semvec/pypi-packages huggingface dataset:
ouverture-firefox 1.0.0
Un package d ouverture de firefox qu une seule fois
Requires Python: >=3.6

# 📦 NomDuProjet

Une courte description de ce que fait ton projet.

---

## 🚀 Fonctionnalités

- ✅ Fonctionnalité 1
- ✅ Fonctionnalité 2
- 🔧 Fonctionnalité en cours de développement

---

## 🛠️ Installation

Installe ce paquet via `pip` :

```bash
pip install nomduprojet
physiboss-models 0.1.2
Library for using PhysiBoSS-Models
Requires Python: >3.8

# physiboss-models 
[![PyPI version](https://badge.fury.io/py/physiboss-models.svg)](https://badge.fury.io/py/physiboss-models)


![PhysiBoSS logo](https://avatars.githubusercontent.com/u/179001945?s=400&u=02c8638da9de9d9cd68820187adbfcb45c9d8007&v=4)

This python library provides and API to the [PhysiBoSS-Models Database](https://github.com/PhysiBoSS-Models). You can list models, look at their metadata, and download them. 

## Install

```
pip install physiboss-models
```

## Usage

To start, you need to create the Database object:

```
import physiboss_models as pm
db = pm.DataBase()
```

### List models
```
models = db.all()
```

### Search models
```
models = db.search("invasion")
```

### List versions of a model
```
versions = db.versions(model)
```

### Download model
```
db.download_model(model, path, version)
```

This will download a model (pre-compiled binary, config files) into the informed path. You can soecify a version, if you don't it will download the latest one.

Once loaded, you can access the model metadata with 
```
metadata = db.current_model_info()
```
khalil-zaidi-calculator 0.1.0
Advanced calculator with extra math operations
Requires Python: >=3.6

# khalil-zaidi-calculator

آلة حاسبة متقدمة بلغة بايثون تدعم العمليات الأساسية والإضافية.

## التثبيت
```bash
pip install khalil-zaidi-calculator
```

## الاستخدام
```python
from khalil_zaidi_calculator import Calculator

calc = Calculator()

print(calc.add(5, 3))       # 8
print(calc.divide(10, 2))   # 5
print(calc.power(2, 4))     # 16
print(calc.sqrt(25))        # 5
print(calc.average([1,2,3])) # 2
```

## المزايا
- جمع، طرح، ضرب، قسمة
- رفع للأس (Power)
- جذر تربيعي
- باقي القسمة (Modulo)
- المتوسط الحسابي
- معالجة أخطاء ذكية
geonamescache 3.0.0
Geonames data for continents, cities and US states.
Requires Python: >=3.10
Keywords: counties, countries, fips, geo, geodata, geonames, iso-codes, states

# GeonamesCache

[![image](https://img.shields.io/pypi/v/geonamescache.svg)](https://pypi.python.org/pypi/geonamescache)

A Python library that provides functions to retrieve names, ISO and FIPS codes of continents, countries as well as US states and counties as Python dictionaries. The country and city datasets also include population and geographic data.

Geonames data is obtained from [GeoNames](http://www.geonames.org/).

## Installation

    pip install geonamescache

## Usage

A simple example:

    import geonamescache

    gc = geonamescache.GeonamesCache()
    print(gc.get_countries())

## Settings

### Cities dataset

When creating a `GeonamesCache` you can set the `min_city_population` parameter to either of 500, 1000, 5000 or the default 15000. The smaller the minimum population the more cities are included in the cities dataset.

## Methods

Currently geonamescache provides the following methods, that return dictionaries with the requested data:

* get\_continents()
* get\_countries()
* get\_us\_states()
* get\_cities()
* get\_countries\_by\_names()
* get\_us\_states\_by\_names()
* get\_cities\_by\_name(name)
* get\_us\_counties()

In addition you can search for cities by name.

* search\_cities(\'NAME\', case\_sensitive=True, contains\_search=True)

This function returns a list of city records that match the given `NAME`.

* By default the `alternatenames` attribute is searched for matches.
* By default the search is case insensitive, it can be made case sensitive by changing `case_sensitive` to True.
* By default the search is contains, it can be made exact equality by changing `contains_search` to False.

## Mappers

The mappers module provides function(s) to map data properties. Currently you can create a mapper that maps country properties, e. g. the `name` property to the `iso3` property, to do so you'd write the following code:

    from geonamescache.mappers import country
    mapper = country(from_key='name', to_key='iso3')

    iso3 = mapper('Spain') # iso3 is assigned ESP

## Contributing

Please write test(s) for any new feature. If you wish to build the data from scratch, run `make dl` and `make json`.