semvec/pypi-packages huggingface dataset:
cloud-storage-service 0.2.42
A unified cloud storage package for AWS, Azure, and GCP
License: MIT
Requires Python: >=3.6

# Cloud Storage Service

A unified cloud storage package that provides seamless integration with major cloud providers: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). This library allows developers to easily access and manage cloud storage services with a consistent interface.

## Package Structure

```plaintext
- storage_manager.py   # Factory function to create DB connection based on the service type
- aws_storage.py       # AWS RDS MySQL connection class
- azure_storage.py     # Azure SQL Database connection class        
- gcp_storage.py       # Google Cloud MySQL connection class
```

## Features

- **Supports Multiple Cloud Providers**: Easily switch between AWS, Azure, and GCP.
- **Flexible Configuration**: Configure services with required parameters for each provider.
- **Intuitive API**: Simple methods for managing cloud storage operations.

## Installation
Ensure all necessary dependencies are installed:
```python
pip install cloud_storage_service
```

## Usage

```python
#! pip install cloud_storage_service

from cloud_storage_service import get_cloud_storage_service

def test_get_document_details():
    bucket_name = 'testbucket'
    prefix = '000740194c8c-adfe-2ab061872773d3/test_data/'  

    aws_service = get_cloud_storage_service('aws')

    try:
        documents = aws_service.get_document_details(bucket_name, prefix=prefix, file_type='.xml')
        
        if documents:
            print("Fetched document details:")
            for doc_name, doc_info in documents.items():
                print(f"Document Name: {doc_info['document_name']}")
                print(f"Document Hash: {doc_info['document_hash']}")
                print(f"Document Size: {doc_info['document_size']} bytes")
                print(f"File Type: {doc_info['file_type']}")
                print("-" * 40)
        else:
            print("No documents found.")
    
    except Exception as e:
        print(f"Error occurred: {e}")

test_get_document_details()
```
GUMPGPD 0.1.0
GPD analysis tools with DVCS, DVMP, lattice inputs, ... 
License: MIT
Requires Python: >=3.8

# GUMP: Generalized Parton Distributions through Universal Moment Parameterization

This repository contains the source code for the **Generalized Parton Distributions through Universal Moment Parameterization (GUMP)** program, designed for global analysis of GPDs.

## Overview

- **GPD Calculations:**  
  The script under folder `/tests` provides example workflows to generate PDFs, GPDs and cross-sections using GUMP parameters obtained from the fitting program.

- **Performance Note:**  
  Evaluating GPDs can be computationally intensive, as it involves QCD evolution in moment space and numerical contour integrals to transform back to the momentum fraction (x) space.

For detailed documentation and further information, please visit:  
[https://yuxunguo.github.io/GUMP-Global-GPDs/](https://yuxunguo.github.io/GUMP-Global-GPDs/)