semvec/pypi-packages huggingface dataset:
mdb-models 3.0.1
A data mapper for mongodb (Formerly mongodb_data_layer)

# MongoDB Data Layer

A data modeling **MongoDB** library for **Python**

<hr />

### Installation
1. Install the python package via pip:

```bash
pip install mdb-models
```
**Note**: It is better to create a python virtual environment...

2. Setup an environment variables:
   
   - To create an environment variables, simply create a file named **".env"**.
    - Then, add these following variables to a created file:

    ```bash
    MONGO_DB_URL="mongodb://localhost:27020" # The default mongodb localhost but you can also put a connection string from atlas server.
    MONGO_DB_NAME="my_database" # Your created database
    ```

3. To create a model you can simply enter this command on a command promt:

```bash
generate-model /models/test.py  # where '/models/test_model.py' is your file path and file name

# ============== or ===============

generate-authmodel /models/user.py # creates an authenticatable model
```

4. It will generate a file like this:

```python
#A MongoDB model for the tests collection
from mdb_models.base import BaseMongoModel

class Test(BaseMongoModel):
    
    collection_name = 'tests' # Create a collection with this name in the database
```

<hr />

### Notes

<p>This library is very useful to lessen the configuration for mongodb database. </p>

<p>This package is build on top of MongoDB official package/drivers.</p>

<p>This is also works well in fastapi.</p>

<p>This library is currently in development. Feel free to contribute.</p>

<hr />

Official repository: <a href="https://github.com/nojram00/mongodb-data-layer">https://github.com/nojram00/mongodb-data-layer</a>
TgBee 1.1.12
An asynchronous Python Telegram Bot API wrapper
Requires Python: >=3.7

# TgBee

TgBee is an asynchronous Python wrapper for the Telegram Bot API. It provides a simple and intuitive interface for creating Telegram bots using modern Python features.

Don't forget to ⭐ the repository on
[![GitHub Stars](https://img.shields.io/github/stars/x7007x/repository?style=social)](https://github.com/x7007x/TgBee/stargazers)

![PyPI](https://img.shields.io/pypi/v/TgBee?style=flat-square)
[![Telegram](https://img.shields.io/badge/Telegram-Join-blue?style=flat-square)](https://t.me/i88y8)

## Features

- Asynchronous API calls using `aiohttp`
- Easy-to-use decorator-based handler system
- Support for inline keyboards and callback queries
- Plugin system for modular bot development
- FastAPI integration for webhook support

## Installation

You can install TgBee using pip: 
```bash
pip3 install -U TgBee
```

## Example

```python
import asyncio
from TgBee import Client, filters

bot = Client(token="YOUR_BOT_TOKEN")

@bot.on_message(filters.command("start"))
async def start_command(client, message):
    reply_markup = {
        "inline_keyboard": [
            [
                {"text": "Button 1", "callback_data": "button1"},
                {"text": "Button 2", "callback_data": "button2"}
            ]
        ]
    }

    mention = message.from_user.mention
    sent_message = await client.send_message(
        chat_id=message.chat.id,
        text=f"Welcome {mention} to the bot! Here's a message with some buttons:",
        parse_mode="HTML",
        reply_markup=reply_markup
    )

@bot.on_callback_query()
async def handle_callback(client, callback_query):
    callback_query_id = callback_query.id
    data = callback_query.data

    if data == "button1":
        await client.answer_callback_query(callback_query_id=callback_query_id, text="You pressed Button 1!", show_alert=True)
    elif data == "button2":
        await client.answer_callback_query(callback_query_id=callback_query_id, text="You pressed Button 2!", show_alert=True)
    else:
        await client.answer_callback_query(callback_query_id=callback_query_id, text="Unknown button pressed", show_alert=True)

async def main():
    await bot.run()

if __name__ == "__main__":
    asyncio.run(main())
```
vdk-oauth-auth 0.3.1702643990
Versatile Data Kit SDK plugin adds Oauth support.


The plugin provides Oauth authentication on data job startup.

# Usage

To install the plugin, run:

```bash
pip install vdk-oauth-auth
```

## Configuration

The following environment variables can be used to configure this plugin:

| name                 | description                                   |
|----------------------|-----------------------------------------------|
| `TEAM_CLIENT_ID`     | Client id to fetch access token from CSP.     |
| `TEAM_CLIENT_SECRET` | Client secret to fetch access token from CSP. |