SQLAlchemy equivalent to SQL "LIKE" statement

SQLAlchemy equivalent to SQL "LIKE" statement

In SQLAlchemy, you can use the like() method to perform SQL "LIKE" operations. The like() method is part of SQLAlchemy's querying system and is used to filter rows based on patterns in a column. Here's how to use it:

from sqlalchemy import create_engine, Column, Integer, String from sqlalchemy.orm import sessionmaker from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import text # Define the SQLAlchemy model Base = declarative_base() class MyModel(Base): __tablename__ = 'my_table' id = Column(Integer, primary_key=True) name = Column(String) # Create a SQLAlchemy engine and session engine = create_engine('sqlite:///my_database.db') Session = sessionmaker(bind=engine) session = Session() # Define the pattern you want to search for search_pattern = '%example%' # This represents "LIKE '%example%'" # Create a query with the "LIKE" condition filtered_query = session.query(MyModel).filter(MyModel.name.like(search_pattern)) # Execute the query and retrieve results results = filtered_query.all() # Print the results for result in results: print(result.id, result.name)

In this example:

  1. We define a SQLAlchemy model MyModel representing a table with a name column.

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

  3. We define the search_pattern, which is the pattern you want to search for using "LIKE". % represents any number of characters, so '%example%' matches any string containing "example".

  4. We create a query using session.query(MyModel).filter(), and we use .like() to specify the "LIKE" condition with the search_pattern.

  5. We execute the query using .all() to retrieve the filtered rows.

  6. Finally, we iterate through the results and print them.

You can modify the search_pattern to perform different types of "LIKE" operations, such as prefix matching, suffix matching, or exact matching, by adjusting the placement of % characters within the pattern.

Examples

  1. "SQLAlchemy 'LIKE' statement for string matching"

    • Description: To perform string matching in SQLAlchemy, you can use the .like() method on a column, similar to SQL's LIKE statement.
    • Code:
      from sqlalchemy import create_engine from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker from sqlalchemy import Column, Integer, String Base = declarative_base() class User(Base): __tablename__ = 'users' id = Column(Integer, primary key=True) name = Column(String) engine = create_engine('sqlite:///example.db') Base.metadata.create_all(engine) Session = sessionmaker(bind=engine) session = Session() # Find users with names starting with 'J' result = session.query(User).filter(User.name.like('J%')).all() for user in result: print(user.name)

  2. "SQLAlchemy 'LIKE' with wildcard characters"

    • Description: In SQLAlchemy, you can use wildcard characters like % and _ to represent patterns, similar to SQL's LIKE statement.
    • Code:
      from sqlalchemy import create_engine from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker from sqlalchemy import Column, Integer, String Base = declarative_base() class Product(Base): __tablename__ = 'products' id = Column(Integer, primary_key=True) name = Column(String) engine = create_engine('sqlite:///example.db') Base.metadata.create_all(engine) Session = sessionmaker(bind=engine) session = Session() # Find products with names containing 'box' result = session.query(Product).filter(Product.name.like('%box%')).all() for product in result: print(product.name)

  3. "SQLAlchemy 'LIKE' with case-insensitive matching"

    • Description: For case-insensitive string matching in SQLAlchemy, you can use ilike() instead of like().
    • Code:
      from sqlalchemy import create_engine from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker from sqlalchemy import Column, Integer, String Base = declarative_base() class User(Base): __tablename__ = 'users' id = Column(Integer, primary_key=True) name = Column(String) engine = create_engine('sqlite:///example.db') Base.metadata.create_all(engine) Session = sessionmaker(bind=engine) session = Session() # Case-insensitive search for names containing 'john' result = session.query(User).filter(User.name.ilike('%john%')).all() for user in result: print(user.name)

  4. "SQLAlchemy 'LIKE' with custom escape characters"

    • Description: When your pattern includes wildcard characters, you might need custom escape characters to avoid unintended matches. This example shows how to do this.
    • Code:
      from sqlalchemy import create_engine from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker from sqlalchemy import Column, Integer, String Base = declarative_base() class Document(Base): __tablename__ = 'documents' id = Column(Integer, primary_key=True) content = Column(String) engine = create_engine('sqlite:///example.db') Base.metadata.create_all(engine) Session = sessionmaker(bind=engine) session = Session() # Custom escape character in LIKE pattern = r'%20\%%' # '20%' with custom escape '\' result = session.query(Document).filter(Document.content.like(pattern, escape='\\')).all() for doc in result: print(doc.content)

  5. "SQLAlchemy 'LIKE' for SQL patterns in PostgreSQL"

    • Description: PostgreSQL has specific LIKE operators, including ILIKE for case-insensitive matching. This example demonstrates how to use them in SQLAlchemy.
    • Code:
      from sqlalchemy import create_engine, text from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker from sqlalchemy import Column, Integer, String Base = declarative_base() class Customer(Base): __tablename__ = 'customers' id = Column(Integer, primary_key=True) email = Column(String) engine = create_engine('postgresql://user:password@localhost:5432/mydatabase') Base.metadata.create_all(engine) Session = sessionmaker(bind=engine) session = Session() # Using text-based LIKE for more complex patterns query = text("SELECT * FROM customers WHERE email ILIKE '%gmail.com%'") result = session.execute(query).fetchall() for row in result: print(row)

  6. "SQLAlchemy 'LIKE' with case-insensitive and custom collations"

    • Description: Some databases support custom collations for case-insensitive comparisons. This example shows how to set custom collations for SQLAlchemy.
    • Code:
      from sqlalchemy import create_engine, Column, Integer, String from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker from sqlalchemy.dialects.mysql import COLLATE Base = declarative_base() class Product(Base): __tablename__ = 'products' id = Column(Integer, primary_key=True) name = Column(String, COLLATE='utf8_general_ci') # Case-insensitive collation engine = create_engine('mysql://user:password@localhost:3306/mydatabase') Base.metadata.create_all(engine) Session = sessionmaker(bind=engine) session = Session() # Case-insensitive LIKE with custom collation result = session.query(Product).filter(Product.name.like('%product%')).all() for product in result: print(product.name)

  7. "SQLAlchemy 'LIKE' with bound parameters"

    • Description: To ensure safe SQL queries and avoid SQL injection, always use bound parameters when constructing LIKE patterns in SQLAlchemy.
    • Code:
      from sqlalchemy import create_engine, Column, Integer, String from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker Base = declarative_base() class User(Base): __tablename__ = 'users' id = Column(Integer, primary_key=True) name = Column(String) engine = create_engine('sqlite:///example.db') Base.metadata.create_all(engine) Session = sessionmaker(bind=engine) session = Session() # Using bound parameters to avoid SQL injection pattern = '%John%' result = session.query(User).filter(User.name.like(pattern)).all() for user in result: print(user.name)

  8. "SQLAlchemy 'LIKE' with case-insensitive pattern matching"

    • Description: To perform case-insensitive pattern matching, use the ilike() method. This approach is helpful when case sensitivity is not required.
    • Code:
      from sqlalchemy import create_engine, Column, Integer, String from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker Base = declarative_base() class Product(Base): __tablename__ = 'products' id = Column(Integer, primary_key=True) name = Column(String) engine = create_engine('sqlite:///example.db') Base.metadata create_all(engine) Session = sessionmaker(bind=engine) session = Session() # Case-insensitive pattern matching with ILIKE result = session.query(Product).filter(Product.name.ilike('%box%')).all() for product in result: print(product.name)

  9. "SQLAlchemy 'LIKE' with complex conditions"

    • Description: You can use complex conditions with LIKE to build more flexible queries in SQLAlchemy. This example combines LIKE with other SQL conditions.
    • Code:
      from sqlalchemy import create_engine, Column, Integer, String from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker Base = declarative_base() class User(Base): __tablename__ = 'users' id = Column(Integer, primary key=True) name = Column(String) age = Column(Integer) engine = create_engine('sqlite:///example.db') Base.metadata create_all(engine) Session = sessionmaker(bind=engine) session = Session() # Complex condition with LIKE and other filters result = session.query(User).filter((User.name.like('J%')) & (User.age > 20)).all() for user in result: print(user.name)

  10. "SQLAlchemy 'LIKE' with raw SQL queries"

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