions when declaring the type requires some
kind of parameter. E.g., the max and min values for a constrained numeric
field.
Indexing probably requires, in some cases, parameters... so it should be a
function, probably. And in general, function vs. class appears to be only a case
of whether parameters are required.
1. unique() and indexed() require lots of work.
2. IndexedStr - what does that even mean exactly?
3. indexes = [] - Here, we could hook into class-level validation and add logic
to make sure that any indexed values were unique. Right?
### Unique checking
When is the right time to check if e.g. an email field is unique in Redis?
If we check on instantiation of the model, we'll still need to check again when
we save the model.
### Field() vs constrained int, etc.
Pydantic includes field helpers like constr, etc. that apply a schema to values.
On top of that, we'll have a Field() helper that includes options common to all
data types possible for a field.
This is where we'll track if we should index a field, verify uniqueness, etc.
But for facts like numeric constraints, we'll rely on Pydantic.
### Automatic fields
Redis doesn't have server-side automatic values, dates, etc. So we don't need to
worry about refreshing from the server to get the automatically-created values.
As soon as someone saves a model, we, the ORM, will have created the automatic
values, so we can just set them in the model instance.

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20
pyproject.toml Normal file
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[tool.poetry]
name = "redis-developer-python"
version = "0.1.0"
description = "A high-level library containing useful Redis abstractions and tools, like an ORM and leaderboard."
authors = ["Andrew Brookins <andrew.brookins@redislabs.com>"]
license = "MIT"
[tool.poetry.dependencies]
python = "^3.9"
redis = "^3.5.3"
aioredis = "^2.0.0"
pydantic = "^1.8.2"
[tool.poetry.dev-dependencies]
pytest = "^6.2.4"
ipdb = "^0.13.9"
[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

0
redis_developer/__init__.py Normal file
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5
redis_developer/orm/__init__.py Normal file
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from .model import (
RedisModel,
Relationship,
Field
)

5
redis_developer/orm/connections.py Normal file
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import redis
def get_redis_connection() -> redis.Redis:
return redis.Redis()

179
redis_developer/orm/encoders.py Normal file
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"""
This file adapted from FastAPI's encoders.
Licensed under the MIT License (MIT).
Copyright (c) 2018 Sebastián Ramírez
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
"""
import dataclasses
from collections import defaultdict
from enum import Enum
from pathlib import PurePath
from types import GeneratorType
from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
from pydantic import BaseModel
from pydantic.json import ENCODERS_BY_TYPE
SetIntStr = Set[Union[int, str]]
DictIntStrAny = Dict[Union[int, str], Any]
def generate_encoders_by_class_tuples(
type_encoder_map: Dict[Any, Callable[[Any], Any]]
) -> Dict[Callable[[Any], Any], Tuple[Any, ...]]:
encoders_by_class_tuples: Dict[Callable[[Any], Any], Tuple[Any, ...]] = defaultdict(
tuple
)
for type_, encoder in type_encoder_map.items():
encoders_by_class_tuples[encoder] += (type_,)
return encoders_by_class_tuples
encoders_by_class_tuples = generate_encoders_by_class_tuples(ENCODERS_BY_TYPE)
def jsonable_encoder(
obj: Any,
include: Optional[Union[SetIntStr, DictIntStrAny]] = None,
exclude: Optional[Union[SetIntStr, DictIntStrAny]] = None,
by_alias: bool = True,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
custom_encoder: Dict[Any, Callable[[Any], Any]] = {},
sqlalchemy_safe: bool = True,
) -> Any:
if include is not None and not isinstance(include, (set, dict)):
include = set(include)
if exclude is not None and not isinstance(exclude, (set, dict)):
exclude = set(exclude)
if isinstance(obj, BaseModel):
encoder = getattr(obj.__config__, "json_encoders", {})
if custom_encoder:
encoder.update(custom_encoder)
obj_dict = obj.dict(
include=include, # type: ignore # in Pydantic
exclude=exclude, # type: ignore # in Pydantic
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_none=exclude_none,
exclude_defaults=exclude_defaults,
)
if "__root__" in obj_dict:
obj_dict = obj_dict["__root__"]
return jsonable_encoder(
obj_dict,
exclude_none=exclude_none,
exclude_defaults=exclude_defaults,
custom_encoder=encoder,
sqlalchemy_safe=sqlalchemy_safe,
)
if dataclasses.is_dataclass(obj):
return dataclasses.asdict(obj)
if isinstance(obj, Enum):
return obj.value
if isinstance(obj, PurePath):
return str(obj)
if isinstance(obj, (str, int, float, type(None))):
return obj
if isinstance(obj, dict):
encoded_dict = {}
for key, value in obj.items():
if (
(
not sqlalchemy_safe
or (not isinstance(key, str))
or (not key.startswith("_sa"))
)
and (value is not None or not exclude_none)
and ((include and key in include) or not exclude or key not in exclude)
):
encoded_key = jsonable_encoder(
key,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_none=exclude_none,
custom_encoder=custom_encoder,
sqlalchemy_safe=sqlalchemy_safe,
)
encoded_value = jsonable_encoder(
value,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_none=exclude_none,
custom_encoder=custom_encoder,
sqlalchemy_safe=sqlalchemy_safe,
)
encoded_dict[encoded_key] = encoded_value
return encoded_dict
if isinstance(obj, (list, set, frozenset, GeneratorType, tuple)):
encoded_list = []
for item in obj:
encoded_list.append(
jsonable_encoder(
item,
include=include,
exclude=exclude,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
custom_encoder=custom_encoder,
sqlalchemy_safe=sqlalchemy_safe,
)
)
return encoded_list
if custom_encoder:
if type(obj) in custom_encoder:
return custom_encoder[type(obj)](obj)
else:
for encoder_type, encoder in custom_encoder.items():
if isinstance(obj, encoder_type):
return encoder(obj)
if type(obj) in ENCODERS_BY_TYPE:
return ENCODERS_BY_TYPE[type(obj)](obj)
for encoder, classes_tuple in encoders_by_class_tuples.items():
if isinstance(obj, classes_tuple):
return encoder(obj)
errors: List[Exception] = []
try:
data = dict(obj)
except Exception as e:
errors.append(e)
try:
data = vars(obj)
except Exception as e:
errors.append(e)
raise ValueError(errors)
return jsonable_encoder(
data,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
custom_encoder=custom_encoder,
sqlalchemy_safe=sqlalchemy_safe,
)

390
redis_developer/orm/model.py Normal file
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import datetime
from dataclasses import dataclass
from enum import Enum
from typing import (
AbstractSet,
Any,
Callable,
Dict,
Mapping,
Optional,
Set,
Tuple,
Type,
TypeVar,
Union,
Sequence, ClassVar, TYPE_CHECKING, no_type_check,
)
import redis
from pydantic import BaseModel
from pydantic.fields import FieldInfo as PydanticFieldInfo
from pydantic.fields import ModelField, Undefined, UndefinedType
from pydantic.main import BaseConfig, ModelMetaclass, validate_model
from pydantic.typing import NoArgAnyCallable, resolve_annotations
from pydantic.utils import Representation
from .encoders import jsonable_encoder
from .util import uuid_from_time
_T = TypeVar("_T")
class RedisModelError(Exception):
pass
class NotFoundError(Exception):
pass
class Operations(Enum):
EQ = 1
LT = 2
GT = 3
@dataclass
class Expression:
field: ModelField
op: Operations
right_value: Any
class ExpressionProxy:
def __init__(self, field: ModelField):
self.field = field
def __eq__(self, other: Any) -> Expression:
return Expression(field=self.field, op=Operations.EQ, right_value=other)
def __lt__(self, other: Any) -> Expression:
return Expression(field=self.field, op=Operations.LT, right_value=other)
def __gt__(self, other: Any) -> Expression:
return Expression(field=self.field, op=Operations.GT, right_value=other)
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)
nullable = kwargs.pop("nullable", Undefined)
foreign_key = kwargs.pop("foreign_key", Undefined)
index = kwargs.pop("index", Undefined)
unique = kwargs.pop("unique", Undefined)
super().__init__(default=default, **kwargs)
self.primary_key = primary_key
self.nullable = nullable
self.foreign_key = foreign_key
self.index = index
self.unique = unique
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,
unique: bool = False,
foreign_key: Optional[Any] = None,
nullable: Union[bool, UndefinedType] = Undefined,
index: 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,
unique=unique,
foreign_key=foreign_key,
nullable=nullable,
index=index,
**current_schema_extra,
)
field_info._validate()
return field_info
def Relationship(
*,
back_populates: Optional[str] = None,
link_model: Optional[Any] = None
) -> Any:
relationship_info = RelationshipInfo(
back_populates=back_populates,
link_model=link_model,
)
return relationship_info
@__dataclass_transform__(kw_only_default=True, field_descriptors=(Field, FieldInfo))
class RedisModelMetaclass(ModelMetaclass):
__redismodel_relationships__: Dict[str, RelationshipInfo]
__config__: Type[BaseConfig]
__fields__: Dict[str, ModelField]
# From Pydantic
def __new__(cls, name, bases, class_dict: dict, **kwargs) -> Any:
relationships: Dict[str, RelationshipInfo] = {}
dict_for_pydantic = {}
original_annotations = resolve_annotations(
class_dict.get("__annotations__", {}), class_dict.get("__module__", None)
)
pydantic_annotations = {}
relationship_annotations = {}
for k, v in class_dict.items():
if isinstance(v, RelationshipInfo):
relationships[k] = v
else:
dict_for_pydantic[k] = v
for k, v in original_annotations.items():
if k in relationships:
relationship_annotations[k] = v
else:
pydantic_annotations[k] = v
dict_used = {
**dict_for_pydantic,
"__weakref__": None,
"__redismodel_relationships__": relationships,
"__annotations__": pydantic_annotations,
}
# Duplicate logic from Pydantic to filter config kwargs because if they are
# passed directly including the registry Pydantic will pass them over to the
# superclass causing an error
allowed_config_kwargs: Set[str] = {
key
for key in dir(BaseConfig)
if not (
key.startswith("__") and key.endswith("__")
) # skip dunder methods and attributes
}
pydantic_kwargs = kwargs.copy()
config_kwargs = {
key: pydantic_kwargs.pop(key)
for key in pydantic_kwargs.keys() & allowed_config_kwargs
}
new_cls = super().__new__(cls, name, bases, dict_used, **config_kwargs)
new_cls.__annotations__ = {
**relationship_annotations,
**pydantic_annotations,
**new_cls.__annotations__,
}
return new_cls
@dataclass
class PrimaryKey:
name: str
field: ModelField
class DefaultMeta:
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
class RedisModel(BaseModel, metaclass=RedisModelMetaclass):
"""
TODO: Convert expressions to Redis commands, execute
TODO: Key prefix vs. "key pattern" (that's actually the primary key pattern)
TODO: Default key prefix is model name lowercase
TODO: Build primary key pattern from PK field name, model prefix
TODO: Default PK pattern is model name:pk field
"""
pk: Optional[str] = Field(default=None, primary_key=True)
class Config:
orm_mode = True
arbitrary_types_allowed = True
extra = 'allow'
Meta = DefaultMeta
def __init_subclass__(cls, **kwargs):
# Create proxies for each model field so that we can use the field
# in queries, like Model.get(Model.field_name == 1)
super().__init_subclass__(**kwargs)
for name, field in cls.__fields__.items():
setattr(cls, 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:
cls.Meta.primary_key = PrimaryKey(name=name, field=field)
if not hasattr(cls.Meta, 'primary_key_pattern'):
cls.Meta.primary_key_pattern = f"{cls.Meta.primary_key.name}:{{pk}}"
def __init__(__pydantic_self__, **data: Any) -> None:
# Uses something other than `self` the first arg to allow "self" as a
# settable attribute
if TYPE_CHECKING:
__pydantic_self__.__dict__: Dict[str, Any] = {}
__pydantic_self__.__fields_set__: Set[str] = set()
values, fields_set, validation_error = validate_model(
__pydantic_self__.__class__, data
)
if validation_error:
raise validation_error
__pydantic_self__.validate_primary_key()
object.__setattr__(__pydantic_self__, '__dict__', values)
@classmethod
@no_type_check
def _get_value(cls, *args, **kwargs) -> Any:
"""
Always send None as an empty string.
TODO: How broken is this?
"""
val = super()._get_value(*args, **kwargs)
if val is None:
return ""
return val
@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 field.field_info.primary_key:
primary_keys += 1
# TODO: Automatically create a primary key field instead?
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 key(cls, part: str):
global_prefix = getattr(cls.Meta, 'global_key_prefix', '')
model_prefix = getattr(cls.Meta, 'model_key_prefix', '')
return f"{global_prefix}{model_prefix}{part}"
@classmethod
def get(cls, pk: Any):
# TODO: Getting related objects
pk_pattern = cls.Meta.primary_key_pattern.format(pk=str(pk))
print("GET ", cls.key(pk_pattern))
document = cls.db().hgetall(cls.key(pk_pattern))
if not document:
raise NotFoundError
return cls.parse_obj(document)
def delete(self):
# TODO: deleting relationships
pk = self.__fields__[self.Meta.primary_key.field.name]
pk_pattern = self.Meta.primary_key_pattern.format(pk=pk)
return self.db().delete(self.key(pk_pattern))
@classmethod
def db(cls):
return cls.Meta.database
@classmethod
def filter(cls, *expressions: Sequence[Expression]):
return cls
@classmethod
def exclude(cls, *expressions: Sequence[Expression]):
return cls
@classmethod
def add(cls, models: Sequence['RedisModel']) -> Sequence['RedisModel']:
return [model.save() for model in models]
@classmethod
def update(cls, **field_values):
return cls
@classmethod
def values(cls):
"""Return raw values from Redis instead of model instances."""
return cls
def save(self) -> 'RedisModel':
pk_field = self.Meta.primary_key.field
document = jsonable_encoder(self.dict())
pk = document[pk_field.name]
if not pk:
pk = str(uuid_from_time(datetime.datetime.now()))
setattr(self, pk_field.name, pk)
document[pk_field.name] = pk
pk_pattern = self.Meta.primary_key_pattern.format(pk=pk)
success = self.db().hset(self.key(pk_pattern), mapping=document)
return success
Meta = DefaultMeta
def __init__(self, **data: Any) -> None:
"""Validate that a model instance has a primary key."""
super().__init__(**data)

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# Adapted from the Cassandra Python driver.
#
# Copyright DataStax, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import calendar
import random
import uuid
def uuid_from_time(time_arg, node=None, clock_seq=None):
"""
Converts a datetime or timestamp to a type 1 :class:`uuid.UUID`.
:param time_arg:
The time to use for the timestamp portion of the UUID.
This can either be a :class:`datetime` object or a timestamp
in seconds (as returned from :meth:`time.time()`).
:type datetime: :class:`datetime` or timestamp
:param node:
None integer for the UUID (up to 48 bits). If not specified, this
field is randomized.
:type node: long
:param clock_seq:
Clock sequence field for the UUID (up to 14 bits). If not specified,
a random sequence is generated.
:type clock_seq: int
:rtype: :class:`uuid.UUID`
"""
if hasattr(time_arg, 'utctimetuple'):
seconds = int(calendar.timegm(time_arg.utctimetuple()))
microseconds = (seconds * 1e6) + time_arg.time().microsecond
else:
microseconds = int(time_arg * 1e6)
# 0x01b21dd213814000 is the number of 100-ns intervals between the
# UUID epoch 1582-10-15 00:00:00 and the Unix epoch 1970-01-01 00:00:00.
intervals = int(microseconds * 10) + 0x01b21dd213814000
time_low = intervals & 0xffffffff
time_mid = (intervals >> 32) & 0xffff
time_hi_version = (intervals >> 48) & 0x0fff
if clock_seq is None:
clock_seq = random.getrandbits(14)
else:
if clock_seq > 0x3fff:
raise ValueError('clock_seq is out of range (need a 14-bit value)')
clock_seq_low = clock_seq & 0xff
clock_seq_hi_variant = 0x80 | ((clock_seq >> 8) & 0x3f)
if node is None:
node = random.getrandbits(48)
return uuid.UUID(fields=(time_low, time_mid, time_hi_version,
clock_seq_hi_variant, clock_seq_low, node), version=1)

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import decimal
import datetime
from typing import Optional, List
import redis
from pydantic import ValidationError
from redis_developer.orm import (
RedisModel,
Field,
Relationship,
)
# Declarative model classes
class BaseRedisModel(RedisModel):
class Meta:
database = redis.Redis(password="my-password", decode_responses=True)
model_key_prefix = "redis-developer:"
class Address(BaseRedisModel):
address_line_1: str
address_line_2: Optional[str]
city: str
country: str
postal_code: str
class Order(BaseRedisModel):
total: decimal.Decimal
currency: str
created_on: datetime.datetime
class Member(BaseRedisModel):
first_name: str
last_name: str
email: str = Field(unique=True, index=True)
join_date: datetime.date
# Creates an embedded document: stored as hash fields or JSON document.
address: Address
# Creates a relationship to data in separate Hash or JSON documents.
orders: Optional[List[Order]] = Relationship(back_populates='member')
# Creates a self-relationship.
recommended_by: Optional['Member'] = Relationship(back_populates='recommended')
class Meta(BaseRedisModel.Meta):
model_key_prefix = "member"
primary_key_pattern = ""
# Validation
address = Address(
address_line_1="1 Main St.",
city="Happy Town",
state="WY",
postal_code=11111,
country="USA"
)
# Raises ValidationError: last_name, address are required
try:
Member(
first_name="Andrew",
zipcode="97086",
join_date=datetime.date.today()
)
except ValidationError as e:
pass
# Raises ValidationError: join_date is not a date
try:
Member(
first_name="Andrew",
last_name="Brookins",
join_date="yesterday"
)
except ValidationError as e:
pass
# Passes validation
member = Member(
first_name="Andrew",
last_name="Brookins",
email="a@example.com",
address=address,
join_date=datetime.date.today()
)
exit()
# Save a model instance to Redis
address.save()
address2 = Address.get(address.pk)
assert address2 == address
exit()
# Save a model with relationships (TODO!)
member.save()
# Save many model instances to Redis
today = datetime.date.today()
members = [
Member(
first_name="Andrew",
last_name="Brookins",
email="a@example.com",
address=address,
join_date=today
),
Member(
first_name="Kim",
last_name="Brookins",
email="k@example.com",
address=address,
join_date=today
)
]
Member.add(members)
# Get a model instance from Redis using the primary key.
member = Member.get(1)
# Update a model instance in Redis
member.first_name = "Brian"
member.last_name = "Sam-Bodden"
member.save()
# Or, with an implicit save:
member.update(first_name="Brian", last_name="Sam-Bodden")
# Or, affecting multiple model instances with an implicit save:
Member.filter(Member.last_name == "Brookins").update(last_name="Sam-Bodden")
# Exact-value queries on indexed fields
# What if the field wasn't unique and there were two "a@example.com"
# entries? This would raise a MultipleObjectsReturned error:
member = Member.get(Member.email == "a.m.brookins@gmail.com")
# What if you know there might be multiple results? Use filter():
members = Member.filter(Member.last_name == "Brookins")
# What if you want to only return values that don't match a query?
members = Member.exclude(Member.last_name == "Brookins")
# You can combine filer() and exclude():
members = Member.filter(Member.last_name == "Brookins").exclude(
Member.first_name == "Andrew")