semvec/pypi-packages huggingface dataset:
para-api-security 0.0.9
Common Package to authenticate APIs

# Para Common Lib
Common Utilities Python library for Para Projects

## How to Package

Create the setup.py file

Before uploading to PyPI, you need a few tools to package and upload your project. Run these commands to install them:
```bash
pip install setuptools wheel twine
```
Build Your Package
```bash
python setup.py sdist bdist_wheel
```
This will create a dist/ folder that contains the files you need to upload to PyPI. Inside dist/, you should see files like my_package-0.1.0.tar.gz and my_package-0.1.0-py3-none-any.whl.


Upload Your Package to PyPI
```bash
twine upload dist/*
```

You can install the package with pip:

```bash
pip install my-package
```

Here's an example of how to use the package:
```bash
from my_package import authenticate
authenticate_user()
```
deltau 0.1.1
A backtesting and performance analysis package
Requires Python: >=3.11.7

# DeltaU

DeltaU is a backtesting and performance analysis package for quantitative trading strategies.

## Installation

You can install DeltaU using `pip install deltau':


## Usage

Example usage:

```python
from DeltaU.core.backtester import Backtester, Executor
from DeltaU.visualization.tear_sheet import TearSheet

# Create a strategey and generate signals
def class MyStrategy:
     def __init__(self, window=1):
        self.window = window
        
        def generate_signals(self, data):
            #generate signals

             return signals

# Instantiate the strategy, executor, and backtester
strategy = MyStrategy(window=self.window)
executor = Executor(initial_capital=initial_capital)
backtester = Backtester(strategy=strategy, executor=executor, data=data)

# Run the backtest
portfolio_values, final_metrics = backtester.run()

# Create a TearSheet object with the results and metrics
tear_sheet = TearSheet(backtest_results=portfolio_values, metrics=final_metrics)

# Generate the report and show plots
tear_sheet.display_report()

## In case you get an error when calling tear_sheet function while using jupyter 
## Copy and paste: pip install nbformat>=4.2.0 into your envrionment, restart the environment and than re-run the code.