semvec/pypi-packages huggingface dataset:
sonar-client 0.0.5
Client library and CLI for sonarqube API

# Python Sonarqube Client

This library provide a programmatic interface to interact with SonarQube.
It exposes both a client class and a CLI.

* Fore more information, checkout [sonar-client documentation](https://sylvanld.gitlab.io/open-source/python-sonar-client)

## Installation

```bash
pip install sonar-client
```

## Example Usage

**Using python interface**

```python
from sonar_client import SonarClient

sonar_token = "fake-token"
sonar = SonarClient(sonar_token, sonar_url="https://sonarcloud.io")
projects = sonar.search_project(organization="myorg")
```

**Using CLI interface**

You can discover available CLI commands by using `--help` options.

```bash
$ sonar-cli --help
Usage: sonar-cli [OPTIONS] COMMAND [ARGS]...

  SonarQube CLI

Options:
  --token TEXT  Sonar access token
  --help        Show this message and exit.

Commands:
  project  Sonar project management
```

```bash
$ sonar-cli project create --help
Usage: sonar-cli project create [OPTIONS]

  Create sonarqube project

Options:
  --org TEXT    Sonar organization  [required]
  --key TEXT    Sonar project key  [required]
  --title TEXT  Sonar project title  [required]
  --help        Show this message and exit.
```
cyvincenty 1.0.7
Cython implementation of Vincenty distance.
Requires Python: >=3

# Cyvincenty

A fast Cython implementation of the Vincenty algorithm for calculating the distance in kilometers between 2 co-ordinates.

This module is heavily inspired by [uvincenty](https://github.com/vivescere/uvincenty) and [vincenty](https://github.com/maurycyp/vincenty). It is just as fast if not slightly faster than uvincenty which is a pure C Python extension despite being written in Python! (technically Cython).

## Installation

```bash
pip install cyvincenty
```

## Usage

```python
>> from cyvincenty import vincenty

>> boston = (42.3541165, -71.0693514)
>> newyork = (40.7791472, -73.9680804)

>> vincenty(*boston, *newyork)
```


## Benchmarks

Using ipython

```python
>> import cyvincenty
>> import uvincenty
>> import vincenty
>> import geopy.distance

>> boston = (42.3541165, -71.0693514)
>> newyork = (40.7791472, -73.9680804)

>> %timeit uvincenty.vincenty(*boston, *newyork)
744 ns ± 2.58 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)

>> %timeit cyvincenty.vincenty(*boston, *newyork)
736 ns ± 2.82 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)

>> %timeit vincenty.vincenty(boston, newyork)
10.2 µs ± 60.1 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)

>> %timeit geopy.distance.geodesic(boston, newyork)
191 µs ± 1.52 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
```