semvec/pypi-packages huggingface dataset:
meteofr 0.0.6
Access Meteo France API to fetch weather data.
Requires Python: >=3.8

[![PyPI - Version](https://img.shields.io/pypi/v/meteofr.svg)](https://pypi.org/project/meteofr)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/meteofr.svg)](https://pypi.org/project/meteofr)

-----

Tool to fetch weather data from Meteo France API based on latitude and longitude coordinates.

## Table of Contents

- [Table of Contents](#table-of-contents)
- [Installation](#installation)
- [Quickstart](#quickstart)
- [License](#license)
- [See also](#see-also)

## Installation

```console
pip install meteofr
```

## Quickstart

Set up a (free) API key at [portail-api.meteofrance.fr](https://portail-api.meteofrance.fr/web/fr/api/DonneesPubliquesClimatologie).

A first download of the list of weather stations is required to compute closest active at the time station from given point.

```python
from pandas import Timestamp, Timedelta, DatetimeIndex
from meteofr.get_data import get_weather

test_point = (47.218102, -1.552800)

td = Timestamp("today", tz="Europe/Paris").normalize().tz_convert("UTC")
dates = DatetimeIndex([td - Timedelta("30d"), td])  # 1 year max

df = get_weather(dates=dates, point=test_point)
print(df.head)

#       POSTE      DATE   RR  QRR  DRR  QDRR   TN  QTN  HTN  ...  QTMERMAX  TMERMIN  QTMERMIN  HNEIGEF  QHNEIGEF  NEIGETOTX  QNEIGETOTX  NEIGETOT06  QNEIGETOT06  
# 0  44109012  20250301  0.0    1  NaN   NaN  2.8    1  448  ...       NaN      NaN       NaN      NaN       NaN        NaN         NaN         NaN          NaN  
# 1  44109012  20250302  0.0    1  NaN   NaN  1.8    1  442  ...       NaN      NaN       NaN      NaN       NaN        NaN         NaN         NaN          NaN  
# 2  44109012  20250303  0.0    1  NaN   NaN  2.3    1  553  ...       NaN      NaN       NaN      NaN       NaN        NaN         NaN         NaN          NaN  
# 3  44109012  20250304  0.0    1  NaN   NaN  4.9    1  547  ...       NaN      NaN       NaN      NaN       NaN        NaN         NaN         NaN          NaN  
# 4  44109012  20250305  0.2    1  NaN   NaN  4.0    1  647  ...       NaN      NaN       NaN      NaN       NaN        NaN         NaN         NaN          NaN  

# [5 rows x 136 columns]
```

## License

`meteofr` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.

## See also

- meteofetch ([data.gouv](https://www.data.gouv.fr/fr/reuses/meteofetch/) and [github](https://github.com/CyrilJl/MeteoFetch) links) for Arome model forecasting
- [meteostat](https://dev.meteostat.net/) for global weather data (based on [data.europa](.eu/data/datasets) for Europe data)
atmoswing-vigicrues 1.2.0
Package to integrate AtmoSwing in the Vigicrues network.
Requires Python: >=3.7

# atmoswing-vigicrues

[![GitHub release](https://img.shields.io/github/v/release/atmoswing/atmoswing-vigicrues)](https://github.com/atmoswing/atmoswing-vigicrues)
[![PyPI](https://img.shields.io/pypi/v/atmoswing-vigicrues)](https://pypi.org/project/atmoswing-vigicrues/)
[![Docker Image Version](https://img.shields.io/docker/v/atmoswing/atmoswing-vigicrues)](https://hub.docker.com/r/atmoswing/atmoswing-vigicrues)
![Static Badge](https://img.shields.io/badge/python-%3E%3D3.7-blue)
   
Module Python pour l'intégration d'AtmoSwing dans le réseau Vigicrues.

Documentation API: http://atmoswing.org/atmoswing-vigicrues


Objectif
--------

Le module a pour but la gestion du flux de la prévision par AtmoSwing. Il permet :

* de télécharger les fichiers de sortie de modèles météo (p. ex. GFS),
* de transformer de tels fichiers en un format netCDF générique,
* d'exécuter les prévisions par AtmoSwing,
* d'extraire les résultats en d'autres formats (p.ex. json),
* et de diffuser ces fichiers par SFTP.


Installation
------------

Pour utiliser le module atmoswing-vigicrues, il faut installer :

* Python >= 3.7
* AtmoSwing Forecaster (de préférence la version serveur)
* Le module atmoswing-vigicrues (``pip install atmoswing-vigicrues`` ou l'image docker ``docker pull atmoswing/atmoswing-vigicrues``)

Utilisation
-----------

Le paquet est constitué de plusieurs modules qui peuvent être activés et configurés dans un fichier de configuration. Plusieurs flux de prévision peuvent être configurés sur un serveur / PC par la création de différents fichiers de configuration. Il n’y a pas de paramètres codés en dur dans le code. L’exécution d’un flux de prévision est effectuée par la commande :

```
python -m atmoswing_vigicrues --config-file="chemin/vers/fichier/config.yaml
```

Le fichier de configuration définit :

* Les propriétés de la prévision par AtmoSwing
* Les pré-actions : les actions à effectuer préalablement à la prévision par AtmoSwing
* Les post-actions : les actions à effectuer après la prévision par AtmoSwing
* Les disséminations : les actions de transfert des résultats

Le flux de la prévision est le suivant :

1. pré-actions
2. prévision par AtmoSwing
3. post-actions
4. diffusion

Documentation API: http://atmoswing.org/atmoswing-vigicrues
STEM-Vibrations 1.2.3
STEM model
Requires Python: <3.12,>=3.9

```
     _______..___________. _______ .___  ___.
    /       ||           ||   ____||   \/   |
   |   (----``---|  |----`|  |__   |  \  /  |
    \   \        |  |     |   __|  |  |\/|  |
.----)   |       |  |     |  |____ |  |  |  |
|_______/        |__|     |_______||__|  |__|

```

# STEM: Soil and Track System Modeling Tool

![Tests](https://github.com/StemVibrations/STEM/actions/workflows/tests.yml/badge.svg)
[![Documentation Status](https://readthedocs.org/projects/stemvibrations/badge/?version=latest)](https://stemvibrations.readthedocs.io/)
[![codecov](https://codecov.io/gh/stemvibrations/stem/graph/badge.svg?token=0DMYCZF4BU)](https://codecov.io/gh/stemvibrations/stem)
[![PyPI version](https://img.shields.io/pypi/v/STEM-Vibrations.svg)](https://pypi.org/project/STEM-Vibrations/)
[![Python versions](https://img.shields.io/pypi/pyversions/STEM-Vibrations.svg)](https://pypi.org/project/STEM-Vibrations/)
[![License](https://img.shields.io/pypi/l/STEM-Vibrations.svg)](https://pypi.org/project/STEM-Vibrations/)

The STEM model is designed to create and analyse models of soil and track systems.
The tool provides a set of commands for creating the geometry of the model, defining the soil and track properties, setting the boundary conditions and loads, generating the mesh, and performing post-processing on the results.

## Installation

STEM can be downloaded and installed on any system that supports Python.
To install the STEM, follow the following steps:

```python
pip install STEM-Vibrations
```

Further details about the installation can be found [here](https://stemvibrations.readthedocs.io/v1.2/installation.html#).

## Usage

To use STEM please refer to the tutorials available [here](https://stemvibrations.readthedocs.io/v1.2/#tutorials).

## License

This project is licensed under the BSD 3-Clause License - see the [LICENSE](LICENSE) file for details.
hp23005equation-solver 0.1.1
Librería para resolver ecuaciones lineales y no lineales con métodos numéricos
Requires Python: >=3.7

# Equation Solver

`equation-solver` es una librerÃ­a de Python que permite resolver sistemas de ecuaciones lineales y no lineales mediante distintos mÃ©todos numÃ©ricos.

## MÃ©todos disponibles

### Ecuaciones lineales:
- EliminaciÃ³n de Gauss
- Gauss-Jordan
- Regla de Cramer
- DescomposiciÃ³n LU
- MÃ©todo de Jacobi
- MÃ©todo de Gauss-Seidel

### Ecuaciones no lineales:
- MÃ©todo de BisecciÃ³n

## InstalaciÃ³n
```bash
pip numpy
pip install --upgrade setuptools pip wheel
pip install hp23005equation-solver
cydifflib 1.2.0
Fast implementation of difflib's algorithms
Requires Python: >=3.9

<h1 align="center">
 CyDifflib
</h1>
<p align="center">
  <a href="https://github.com/rapidfuzz/CyDifflib/actions">
    <img src="https://github.com/rapidfuzz/CyDifflib/workflows/Build/badge.svg"
         alt="Continuous Integration">
  </a>
  <a href="https://pypi.org/project/cydifflib/">
    <img src="https://img.shields.io/pypi/v/cydifflib"
         alt="PyPI package version">
  </a>
  <a href="https://www.python.org">
    <img src="https://img.shields.io/pypi/pyversions/cydifflib"
         alt="Python versions">
  </a><br/>
  <a href="https://github.com/rapidfuzz/CyDifflib/blob/main/LICENSE">
    <img src="https://img.shields.io/github/license/rapidfuzz/CyDifflib"
         alt="GitHub license">
  </a>
</p>

<h4 align="center">CyDifflib is a fast implementation of difflib's algorithms, which can be used as a drop-in replacement</a>.</h4>


## 🚀 Benchmarks
The following [benchmark](https://github.com/rapidfuzz/CyDifflib/tree/main/bench) compares the performance in the original [difflib](https://docs.python.org/3.10/library/difflib.html) implementation, the library [cdifflib](https://github.com/mduggan/cdifflib) and CyDifflib

<p align="center">
<img src="https://raw.githubusercontent.com/rapidfuzz/CyDifflib/main/bench/CyDifflib.svg?sanitize=true" alt="Benchmark CyDifflib">
</p>

## ⚙️ Installation

You can install this library from [PyPI](https://pypi.org/project/cydifflib/) with pip:
```
pip install cydifflib
```
CyDifflib provides binary wheels for all common platforms.

### Source builds

For a source build (for example from a SDist packaged) you only require a C++11 compatible compiler. You can install directly from GitHub if you would like.
```
pip install git+https://github.com/rapidfuzz/CyDifflib.git@main
```

## 📖 Usage

The library can be used in the same way as difflib. Just use the `cydifflib` module instead of `difflib`:
```python
# from difflib import SequenceMatcher
from cydifflib import SequenceMatcher
```
The official [documentation of difflib](https://docs.python.org/3.10/library/difflib.html) explains how to use the library. If you work with a library which internally uses some of the algorithms of difflib it is possible to replace the implementation before importing this library. E.g. for `thefuzz` this can be done in the following way:
```python
from cydifflib import SequenceMatcher
import difflib

difflib.SequenceMatcher = SequenceMatcher
from thefuzz import fuzz
```

## 👍 Contributing

PRs are welcome!
- Found a bug? Report it in form of an [issue](https://github.com/rapidfuzz/CyDifflib/issues). Any difference in behavior to difflib is considered as a bug.
- Can make something faster? Great! Just avoid external dependencies and remember that external behavior does not change.
- Have no time to code? Tell your friends and subscribers about CyDifflib.

Thank you :heart:

## ⚠️ License
Copyright 2021-present [Max Bachmann](https://github.com/maxbachmann). `CyDifflib` is free and open-source software licensed under the [MIT License](https://github.com/rapidfuzz/CyDifflib/blob/main/LICENSE).