An in-depth guide to Python ORM: Master the basics of object-relational mapping

Object Relational Mapping (ORM) is the middle layer that connects objects and relational databases. Using an ORM, you can use objects to manipulate the database, simplifying data processing and improving code readability.

Basics of ORM

The core of ORM is to associate objects with tables, properties with columns, and methods with sql queries. When you save an object, the ORM converts it into a SQL query and sends it to the database. When you query an object, the ORM maps the database results back to the object.

Popular Python ORM

• SQLAlchemy: A flexible and powerful ORM that supports a variety of databases.
• Django: A WEB framework that includes an integrated ORM.
• Peewee: A lightweight ORM, suitable for small projects.
• Pony: A object-oriented ORM with automatic fault detection.

Steps to use ORM

1. Connect to the database: Use the connection function provided by the ORM to connect to the database.
2. Define the model: Create a model class to represent the table. Define properties to represent columns and specify data types.
3. Create table: Use the ORM's create table function to create a table in the database.
4. Create objects: Create instances of model classes to represent database rows.
5. Save the object: Call the ORM save function to save the object to the database.
6. Query objects: Use ORM's query function to query the database and retrieve objects.
7. Update object: Modify the object properties and call the ORM's update function to update the database.
8. Delete objects: Call the ORM delete function to delete objects from the database.

Advantages of ORM

• Object-based data access: Use objects to interact with the database to improve readability and maintainability.
• Reduce SQL queries: ORM automatically generates SQL queries, saving development time.
• Relational Modeling: ORM handles relational tables, allowing you to use objects to represent complex database structures.
• Data validation: ORM can automatically validate data to ensure it complies with defined rules.
• Unit Testing: ORM simplifies database unit testing because you can use objects instead of SQL queries.

Limitations of ORM

• Performance overhead: ORM may be slower than using SQL queries directly in some cases.
• Flexibility: ORMs may not be flexible enough to handle certain complex queries or database schemas.
• Learning Curve: Learning ORM requires time and effort.
• Database Dependencies: ORM is dependent on a specific database and therefore may be difficult to use across different databases.
• Potential errors: ORM may introduce errors, such as object state being out of sync with database state.

Choose the right ORM

Choosing the right ORM depends on your project needs and preferences. Consider the following factors:

• Database support
• performance
• flexibility
• Ease of use
• Community Support

in conclusion

Mastering python ORM can significantly improve data processing efficiency and simplify database interaction. By understanding the basics of ORMs, popular Python ORMs, usage steps, advantages and limitations, you can choose the right ORM for your project and take your database operations to the next level.

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