semvec/pypi-packages huggingface dataset:
tshistory-editor 0.8.2
Web tool to edit time series

TSHISTORY EDITOR
=================

This is a [tshistory][tshistory] plugin which provides a flask blueprint
to allow series edition.

[tshistory]: https://hg.sr.ht/~pythonian/tshistory

This provides a browser for time series, allowing online edition of
values.  If the [tshistory_formula][tshistory_formula] component is
installed, formula components will also be shown.

[tshistory_formula]: https://hg.sr.ht/~pythonian/tshistory_formula


Basic edition abilities:

![editor](editor.png)

Formula display:

![editor formula](editor_alias.png)
distributions-harsh 0.1
Gaussian and Binomial distributions

# distributions-harsh package

This is a simple distributions package for calculating Gaussian and Binomial distributions.

## Files

- Generaldistribution.py

Generic distribution class for calculating and visualizing a probability distribution.

- Gaussiandistribution.py

Gaussian distribution class for calculating and visualizing a Gaussian distribution.

- Binomialdistribution.py

Binomial distribution class for calculating and visualizing a Binomial distribution.

## Installation

`pip install distributions-harsh`
libqtum 0.1.1
Python library to work with QTUM Blockchain
Requires Python: >=3.7

# libqtum
[![GitHub license][license-image]][license-url]
[![PyPI Version][pypi-image]][pypi-url]
[![Build Status][build-image]][build-url]
[![Code Coverage][coverage-image]][coverage-url]
[![Code Quality][quality-image]][quality-url]
<!-- Badges -->
[license-image]: https://img.shields.io/github/license/ivanovart/libqtum?style=flat-square
[license-url]: https://github.com/ivanovart/libqtum/blob/master/LICENSE
[pypi-image]: https://img.shields.io/pypi/v/libqtum?style=flat-square
[pypi-url]: https://pypi.org/project/libqtum/
[build-image]: https://img.shields.io/travis/com/ivanovart/libqtum?style=flat-square
[build-url]: https://travis-ci.com/ivanovart/libqtum
[coverage-image]: https://img.shields.io/coveralls/github/ivanovart/libqtum?style=flat-square
[coverage-url]: https://coveralls.io/github/ivanovart/libqtum?branch=master
[quality-image]: https://img.shields.io/codeclimate/maintainability/ivanovart/libqtum?style=flat-square
[quality-url]: https://codeclimate.com/github/ivanovart/libqtum/maintainability


Python library to work with QTUM Blockchain
fill_enum 0.1.0
Decorator to automatically create Enum with filled values

# libqtum
[![GitHub license][license-image]][license-url]
[![PyPI Version][pypi-image]][pypi-url]

<!-- Badges -->
[license-image]: https://img.shields.io/github/license/ivanovart/fill_enum?style=flat-square
[license-url]: https://github.com/ivanovart/fill_enum/blob/master/LICENSE
[pypi-image]: https://img.shields.io/pypi/v/fill_enum?style=flat-square
[pypi-url]: https://pypi.org/project/fill_enum/

This Decorator returns an Enum, which contains all values in `values`.

Values, which the passed class not include, will be auto generated with
`prefix` + value as name if they are in the `values` list.

Args:
    values: An iterable list of values for the Enum members.
    enum_cls: The Enum class or a subclass of it.
    prefix: The prefix for the name of the auto generated Enum members.
    *args: Will be passed to the `enum_cls` constructor.
    **kwargs: Will be passed to the `enum_cls` constructor.

[Gitlab Snippet](https://gitlab.com/snippets/5976)

[Original Blog Post](https://bubblesorted.raab.link/content/automatically-fill-missing-values-python-enum#simple-table-of-contents-1)
img2img 0.2.0
Convert image format.

# img2img: Image to Image

🔮快速转化图片格式

[![](https://award.dovolopor.com?lt=language&rt=Py36&rbc=pink)](https://docs.python.org/3.6/)
[![](https://award.dovolopor.com?lt=PyPI&rt=0.1.2)](https://pypi.org/project/img2img/)
[![](https://award.dovolopor.com?lt=Ailln's&rt=idea&lbc=lightgray&rbc=red&ltc=red)](https://github.com/Ailln/award)

> **🚨更新日志：**
>
> - `v0.0.1` 初始化项目，添加在命令行使用 jpg2png 方法；
> - `v0.1.0` 添加常见的 6 种转化方法；
> - `v0.1.1` 修复版本错误问题；
> - `v0.1.2` 回保存图片的路径；
> - `v0.2.0` 支持命令行批量转化。

## 1 功能

1. 支持 **6 种**常见图片格式转化；
2. 支持在**命令行**调用；
3. 支持在[**网页上**](https://www.dovolopor.com/img2img)使用。

![](./src/img2img-site.png)
🔗[点我访问](https://www.dovolopor.com/img2img)

## 2 安装

### 2.1 使用 pip 安装

```shell
pip install img2img
```

### 2.2 从代码库安装

```shell
git clone https://github.com/Ailln/img2img.git
cd img2img
python setup.py install
```

## 3 使用

目前总共支持6种方法，如下：

1. jpg2png
2. png2jpg
3. jpg2ico
4. ico2jpg
5. png2ico
6. ico2png

下文中使用 `jpg2png` 作为演示，其他方法同理。

### 3.1 在代码中调用

```python
# 在文件首部引入包
import img2img

# 查看版本
img2img.__version__
# output: 0.2.0

img = img2img.Img2img()

# 默认输出路径和输入路径相同
img.convert("jpg2png", "./test.jpg")

# 支持手动修改输出路径
img.convert("jpg2png", "./test.jpg", "../new_test.png")
```

### 3.2 在命令行中使用

```bash
# 默认输出路径和输入路径相同
jpg2png ./test.jpg

# 支持手动修改输出路径
jpg2png ./test.jpg ../new_test.png

# 支持文件夹批量转化
jpg2png ./test/
```

## 4 版本支持

- 理论上支持 `Windows`、`MacOS`、`Ubuntu` 下的所有 `Python 3.6` 的版本。
- 实际上仅在 `Windows 10`、`MacOS 10.14`、`Ubuntu 16.04` 的 `Python 3.6.3` 上做过完整测试。
- 欢迎提交其他版本使用情况到 [Issues](https://github.com/Ailln/img2img/issues) 中，期待你的反馈。
- 如果你有 `Python 2` 的使用需求，可 Fork 代码自行修改。当然也欢迎提 PR，贡献自己代码给其他人。

## 5 协议

[![](https://award.dovolopor.com?lt=License&rt=MIT&rbc=green)](./LICENSE)

## 6 参考

- [如何发布自己的包到 pypi ？](https://www.v2ai.cn/python/2018/07/30/PY-1.html)
- [python 中的小陷阱](https://www.v2ai.cn/python/2019/01/01/PY-6.html)
leaderdata-sdk 0.0.1
LeaderData API SDK
Requires Python: >=3.7

# LeaderData API SDK

Python SDK для работы с API LeaderData.


## Установка

```console
pip install leaderdata-sdk
```

После этого необходимо получить файл `openapi.json`:

```console
python -m leaderdata update
```

API периодически меняется и файл `openapi.json` нужно обновлять для актулизации SDK.


## Конфигурация

И импортируемый модуль и интерфейс командной строки для запросов обращаются к API по
адресу `https://data.leader-id.ru`, этот адрес можно изменить переменными окружения
`DSN` и `SPEC_PATH`; где первая задает адрес хоста: проткол, домен, порт; а вторая
путь относительно хоста до `openapi.json`.


## Использование

Методы клиента соответствуют операциям API, и состоят из:

- имя метода – идентификатор операции;
- позиционный аргумент – может быть только один и используется для задания тела запроса;
- именованные аргументы - используются для передачи параметров строки запроса и
подстановки переменных в пути, где они необходимы; клиент SDK сам определит какие
аргументы чем являются.

Опциональность / обязательность аргументов можно определить из документации.

Идентификатор операции можно получить из [документации API LeaderData](https://data.leader-id.ru/api/redoc).
Для этого нужно выбрать необходимую операцию и обратить внимание на адресную строку, к
примеру ссылка документации на операцию по чтению коллекций будет такой:

```
https://data.leader-id.ru/api/redoc#operation/collections__list_collections
```

Где идентификатор операции это: `collections__list_collections`.

### Таймаут на выполнение запроса

По умолчанию равен 5 секундам. Переопределить можно именованным аргументом `_timeout`
при вызове метода API. Допускается как число (целое / с плавающей точкой) обозначающее
таймут на весь запрос, так и экземпляр класса `httpx.Timeout`, которым можно задать
таймауты на каждый этап запроса, подробнее об этом объекте и типах таймаутов
[по ссылке](https://www.python-httpx.org/advanced/#fine-tuning-the-configuration)


### Примеры

Инициализация клиента

```python
from leaderdata.api import Client


client = Client(client_id='APP_ID', client_secret='APP_SECRET')
```

Чтение списка принадлежащих приложению коллекций:

```python
for collection in client.collections__list_collections(is_own=True):
    print(f'collection id: {collection.id}, name: {collection.name}')
```

Создание новой коллекции:

```python
collection = client.collections__create_collection({
  'access_type': 'private',
  'name': 'Very simple collection',
  'description': 'From SDK README.md'
})

print(f'new collection id: {collection.id}')
```

Чтение созданной только что коллекции:

```python
actual_collection_data = client.collections__read_collection(
  collection_id=collection.id
)

print(f'collection current name: {actual_collection_data.name}')
```
gaussian-distributions-kueen 0.1
Gaussian and Binomial distributions

# distributions-kueen package

This is a simple distributions package for calculating Gaussian and Binomial distributions.

## Files

- Generaldistribution.py
Generic distribution class for calculating and visualizing a probability distribution.

- Gaussiandistribution.py
Gaussian distribution class for calculating and visualizing a Gaussian distribution.

- Binomialdistribution.py
Binomial distribution class for calculating and visualizing a Binomial distribution.

## Installation

`pip install distributions-kueen`
ehpp 0.1
EHPP is a preprocessor for EspHome (formely esphomeyaml)
Requires Python: >=3.0, <4
Keywords: home,automation,esphome,esphomeyaml,preprocessor,home-assistant

EHPP is a preprocessor for [EspHome](https://esphomelib.com/esphomeyaml/) that simplifies the management of configuration files when you have multiple devices.

(more to come...)
django-project-heroku-template 0.1.0
A Django project template ready for heroku
Requires Python: >=3.6,<4.0

==============================
django_project_heroku_template
==============================

*A Django project template ready for heroku* + some useful tools

It is a template for working in a Django project with some useful tools, using

- Python >=3.6 (because we love ``f-strings``)
- Django >=3.0

:Usage: Just clone this repo or install via ``pip`` and start your own app

``django-admin startapp my_django_app``


.. contents:: Tools

IDE
---

- Visual Studio Code (vscode) in any of its flavour: code, vscodium, visual-studio-code, etc.

Configuration in ``.vscode/settings.json``.

Packaging and dependency management
-----------------------------------

- `poetry <https://python-poetry.org/>`_

Testing
-------

- `pytest <https://docs.pytest.org/>`_
- `pytest-django <https://pytest-django.readthedocs.io/>`_

Configuration in ``pytest.ini``, ``.vscode/launch.json`` and  ``.vscode/settings.json``.

Formatting code
---------------

- `black <https://black.readthedocs.io/>`_

Configuration in ``pyproject.toml``.

Linting
-------

- `flake8 <https://flake8.pycqa.org/>`_

Configuration in ``.vscode/settings.json``.

Python Shell
------------

- `ipython <https://ipython.org/>`_

Django Extensions
-----------------

- `django_extensions <https://django-extensions.readthedocs.io/>`_

graph data model
^^^^^^^^^^^^^^^^

- `pygraphviz <https://pygraphviz.github.io/>`_

``python manage.py graph_models auth -o auth_models.png``

Maybe replaced by `pydot <https://pypi.org/project/pydot/>`_.

Deployment
----------

- `heroku <https://www.heroku.com/>`_

``heroku create <<django-app-name>>``

``git push heroku master``

``heroku run python manage.py migrate``

``heroku run python manage.py createsuperuser``

``heroku config:set DJANGO_SECRET_KEY='<<your-secret-key>>'``

Get one here: `Django Secret Key Generator <https://www.miniwebtool.com/django-secret-key-generator/>`_

``heroku config:set DJANGO_DEBUG='False'``
pywebcapture 0.0.3
A package that allows users to capture full-page screenshots of websites using Selenium and Chrome webdriver.
Requires Python: >=3.8

# Pywebcapture
A package that allows users to capture full-page screenshots of websites using Selenium and Chrome webdriver.

Tested with Python version 3.8.3

## Installation

1. Download the latest version of [Chrome webdriver](http://chromedriver.chromium.org/downloads)
2. Add chrome webdriver path to your system PATH (its also possible to pass the absolute path of your driver to the Driver instance)
2. Run ```pip install pywebcapture```

## Basic Usage

**Import the modules:**

```python
from pywebcapture import loader, driver
```

**Use the CSVLoader to load your csv file containing the urls and optional file names:**

Options:
* input_filepath - The absolute path to your csv file (str)
* has_header - Whether your csv has a header row or now (bool)
* uri_column - The column that contains the uri's, can use either column name (str) or the index position (int)
* filename_column - The column that contains the desired file names (str), can be set to None, where the driver will use the uri netloc as the filename

```python
csv_file = loader.CSVLoader("example.csv", True, 3, None)
```

**Call the get_uri_dict() method from the CSVLoader instance, this parses the CSV into a Python dictionary:**

```python
uri_dict = csv_file.get_uri_dict()
```

**Create instance of the web driver:**

Options:
* driver_path - This is the absolute path to the chrome webdriver, if None or "chromedriver" it will attempt to search %PATH
* output_path - This is the output path that you want to save screen shots at (str)
* delay - This is the delay in seconds between each page request, minimum is 2 seconds, please crawl pages respectfully :)
* uri_dict - The Python dictionary containing your file names and uri's

```python
d = driver.Driver("path/to/chrome/webdriver", None, 3, uri_dict)
```

**Run the driver, this will loop through all uri's, get the maximum scrollheight and then take a screenshot**

```python
d.run()
```
esphomepreprocessor 0.5
EspHomePreprocessor is a preprocessor for EspHome (formely esphomeyaml)
Requires Python: >=3.0, <4
Keywords: home,automation,esphome,esphomeyaml,preprocessor,home-assistant

EspHomePreprocessor is a preprocessor for [EspHome](https://esphomelib.com/esphomeyaml/) (formely esphomeyaml) that simplifies the management of configuration files when you have multiple devices.

(more to come...)