semvec/pypi-packages huggingface dataset:
py-baselinker 0.0.2
Python library to communication with baselinker
Requires Python: >=3.8

# Python BaseLinker API

py-baselinker is a Python client library for accessing the [BaseLinker](https://baselinker.com/) service.

Currently, **library is BETA version** and testing only on Python version 3.8.

Library not implement each of method from BaseLinker API [Documentation](https://api.baselinker.com/) yet.

## Install

```shell script
pip install py-baselinker
```

## Versioning 

Versioning is base on [semver](https://semver.org/). 
The new version is release by a new tag.

## Licence

This library is distributed under the BSD 3 Licence, see LICENSE for more information.

## Contributing

Author of this library is [Mikołaj Jeziorny](https://mikolaj-jeziorny.pl).

If you want to help with development it - **fork me!**
AirflowDocZh 2020.9.20.0
Airflow 中文文档
Requires Python: >=3.6

# Airflow 中文文档

![Airflow](img/logo.png)

> 原文：[Apache Airflow Documentation](https://airflow.readthedocs.io/en/stable/)
>
> 协议：[CC BY-NC-SA 4.0](http://creativecommons.org/licenses/by-nc-sa/4.0/)
>
> 欢迎任何人参与和完善：一个人可以走的很快，但是一群人却可以走的更远。

* [在线阅读](https://airflow.apachecn.org)
* [ApacheCN 大数据交流群 152622464](http://shang.qq.com/wpa/qunwpa?idkey=30e5f1123a79867570f665aa3a483ca404b1c3f77737bc01ec520ed5f078ddef)
* [ApacheCN 学习资源](http://www.apachecn.org/)

## 负责人

* [@ImPerat0R\_](https://github.com/tssujt)

## 翻译进度

* Airflow 1.10.2 文档已翻译完成

## 贡献指南

[请见这里](CONTRIBUTING.md)

> 请您勇敢地去翻译和改进翻译。虽然我们追求卓越，但我们并不要求您做到十全十美，因此请不要担心因为翻译上犯错——在大部分情况下，我们的服务器已经记录所有的翻译，因此您不必担心会因为您的失误遭到无法挽回的破坏。（改编自维基百科）

## 赞助我们

![Donate](http://data.apachecn.org/img/about/donate.jpg)
samternary 0.0.3
package to plot ternary phase diagrams
Requires Python: >=3.3

# samternary

`samternary` allows users to generate a ternary diagram, which is a visualisation useful for 3D data sets, where two of the dimensions are constrained an isoceles triangle.

For instance, consider a data set (x,y,z). For ternary diagrams to be useful, the domain D in the xy plane should be restricted to D:=\{x>0,y>0,x+y <= 1\}.

If user data has this property (or can be re-scaled to have this property), then this package could be useful.

See the examples folder for a list of examples on how to use this package.

![A boring 2D plot converted to an exciting ternary plot!](/examples/example_meshdata.png)
superdata 0.1.1
A super package that imports datascience packages to the namespace
Requires Python: >=3

# SuperData

A small python package to import common Data science packages to the namespace.
That is, no need to `import numpy as np` in your code.

For example:
```
1 from superdata import *
2 a=np.array([1,2,3])
3 plt.plot(a)
```
For now, only covers:
```
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import matplotlib as mpl
```

## installation

Easy installation using pip: https://pypi.org/project/superdata/0.1/
jinete 0.1.0
High Performance solving suite for the Pickup and Delivery Problem and its related extensions.

# jinete

<img align="right" width="15%" src="https://raw.githubusercontent.com/garciparedes/jinete/master/res/images/jinete.svg?sanitize=true" alt="jinete">

[![PyPI](https://img.shields.io/pypi/v/jinete.svg)](https://pypi.org/project/jinete)
[![Documentation](https://img.shields.io/website?down_color=red&down_message=broken&label=docs&up_color=success&up_message=passing&url=https%3A%2F%2Fgarciparedes.me%2Fjinete%2F)](https://garciparedes.me/jinete)
[![Travis (.org) branch](https://img.shields.io/travis/garciparedes/jinete/master.svg)](https://travis-ci.org/garciparedes/jinete/branches)
[![Codecov](https://img.shields.io/codecov/c/github/garciparedes/jinete.svg)](https://codecov.io/gh/garciparedes/jinete)
[![GitHub](https://img.shields.io/github/license/garciparedes/jinete.svg)](https://github.com/garciparedes/jinete/blob/master/LICENSE)
[![GitHub stars](https://img.shields.io/github/stars/garciparedes/jinete.svg)](https://github.com/garciparedes/jinete)

## Description 

High Performance solving suite for the Pickup and Delivery Problem and its related extensions. 

*IMPORTANT*: This project is still under its early stage of development. So it's not recommended yet to use on real world projects. 

This library has been inspired (and created) by a Final Degree Project, which you can read at: https://github.com/garciparedes/tfg-pickup-and-delivery


## Getting Started

### Prerequisites
* `python>=3.7`

### Installation
```bash
pip install jinete
```

Here is a simple example about how to run `jinete` to solve a HashCode 2018 Online Qualification instance. 
```python
import jinete as jit

file_path = './res/datasets/hashcode/a_example.in'

solver = jit.Solver(
    loader=jit.FileLoader,
    loader_kwargs={
        'file_path': file_path,
        'formatter_cls': jit.HashCodeLoaderFormatter
    },
    algorithm=jit.InsertionAlgorithm,
)
result = solver.solve()
# ...

```

## Documentation
You can find the documentation at: https://garciparedes.me/jinete


## Development

First of all, you need to create a `virtualenv`:

```bash
python -m venv venv
source venv/bin/activate
```

Then install the library and all its extra dependencies (with the `all` option):

```bash
pip intall -e .[all]
```

To run code style checks you can simply type:
```bash
flake8
```

To perform the tests with coverage you can need to type:

```bash
coverage run -m unittest discover tests
```

## LICENSE
This project is licensed under [MIT](LICENSE) license.