Utility to convert JSON/objects to SQLAlchemy queryset, which is used later to generate SQL queries to fetch data from RDBMS.

• Overview
• Installation
• Features
• Usage
• Operators
• Examples
• Contribution
• TODO

pip install sqlalchemy-json-querybuilder

• Multiple operators' support.

  • Support for Filter operators.
  • Support for Relationship operators i.e. any, has.

• Filter in relationship as well as in collections.

• Pagination using windowing & slicing. Pagination can be disabled if needed.

• Ordering/Sorting in ASC & DESC order.

• Supports AND & OR, so multiple query criterion can be glued and bundled using AND or OR as follows -

  criteria = {
      'and': [and_criterion_dict_1, and_criterion_dict_2, ... and_criterion_dict_n],
      'or': [or_criterion_dict_1, or_criterion_dict_2, ... or_criterion_dict_n]
  }

  which is equivalent to -

  SELECT field_1, field_2..field_n FROM some_table WHERE
        (and_criterion_dict_1 AND and_criterion_dict_2 AND....AND and_criterion_dict_n)
                                  AND
        (or_criterion_dict_1 OR or_criterion_dict_2 OR....OR or_criterion_dict_n);

• Filter criteria

  # Each criterion has 3 attributes: field_name, operator, field_value
  
  criterion_1 = {
      'field_name': 'MyModel1.some_field',
      'operator': 'some_operator'  # Supported operators are listed below
      'field_value': 'some_value'
  }
  
  # Once all the critera are defined in the form of dictionary/object, bundle them as follows -
  
  filter_by = {
      'and': [criterion_1, criterion_2,....criterion_n],
      'or': [other_criterion_1, other_criterion_2,....other_criterion_n]
  }
  
  # If there are `and` critera only, then they can be bundled in following 2 ways -
  filter_by = [criterion_1, criterion_2,....criterion_n] 
  
  # Alternative way to bundle `and` criteria
  filter_by = {
      'and': [criterion_1, criterion_2,....criterion_n]
  }
  
  # If there are `or` critera only, then they can be bundled as -
  filter_by = {
      'or': [criterion_1, criterion_2,....criterion_n]
  }

• Ordering

  ordering = ['MyModel1.some_field', '-MyModel1.other_field']   # `-` sign indicates DESC order.

• Pagination

  Following 3 attributes are used to control pagination:

  • page: Current page number.
  • per_page: Number of records to be displayed on a page.
  • all: Defaults to False, make it True in order to disable the pagination and fetch all records at once.

• Querying

  from sqlalchemy_json_querybuilder.querybuilder.search import Search
  
  # session - SqlAlchemy session
  # 'some_module.models' - Package/module where all the models are placed.
  search_obj = Search(session, 'some_module.models', (MyModel1,), filter_by=criteria, 
                                           order_by=ordering, page=1, per_page=10, all=False)
  
  # `results` property will query the DB and fetch the results, Results contains `data` & `count`
  results = search_obj.results
  
  #  SQLAlchemy `queryset` can also be obtanied, all the functions supported by SQLAlchemy on queryset can be invoked on the underlying queryset and later records can be fetched -
  
  queryset = search_obj.query
  queryset = queryset.join(Address, User.id==Address.user_id).join(UserProfile)
  # Fetching records
  results = queryset.all() 

Following operators are supported -

equals, eq, ==, =,

not_equals, ne, !=, ~=,

less_than, lt, <,

less_than_equals, lte, <=,

greater_than, gt, >,

greater_than_equals, gte, >=,

like, ilike,

startswith, istartswith, endswith, iendswith,

contains, icontains,

match,

in, notin,

isnull, isnotnull,

any, has

Note - i stands for case insensitive.

• any

  filter_by = [{
      'field_name': 'User.addresses',
      'operator': 'any',
      'field_value': {
          'field_name': 'Address.email_address',
          'operator': 'equals',
          'field_value': 'bar'
      }
  }]

  is translated to

  query.filter(User.addresses.any(Address.email_address == 'bar'))
  
  # also takes keyword arguments:
  query.filter(User.addresses.any(email_address='bar'))

• has

  filter_by = [{
      'field_name': 'Address.user',
      'operator': 'has',
      'field_value': {
          'field_name': 'User.name',
          'operator': 'equals',
          'field_value': 'bar'
      }
  }]

  is translated to

  query.filter(Address.user.has(name='ed'))

• equals

  filter_by = [dict(field_name='User.name', field_value='ed', operator='equals')]

  is translated to

  query.filter(User.name == 'ed')

• notequals

  filter_by = [dict(field_name='User.name', field_value='ed', operator='not_equals')]

  is translated to

  query.filter(User.name != 'ed')

• lt

  filter_by = [dict(field_name='User.age', field_value=18, operator='lt')]

  is translated to

  query.filter(User.age < 18)

• lte

  filter_by = [dict(field_name='User.age', field_value=18, operator='lte')]

  is translated to

  query.filter(User.age <= 18)

• gt

  filter_by = [dict(field_name='User.age', field_value=18, operator='gt')]

  is translated to

  query.filter(User.age > 18)

• gte

  filter_by = [dict(field_name='User.age', field_value=18, operator='gte')]

  is translated to

  query.filter(User.age >= 18)

• in

  filter_by = [dict(field_name='User.name', field_value=['ed', 'wendy', 'jack'], operator='in')]

  is translated to

  query.filter(User.name.in_(['ed', 'wendy', 'jack']))

• notin

  filter_by = [dict(field_name='User.name', field_value=['ed', 'wendy', 'jack'], operator='notin')]

  is translated to

  query.filter(~User.name.in_(['ed', 'wendy', 'jack']))

• isnull

  filter_by = [dict(field_name='User.name', field_value=null, operator='isnull')]

  is translated to

  query.filter(User.name == None)
  
  # alternatively, if pep8/linters are a concern
  query.filter(User.name.is_(None))

• isnotnull

  filter_by = [dict(field_name='User.name', field_value=null, operator='isnotnull')]

  is translated to

  query.filter(User.name != None)
  
  # alternatively, if pep8/linters are a concern
  query.filter(User.name.isnot(None))

• contains

  filter_by = [dict(field_name='User.name', field_value='ed', operator='contains')]

  is translated to

  query.filter(User.name.like('%ed%'))

• startswith

  filter_by = [dict(field_name='User.name', field_value='ed', operator='startswith')]

  is translated to

  query.filter(User.name.like('ed%'))

• endswith

  filter_by = [dict(field_name='User.name', field_value='ed', operator='endswith')]

  is translated to

  query.filter(User.name.like('%ed'))

• match

  filter_by = [dict(field_name='User.name', field_value='wendy', operator='match')]

  is translated to

  query.filter(User.name.match('wendy'))

Some examples are given below. More examples can be found here.

#-------------- Creating connection & session ---------------#

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker, scoped_session

Base = declarative_base()
con_url = 'mysql+pymysql://{username}:{password}@{host}:{port}/{database}'.format(
    username='root', password='', host='localhost', port=3306, database='test'
)
engine = create_engine(con_url, pool_recycle=3600)

# Set up the session
session_maker = sessionmaker(bind=engine, autoflush=True, autocommit=False, expire_on_commit=True)
session = scoped_session(session_maker)

#-------------- Models ---------------#

from uuid import uuid4
from sqlalchemy import Column, Integer, String, Text, ForeignKey
from sqlalchemy.orm import relationship

def generate_uuid():
    return str(uuid4())
    
class NotificationGroup(Base):
    __tablename__ = "notification_group"

    id = Column("id", String(75), primary_key=True, default=generate_uuid)
    client_id = Column('client_id', Integer, nullable=False)
    denotation = Column('denotation', String(250), nullable=False) 
    description = Column('description', String(500))
    customers_sites = Column('customers_sites', Text, nullable=False)
    group_mappings = relationship("NotificationGroupMapping", backref="notification_group_mapping", lazy='dynamic')
 
class NotificationGroupMapping(Base):
    __tablename__ = "notification_group_mapping"

    id = Column("id", String(75), primary_key=True, default=generate_uuid)
    notification_group_id = Column(String(75), ForeignKey('notification_group.id'))
    event_id = Column(String(75), nullable=False)
    recipient_id = Column(String(75), ForeignKey('recipient_group.id'))
    recipient = relationship("Recipient")
    is_used = Column(String(75), nullable=False)

class Recipient(Base):
    __tablename__ = 'recipients'

    client_id = Column('client_id', Integer, nullable=False)
    user_id = Column('user_id', Integer, nullable=False)
    email = Column('email', String(256), nullable=False)

#-------------- Query -------------#

from sqlalchemy_json_querybuilder.querybuilder.search import Search

# `filter_by` can have multiple criteria objects bundled as a list.
filter_by = [{
    "field_name": "NotificationGroup.group_mappings",
    "field_value": {
      "field_name": "NotificationGroupMapping.recipient",
      "field_value": {
        "field_name": "Recipient.email",
        "field_value": "[email protected]",
        "operator": "equals"
      },
      "operator": "has"
    },
    "operator": "any"
}]

# `order_by` can have multiple column names. `-` indicates arranging the results in `DESC` order.
order_by = ['-NotificationGroup.client_id']

# returns `results` dict containing `data` & `count`
results = Search(session, "models.notification_group", (NotificationGroup,), 
                filter_by=filter_by, order_by=order_by, page=1, per_page=5).results

# Above code snippet is equivalent to

results = session.query(NotificationGroup).filter(
            NotificationGroup.group_mappings.any(
                NotificationGroupMapping.recipient.has(
                    Recipient.email=='[email protected]'
                )
            )
          ).all()
 

Pull requests are welcome! Please create new pull requests from dev branch.

• Support for JSON columns.