semvec/pypi-packages huggingface dataset:
gwas-assoc 0.1.0
GWAS Association Tools
Requires Python: <4.0,>=3.10

# GWAS Association Tools

A command-line tool for genomic-wide association studies (GWAS) data validation and analysis.

## Features

- Validate:
  - Input: File path of GWAS Submission template that contains top associations
  - Output: Validation report of top associations

## Installation

Install from PyPI:

```bash
pip install gwas-assoc
```

## Usage

```bash
# Basic validation command
gwas-assoc validate <template excel file path>

# For help
gwas-assoc --help
gwas-assoc validate --help
```

## Development

### Setup

```bash
# Install Poetry (if not already installed)
curl -sSL https://install.python-poetry.org | python3 -

# Install dependencies
poetry install

# Activate virtual environment
poetry shell
```

### Building and Installation

```bash
# Build the package (creates .whl and .tar.gz in dist/)
poetry build

# Install your new package in development mode
poetry install
```

### Testing

TODO

### Running with Real Files

```bash
# Run the CLI command through Poetry
poetry run gwas-assoc validate ./tests/snp_validator.xlsx

# Or after activating the shell
poetry shell
gwas-assoc validate ./tests/snp_validator.xlsx
```

### Dependency Management

```bash
# Add a new dependency
poetry add new-package

# Add a development dependency
poetry add --group dev pytest-mock

# Check for dependency updates
poetry update --dry-run

# Update dependencies
poetry update
```

### Code Quality

```bash
# Run formatting
poetry run black .
poetry run isort .

# Run linting
poetry run ruff check .

# Run type checking
poetry run mypy src

# Run all formatting checks
poetry run pre-commit run --all-files
```

## License

[License](LICENSE)
uwqsc-backtesting-framework 2025.3.7
The University of Waterloo quantitative analysis stocks club backtesting framework repository.
Requires Python: >=3.9

# backtesting-framework
# The University of Waterloo Quantitative Analysis Stocks Club Backtesting Framework

Welcome to the University of Waterloo Quantitative Analysis Stocks Club Backtesting Framework repository. This framework is designed to help you test and analyze various stock trading strategies using historical data.

## Features

- **Historical Data Analysis**: Import and analyze historical stock data to backtest trading strategies.
- **Strategy Implementation**: Implement and test custom trading strategies.
- **Performance Metrics**: Evaluate the performance of your strategies with various metrics.
- **Visualization**: Visualize the results of your backtests with charts and graphs.

## Getting Started

### Prerequisites

- Python 3.x
- Required Python libraries (listed in `requirements.txt`)

### Installation

1. Clone the repository:
    ```bash
    git clone https://github.com/yourusername/backtesting-framework.git
    ```
2. Navigate to the project directory:
    ```bash
    cd backtesting-framework
    ```
3. Install the required dependencies:
    ```bash
    pip install -r requirements.txt
    ```


### Usage

1. Prepare your historical data in the required format.
2. The current application runs on data in csv format and uses streamlit.
3. Run the application:
    ```python
    streamlit run main.py
    ```
4. **CSV File Access:**
    - Due to file size constraints, the CSV file 'hackathon_sample_v2.csv' used for backtesting is stored externally
    - You can download it from **[https://drive.google.com/file/d/1H3ktLEsd3Bg9A9Rx5P45OdnYMEdkX29s/view?usp=sharing]** and place it in the `data/` directory.


Happy backtesting!