semvec/pypi-packages huggingface dataset:
gtauthclient 0.0.7
GT Auth Client Functions
Requires Python: >=3.10

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# GT Auth Client

This is the Python GT Auth Client for FastAPI. It is used to authenticate with the GT Auth API.
## Installation

You can install the package using pip:

```bash
pip install gtauthclient
```

## Usage

An example of how to use the package is shown below:

```python
from fastapi import FastAPI, Depends
from gtauthclient import GTAuthClient

auth = GTAuthClient(key="Your encryption key")
app = FastAPI()

@app.get("/v1/users", dependencies=[Depends(auth.verify_user)])
async def list_users():
    return ["John", "Jane", "Jack"]
```
torf-gui 0.4.1
An advanced GUI torrent file creator with batch functionality, powered by PyQt and torf.
Keywords: bittorrent torrent

# torf-gui

[![GitHub Build Status](https://img.shields.io/github/actions/workflow/status/SavageCore/torf-gui/build.yml?style=flat-square&logo=pytest)](https://github.com/SavageCore/torf-gui/actions/workflows/build.yml)
[![Code Style: black](https://img.shields.io/badge/code%20style-black-black)](https://pypi.org/project/black/)

[![PyPI - Downloads](https://img.shields.io/pypi/dm/torf-gui?style=flat-square&logo=pypi)](https://pypi.org/project/torf-gui/)
[![PyPI - Version](https://img.shields.io/pypi/v/torf-gui?style=flat-square)](https://pypi.org/project/torf-gui/)

A quick and dirty port of
[dottorrent-gui](https://github.com/kz26/dottorrent-gui) for
[torf](https://github.com/rndusr/torf)

![image](img/screenshot_light.png)

![image](img/screenshot_dark.png)

## Features

- Fast (capable of several hundred MB/s)
- Cross-platform
- Full Unicode support
- Use multiple CPU cores to compute piece hashes
- Automatic and manual piece size selection, up to 16MB
- Batch torrent creation mode
- Filename exclusion patterns (globs)
- HTTP/web seeds support [(BEP
    19)](http://www.bittorrent.org/beps/bep_0019.html)
- Private flag support [(BEP
    27)](http://www.bittorrent.org/beps/bep_0027.html)
- Randomize info hash to help with cross-seeding
- User-definable source string
- Optional MD5 file hash inclusion
- [Import/export of
    profiles](https://github.com/SavageCore/torf-gui/wiki/Profiles)
    (trackers, web seeds, source string, filename exclusion patterns)
- Automatic dark mode!

## Installation

### Windows and macOS

You can find the latest releases [here](https://github.com/SavageCore/torf-gui/releases).

On Windows, simply download and run `torf-gui-win64.exe`. You may need
to download and install the [Microsoft Visual C++ Redistributable for
Visual Studio
2015](https://www.microsoft.com/en-us/download/details.aspx?id=48145).

On macOS, download and extract `torf-gui-macOS.zip` then run the app.
You may need to allow the app to run in your security settings.

### Linux

#### Requirements

- Python 3.3+
- PyQt5 5.7+
- libxcb-xinerama0 (Debian/Ubuntu)

Latest stable release: `pip install torf-gui`

Development: `git clone` this repository, then `pip install .`

To run: `torf-gui`

## Portable Mode

torf-gui can be configured to run in portable mode, good for running
from USB drives and network shares. To enable this, simply create an
empty file named `torf-gui.ini` in the same directory as the main
excecutable.

## License

© 2023 Oliver Sayers. Made available under the terms of the [GNU General
Public License v3](http://choosealicense.com/licenses/gpl-3.0/).

[![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/E1E6P7VIQ)
blaze-net 1.1.1
A Python web framework

# BlazeNet

BlazeNet is a Python web framework inspired by Flask. It provides a simple and lightweight solution for building web applications.

## Features

- Routing: Define routes and associate them with view functions.
- Templating: Render HTML templates using Jinja2.
- Database Integration: Integrate SQLAlchemy for database operations.
- Easy to Use: Simple and intuitive API for developing web applications.

## Installation

You can install BlazeNet using pip:

```bash
pip install blaze-net
```

Or clone this repository to your local machine:

```bash
git clone https://github.com/Alan69/blaze_net.git
```

## Usage

```python
from blaze_net import BlazeNet
from model import User

app = BlazeNet()

@app.route('/')
def index(request):
    return 'Hello, BlazeNet!'

@app.route('/json-reponce/')
def json_reponce(request):
    # Create a session
    session = app.Session()

    # Query all users from the database
    users = session.query(User).all()
    user_dicts = []
    for user in users:
        user_dict = {
            'id': user.id,
            'username': user.username,
            'email': user.email
        }
        user_dicts.append(user_dict)
    # Close the session
    session.close()
    return app.json_response(user_dicts)

if __name__ == "__main__":
    app.run()
```

## Model

```python
from typing import List
from typing import Optional
from sqlalchemy import ForeignKey
from sqlalchemy import String
from sqlalchemy.orm import DeclarativeBase
from sqlalchemy.orm import Mapped
from sqlalchemy.orm import mapped_column
from sqlalchemy.orm import relationship
from blaze_net import BlazeNet

app = BlazeNet()

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    username: Mapped[str] = mapped_column(String(30))
    email: Mapped[Optional[str]]
    addresses: Mapped[List["Address"]] = relationship(
        back_populates="user", cascade="all, delete-orphan"
    )
    def __repr__(self) -> str:
        return f"User(id={self.id!r}, name={self.name!r}, fullname={self.fullname!r})"

class Address(Base):
    __tablename__ = "address"
    id: Mapped[int] = mapped_column(primary_key=True)
    email_address: Mapped[str]
    user_id: Mapped[int] = mapped_column(ForeignKey("user_account.id"))
    user: Mapped["User"] = relationship(back_populates="addresses")
    def __repr__(self) -> str:
        return f"Address(id={self.id!r}, email_address={self.email_address!r})"

Base.metadata.create_all(app.engine)
```

## Documentation
For more information on how to use BlazeNet, please refer to the documentation.

## Contributing
Contributions are welcome! If you find a bug or have a feature request, please open an issue or submit a pull request.

## License
This project is licensed under the MIT License - see the LICENSE file for details.
simple-spykes 0.1.0
Utility library for spike sorting quality metrics
Keywords: neuroscience, spike sorting, tools, science

#############
Simple-Spykes
#############

- Please see the documentation at TODO

- GitHub available with more information `here <https://github.com/Anschutz-Visual-Cluster/simple-spykes>`_


Made for CU Anschutz Vision Cluster