semvec/pypi-packages huggingface dataset:
classifier-pipeline 0.0.48
Classifier Pipeline
Requires Python: >=3.6

# PI classifier

This pacakge will install the cacophony pipeline tracking onto a RPI

You will also need to install these system packages in order to run the package
`sudo apt install python3-opencv libglib2.0-dev libgirepository1.0-dev libcairo2-dev libcairo2  python3-dbus build-essential libdbus-glib-1-dev libgirepository1.0-dev`

Once installed the tracking can be run using `pi_classifier`

The default config is installed with this package if you would like to override the config you can create a config file at
`/etc/cacophony/classifier.yaml`
magiqa-finance 0.1.0
Python library for accessing Magiqa Finance API - comprehensive stock data, fundamentals, technical indicators, historical data, and options chains
Requires Python: >=3.8
Keywords: finance, stocks, trading, api, financial data, technical indicators, fundamentals

# Magiqa Finance Python Library

[![Python Version](https://img.shields.io/badge/python-3.8%2B-blue.svg)](https://www.python.org/downloads/)
[![License](https://img.shields.io/badge/license-MIT-green.svg)](LICENSE)

Python library for accessing the Magiqa Finance API - comprehensive stock data, fundamentals, technical indicators, historical data, and options chains.

## Installation

```bash
pip install magiqa-finance
```

## Quick Start

### 1. Get Your API Key

Register at [https://options.magiqa.us/register](https://options.magiqa.us/register) and generate an API key.

### 2. Basic Usage

```python
import magiqa

# Initialize client with your API key
client = magiqa.Client(api_key="your-api-key-here")

# Get fundamental data
data = client.fundamentals("AAPL")
print(f"Price: ${data['price']}")
print(f"Market Cap: ${data.get('market_cap', 'N/A')}")

# Get technical indicators
technical = client.technical("AAPL")
print(f"RSI: {technical.get('rsi', 'N/A')}")

# Get financial statements
financials = client.financials("AAPL")

# Get historical data
hist = client.historical_data("AAPL", start_date="2024-01-01", end_date="2024-01-31")

# Get options chain
options = client.options("AAPL", "2024-02-16")
```

### 3. Using Environment Variables

```bash
export MAGIQA_API_KEY="your-api-key-here"
```

```python
import magiqa

client = magiqa.Client()  # Uses MAGIQA_API_KEY from environment
data = client.fundamentals("AAPL")
```

## Features

- **Fundamental Data**: Get comprehensive stock fundamentals including price, market cap, P/E ratio, and more
- **Technical Indicators**: Access RSI, MACD, moving averages, and trend analysis
- **Financial Statements**: Retrieve income statements, balance sheets, and cash flow statements
- **Historical Data**: Fetch historical price data with customizable date ranges
- **Options Chains**: Get complete options chains with Greeks (delta, gamma, theta, vega)

## Documentation

For detailed documentation, see [magiqa/README.md](magiqa/README.md) or visit [https://options.magiqa.us](https://options.magiqa.us).

## Requirements

- Python 3.8+
- requests >= 2.28.0

## License

MIT License - see [LICENSE](LICENSE) file for details.

## Support

- Documentation: [https://options.magiqa.us](https://options.magiqa.us)
- Issues: [https://github.com/magiqa/magiqa-finance-python/issues](https://github.com/magiqa/magiqa-finance-python/issues)
- Email: support@magiqa.com
gmol-core 0.1.0b1
Core components of GalaxyMol
Requires Python: <3.14,>=3.10

# gmol-core

Core components of GalaxyMol.

## Notes to developers

Before starting development, make sure to create the virtual environment and
install the pre-commit hooks by running the following command:

```bash
uv sync
uv run pre-commit install --install-hooks --overwrite
```

Before you push to the development branch, make sure to run mypy checks for
any type-related errors.

```bash
mypy [--pretty]
```

Although it's not a strict requirement, consider following the
[conventional commits](https://www.conventionalcommits.org/en/v1.0.0/)
guidelines for commit messages. This will help reviewers to understand the
changes in a more structured way.

## License

This project is licensed under the Apache License, Version 2.0. See the
[LICENSE](LICENSE) file for details.
pasarguard-node-bridge-insecure 0.4.3
python package to connect your project with PasarGuard node go (insecure/no-TLS variant)
Requires Python: >=3.12
Keywords: PasarGuard, PasarGuard API, PasarGuard python, PasarGuard-Node, PasarGuard-panel

# node_bridge_py
Library to connect and use https://github.com/PasarGuard/node

# Usage
```shell
pip install pasarguard-node-bridge
```
Library is fully async for both `gRPC` and `REST API` connection.

# Example
```python
import PasarGuardNodeBridge as Bridge
# or
import PasarGuardNodeBridge as PGNB
```

## Creating Node
```python
node = Bridge.create_node(
    connection=Bridge.NodeType.GRPC, # GRPC or REST
    address=address, # Node ip address or domain
    port=port, 
    client_cert=client_cert_content, # client side ssl certificate as string
    client_key=client_key_content, # client side ssl key as string
    server_ca=server_ca_content, # server side ssl key as string
    extra={}, # a dictionary to hold node data on production, optional, default: None
    )
```

## Proto Structure
If you need to have access proto structure you can use:
```python
from PasarGuardNodeBridge.common import service_pb2 as service
```

## Create User
```python
user = Bridge.create_user(
    email="jeff", 
    proxies=Bridge.create_proxy(
        vmess_id="0d59268a-9847-4218-ae09-65308eb52e08", # UUID converted to str
        vless_id="0d59268a-9847-4218-ae09-65308eb52e08", # UUID converted to str
        vless_flow="",              # Valid vless flow if is set for user (str)
        trojan_password="",         # Trojan password (str)
        shadowsocks_password="",    # Shadowsocks password (str)
        shadowsocks_method="",      # Valid shadowsocks method supported by backend
        ), 
    inbounds=[]                     # List of outbound tag, List[str]
    )
```

## Methods
Before use any method you need to call start method and connect to node unless you will face `NodeAPIError` for every method
```python
await node.start(
    config=config,  # backend config as string 
    backend_type=0, # backend type , XRAY = 0
    users=[],       # list of users you want to add to this node, will be recheck in node with config
    timeout=20,
    )
```

### Sync Users
- Use `sync_users` for small updates.
- Use `sync_users_chunked` for large user lists to stream `UsersChunk` messages over gRPC or REST without overwhelming a single request.

```python
await node.sync_users(users)

# Large batches
await node.sync_users_chunked(users, chunk_size=500)
```

### Get User Stats
```python
stats = await node.get_user_stats(
    email="noreply@donate.pasarguard.org",
    reset=True,
    timeout=10,
    )
```

### Health
Return a `Bridge.Health`
```python
health = await node.get_health()
```

### Logs
Return a `asyncio.Queue[str]` 
```python
logs = await node.get_logs()
```