284 lines
9.1 KiB
Python
284 lines
9.1 KiB
Python
from __future__ import annotations
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import random
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from collections import defaultdict
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from functools import lru_cache
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from typing import Optional, Dict, Tuple, List, Type, Generic, Any, TypeVar, Set
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from pathlib import Path
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import inspect
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from .metadata import Metadata
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from ..utils import get_unix_time, object_trace
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from ..utils.config import logging_settings, main_settings
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from ..utils.shared import HIGHEST_ID
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from ..utils.hacking import MetaClass
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LOGGER = logging_settings["object_logger"]
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P = TypeVar("P", bound="OuterProxy")
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class InnerData:
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"""
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This is the core class, which is used for every Data class.
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The attributes are set, and can be merged.
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The concept is, that the outer class proxies this class.
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If the data in the wrapper class has to be merged, then this class is just replaced and garbage collected.
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"""
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_refers_to_instances: set = None
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def __init__(self, object_type, **kwargs):
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self._refers_to_instances = set()
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# collection : collection that is a collection of self
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self._is_collection_child: Dict[Collection, Collection] = {}
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self._is_collection_parent: Dict[Collection, Collection] = {}
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# initialize the default values
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self._default_values = {}
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for name, factory in object_type._default_factories.items():
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self._default_values[name] = factory()
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for key, value in kwargs.items():
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self.__setattr__(key, value)
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def __merge__(self, __other: InnerData, override: bool = False):
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"""
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:param __other:
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:param override:
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:return:
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"""
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for key, value in __other.__dict__.copy().items():
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# just set the other value if self doesn't already have it
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if key not in self.__dict__ or (key in self.__dict__ and self.__dict__[key] == self._default_values.get(key)):
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self.__setattr__(key, value)
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continue
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# if the object of value implemented __merge__, it merges
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existing = self.__getattribute__(key)
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if hasattr(type(existing), "__merge__"):
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existing.__merge__(value, override)
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continue
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# override the existing value if requested
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if override:
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self.__setattr__(key, value)
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class OuterProxy:
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"""
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Wraps the inner data, and provides apis, to naturally access those values.
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"""
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_default_factories: dict = {}
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_outer_attribute: Set[str] = {"options", "metadata", "indexing_values", "option_string"}
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DOWNWARDS_COLLECTION_STRING_ATTRIBUTES = tuple()
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UPWARDS_COLLECTION_STRING_ATTRIBUTES = tuple()
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TITEL = "id"
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def __init__(self, _id: int = None, dynamic: bool = False, **kwargs):
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_automatic_id: bool = False
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if _id is None and not dynamic:
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"""
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generates a random integer id
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the range is defined in the config
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"""
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_id = random.randint(0, HIGHEST_ID)
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_automatic_id = True
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kwargs["automatic_id"] = _automatic_id
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kwargs["id"] = _id
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kwargs["dynamic"] = dynamic
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for name, factory in type(self)._default_factories.items():
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if kwargs.get(name, None) is None:
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kwargs[name] = factory()
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collection_data: Dict[str, list] = {}
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for name, value in kwargs.copy().items():
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if isinstance(value, list) and name.endswith("_list"):
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collection_name = name.replace("_list", "_collection")
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collection_data[collection_name] = value
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del kwargs[name]
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self._fetched_from: dict = {}
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self._inner: InnerData = InnerData(type(self), **kwargs)
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self._inner._refers_to_instances.add(self)
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object_trace(f"creating {type(self).__name__} [{self.title_string}]")
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self.__init_collections__()
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for name, data_list in collection_data.items():
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collection = self._inner.__getattribute__(name)
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collection.extend(data_list)
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self._inner.__setattr__(name, collection)
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def __init_collections__(self):
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pass
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def __getattribute__(self, __name: str) -> Any:
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"""
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Returns the attribute of _inner if the attribute exists,
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else it returns the attribute of self.
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That the _inner gets checked first is essential for the type hints.
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:param __name:
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:return:
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"""
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if __name.startswith("_") or __name in self._outer_attribute or __name.isupper():
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return object.__getattribute__(self, __name)
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_inner: InnerData = super().__getattribute__("_inner")
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try:
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return _inner.__getattribute__(__name)
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except AttributeError:
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return super().__getattribute__(__name)
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def __setattr__(self, __name, __value):
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if not __name.startswith("_") and hasattr(self, "_inner"):
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_inner: InnerData = super().__getattribute__("_inner")
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return _inner.__setattr__(__name, __value)
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return super().__setattr__(__name, __value)
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def _add_other_db_objects(self, object_type: Type[OuterProxy], object_list: List[OuterProxy]):
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pass
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def add_list_of_other_objects(self, object_list: List[OuterProxy]):
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d: Dict[Type[OuterProxy], List[OuterProxy]] = defaultdict(list)
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for db_object in object_list:
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d[type(db_object)].append(db_object)
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for key, value in d.items():
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self._add_other_db_objects(key, value)
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def __hash__(self):
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return id(self)
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def __eq__(self, other: Any):
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return self.__hash__() == other.__hash__()
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def merge(self, __other: Optional[OuterProxy], override: bool = False):
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"""
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1. merges the data of __other in self
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2. replaces the data of __other with the data of self
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:param __other:
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:param override:
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:return:
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"""
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if __other is None:
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return
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a = self
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b = __other
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if a.id == b.id:
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return
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# switch instances if more efficient
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if len(b._inner._refers_to_instances) > len(a._inner._refers_to_instances):
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a, b = b, a
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object_trace(f"merging {type(a).__name__} [{a.title_string} | {a.id}] with {type(b).__name__} [{b.title_string} | {b.id}] called by [{' | '.join(f'{s.function} {Path(s.filename).name}:{str(s.lineno)}' for s in inspect.stack()[1:5])}]")
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for collection, child_collection in b._inner._is_collection_child.items():
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try:
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collection.children.remove(child_collection)
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except ValueError:
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pass
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for collection, parent_collection in b._inner._is_collection_parent.items():
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try:
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collection.parents.remove(parent_collection)
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except ValueError:
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pass
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old_inner = b._inner
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for instance in b._inner._refers_to_instances.copy():
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instance._inner = a._inner
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a._inner._refers_to_instances.add(instance)
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a._inner.__merge__(old_inner, override=override)
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del old_inner
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def __merge__(self, __other: Optional[OuterProxy], override: bool = False):
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self.merge(__other, override)
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def mark_as_fetched(self, *url_hash_list: List[str]):
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for url_hash in url_hash_list:
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self._fetched_from[url_hash] = {
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"time": get_unix_time(),
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"url": url_hash,
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}
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def already_fetched_from(self, url_hash: str) -> bool:
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res = self._fetched_from.get(url_hash, None)
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if res is None:
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return False
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return get_unix_time() - res["time"] < main_settings["refresh_after"]
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@property
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def metadata(self) -> Metadata:
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"""
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This is an interface.
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:return:
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"""
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return Metadata()
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@property
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def options(self) -> List[P]:
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return [self]
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@property
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def indexing_values(self) -> List[Tuple[str, object]]:
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"""
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This is an interface.
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It is supposed to return a map of the name and values for all important attributes.
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This helps in comparing classes for equal data (e.g. being the same song but different attributes)
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TODO
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Rewrite this approach into a approach, that is centered around statistics, and not binaries.
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Instead of: one of this matches, it is the same
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This: If enough attributes are similar enough, they are the same
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Returns:
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List[Tuple[str, object]]: the first element in the tuple is the name of the attribute, the second the value.
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"""
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return []
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@property
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@lru_cache()
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def all_collections(self):
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r = []
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for key in self._default_factories:
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val = self._inner.__getattribute__(key)
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if hasattr(val, "__is_collection__"):
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r.append(val)
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return r
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def __repr__(self):
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return f"{type(self).__name__}({', '.join(key + ': ' + str(val) for key, val in self.indexing_values)})"
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@property
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def title_string(self) -> str:
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return str(self.__getattribute__(self.TITEL))
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