semvec/pypi-packages huggingface dataset:
filecloudapi-python 0.5.1
A Python library to connect to a Filecloud server
License: Apache-2.0
Requires Python: <4.0,>=3.11

# Overview

A Python library to connect to a Filecloud server

This project was generated with [cookiecutter](https://github.com/audreyr/cookiecutter) using [jacebrowning/template-python](https://github.com/jacebrowning/template-python).

[![Linux Build](https://img.shields.io/github/actions/workflow/status/codelathe/template-python-demo/main.yml?branch=main&label=linux)](https://github.com/codelathe/filecloudapi-python/actions)
[![Windows Build](https://img.shields.io/appveyor/ci/codelathe/template-python-demo/main.svg?label=windows)](https://ci.appveyor.com/project/codelathe/filecloudapi-python)
[![Code Coverage](https://img.shields.io/codecov/c/github/codelathe/filecloudapi-python)
](https://codecov.io/gh/codelathe/filecloudapi-python)
[![Code Quality](https://img.shields.io/scrutinizer/g/codelathe/filecloudapi-python.svg?label=quality)](https://scrutinizer-ci.com/g/codelathe/filecloudapi-python/?branch=main)
[![PyPI License](https://img.shields.io/pypi/l/filecloudapi-python.svg)](https://pypi.org/project/filecloudapi-python)
[![PyPI Version](https://img.shields.io/pypi/v/filecloudapi-python.svg?label=version)](https://pypi.org/project/filecloudapi-python)
[![PyPI Downloads](https://img.shields.io/pypi/dm/filecloudapi-python.svg?color=orange)](https://pypistats.org/packages/filecloudapi-python)

## Setup

### Requirements

* Python 3.11+

### Installation

Install it directly into an activated virtual environment:

```text
$ pip install filecloudapi-python
```

or add it to your [Poetry](https://poetry.eustace.io/) project:

```text
$ poetry add filecloudapi-python
```

## Usage

After installation, the package can be imported:

```text
$ python
>>> import filecloudapi
>>> filecloudapi.__version__
```
irrapy2 0.1.0
A unified multi-source solar radiation and ground meteorological data downloader with forecasting tools.
License: Apache-2.0
Requires Python: >=3.8

# irrapy2

**irrapy2** is a lightweight Python toolkit for downloading, parsing, and processing **multi-source ground-based solar radiation and meteorological datasets**, combined with a simple forecasting module (RNN / LSTM / Informer).

The package provides a unified interface to several international radiation networks:

- **BSRN** – Baseline Surface Radiation Network  
- **MIDC (NREL)** – Measurement & Instrumentation Data Center  
- **SAURAN** – Southern African Universities Radiometric Network  
- **SRML** – Solar Radiation Monitoring Laboratory (UOregon)  
- **SURFRAD (NOAA)** – Surface Radiation Budget Network  
- **SOLRAD (NOAA)** – Solar Radiation Network  

It also includes a built-in forecasting tool for solar irradiance time series.

---

## 📦 Installation

```bash
pip install irrapy2
```

---

## 🚀 Quick Start

### Download BSRN data

```python
from irrapy2 import download_bsrn

download_bsrn(
    site="cab",
    start="2023-01-01",
    end="2023-01-31",
    username="your_bsrn_username",
    password="your_bsrn_password",
    save_path="bsrn_out.csv"
)
```

### Download MIDC data

```python
from irrapy2 import download_midc

download_midc(
    site="BMS",
    begin="20230101",
    end="20230131",
    save_path="midc_out.csv"
)
```

### Forecast Solar Radiation

```python
from irrapy2 import run_forecast

metrics = run_forecast(
    csv_path="bsrn_out.csv",
    model="lstm",       # rnn / lstm / informer
    seq_len=72,
    horizon=6,
    epochs=10
)

print(metrics)
```

---

## 📁 Supported Datasets

| Source | Region | Module | Time Handling |
|--------|--------|---------|---------------|
| BSRN | Global | `download_bsrn` | UTC |
| MIDC (NREL) | USA | `download_midc` | Local + DST + UTC |
| SAURAN | Africa | `download_sauran` | Local → UTC |
| SRML | USA | `download_srml` | America/Los_Angeles |
| SURFRAD | USA | `download_surfrad` | UTC |
| SOLRAD | USA | `download_solrad` | UTC + Local |

---

## 🔧 Requirements

```
pandas
numpy
requests
pytz
torch
scikit-learn
```

---

## 📄 License

This project is open-source and licensed under the **Apache License 2.0**.

---

## 🙌 Contributing

Issues and pull requests are welcome.  
Feel free to open a PR if you want to add more stations, enhance parsing logic, or improve the forecasting module.