Filter, sort and paginate SQLAlchemy query objects. Ideal for exposing these actions over a REST API.
Assuming that we have a SQLAlchemy query object:
from sqlalchemy import Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
class Base(object):
id = Column(Integer, primary_key=True)
name = Column(String(50), nullable=False)
count = Column(Integer, nullable=True)
@hybrid_property
def count_square(self):
return self.count * self.count
@hybrid_method
def three_times_count(self):
return self.count * 3
Base = declarative_base(cls=Base)
class Foo(Base):
__tablename__ = 'foo'
# ...
query = session.query(Foo)Then we can apply filters to that query object (multiple times):
from sqlalchemy_filters import apply_filters
# `query` should be a SQLAlchemy query object
filter_spec = [{'field': 'name', 'op': '==', 'value': 'name_1'}]
filtered_query = apply_filters(query, filter_spec)
more_filters = [{'field': 'foo_id', 'op': 'is_not_null'}]
filtered_query = apply_filters(filtered_query, more_filters)
result = filtered_query.all()It is also possible to filter queries that contain multiple models, including joins:
class Bar(Base):
__tablename__ = 'bar'
foo_id = Column(Integer, ForeignKey('foo.id'))query = session.query(Foo).join(Bar)
filter_spec = [
{'model': 'Foo', 'field': 'name', 'op': '==', 'value': 'name_1'},
{'model': 'Bar', 'field': 'count', 'op': '>=', 'value': 5},
]
filtered_query = apply_filters(query, filter_spec)
result = filtered_query.all()apply_filters will attempt to automatically join models to query
if they're not already present and a model-specific filter is supplied.
For example, the value of filtered_query in the following two code
blocks is identical:
query = session.query(Foo).join(Bar) # join pre-applied to query
filter_spec = [
{'model': 'Foo', 'field': 'name', 'op': '==', 'value': 'name_1'},
{'model': 'Bar', 'field': 'count', 'op': '>=', 'value': 5},
]
filtered_query = apply_filters(query, filter_spec)query = session.query(Foo) # join to Bar will be automatically applied
filter_spec = [
{field': 'name', 'op': '==', 'value': 'name_1'},
{'model': 'Bar', 'field': 'count', 'op': '>=', 'value': 5},
]
filtered_query = apply_filters(query, filter_spec)The automatic join is only possible if SQLAlchemy can implictly determine the condition for the join, for example because of a foreign key relationship.
Automatic joins allow flexibility for clients to filter and sort by related
objects without specifying all possible joins on the server beforehand. Feature
can be explicitly disabled by passing do_auto_join=False argument to the
apply_filters call.
Note that first filter of the second block does not specify a model.
It is implictly applied to the Foo model because that is the only
model in the original query passed to apply_filters.
It is also possible to apply filters to queries defined by fields, functions or
select_from clause:
query_alt_1 = session.query(Foo.id, Foo.name)
query_alt_2 = session.query(func.count(Foo.id))
query_alt_3 = session.query().select_from(Foo).add_column(Foo.id)You can filter by a hybrid attribute: a hybrid property or a hybrid method.
query = session.query(Foo)
filter_spec = [{'field': 'count_square', 'op': '>=', 'value': 25}]
filter_spec = [{'field': 'three_times_count', 'op': '>=', 'value': 15}]
filtered_query = apply_filters(query, filter_spec)
result = filtered_query.all()You can restrict the fields that SQLAlchemy loads from the database by
using the apply_loads function:
query = session.query(Foo, Bar).join(Bar)
load_spec = [
{'model': 'Foo', 'fields': ['name']},
{'model': 'Bar', 'fields': ['count']}
]
query = apply_loads(query, load_spec) # will load only Foo.name and Bar.countThe effect of the apply_loads function is to _defer_ the load
of any other fields to when/if they're accessed, rather than loading
them when the query is executed. It only applies to fields that would be
loaded during normal query execution.
The default SQLAlchemy join is lazy, meaning that columns from the
joined table are loaded only when required. Therefore apply_loads
has limited effect in the following scenario:
query = session.query(Foo).join(Bar)
load_spec = [
{'model': 'Foo', 'fields': ['name']}
{'model': 'Bar', 'fields': ['count']} # ignored
]
query = apply_loads(query, load_spec) # will load only Foo.nameapply_loads cannot be applied to columns that are loaded as
joined eager loads.
This is because a joined eager load does not add the joined model to the
original query, as explained
here
The following would not prevent all columns from Bar being eagerly
loaded:
query = session.query(Foo).options(joinedload(Foo.bar))
load_spec = [
{'model': 'Foo', 'fields': ['name']}
{'model': 'Bar', 'fields': ['count']}
]
query = apply_loads(query, load_spec)Automatic Join
In fact, what happens here is that Bar is automatically joined
to query, because it is determined that Bar is not part of
the original query. The load_spec therefore has no effect
because the automatic join results in lazy evaluation.
If you wish to perform a joined load with restricted columns, you must
specify the columns as part of the joined load, rather than with
apply_loads:
query = session.query(Foo).options(joinedload(Bar).load_only('count'))
load_spec = [
{'model': 'Foo', 'fields': ['name']}
]
query = apply_loads(query. load_spec) # will load ony Foo.name and Bar.countfrom sqlalchemy_filters import apply_sort
# `query` should be a SQLAlchemy query object
sort_spec = [
{'model': 'Foo', 'field': 'name', 'direction': 'asc'},
{'model': 'Bar', 'field': 'id', 'direction': 'desc'},
]
sorted_query = apply_sort(query, sort_spec)
result = sorted_query.all()apply_sort will attempt to automatically join models to query if
they're not already present and a model-specific sort is supplied.
The behaviour is the same as in apply_filters.
This allows flexibility for clients to sort by fields on related objects without specifying all possible joins on the server beforehand.
You can sort by a hybrid attribute: a hybrid property or a hybrid method.
from sqlalchemy_filters import apply_pagination
# `query` should be a SQLAlchemy query object
query, pagination = apply_pagination(query, page_number=1, page_size=10)
page_size, page_number, num_pages, total_results = pagination
assert 10 == len(query)
assert 10 == page_size == pagination.page_size
assert 1 == page_number == pagination.page_number
assert 3 == num_pages == pagination.num_pages
assert 22 == total_results == pagination.total_resultsFilters must be provided in a list and will be applied sequentially. Each filter will be a dictionary element in that list, using the following format:
filter_spec = [
{'model': 'model_name', 'field': 'field_name', 'op': '==', 'value': 'field_value'},
{'model': 'model_name', 'field': 'field_2_name', 'op': '!=', 'value': 'field_2_value'},
# ...
]The model key is optional if the original query being filtered only
applies to one model.
If there is only one filter, the containing list may be omitted:
filter_spec = {'field': 'field_name', 'op': '==', 'value': 'field_value'}Where field is the name of the field that will be filtered using the
operator provided in op (optional, defaults to ==) and the
provided value (optional, depending on the operator).
This is the list of operators that can be used:
is_nullis_not_null==,eq!=,ne>,gt<,lt>=,ge<=,lelikeilikenot_ilikeinnot_inanynot_any
PostgreSQL specific operators allow to filter queries on columns of type ARRAY.
Use any to filter if a value is present in an array and not_any if it's not.
and, or, and not functions can be used and nested within the
filter specification:
filter_spec = [
{
'or': [
{
'and': [
{'field': 'field_name', 'op': '==', 'value': 'field_value'},
{'field': 'field_2_name', 'op': '!=', 'value': 'field_2_value'},
]
},
{
'not': [
{'field': 'field_3_name', 'op': '==', 'value': 'field_3_value'}
]
},
],
}
]Note: or and and must reference a list of at least one element.
not must reference a list of exactly one element.
Sort elements must be provided as dictionaries in a list and will be applied sequentially:
sort_spec = [
{'model': 'Foo', 'field': 'name', 'direction': 'asc'},
{'model': 'Bar', 'field': 'id', 'direction': 'desc'},
# ...
]Where field is the name of the field that will be sorted using the
provided direction.
The model key is optional if the original query being sorted only
applies to one model.
sort_spec = [
{'model': 'Baz', 'field': 'count', 'direction': 'asc', 'nullsfirst': True},
{'model': 'Qux', 'field': 'city', 'direction': 'desc', 'nullslast': True},
# ...
]nullsfirst is an optional attribute that will place NULL values first
if set to True, according to the SQLAlchemy documentation.
nullslast is an optional attribute that will place NULL values last
if set to True, according to the SQLAlchemy documentation.
If none of them are provided, then NULL values will be sorted according
to the RDBMS being used. SQL defines that NULL values should be placed
together when sorting, but it does not specify whether they should be placed
first or last.
Even though both nullsfirst and nullslast are part of SQLAlchemy,
they will raise an unexpected exception if the RDBMS that is being used does
not support them.
At the moment they are supported by PostgreSQL, but they are not supported by SQLite and MySQL.
The default configuration uses SQLite, MySQL (if the driver is
installed, which is the case when tox is used) and PostgreSQL
(if the driver is installed, which is the case when tox is used) to
run the tests, with the following URIs:
sqlite+pysqlite:///test_sqlalchemy_filters.db
mysql+mysqlconnector://root:@localhost:3306/test_sqlalchemy_filters
postgresql+psycopg2://postgres:@localhost:5432/test_sqlalchemy_filters?client_encoding=utf8'A test database will be created, used during the tests and destroyed afterwards for each RDBMS configured.
There are Makefile targets to run docker containers locally for both MySQL and PostgreSQL, using the default ports and configuration:
$ make mysql-container
$ make postgres-containerTo run the tests locally:
$ # Create/activate a virtual environment
$ pip install tox
$ toxThere are some other Makefile targets that can be used to run the tests:
There are other Makefile targets to run the tests, but extra dependencies will have to be installed:
$ pip install -U --editable ".[dev,mysql,postgresql]"
$ # using default settings
$ make test
$ make coverage
$ # overriding DB parameters
$ ARGS='--mysql-test-db-uri mysql+mysqlconnector://root:@192.168.99.100:3340/test_sqlalchemy_filters' make test
$ ARGS='--sqlite-test-db-uri sqlite+pysqlite:///test_sqlalchemy_filters.db' make test
$ ARGS='--mysql-test-db-uri mysql+mysqlconnector://root:@192.168.99.100:3340/test_sqlalchemy_filters' make coverage
$ ARGS='--sqlite-test-db-uri sqlite+pysqlite:///test_sqlalchemy_filters.db' make coverageThe following RDBMS are supported (tested):
- SQLite
- MySQL
- PostgreSQL
The following SQLAlchemy versions are supported: 1.0, 1.1,
1.2, 1.3, 1.4.
Consult the CHANGELOG document for fixes and enhancements of each version.
Apache 2.0. See LICENSE for details.
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