# sqlagen
Model Generator from projects using SQLAlchemy as their orm.
This package is helpful while building web apps with FastAPI and SQLAlchemy.
It provides capability which can:
- generate SQLAlchemy from database schema
- generates Pydantic Model from SQLAlchemy Model.
Project was originally forked from https://github.com/agronholm/sqlacodegen
However, we design to modify some of the features and add new features to the project to fit our own project needs, so we decided to create a new project.
Installation
============
To install,
pip install sqlagen
Quickstart
==========
Please be aware that we are using `pydantic >= 2.0.0` and `sqlalchemy >= 2.0` in this project.
### Generate SQLAlchemy Models
You may use `generate_db_models` function directly to generate Pydantic Model from SQLAlchemy Model. It takes `Generator`'s init arguments and init a Generator class.
Examples:
```python
from sqlagen import generate_db_models
generate_db_models(db_url="pymysql+mysql://localhost:6306/test")
```
```python
from sqlagen import DeclarativeGenerator
from sqlalchemy.engine import create_engine
from sqlalchemy.schema import MetaData
metadata = MetaData()
engine = create_engine("pymysql+mysql://localhost:6306/test")
generator = DeclarativeGenerator(metadata=metadata, engine=engine, options={})
print(generator.generate())
```
### Generate Pydantic Schema Models
You may use `generate_db_models` function directly to generate Pydantic Model from SQLAlchemy Model. It takes `Generator`'s init arguments and init a Generator class.
Examples:
```python
from sqlagen import generate_schema_models
generate_schema_models(models=[MyModel], base_model=CustomBaseModel)
```
```python
from sqlagen import SchemaModelGenerator
generator = SchemaModelGenerator(base_model=CustomBaseModel)
generator.generate_from_module(models=my_models_module, output_path="schemas.py")
```
Generator Class takes following init arguments
- `split_models`: Whether to split models into Base, Create, Update and Read models. Default is `Fakse`.
- `base_model`: Base model to inherit from. Default is `BaseModel` from `pydantic`.
- `restrict_fields`: Which takes a `set` of fields to restrict. Default is `None`. This is useful when you want to restrict some fields to be readonly such as id, created_at, updated_at.
- `indentation`: Indentation to use in generated code.
## More Examples
Since most of our projects use `sqlalchemy` and `pydantic`, so we often need to generate models from database schema and generate pydantic models from sqlalchemy models.
```python
from sqlagen import generate_db_models, SchemaModelGenerator
generate_db_models(db_url="pymysql+mysql://localhost:6306/test",outfile_path="./models")
generate_schema_models(models=[MyModel], base_model=CustomBaseModel, outfile_path="./schemas")
```
## RoadMap
- Strict typing, such as using `conint` for limiting `Integer` size and `constr` for `String` length.
- Probably, generate relationships as well.
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"description": "# sqlagen\n\nModel Generator from projects using SQLAlchemy as their orm.\n\nThis package is helpful while building web apps with FastAPI and SQLAlchemy. \n\nIt provides capability which can:\n- generate SQLAlchemy from database schema\n- generates Pydantic Model from SQLAlchemy Model.\n\nProject was originally forked from https://github.com/agronholm/sqlacodegen\n\nHowever, we design to modify some of the features and add new features to the project to fit our own project needs, so we decided to create a new project.\n\n\nInstallation\n============\n\nTo install,\n\n pip install sqlagen\n\n\nQuickstart\n==========\n\nPlease be aware that we are using `pydantic >= 2.0.0` and `sqlalchemy >= 2.0` in this project.\n\n### Generate SQLAlchemy Models\n\nYou may use `generate_db_models` function directly to generate Pydantic Model from SQLAlchemy Model. It takes `Generator`'s init arguments and init a Generator class. \n\nExamples:\n\n```python\nfrom sqlagen import generate_db_models\n\ngenerate_db_models(db_url=\"pymysql+mysql://localhost:6306/test\")\n```\n\n```python\nfrom sqlagen import DeclarativeGenerator\nfrom sqlalchemy.engine import create_engine\nfrom sqlalchemy.schema import MetaData\n\nmetadata = MetaData()\nengine = create_engine(\"pymysql+mysql://localhost:6306/test\")\ngenerator = DeclarativeGenerator(metadata=metadata, engine=engine, options={})\nprint(generator.generate())\n```\n\n\n### Generate Pydantic Schema Models\n\nYou may use `generate_db_models` function directly to generate Pydantic Model from SQLAlchemy Model. It takes `Generator`'s init arguments and init a Generator class. \n\nExamples:\n\n```python\nfrom sqlagen import generate_schema_models\n \ngenerate_schema_models(models=[MyModel], base_model=CustomBaseModel)\n\n```\n\n```python\nfrom sqlagen import SchemaModelGenerator\n\ngenerator = SchemaModelGenerator(base_model=CustomBaseModel)\ngenerator.generate_from_module(models=my_models_module, output_path=\"schemas.py\")\n```\n\n\nGenerator Class takes following init arguments\n- `split_models`: Whether to split models into Base, Create, Update and Read models. Default is `Fakse`.\n- `base_model`: Base model to inherit from. Default is `BaseModel` from `pydantic`.\n- `restrict_fields`: Which takes a `set` of fields to restrict. Default is `None`. This is useful when you want to restrict some fields to be readonly such as id, created_at, updated_at.\n- `indentation`: Indentation to use in generated code.\n\n## More Examples\n\nSince most of our projects use `sqlalchemy` and `pydantic`, so we often need to generate models from database schema and generate pydantic models from sqlalchemy models.\n```python\nfrom sqlagen import generate_db_models, SchemaModelGenerator\n\ngenerate_db_models(db_url=\"pymysql+mysql://localhost:6306/test\",outfile_path=\"./models\")\ngenerate_schema_models(models=[MyModel], base_model=CustomBaseModel, outfile_path=\"./schemas\")\n```\n\n## RoadMap\n- Strict typing, such as using `conint` for limiting `Integer` size and `constr` for `String` length.\n- Probably, generate relationships as well.\n",
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