semvec/pypi-packages huggingface dataset:
dbml-builder 0.4.1
Builds usable models from DBML
License: MIT
Requires Python: >=3.10,<4.0
Keywords: dbml,sql

# dbml-builder

Generates Pydantic and SQLAlchemy from a DBML file.

This package is for users wanting to use their data model represented
in [DBML](https://www.dbml.org/home/) in production. `dbml-builder` accomplishes this
by:
1. Generating Pydantic and SQLAlchemy code.
2. Verifying existing generated code to see if it matches the specified version and
   has not been changed since creation.

Currently, there doesn't seem to be a good solution for code generation with DBML in Python
hence the creation of `dbml-builder`. Additionally, large software systems tend to break as
Pydantic schemas are modified which is the reason why the package includes verification
functionality.

`dbml-builder` is new and actively developed. If you have any feature requests or issues,
please submit them [here](https://github.com/jataware/dbml-builder/issues). 


## Installation

Install using pip:

```
pip install dbml_builder
```

## Usage

Generate your ORM and schemas by running:

```
model-build generate ./project.dbml ./generated
```
or call `generate_models` directly in Python code.


You can check to if the model code is still valid by running:
```
model-build check v0.9.3 ./generated
```
or call `verify` directly in Python code.

Note that the version is what is specified in the `note` for
a given project in DBML.

### Example

Suppose we have a project:

```
>> ls
src/  LICENSE  poetry.lock  data-model.dbml  pyproject.toml
```
where `src` contains your code for your python project.

We can automatically generate code using:

```
pip install dbml_builder
model-build generate ./data-model.dbml ./src/generated
```

We can now submit `src/generated` to version control and
use the generated code in a module:
```
from generated.schema import SOME_PYDANTIC_SCHEMA
from generated.orm import SOME_SQLALCHEMY_TABLE
```

We can also ensure the generated code is not changed by 
placing a check in our code:
```
# src/main.py
from dbml_builder import verify

verify('v0.1.0', '../data-model.dbml')
```
greeting-package 0.1.3
A simple greeting package
License: MIT
Requires Python: >=3.7


# greeting_package

[![PyPI version](https://badge.fury.io/py/greeting-package.svg)](https://badge.fury.io/py/greeting-package)

`greeting-package` is a Python package for greeting people.

## Installation

You can install `greeting-package` via `pip`:

```bash
pip install greeting-package
```
## Usage
```
from greeting_package.greeting import say_hello

say_hello('John')  # 'Hello, John!'
say_hello('Jane')  # 'Hello, Jane!'
```
## Contributing

Bug reports and pull requests are welcome on GitHub at 
[Here](https://github.com/osundwajeff/greeting_package).

## Documentation

The greeting-package documentation includes:
- Installation instructions
- Usage examples
- API reference
- Development instructions

### API Reference
```
greeting_package.greeting.say_hello(name: str) -> str
```
Greet someone by name.
```
Parameters:

    name (str): # The name of the person to greet.

Returns:

    A greeting message (str).
```
## Contributing
Bug Reports and Feature Requests

Please use the issue tracker to report any bugs or feature requests.
Development

Clone the repository:
```
git clone https://github.com/osundwajeff/greeting_package.git
cd greeting-package
```
  Create a virtual environment:
```
python3 -m venv env
source env/bin/activate
```

Install development dependencies:
```
pip install -r requirements-dev.txt
```

Make changes and add tests.
Run the tests:
```
pytest tests/
```

Build the package:
```
python3 -m build
```

Install the package:
```
pip install .
```

Push your changes and create a pull request.

## License

greeting-package is released under the MIT License. See LICENSE for details.
ml-random-utils 0.0.2
Random utilities I use in ML projects.
License: MIT
Requires Python: >=3.10,<4.0

# ml_random_utils

Random utilities I use in ML projects.

[![ci-cd](https://github.com/marcopodda/ml_random_utils/actions/workflows/ci-cd.yml/badge.svg)](https://github.com/marcopodda/ml_random_utils/actions/workflows/ci-cd.yml)

## Installation

```bash
$ pip install ml_random_utils
```

## Usage

- TODO

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`ml_random_utils` was created by Marco Podda. It is licensed under the terms of the MIT license.

## Credits

`ml_random_utils` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).