semvec/pypi-packages huggingface dataset:
nucleus-chat 0.4.0
nucleus is AI tools assistant in your terminal for Bioinformaticians
Requires Python: <3.13,>=3.9
Keywords: egg, bacon, sausage, tomatoes, Lobster Thermidor

## Nucleus: A Tool for Bioinformaticians. 

Just as software developers have Visual Studio Code, bioinformaticians now have Nucleus.

Nucleus is designed to simplify bioinformatics workflows by integrating powerful language models with essential bioinformatics tools. 

![Descriptive Alt Text](https://pratikkatte.github.io/nucleus-bio/assets/demo.gif)

## Installation
```
pip install nucleus-chat
```

## Getting Started

```
# Navigate to your desired project directory. 
cd /to/your/project

# Nucleus currently supports OpenAI models.

# Use OpenAI 4o on your files
nucleus --openai-api-key your-key-goes-here

```

Refer to usage [documentation](https://pratikkatte.github.io/nucleus-bio/docs/Usage) for more details.

## Features
- Ask for queries related to bioinformatic tools and commands. 

## Upcoming Features
- Integration of BioWASM tools to eliminate the need for local installation of bioinformatics software.
- Visualizae bioinformatics file formats.
- Search and download bioinformatics datasets directly.

<!-- ## Kind words from users -->
arxivsummary 0.3
arxivsummary - Arxiv summary report generator. 

# arxivsummary - Generate summary reports from arxiv

See CONTRIBUTING.md for build instructions, or install from PyPI with:

```
python -m pip install arxivsummary
```

Use `arxivsummary -h` for help.

For an example report, see https://github.com/gramster/arxivsummary/blob/main/example.md

The example was generated with:

    python -m arxivsummary report -T DBG -t ollama -v

using ollama running locally with the vanilj/Phi-4 model.

The following topics are supported, and expand to the terms shown:

    "ML": ["machine learning", "deep learning", "natural language processing"],
    "CV": ["computer vision", "image processing", "object detection"],
    "SE": ["software engineering", "programming languages", "software testing"],
    "DS": ["data science", "big data", "data visualization"],
    "DB": ["database systems", "data management", "data mining"],
    "AI": ["artificial intelligence", "expert systems", "knowledge representation"],
    "HCI": ["human-computer interaction", "user experience", "user interface design"],
    "CC": ["cloud computing", "distributed systems", "networking"],
    "SEC": ["cybersecurity", "information security", "cryptography"],
    "WEB": ["web development", "web design", "web applications"],
    "IOT": ["internet of things", "smart devices", "sensor networks"],
    "DBG": ["debugging", "fault localization", "breakpoints", "stack trace"],
    "TST": ["testing", "test automation", "test case generation", "test coverage"],

You can mix and match these; e.g.:

    python -m arxivsummary report -T WEB,IOT,networking -t ollama -v

## Development

This project uses `flit`. First install `flit`:

```
python -m pip install flit
```

Then to build:

```
flit build
```

To install locally:

```
flit install
```

To publish to PyPI:

```
flit publish
```

## Version History

0.1 Initial release
shelly-control 0.3
A python package for Shelly Cloud API. Shelly is devoted to the development of innovative IoT solutions and products.
Requires Python: >=3.8
Keywords: Shelly, Shelly plug, Shelly cloud api, shelly cloud, Shelly access control, Shelly python library

# Shelly Easy Smart Home Automation


SHELLY: The go-to access control for smart homes.

This Python library provides convenient access to the Shelly cloud API, allowing you to manage your relays, rollers and lights.


[Shelly Shop](https://www.shelly.com/en/products/shop)<br>
Request Feature/Suggestion: https://forms.gle/efGD5DuTpWsX96GG7

# Download stats

[![Downloads](https://static.pepy.tech/badge/shelly-control)](https://pepy.tech/project/shelly-control)

## Installation
```console
pip install shelly_control
```
Shelly supports Python 3+.

## Usage
#### Default
```python
import shelly_control
```

#### Authentication

Before making requests, you need to authenticate using your Shelly API key. Initialize the `Connect` class with your API key:

```python
from shelly_control import Connect

base_url = "Your Cloud Server Address"
api_key = "Your Authorization cloud key"
sh = Connect(base_url,api_key)
```
OR
```python
import shelly_control 

base_url = "Your Cloud Server Address"
api_key = "Your Authorization cloud key"
sh = shelly_control.Connect(base_url,api_key)
```
Get Key & Server address from here [Shelly Control Cloud Dashboard](https://control.shelly.cloud/#/settings/user)

### Relay
#### Fetch Devices
```python
# Fetch device status
sh.get_device('device_id')

```

#### Control Devices
```python
# Control device
sh.control_device(channel , 'on'/'off' , device_id)

```
#### Bulk Control Devices
```python
# Bulk Control device
sh.bulk_control_relays('devices')

# Parameters:
#        - devices (list of dict): List of devices to control, each device should be a dictionary with keys:
#            - "id" (int): ID of the device.
#            - "channel" (int): Index of the relay or switch component.
```

### Rollers
#### Control Roller Direction
```python
# Control Roller
sh.control_roller_direction(direction , device_id)

```

#### Control Roller Position
```python
# Control Roller
sh.control_roller_position(position , device_id)

```

#### Bulk Control Roller
```python
# Bulk Control Roller
sh.bulk_control_rollers(device_id)

```

### Lights
#### Control Lights
```python
# Bulk Control Roller
sh.control_light(turn=None , white=None , red=None , green=None , blue=None , gain=None , device_id=None)

```
Wordpress 1.2
A Python library for interacting with the WordPress REST API
Requires Python: >=3.8
Keywords: WordPress, WordPress API, WordPress SDK, REST API, wp python, WP

# Wordpress Python Library

The `wordpress` Python library provides a simple interface to interact with the WordPress REST API. It allows you to manage various aspects of your WordPress site, including pages, posts, categories, media, users, and comments.

## Download stats
[![Downloads](https://static.pepy.tech/badge/Wordpress)](https://pepy.tech/project/Wordpress)
## Features

- Fetch, create, update, and delete `pages`
- Fetch, create, update, and delete `posts`
- Fetch, create, update, and delete `categories`
- Upload and manage `media`
- Fetch and manage `users`
- Fetch and manage `comments`

## Installation

You can install the library using pip:

```bash
pip install wordpress
```

## Usage
Importing the Library
```python
import wordpress
```

## Connecting to WordPress
To use the library, create an instance of the wordpress.Connect class by providing the base URL of your WordPress site and authentication details (username and password).

```python
site_url = "https://yourwordpresssite.com"
username = "yourusername"
password = "your_application_password" #read documentation https://wordpress.com/support/security/two-step-authentication/application-specific-passwords/
wp = wordpress.Connect(site_url, username, password)
```

## Pages
### Fetch All Pages
```python
wp.page.fetch_all_pages()
```
### Create a New Page
```python
wp.page.create_page(title="About Us", content="This is the About Us page.")
```
### Fetch a Specific Page
```python
wp.page.fetch_page(page_id=123)
```
### Delete a Page
```python
wp.page.delete_page(page_id=123)
```
## Posts
### Fetch All Posts
```python
wp.post.fetch_all_posts()
```
### Create a New Post
```python
wp.post.create_post(title="New Blog Post", content="This is a new blog post.")
```
### Fetch a Specific Post
```python
wp.post.fetch_post(post_id=123)
```
### Delete a Post
```python
wp.post.delete_post(post_id=123)
```
### Categories
### Fetch All Categories
```python
wp.category.fetch_all_categories()
```
### Create a New Category
```python
wp.category.create_category(name="New Category")
```
### Fetch a Specific Category
```python
wp.category.fetch_category(category_id=123)
```
### Delete a Category
```python
wp.category.delete_category(category_id=123)
```
## Media
### Upload Media
```python
wp.media.upload_media(file_path="path/to/your/image.jpg")
```
### Fetch All Media
```python
wp.media.fetch_all_media()
```
### Fetch a Specific Media Item
```python
wp.media.fetch_media(media_id=123)
```
### Delete Media
```python
wp.media.delete_media(media_id=123)
```
## Users
### Fetch All Users
```python
wp.user.fetch_all_users()
```
### Fetch a Specific User
```python
wp.user.fetch_user(user_id=123)
```
## Comments
### Fetch All Comments
```python
wp.comment.fetch_all_comments()
```
### Fetch a Specific Comment
```python
wp.comment.fetch_comment(comment_id=123)
```
dopy-cli 0.2.0
A python preprocessor that enables do..end syntax replacing strict indentation
Requires Python: <4.0,>=3.10

# dopy

An experimental Python preprocessor that enables do..end syntax in place of strict indentation

## Requirements

- `python 3.10+`
- `pip`

## Installation

```bash
pip install dopy-cli
```

## Features

- Converts ruby/lua style `do..end` blocks into indented blocks
- Maintains python's semantics
- Preserves string literals and comments
- Processes .dopy files into pep8 compliant .py files (maintaining the dir structure)
- Recursively transpiles imports

## Usage

### Programmatic

```python
from dopy.core import Dopy
dopy = Dopy()

source = '''
def hello_world() do
  print("Hello")
end
hello_world()
'''

processed = dopy.preprocess(source)
exec(processed, namespace={})
```

More examples in the [examples](./examples/) dir

### cli

`dopy my_module.dopy`

Will use the current active python interpreter, can be overridden with `PYTHON_PATH` env var

## Flags

`-h --help`: Print help text

`-k --keep`: Keep transpiled python files in place (will overwrite)

`-d --dry-run`: Print the transpiled python code to console and exit

`-c --check`: Check dopy syntax without transpiling

## Syntax Rules

- Make sure the `do` keyword is on the same line as rest of the block declaration,
- `end` should be on its own line
- all imports at the top of the module
- must create a `__init__.py` file in dirs so that the transpiled python modules can be recognised

## Acknowledgements

This project is hugely inspired by [`mathialo/bython`](https://github.com/mathialo/bython)

### Todo

- [ ] support type hints
- [ ] `py2dopy` script
- [ ] function level imports
- [ ] nvim-treesitter support

### License

See [LICENSE](./LICENSE)
minimax-platform-video 0.0.4
minimax 开放平台视频生成插件
Requires Python: <3.12,>=3.10

#### 开放平台视频生成批量操作

#### 项目简介 

本项目是基于开放平台的视频生成批量操作，主要包括视频生成功能，通过本demo你可以快速生成多个一致性高度相同的视频备选素材。

提交包含 input_text, image_path 字段的 level_contexts.xlsx 文件

**input_text**：文本内容

**image_path**: 图片绝对路径

输出结果为视频任务 id 的 csv文件，
#### 快速尝试

#### 使用
 
- 1、安装依赖 python 需要3.10以上版本
```shell
pip install minimax-platform-video -U
```

- 2、设置环境变量
我们设定好 API Key。
```shell
export API_KEY="开放平台key" 
```

- 3、准备数据

基础表格里需要准备的数据包含了 **input_text**, **image_path** 字段

**input_text** 为生成提示词，用于控制镜头

**image_path** 为起始帧的图片，这个图片可以不存在，使用 request_img 命令参数控制是否必须采用起始帧，默认必须存在


- 4、运行

> 启动目录为项目根目录

```shell
python -m minimax_platform_video.start --input_excel C:\\Users\\Administrator\\Desktop\\data\\level_contexts.xlsx --output_path C:\\Users\\Administrator\\Desktop\\data\\
```

> 参数说明
> 
> **input_excel**：为包含input_text,image_path字段的的level_contexts.xlsx文件
> 
> **output_path**：为输出文件路径，生成 video_report.csv文件
> 
> 可以断点续传，会自动跳过已经生成的任务, 
> 
> 根据需要配置线程
> 
> **prompt_num_threads**: 提示词线程数,默认2
> 
> **video_num_threads**: 视频生成线程数,默认1
> 

- 5、获取任务结果 

> 启动目录为项目根目录
```shell
python -m minimax_platform_video.video_pull --task_video_csv C:\\Users\\Administrator\\Desktop\\data\\video_report.csv --output_path C:\\Users\\Administrator\\Desktop\\data\\
```
> 参数说明
> 
> **input_excel**： video_report.csv文件
> 
> **output_path**：为输出文件路径 生成video_pull_report.csv文件
> 
> 会自动跳过已经获取的任务, 删除根目录**cache_data/VideoPullGenerator**的文件可以重新获取
> 
> 根据需要配置线程
> 
> **num_threads**: 线程数,默认2
> 


- 6、下载视频 

> 启动目录为项目根目录
```shell
python -m minimax_platform_video.download_video  --csv_file_path  C:\\Users\\renrui\\Desktop\\data\\video_pull_report.csv --output_path C:\\Users\\renrui\\Desktop\\data\\

```
> 参数说明
> 
> **csv_file_path**： video_pull_report.csv文件
> 
> **output_path**：为输出文件路径 视频下载目录
>   
>