semvec/pypi-packages huggingface dataset:
data-whiz 0.0.2
this package can be used to calculate distance between two points in the curved surface
Requires Python: >=3.6


# Calculate the distance between points in curved surface

### Download the library

!pip install curved-surface-distance

### Importing the library

from curved_surface_distance import distance

### HSV_distance

- HSV_distance is used to Calculate the distance between the HSV color codes.

- H represents Hue ranges from 0 to 360, S represents Saturation and V represents Value(brightness) both ranges from 0 to 100. 
    syntax  -   distance.HSV_distance([H1,S1,V1],[H2,S2,V2])
    -
    example -   distance.HSV_distance([0,0,0],[360,100,100]) 
    
### distance

- distance is used to find the distance between two points or between two list of points in curved surface.
    
        1. This is to find distance between two list of points 
            
            syntax  -   distance.distance([p11,p12,p13],[p21,p22,p23])
            
            example -   distance.distance([0,0,0],[360,360,360])

        2. This is to find distance between two points in the curved surface. 
            
            syntax  -   distance.distance(p1,p2)
            
            example -   distance.distance(0,500)



## License

[MIT](https://choosealicense.com/licenses/mit/)
georetriever 0.1.1
Retrieve geological data for geothermal systems from coordinates in Python!
Keywords: python,geo,geological,heatflow,thermal,lithography,conductivity


## GeoRetriever 🌋🐕

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)


##### A Python package for array-based retrieval of geological data. In a second step (available in a future version), the data can be converted to localized thermal energy system suitability.

Based on the tools used in the great [atlite](https://github.com/PyPSA/atlite) package, GeoRetriever is supported by [dask](https://github.com/dask/dask) and [xarray](https://github.com/pydata/xarray) for parallelized requests of data chunks.
When completed, the package will be able to retrieve all data relevant the following thermal systems:

- Borehole Thermal Energy Storage (BTES)
- Aquifer Thermal Energy Storage (ATES)
- Shallow Ground Source Heat Pumps (CSHP)
- Water Source Heat Pumps (WSHP)
- Pit Thermal Energy Storage (PTES)
- Mine Thermal Energy Storage (MTES)

The library is under development with more features being added in the future. This is a promise - I need this for my PhD 🧗🏼.

| Feature | Data Source | Coverage | Implemented |
|---------|-------------|----------|-------------|
| Lithology | [Macrostrat](https://macrostrat.org/)| global | ✔️|
| Surface Temperature | [ERA5](https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5) | global | ✔️ |
| Soil Temperature | [ERA5](https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5) | global | ✔️ |
| Aquifer Presence |  | | ❌ |
| Soil Type |  | | ❌ |

### Installation

The package runs on `Python>=3.6` and is available from `pypi` via
```
pip install georetriever
```

Note that for the feauture `"temperature"`, the API to `ERA5` will be used, which requires registration and setting up of the CDS API key as [here](https://cds.climate.copernicus.eu/api-how-to).

### Example

The package works through the `GeoCutout` object. During its initialization, the  spatial and temporal scale of the data is defined. Coordinates are in `(lon, lat)`. The actual retrieval of data starts when the `prepare()`, which takes the features of interest are passed method is called.
For instance:
```
from georetriever import GeoCutout

x = slice(-1, 1)
y = slice(50, 52)
dx = 0.05
dy = 0.05
time = "2019-01-01"
dt = "h"

geocutout = GeoCutout(
    x=x,
    y=y,
    dx=dx,
    dy=dy,
    time=time,
    dt=dt,
)

geocutout.prepare(features=["temperature", "lithology"])

print(geocutout.data)
```

### Authors and Contact

__Lukas Franken__ - [lukas.franken@ed.ac.uk](lukas.franken@ed.ac.uk)
University of Edinburgh, Alan Turing Institute

Big thanks to the team at __TU Berlin__ for [atlite](https://github.com/pypsa/atlite), the package this library is leaning on.
Flask-Discord-Interactions 2.1.2
A Flask extension for Discord slash commands.
Requires Python: >=3.7

# Flask-Discord-Interactions

This is a Flask extension that lets you write Discord Application Commands using a decorator syntax similar to Flask's `@app.route()` or Discord.py's `@bot.command()`.

```
@discord.command()
def ping(ctx):
    "Respond with a friendly 'pong'!"
    return "Pong!"
```

Full documentation is available on [readthedocs](https://flask-discord-interactions.readthedocs.io/).
py-wica 1.0.3
A simple python API to access wica-http SSE.
Requires Python: >=3.8,<4.0

# Py-Wica
#### Table of Contents
- [Introduction](#introduction)
- [Installation](#installation)
- [Quick-start Guid](#quick-start-guide)
- [Documentation](#documentation)
- [Dependencies](#dependencies)
- [Contribute](#contribute)
- [Project Changes and Tagged Releases](#project-changes-and-tagged-releases)
- [Developer Notes](#developer-notes)
- [Contact](#contact)

# Introduction
Simple Python API for connecting to a wica-http server and streaming data.
Support for blocking and non blocking operation.


# Installation

# Quick-start Guide

# Documentation

# Dependencies

# Contribute

# Project Changes and Tagged Releases

# Developer Notes

# Contact