forked from Raiza.dev/EliteBot
376 lines
12 KiB
Python
376 lines
12 KiB
Python
"""
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This module provides a decorator function for observing changes in a given
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property. Internally the decorator is implemented using SQLAlchemy event
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listeners. Both column properties and relationship properties can be observed.
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Property observers can be used for pre-calculating aggregates and automatic
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real-time data denormalization.
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Simple observers
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----------------
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At the heart of the observer extension is the :func:`observes` decorator. You
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mark some property path as being observed and the marked method will get
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notified when any changes are made to given path.
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Consider the following model structure:
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::
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class Director(Base):
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__tablename__ = 'director'
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id = sa.Column(sa.Integer, primary_key=True)
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name = sa.Column(sa.String)
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date_of_birth = sa.Column(sa.Date)
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class Movie(Base):
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__tablename__ = 'movie'
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id = sa.Column(sa.Integer, primary_key=True)
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name = sa.Column(sa.String)
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director_id = sa.Column(sa.Integer, sa.ForeignKey(Director.id))
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director = sa.orm.relationship(Director, backref='movies')
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Now consider we want to show movies in some listing ordered by director id
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first and movie id secondly. If we have many movies then using joins and
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ordering by Director.name will be very slow. Here is where denormalization
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and :func:`observes` comes to rescue the day. Let's add a new column called
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director_name to Movie which will get automatically copied from associated
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Director.
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::
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from sqlalchemy_utils import observes
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class Movie(Base):
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# same as before..
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director_name = sa.Column(sa.String)
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@observes('director')
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def director_observer(self, director):
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self.director_name = director.name
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.. note::
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This example could be done much more efficiently using a compound foreign
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key from director_name, director_id to Director.name, Director.id but for
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the sake of simplicity we added this as an example.
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Observes vs aggregated
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----------------------
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:func:`observes` and :func:`.aggregates.aggregated` can be used for similar
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things. However performance wise you should take the following things into
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consideration:
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* :func:`observes` works always inside transaction and deals with objects. If
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the relationship observer is observing has a large number of objects it's
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better to use :func:`.aggregates.aggregated`.
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* :func:`.aggregates.aggregated` always executes one additional query per
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aggregate so in scenarios where the observed relationship has only a handful
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of objects it's better to use :func:`observes` instead.
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Example 1. Movie with many ratings
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Let's say we have a Movie object with potentially thousands of ratings. In this
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case we should always use :func:`.aggregates.aggregated` since iterating
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through thousands of objects is slow and very memory consuming.
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Example 2. Product with denormalized catalog name
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Each product belongs to one catalog. Here it is natural to use :func:`observes`
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for data denormalization.
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Deeply nested observing
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-----------------------
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Consider the following model structure where Catalog has many Categories and
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Category has many Products.
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::
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class Catalog(Base):
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__tablename__ = 'catalog'
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id = sa.Column(sa.Integer, primary_key=True)
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product_count = sa.Column(sa.Integer, default=0)
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@observes('categories.products')
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def product_observer(self, products):
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self.product_count = len(products)
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categories = sa.orm.relationship('Category', backref='catalog')
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class Category(Base):
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__tablename__ = 'category'
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id = sa.Column(sa.Integer, primary_key=True)
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catalog_id = sa.Column(sa.Integer, sa.ForeignKey('catalog.id'))
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products = sa.orm.relationship('Product', backref='category')
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class Product(Base):
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__tablename__ = 'product'
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id = sa.Column(sa.Integer, primary_key=True)
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price = sa.Column(sa.Numeric)
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category_id = sa.Column(sa.Integer, sa.ForeignKey('category.id'))
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:func:`observes` is smart enough to:
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* Notify catalog objects of any changes in associated Product objects
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* Notify catalog objects of any changes in Category objects that affect
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products (for example if Category gets deleted, or a new Category is added to
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Catalog with any number of Products)
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::
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category = Category(
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products=[Product(), Product()]
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)
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category2 = Category(
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product=[Product()]
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)
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catalog = Catalog(
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categories=[category, category2]
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)
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session.add(catalog)
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session.commit()
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catalog.product_count # 2
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session.delete(category)
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session.commit()
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catalog.product_count # 1
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Observing multiple columns
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-----------------------
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You can also observe multiple columns by specifying all the observable columns
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in the decorator.
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::
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class Order(Base):
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__tablename__ = 'order'
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id = sa.Column(sa.Integer, primary_key=True)
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unit_price = sa.Column(sa.Integer)
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amount = sa.Column(sa.Integer)
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total_price = sa.Column(sa.Integer)
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@observes('amount', 'unit_price')
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def total_price_observer(self, amount, unit_price):
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self.total_price = amount * unit_price
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"""
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import itertools
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from collections import defaultdict, namedtuple
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from collections.abc import Iterable
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import sqlalchemy as sa
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from .functions import getdotattr, has_changes
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from .path import AttrPath
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from .utils import is_sequence
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Callback = namedtuple('Callback', ['func', 'backref', 'fullpath'])
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class PropertyObserver:
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def __init__(self):
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self.listener_args = [
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(
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sa.orm.Mapper,
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'mapper_configured',
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self.update_generator_registry
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),
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(
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sa.orm.Mapper,
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'after_configured',
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self.gather_paths
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),
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(
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sa.orm.session.Session,
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'before_flush',
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self.invoke_callbacks
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)
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]
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self.callback_map = defaultdict(list)
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# TODO: make the registry a WeakKey dict
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self.generator_registry = defaultdict(list)
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def remove_listeners(self):
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for args in self.listener_args:
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sa.event.remove(*args)
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def register_listeners(self):
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for args in self.listener_args:
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if not sa.event.contains(*args):
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sa.event.listen(*args)
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def __repr__(self):
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return '<PropertyObserver>'
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def update_generator_registry(self, mapper, class_):
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"""
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Adds generator functions to generator_registry.
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"""
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for generator in class_.__dict__.values():
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if hasattr(generator, '__observes__'):
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self.generator_registry[class_].append(
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generator
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)
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def gather_paths(self):
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for class_, generators in self.generator_registry.items():
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for callback in generators:
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full_paths = []
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for call_path in callback.__observes__:
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full_paths.append(AttrPath(class_, call_path))
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for path in full_paths:
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self.callback_map[class_].append(
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Callback(
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func=callback,
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backref=None,
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fullpath=full_paths
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)
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)
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for index in range(len(path)):
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i = index + 1
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prop = path[index].property
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if isinstance(prop, sa.orm.RelationshipProperty):
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prop_class = path[index].property.mapper.class_
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self.callback_map[prop_class].append(
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Callback(
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func=callback,
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backref=~ (path[:i]),
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fullpath=full_paths
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)
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)
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def gather_callback_args(self, obj, callbacks):
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session = sa.orm.object_session(obj)
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for callback in callbacks:
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backref = callback.backref
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root_objs = getdotattr(obj, backref) if backref else obj
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if root_objs:
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if not isinstance(root_objs, Iterable):
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root_objs = [root_objs]
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with session.no_autoflush:
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for root_obj in root_objs:
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if root_obj:
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args = self.get_callback_args(root_obj, callback)
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if args:
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yield args
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def get_callback_args(self, root_obj, callback):
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session = sa.orm.object_session(root_obj)
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objects = [getdotattr(
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root_obj,
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path,
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lambda obj: obj not in session.deleted
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) for path in callback.fullpath]
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paths = [str(path) for path in callback.fullpath]
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for path in paths:
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if '.' in path or has_changes(root_obj, path):
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return (
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root_obj,
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callback.func,
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objects
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)
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def iterate_objects_and_callbacks(self, session):
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objs = itertools.chain(session.new, session.dirty, session.deleted)
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for obj in objs:
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for class_, callbacks in self.callback_map.items():
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if isinstance(obj, class_):
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yield obj, callbacks
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def invoke_callbacks(self, session, ctx, instances):
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callback_args = defaultdict(lambda: defaultdict(set))
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for obj, callbacks in self.iterate_objects_and_callbacks(session):
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args = self.gather_callback_args(obj, callbacks)
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for (root_obj, func, objects) in args:
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if not callback_args[root_obj][func]:
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callback_args[root_obj][func] = {}
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for i, object_ in enumerate(objects):
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if is_sequence(object_):
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callback_args[root_obj][func][i] = (
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callback_args[root_obj][func].get(i, set()) |
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set(object_)
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)
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else:
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callback_args[root_obj][func][i] = object_
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for root_obj, callback_objs in callback_args.items():
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for callback, objs in callback_objs.items():
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callback(root_obj, *[objs[i] for i in range(len(objs))])
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observer = PropertyObserver()
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def observes(*paths, **observer_kw):
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"""
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Mark method as property observer for the given property path. Inside
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transaction observer gathers all changes made in given property path and
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feeds the changed objects to observer-marked method at the before flush
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phase.
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::
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from sqlalchemy_utils import observes
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class Catalog(Base):
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__tablename__ = 'catalog'
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id = sa.Column(sa.Integer, primary_key=True)
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category_count = sa.Column(sa.Integer, default=0)
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@observes('categories')
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def category_observer(self, categories):
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self.category_count = len(categories)
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class Category(Base):
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__tablename__ = 'category'
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id = sa.Column(sa.Integer, primary_key=True)
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catalog_id = sa.Column(sa.Integer, sa.ForeignKey('catalog.id'))
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catalog = Catalog(categories=[Category(), Category()])
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session.add(catalog)
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session.commit()
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catalog.category_count # 2
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.. versionadded: 0.28.0
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:param *paths: One or more dot-notated property paths, eg.
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'categories.products.price'
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:param **observer: A dictionary where value for key 'observer' contains
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:meth:`PropertyObserver` object
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"""
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observer_ = observer_kw.pop('observer', observer)
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observer_.register_listeners()
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def wraps(func):
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def wrapper(self, *args, **kwargs):
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return func(self, *args, **kwargs)
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wrapper.__observes__ = paths
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return wrapper
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return wraps
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