semvec/pypi-packages huggingface dataset:
Flask-SQLalchemy-Whoosh 0.1.5
A flask extension that adds full text search capabilites to your SQLAlchemy models using the Whoosh search engine

# Flask-SQLAlchemy-Whoosh
A simple and easy to use Flask extension to add full text search to your SQLAlchemy models using the Whoosh search engine.

### Installing
`$ pip install Flask-SQLAlchemy-Whoosh`

### Setup
```python
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from Flask_SQLalchemy_Whoosh.searcher import WhooshSearcher
from Flask_SQLalchemy_Whoosh.mixin import SearchableMixin

app = Flask(__name__)
db = SQLAlchemy(app)
search = WhooshSearcher(app)
# If you want to use the SearchableMixin
SearchableMixin.init_search(search, db)
```

### Documentation
You can find some documentation [here](https://github.com/Momo8289/Flask-SQLAlchemy-Whoosh/wiki/Docs)

### Example
```python
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from Flask_SQLalchemy_Whoosh.searcher import WhooshSearcher
from Flask_SQLalchemy_Whoosh.mixin import SearchableMixin
from whoosh.fields import ID, TEXT, NUMERIC


app = Flask(__name__)
db = SQLAlchemy(app)
search = WhooshSearcher(app)
SearchableMixin.init_search(search, db)


class Product(SearchableMixin, db.Model):
    __tablename__ = "product"
    # __searchable__ is needed to tell the searcher what to index
    # For documentation on the specifics of each field, refer to the Whoosh documentation
    # https://whoosh.readthedocs.io/en/latest/schema.html
    __searchable__ = {
        "id": ID(stored=True, unique=True),
        "name": TEXT(stored=True),
        "desc": TEXT,
        "price": NUMERIC
    }

    id = db.Column(db.Integer, primary_key=True)
    name = db.Column(db.String),
    desc = db.Column(db.String),
    price = db.Column(db.Integer)


# If you want to index a table that  already has entries, use the reindex method
# It will index all entries in the table
Product.reindex()

# Use the search method to search a table
results, total = Product.search("name", "nails")
```
dispersenn2 0.0.7
Neural net for estimating dispersal distance
Requires Python: >=3.9,<3.12

# disperseNN2

[![Documentation Status](https://readthedocs.org/projects/dispersenn2/badge/?version=latest)](https://dispersenn2.readthedocs.io/en/latest/?badge=latest)

`disperseNN2` is a machine learning framework for predicting &#963;, the expected per generation displacement distance between offspring and their parent(s), from genetic variation data.
`disperseNN2` replaces our previous method, `disperseNN`, by introducing
a novel architecture. For details see our [preprint](https://www.biorxiv.org/content/10.1101/2023.07.30.551115v1).

For installation and usage instructions, see the [docs page](https://dispersenn2.readthedocs.io/en/latest/).
toml-package 0.0.2
Packing using pyproject.tom and setuptools
Requires Python: >=3.8

# Package using pyproject.toml


1. The publisher is using the latest version of setuptools
2. The latest version of twine is used to upload the package
3. The user installing the package has at least Pip 9.0, or a client that supports the Metadata 1.2 specification.

## Creating the package files

    packaging_tutorial/
    ├── LICENSE
    ├── pyproject.toml
    ├── README.md
    ├── src/
    │   └── your_package/
    │       ├── __init__.py
    │       └── example.py
    └── tests/

## Dealing with the universal wheels

Traditionally, projects providing Python code that is semantically compatible with both Python 2 and Python 3, produce wheels that have a py2.py3 tag in their names.

It is often configured within setup.cfg under the [bdist_wheel] section by setting universal = 1 if they use setuptools.

## Choosing a build backend

Tools like pip and build do not actually convert your sources into a distribution package (like a wheel); that job is performed by a build backend. 

The build backend determines how your project will specify its configuration, including metadata (information about the project, for example, the name and tags that are displayed on PyPI) and input files.

Build backends have different levels of functionality, such as whether they support building extension modules, and you should choose one that suits your needs and preferences.

1. Hatchling
2. setuptools
3. Flit
4. PDM

others that support the [project] table for metadata.
The pyproject.toml tells build frontend tools like pip and build which backend to use for your project.

## Defining the Python version required

    python3 -m pip install --upgrade setuptools twine

## Generating distribution archives

    python3 -m pip install --upgrade build

    python3 -m build

## Uploading the distribution archives

    python3 -m pip install --upgrade twine
    python3 -m twine upload --repository pypi dist/*

## Installing your newly uploaded package
    
    python3 -m pip install toml_package
py-miraie-ac 0.1.10
A package to control and read MirAIe Aircons by Panasonic
Requires Python: >=3.6

# Python MirAIe AC API

An API to send commands and read the status of MirAIe air conditioners by Panasonic

**Installation**
```
pip install py-miraie-ac
```

**Usage**
```
import asyncio
from api import MirAIeAPI
from enums import AuthType
from device import Device

async with MirAIeAPI(
        auth_type=AuthType.MOBILE, 
        login_id="YOUR_MOBILE_NUMBER", 
        password="YOUR_PASSWORD"
    ) as api:
    await api.initialize()
    for device in api.devices:
        print("Found device: ", device.friendly_name)
        device.set_temperature(24)
        device.turn_on()

asyncio.get_event_loop().run_until_complete(start())
GooseSLURM 0.13.4
Support functions for SLURM
Requires Python: >=3.6

# GooseSLURM

[![CI](https://github.com/tdegeus/GooseSLURM/workflows/CI/badge.svg)](https://github.com/tdegeus/GooseSLURM/actions)
[![Documentation Status](https://readthedocs.org/projects/gooseslurm/badge/?version=latest)](http://gooseslurm.geus.me/en/latest/?badge=latest)

**Project's website: [gooseslurm.rtfd.io](https://gooseslurm.rtfd.io)**
toml-package-mahfooz.iiitian 0.0.1
Packing using pyproject.tom and hatchling
Requires Python: >=3.8

# Package using pyproject.toml

## Creating the package files

    packaging_tutorial/
    ├── LICENSE
    ├── pyproject.toml
    ├── README.md
    ├── src/
    │   └── your_package_YOUR_USERNAME_HERE/
    │       ├── __init__.py
    │       └── example.py
    └── tests/

## Choosing a build backend

Tools like pip and build do not actually convert your sources into a distribution package (like a wheel); that job is performed by a build backend. 

The build backend determines how your project will specify its configuration, including metadata (information about the project, for example, the name and tags that are displayed on PyPI) and input files.

Build backends have different levels of functionality, such as whether they support building extension modules, and you should choose one that suits your needs and preferences.

1. Hatchling
2. setuptools
3. Flit
4. PDM

others that support the [project] table for metadata.
The pyproject.toml tells build frontend tools like pip and build which backend to use for your project.

## Generating distribution archives

    python3 -m pip install --upgrade build

    python3 -m build

## Uploading the distribution archives

    python3 -m pip install --upgrade twine