semvec/pypi-packages huggingface dataset:
Sub-Py-Library 0.1.0
A great Python library.
License: MIT
Requires Python: >=3.6

README.md

DEVELOPED BY SUBHRA CHAKRABORTI
LAST UPDATE: 24TH AUGUST 2024
VERSION: 1

WELCOME TO SubPyNum,
I HAVE BUILT IT IN MIND TAKING ALL THE CONSIDERATIONS OF USERS' EXPERIENCE.
IT CONTAINS A TON OF USEFUL NUMBER CHECKING PROGRAMS.

UTILIZE IT TO SAVE YOUR PRECIOUS TIME.

Installation:

```bash
pip install sub-py-num
```
face-detection-lib 0.8
A library for face detection using YOLOv8
License: MIT


# Face Detection Library

![working](https://img.shields.io/badge/status-working-brightgreen)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
![PyPI Version](https://img.shields.io/pypi/v/face_detection_lib)

A Python library for face detection using YOLOv8. This library enables real-time face detection via webcam, leveraging the YOLOv8 model for high-performance object detection.

## Features

- Real-time face detection with YOLOv8
- Easy integration with webcam
- Customizable detection thresholds and labels

## Installation

You can install the library via pip. Run the following command in your terminal:

```bash
pip install face_detection_lib
```

## Usage

To use the `face_detection_lib` library for face detection, follow these steps:

### Basic Usage

```python
from face_detection_lib.detector import FaceDetector

# Initialize the FaceDetector
detector = FaceDetector()

# Start the webcam and run face detection
detector.run_webcam()
```

### Custom Configuration

You can customize the face detection by passing parameters to the `FaceDetector` class. For example, you can set a custom model path, labels, or confidence threshold:

```python
from face_detection_lib.detector import FaceDetector

# Define custom parameters
custom_model_path = 'path/to/your/custom/model.pt'
custom_labels = {0: 'Person A', 1: 'Person B'}
custom_confidence_threshold = 0.7

# Initialize the FaceDetector with custom parameters
detector = FaceDetector(
    model_path=custom_model_path,
    labels=custom_labels,
    confidence_threshold=custom_confidence_threshold
)

# Start the webcam with custom settings
detector.run_webcam()
```

## Testing

Ensure that your library functions as expected by writing tests in the `tests/test_detector.py` file. Here's a basic example of how you might start testing:

```python
def test_face_detection():
    # Initialize the FaceDetector
    detector = FaceDetector()
    
    # Add tests to verify the functionality
    assert detector is not None
    # Further tests can be added here
```

### Running Tests

To run your tests, execute:

```bash
pytest
```

## Contributing

Contributions are welcome! If you have suggestions or improvements, please submit a pull request or open an issue.

### Contributors
- [Sehastrajit](https://github.com/Sehastrajit)
- [Deena](https://github.com/Deena1412)




## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

---

Thank you for using `face_detection_lib`!
pricefunctions 0.0.10
tool that converts OHLC price tables to candles
License: MIT

Package that stores and converts historical price data to candles. 

Candle classes are used to store candle OHLC data and run quick tests .

Use the to_candle_array method to generate a candle array

Candle Arrays are a data type storing a list of candles.


Dataload tools help to pull historical data. 

Load 15M loads all 15m data and so on, just need to pass a ticker symbol. ES is 'ES'
py-questdb 0.0.2
Python interface for QuestDB
License: MIT
Requires Python: >=3.11

# QuestDB Python Client

This is an open-source Python library for interacting with QuestDB, a high-performance, open-source SQL database designed to process time series data. This client provides an easy-to-use interface for querying and writing data to QuestDB from Python applications.

## Features

- Asynchronous and synchronous query execution
- Write single or multiple messages to QuestDB
- Buffer writes for improved performance
- Convert query results to Pandas DataFrames
- Type conversion and parsing of query results
- Support for both HTTP and TCP interfaces

## Installation

You can install the QuestDB Python Client using pip:

```bash
pip install py-questdb
```

## Quick Start

Here's a simple example to get you started:

```python
import asyncio
from questdb_python_client import QuestDB

async def main():
    # Connect to QuestDB
    db = QuestDB(host="localhost", port=9000)

    # Write some data
    await db.write(
        table_name="sensors",
        symbols={"location": "room1"},
        columns={"temperature": 22.5, "humidity": 60},
        at=datetime.now()
    )

    # Query data
    async for row in db.query("SELECT * FROM sensors ORDER BY timestamp DESC LIMIT 10"):
        print(row)

    # Query data as a DataFrame
    df = await db.query_df("SELECT * FROM sensors WHERE location = 'room1'")
    print(df)

    await db.close()

asyncio.run(main())
```

## Usage

### Connecting to QuestDB

```python
from questdb_python_client import QuestDB

# For HTTP interface
db = QuestDB(host="localhost", port=9000)

# For TCP interface
db = QuestDB(host="localhost", port=9009)
```

### Writing Data

```python
# Write a single message
db.write(
    table_name="sensors",
    symbols={"location": "room1"},
    columns={"temperature": 22.5, "humidity": 60},
    at=datetime.now()
)

# Write multiple messages
messages = [
    QuestMessage(table_name="sensors", symbols={"location": "room1"}, columns={"temperature": 22.5}, at=datetime.now()),
    QuestMessage(table_name="sensors", symbols={"location": "room2"}, columns={"temperature": 23.1}, at=datetime.now())
]
db.write_iter(messages)
```

### Querying Data

```python
# Asynchronous query
async for row in db.query("SELECT * FROM sensors WHERE location = 'room1'"):
    print(row)

# Synchronous query
for row in db.query_sync("SELECT * FROM sensors WHERE location = 'room1'"):
    print(row)

# Query as DataFrame
df = await db.query_df("SELECT * FROM sensors WHERE location = 'room1'")
print(df)
```

## License

This project is licensed under the [MIT License](LICENSE).