A Controller Interface for basic CRUD operations with SQLModel/SQLAlchemy
The library supports advanced features like complex filtering, joins, and custom queries. Refer to the documentation for detailed examples and API reference.
sqlmodel-controller is a Python library that provides a simple and efficient way to perform CRUD (Create, Read, Update, Delete) operations using SQLModel and SQLAlchemy. It offers a high-level abstraction layer that simplifies database interactions in your applications.
- Easy-to-use Controller interface for CRUD operations
- Seamless integration with SQLModel and SQLAlchemy
- Flexible query building and filtering
- Support for pagination and sorting
- Asynchronous operations support
- Support for multiple database types (MySQL, SQLite, PostgreSQL)
To set up the database engine, you need to configure the following environment variables:
DB_TYPE
- sqlite, mysql, postgresql, mssqlDB_HOST
- hostname or ip addressDB_USER
- usernameDB_PASSWORD
- passwordDB_NAME
- database nameDB_PORT
- port number
you can either explicitly set your custom engine based on the following sample code:
from sqlmodel import create_engine
def get_engine():
config = get_db_config()
if config["type"] == "mysql":
db_uri = f"mysql+mysqlconnector://{config['user']}:{config['password']}@{config['host']}:{config['port']}/{config['name']}"
elif config["type"] == "sqlite":
db_uri = f"sqlite:///{config['name']}.db"
elif config["type"] == "postgres":
db_uri = f"postgresql+pg8000://{config['user']}:{config['password']}@{config['host']}:{config['port']}/{config['name']}"
else:
raise ValueError(f"Unsupported database type: {config['type']}")
return create_engine(db_uri)
Define your SQLModel models by inheriting from BaseID
:
from sqlmodel import Field
from sqlmodel_controller import BaseID
class PersonModel(BaseID, table=True):
tax_id: str = Field(unique=True)
name: str
birth_date: date
nickname: str
from sqlmodel_controller import Controller
# if engine is not provided, it will use the default engine which is generated based on environment variables:
controller_with_specific_engice = Controller[PersonModel](engine=engine)
controller = Controller[PersonModel]() # generate engine based on environment variables
person_data = {
"tax_id": "123456789",
"name": "Thiago Martin",
"birth_date": date(1990, 1, 1),
"nickname": "0xthiagomartins",
}
person_id: int = controller.create(data=person_data)
selector = {"by": "id", "value": person_id}
person: dict = controller.get(**selector)
selector = {"by": "tax_id", "value": "123456789"}
person: dict = controller.get(**selector)
selector = {"by": ["name", "archived"], "value": ["Thiago Martin", False]}
person: dict = controller.get(**selector)
updated_data = {"name": "Thiago Martins"}
selector = {"by": "id", "value": person_id}
controller.update(**selector, data=updated_data)
selector = {"by": "id", "value": person_id}
controller.delete(**selector)
# It upsert based on constraints and primary keys (it auto detects if it's a new or existing record)
# Work for 1 PK or multiple PKs or constraints
upsert_data = {
"tax_id": "123456789",
"name": "Thiago Martins",
"birth_date": date(1990, 1, 1),
"nickname": "0xthiagomartins",
}
selector = {"by": "tax_id", "value": "123456789"}
person_id: int = controller.upsert(**selector, data=upsert_data)
selector = {"by": "id", "value": person_id}
controller.archive(**selector)
you can list all records from a table by calling the list
method and setting the parameter mode
to "all"
or you can list the records in a paginated way by setting the parameter mode
to "paginated"
and providing the page
and per_page
parameters.
paginated_result: dict = controller.list(mode="paginated", page=1, per_page=10)
items: list[dict] = paginated_result["data_set"]
current_page: int = paginated_result["current"]
per_page: int = paginated_result["per_page"]
total_pages: int = paginated_result["total_pages"]
total_data: int = paginated_result["total_data"]
previous_page: int = paginated_result["previous"]
next_page: int = paginated_result["next"]
filtered_persons = controller.list(filter={
"name": "John"
}
mode="all"
)
filtered_persons = controller.list(filter={
"birth_date": {
"gte": date(1990, 1, 1),
"lt": date(2000, 1, 1)
},
"archived": False
}
mode="all"
)
sorted_persons = controller.list(order={
"name": "asc",
"birth_date": "desc"
}
mode="all"
)
The joins only are applied for those fields whose relationship is defined in the model. If the field is not a relationship field, the join will not be applied. The join will be a list of objects if the relationship type is ManyToOne or ManyToMany (list). If the relationship type is OneToOne, the join will be a single object (dictionary).
person_with_address = controller.get(
by="id",
value=person_id,
joins=["address"]
)
The library raises exceptions for various error conditions. It's recommended to use try-except blocks to handle potential errors:
from sqlalchemy.exc import NoResultFound
try:
person = controller.get(by="id", value=999999)
except NoResultFound:
print("Person not found")
except Exception as e:
print(f"An error occurred: {str(e)}")
For more detailed information on specific methods and their parameters, please refer to the API documentation.
This guide will help you set up the project for development and testing.
- Python 3.8 or higher
- pip (Python package installer)
- Git
$ pip install sqlmodel-controller
---> 100%
Successfully installed sqlmodel-controller
- Create a
.env
file in the project root directory with the following content:
DB_TYPE=mysql
DB_NAME=test
DB_USER=root
DB_PASSWORD=root
DB_HOST=localhost
DB_PORT=3306
This will use SQLite for development. You can change these settings to use MySQL or PostgreSQL if needed.
-
Create a new branch for your feature or bug fix:
git checkout -b feature/your-feature-name
-
Make your changes and write tests for new functionality.
-
Run the tests to ensure everything is working:
pytest
-
Commit your changes:
git commit -am "Add your commit message here"
-
Push your changes to your fork:
git push origin feature/your-feature-name
-
Create a pull request on GitHub.
This project follows PEP 8 style guide. You can use tools like flake8
or black
to ensure your code adheres to the style guide:
When adding new features or making changes, please update the relevant documentation in the docs/
directory and add docstrings to your functions and classes.
If you encounter any issues during setup or testing, please check the following:
-
Ensure your Python version is 3.8 or higher:
python --version
-
Make sure all dependencies are installed correctly:
pip list
-
Verify that your
.env
file is set up correctly and in the right location.
If you still face issues, please open an issue on the GitHub repository with details about your environment and the problem you're experiencing.
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License.
We adhere to the Code of Conduct. By participating, you are expected to uphold this code. Please report any unacceptable behavior to [email protected].