semvec/pypi-packages huggingface dataset:
LuminaDB-worker 0.0.1
Worker thread extension for LuminaDB
Requires Python: >=3.11
Keywords: sqlite, sqlite3

# LuminaDB Worker

Worker thread extension for **LuminaDB**.

## Install

Use `pip install luminadb_worker`

## Usage?

```python

from uuid import uuid4
from luminadb import model, BaseModel, Primary
from luminadb_worker import DatabaseWorker

db = DatabaseWorker(":memory:")

@model(db)
class Users(BaseModel):
    __schema__ = (Primary('id'),)
    __auto_id__ = lambda: str(uuid4())
    
    id: str
    username: str
    password: str
```
randonneur-data 0.7.2
Data for the randonneur ETL library and spec
Requires Python: >=3.9

# randonneur_data

[![PyPI](https://img.shields.io/pypi/v/randonneur_data.svg)][pypi status]
[![Status](https://img.shields.io/pypi/status/randonneur_data.svg)][pypi status]
[![Python Version](https://img.shields.io/pypi/pyversions/randonneur_data)][pypi status]
[![License](https://img.shields.io/pypi/l/randonneur_data)][license]

[![Read the documentation at https://randonneur_data.readthedocs.io/](https://img.shields.io/readthedocs/randonneur_data/latest.svg?label=Read%20the%20Docs)][read the docs]
[![Tests](https://github.com/brightway-lca/randonneur_data/actions/workflows/python-test.yml/badge.svg)][tests]
[![Codecov](https://codecov.io/gh/brightway-lca/randonneur_data/branch/main/graph/badge.svg)][codecov]

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)][pre-commit]
[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)][black]

[pypi status]: https://pypi.org/project/randonneur_data/
[read the docs]: https://randonneur_data.readthedocs.io/
[tests]: https://github.com/brightway-lca/randonneur_data/actions?workflow=Tests
[codecov]: https://app.codecov.io/gh/brightway-lca/randonneur_data
[pre-commit]: https://github.com/pre-commit/pre-commit
[black]: https://github.com/psf/black

## Installation

You can install _randonneur_data_ via [pip] from [PyPI]:

```console
$ pip install randonneur_data
```

## Contributing

Contributions are very welcome.
To learn more, see the [Contributor Guide][Contributor Guide].

## License

Distributed under the terms of the [MIT license][License],
_randonneur_data_ is free and open source software.

## Issues

If you encounter any problems,
please [file an issue][Issue Tracker] along with a detailed description.


<!-- github-only -->

[command-line reference]: https://randonneur_data.readthedocs.io/en/latest/usage.html
[License]: https://github.com/brightway-lca/randonneur_data/blob/main/LICENSE
[Contributor Guide]: https://github.com/brightway-lca/randonneur_data/blob/main/CONTRIBUTING.md
[Issue Tracker]: https://github.com/brightway-lca/randonneur_data/issues


## Building the Documentation

You can build the documentation locally by installing the documentation Conda environment:

```bash
conda env create -f docs/environment.yml
```

activating the environment

```bash
conda activate sphinx_randonneur_data
```

and [running the build command](https://www.sphinx-doc.org/en/master/man/sphinx-build.html#sphinx-build):

```bash
sphinx-build docs _build/html --builder=html --jobs=auto --write-all; open _build/html/index.html
```
django-tenants-smart-executor 0.1.1
Executors for django-tenants which check whether any migrations need running before running them, making it faster.
Requires Python: >=3.10
Keywords: django, django-tenants, migrations

# Django Tenants Smart Executor

When using [django-tenants](https://github.com/django-tenants/django-tenants), migrations can be quite slow when you have a lot of tenants.
This is the case even if there are actually no migrations to run.
This package provides executors that skip running the migrations for a tenant if there are no migrations to run.
If there's no migratuons to run, the `schema_migrated` signal is still triggered.

## Installation

Install using pip (or your package manager of choice):
```bash
pip install django-tenants-smart-executor
```

And configure the `GET_EXECUTOR_FUNCTION` in your `settings.py`:
```python
GET_EXECUTOR_FUNCTION = "django_tenants_smart_executor.load_executor"
```

## Usage

When you run migrations when all tenants are migrated, the output will look something like this:

```bash
$ python manage.py migrate_schemas
No migrations needed for schema public, only triggering signals
No migrations needed for schema test, only triggering signals
```

The multiprocessing executor is also supported.

```bash
$ python manage.py migrate_schemas --executor multiprocessing
No migrations needed for schema public, only triggering signals
No migrations needed for schema test, only triggering signals
```
kcai-dataset 0.0.3
Splitting strategies package for image datasets
Requires Python: >=3.10
Keywords: dataset, splitting, machine-learning, computer-vision, pytorch

# kcai-dataset

Splitting strategies package for image datasets using the Strategy pattern.

## Installation

### With uv

```bash
# Create virtual environment
uv venv .venv

# Activate virtual environment
source .venv/bin/activate  # On macOS/Linux
# or on Windows: .venv\Scripts\activate

# Install dependencies and package
uv sync
```

### Or with pip

```bash
pip install -e .
```

## Quick Usage

Open the notebook `examples/test.ipynb` and follow the instructions.
fediverse-pasture-inputs 0.3.5
Input data to generate interoperability data from the fediverse-pasture
Requires Python: >=3.13

<!--
SPDX-FileCopyrightText: 2024 Helge

SPDX-License-Identifier: MIT
-->

# fediverse-pasture-inputs

Versioned inputs to generate Fediverse software interoperability data.

These inputs are used to populate the funfedi.dev [Support Tables](https://funfedi.dev/support_tables/).

## Development

```bash
uv build --format wheel
```

will allow you to build a wheel file for the project. By
placing this in the work directory of [interoperability-data](https://codeberg.org/funfedidev/interoperability-data)
and then running pip install with it

```bash
pip install ./fediverse_pasture_inputs-*-py3-none-any.whl
```

one can run the tests against a new input.

### Building the documentation

To build the documentation site, run

```bash
uv run python -mfediverse_pasture_inputs docs
uv run mkdocs serve
```

## Assets

The assets in `assets` should be served under `http://pasture_one_actor/assets`
for some tests to work. These are available as a zip file [here](https://inputs.funfedi.dev/assets/fediverse_pasture_assets.zip).

## Funding

This code was created as part of [Fediverse Test Framework](https://nlnet.nl/project/FediverseTestFramework/).

A project funded through the [NGI0 Core](https://nlnet.nl/core) Fund,
a fund established by [NLnet](https://nlnet.nl/) with financial support from
the European Commission's [Next Generation Internet](https://ngi.eu/) programme,
under the aegis of DG Communications Networks, Content and Technology
under grant agreement No 101092990.