SQLAlchemy - build query filter dynamically from dict

SQLAlchemy - build query filter dynamically from dict

You can build a SQLAlchemy query filter dynamically from a dictionary by iterating through the dictionary's key-value pairs and constructing filter conditions based on the keys and values. Here's an example of how to do this:

Suppose you have a dictionary filter_dict where keys are column names, and values are the values you want to filter on:

filter_dict = { 'name': 'Alice', 'age': 30, 'city': 'New York' }

You can build a query filter using SQLAlchemy as follows:

from sqlalchemy import create_engine, Column, Integer, String from sqlalchemy.orm import sessionmaker from sqlalchemy.ext.declarative import declarative_base # Define the SQLAlchemy model Base = declarative_base() class Person(Base): __tablename__ = 'people' id = Column(Integer, primary_key=True) name = Column(String) age = Column(Integer) city = Column(String) # Create a SQLAlchemy engine and session engine = create_engine('sqlite:///test.db') # Replace with your database URL Session = sessionmaker(bind=engine) session = Session() # Define a base query query = session.query(Person) # Build the dynamic filter for key, value in filter_dict.items(): if hasattr(Person, key): # Check if the model has the specified column column = getattr(Person, key) query = query.filter(column == value) # Execute the query results = query.all() # Print the results for person in results: print(f"Name: {person.name}, Age: {person.age}, City: {person.city}")

In this example:

  1. We define the Person SQLAlchemy model with columns name, age, and city.

  2. We create a SQLAlchemy engine and session to interact with the database.

  3. We define a base query using session.query(Person).

  4. We iterate through the filter_dict and check if the key corresponds to a valid column in the Person model using hasattr(Person, key).

  5. If the key is a valid column, we use getattr(Person, key) to get the corresponding column attribute and construct a filter condition, e.g., column == value, and add it to the query.

  6. We execute the query with query.all() to retrieve the filtered results.

  7. Finally, we print the results.

This approach allows you to dynamically build a query filter based on the contents of the filter_dict.

Examples

  1. SQLAlchemy dynamic filter with dictionary: Description: Dynamically building SQLAlchemy filters from a dictionary allows for flexible query construction based on varying criteria. This query showcases how to achieve this functionality efficiently.

    from sqlalchemy import and_, or_ from sqlalchemy.orm import sessionmaker from your_module import YourModel def build_filter(session, filter_dict): filters = [] for key, value in filter_dict.items(): filters.append(getattr(YourModel, key) == value) return filters filter_criteria = {"column_name": "desired_value", "another_column": "another_value"} Session = sessionmaker(bind=engine) session = Session() query = session.query(YourModel).filter(and_(*build_filter(session, filter_criteria)))

  2. SQLAlchemy dynamic filter with OR condition: Description: Sometimes, it's necessary to construct queries with OR conditions. This snippet demonstrates how to dynamically build such filters from a dictionary.

    from sqlalchemy import or_ from sqlalchemy.orm import sessionmaker from your_module import YourModel def build_or_filter(session, filter_dict): or_filters = [] for key, value in filter_dict.items(): or_filters.append(getattr(YourModel, key) == value) return or_filters filter_criteria = {"column_name": "desired_value", "another_column": "another_value"} Session = sessionmaker(bind=engine) session = Session() query = session.query(YourModel).filter(or_(*build_or_filter(session, filter_criteria)))

  3. SQLAlchemy dynamic filter with LIKE condition: Description: If you need to perform partial string matches, the LIKE condition is handy. This example illustrates how to dynamically construct LIKE filters.

    from sqlalchemy import or_ from sqlalchemy.orm import sessionmaker from sqlalchemy import func from your_module import YourModel def build_like_filter(session, filter_dict): like_filters = [] for key, value in filter_dict.items(): like_filters.append(func.lower(getattr(YourModel, key)).like(f"%{value.lower()}%")) return like_filters filter_criteria = {"column_name": "partial_value", "another_column": "partial_value"} Session = sessionmaker(bind=engine) session = Session() query = session.query(YourModel).filter(or_(*build_like_filter(session, filter_criteria)))

  4. SQLAlchemy dynamic filter with range condition: Description: Range queries are often needed, such as filtering results between two values. This snippet demonstrates how to build such filters dynamically.

    from sqlalchemy import and_ from sqlalchemy.orm import sessionmaker from your_module import YourModel def build_range_filter(session, filter_dict): range_filters = [] for key, (start, end) in filter_dict.items(): range_filters.append(getattr(YourModel, key).between(start, end)) return range_filters filter_criteria = {"column_name": (start_value, end_value), "another_column": (start_value, end_value)} Session = sessionmaker(bind=engine) session = Session() query = session.query(YourModel).filter(and_(*build_range_filter(session, filter_criteria)))

  5. SQLAlchemy dynamic filter with NULL condition: Description: Filtering records based on NULL values is straightforward with SQLAlchemy. This code snippet demonstrates how to build such filters dynamically.

    from sqlalchemy.orm import sessionmaker from your_module import YourModel def build_null_filter(session, filter_dict): null_filters = [] for key, value in filter_dict.items(): if value: null_filters.append(getattr(YourModel, key) == None) else: null_filters.append(getattr(YourModel, key) != None) return null_filters filter_criteria = {"column_name": True, "another_column": False} Session = sessionmaker(bind=engine) session = Session() query = session.query(YourModel).filter(*build_null_filter(session, filter_criteria))

  6. SQLAlchemy dynamic filter with IN condition: Description: Using the IN condition, you can filter records based on a list of values. This snippet demonstrates how to dynamically construct such filters.

    from sqlalchemy.orm import sessionmaker from your_module import YourModel def build_in_filter(session, filter_dict): in_filters = [] for key, values in filter_dict.items(): in_filters.append(getattr(YourModel, key).in_(values)) return in_filters filter_criteria = {"column_name": [value1, value2], "another_column": [value3, value4]} Session = sessionmaker(bind=engine) session = Session() query = session.query(YourModel).filter(*build_in_filter(session, filter_criteria))

  7. SQLAlchemy dynamic filter with NOT condition: Description: Sometimes, you need to negate conditions. This code snippet demonstrates how to dynamically build filters with NOT conditions.

    from sqlalchemy.orm import sessionmaker from your_module import YourModel def build_not_filter(session, filter_dict): not_filters = [] for key, value in filter_dict.items(): not_filters.append(getattr(YourModel, key) != value) return not_filters filter_criteria = {"column_name": "undesired_value", "another_column": "undesired_value"} Session = sessionmaker(bind=engine) session = Session() query = session.query(YourModel).filter(*build_not_filter(session, filter_criteria))

  8. SQLAlchemy dynamic filter with complex conditions: Description: Sometimes, filters need to be combined in complex ways. This code snippet demonstrates how to dynamically construct such complex filters.

    from sqlalchemy import and_, or_ from sqlalchemy.orm import sessionmaker from your_module import YourModel def build_complex_filter(session, filter_dict): complex_filters = [] for key, value in filter_dict.items(): if isinstance(value, dict): for operator, condition in value.items(): if operator == "or": or_filters = [] for col, val in condition.items(): or_filters.append(getattr(YourModel, col) == val) complex_filters.append(or_(*or_filters)) elif operator == "and": and_filters = [] for col, val in condition.items(): and_filters.append(getattr(YourModel, col) == val) complex_filters.append(and_(*and_filters)) else: complex_filters.append(getattr(YourModel, key) == value) return complex_filters filter_criteria = { "column_name": "desired_value", "another_column": {"or": {"col1": "val1", "col2": "val2"}}, "yet_another_column": {"and": {"col3": "val3", "col4": "val4"}} } Session = sessionmaker(bind=engine) session = Session() query = session.query(YourModel).filter(and_(*build_complex_filter(session, filter_criteria)))

  9. SQLAlchemy dynamic filter with aggregate functions: Description: Occasionally, you may need to apply aggregate functions in your filters. This snippet demonstrates how to do that dynamically.

    from sqlalchemy import func from sqlalchemy.orm import sessionmaker from your_module import YourModel def build_aggregate_filter(session, filter_dict): aggregate_filters = [] for key, func_name in filter_dict.items(): aggregate_filters.append(func[func_name](getattr(YourModel, key))) return aggregate_filters filter_criteria = {"column_name": "MAX", "another_column": "MIN"} Session = sessionmaker(bind=engine) session = Session() query = session.query(*build_aggregate_filter(session, filter_criteria))

  10. SQLAlchemy dynamic filter with custom functions: Description: For more complex filtering needs, custom functions can be utilized. This example shows how to apply custom functions dynamically.

    from sqlalchemy.orm import sessionmaker from sqlalchemy import func from your_module import YourModel, custom_function def build_custom_filter(session, filter_dict): custom_filters = [] for key, value in filter_dict.items(): custom_filters.append(custom_function(getattr(YourModel, key), value)) return custom_filters filter_criteria = {"column_name": custom_value} Session = sessionmaker(bind=engine) session = Session() query = session.query(YourModel).filter(*build_custom_filter(session, filter_criteria))

More Tags

windows-8.1 scroll-position mediarecorder react-native-scrollview jpql voting build-definition hsqldb microsoft-teams python-3.7

More Python Questions

More Stoichiometry Calculators

More Gardening and crops Calculators

More General chemistry Calculators

More Biology Calculators