semvec/pypi-packages huggingface dataset:
super-tool 1.2
一个有着许多功能的Python工具库
Requires Python: >=3.10

# super-tool

## super-tool - Python多功能工具库

[![Python Version](https://img.shields.io/badge/python-3.8%2B-blue)](https://www.python.org/)

**super-tool** 是一个集成常用功能的Python工具库。

## 📦 安装

### 使用pip
bash
```pip install super-tool
buscard 0.3.0
A Business Card Management App built with CustomTkinter
Requires Python: >=3.12

# 🧾 BusCard

A lightweight, modern Business Card Manager built with Python and CustomTkinter — perfect for managing professional contact info with a sleek interface.

## 📸 Screenshot

![BusCard Screenshot](buscard/buscardM.png)

---

## ✨ Features

- 📇 Add, view, edit, and delete business card entries
- 🖼️ Store names, phone numbers, emails, and photos
- 🖌️ Beautiful CustomTkinter-based GUI
- 🔐 Configuration via `.env` using `python-decouple`
- 🛢️ Local SQLite database included

---

## 🚀 Installation

Install directly from PyPI:

```bash
pip install buscard

```
inventaire-python-api 0.1.7
Wrappers for the Inventaire API
Requires Python: >=3.10

# Inventaire

![PyPI - Python Version](https://img.shields.io/pypi/pyversions/inventaire-python-api)
![PyPI](https://img.shields.io/pypi/v/inventaire-python-api)
![PyPI - License](https://img.shields.io/pypi/l/inventaire-python-api)

### Project description

This package makes it easy to use Inventaire with Python. You can write simple scripts to manage your library and keep your database up to date automatically.

For more detailed information please see [the project's documentation](https://inventaire-python-api.readthedocs.io/en/latest/index.html).

To be done:

- More usage examples
- Increase the tests coverage
- Convenient docs
- Implementing higher level wrappers

## Installation

```
pip install inventaire-python-api
```

## Authentication

Inventaire auth requires either the username or password or a cookie ([see the how-to](https://api.inventaire.io/#!/Auth/post_auth_action_login))

```python
from inventaire import Inventaire

auth = {"username": "demo-user", "password": "abcde1-fghij2-klmno3"}
inv = Inventaire.server_api(**auth)
```

## Usage

Then it is possible to interact with the low-level api wrappers:

```python
# Get information about the authenticated user
auth_data = inv.api.user.get_authentified_user()

# Get the last public items modified
last_items = inv.api.items.get_last_public_items()

# Get shelves information based on their ids
shelves_ids = inv.api.shelves.get_shelves_by_ids(
    ["b30491238f4a79a466c27418a2280c12", "0c490f3bc5ea9ab450bc24ff55151814"]
)

# Create a new shelf
new_shelf = inv.api.shelves.create_shelf(
    name="demo", listing="private", description="something"

# Get entity details and if it doesn't exist, try to create it
uri_details = inv.api.entities.get_entities_by_uris(
    uris="isbn:9789735087180",
    autocreate=True,
    refresh=True,
)
```

Each Inventaire API wrapper group could be accessed as a property:

```python
iapi = inv.api

# Items
items = iapi.items

# Shelves
shelves = iapi.shelves
```

## License

This library is licensed under the Apache 2.0 License.

## Links

[Inventaire docs](https://api.inventaire.io/)
teste_lr_eagle_issue_7_23062025 0.0.1
Implements LangGraph based agents following the CoALA framework.
Requires Python: <3.14,>=3.10

<p align="center">
    <img src="./assets/EAGLE.jpg" alt="EAGLE Logo" />
</p>

# Enhanced Agents for Generative Language Excellence

## Do que se trata este projeto?

Esse projeto implementa a visão do [framework CoALA (Cognitive Architectures for Language Agents)](https://github.com/ysymyth/awesome-language-agents) no contexto do [LangGraph](https://www.langchain.com/langgraph), com agentes, ferramentas e estratégias de integração multiagentes para servirem de exemplo para novas implementações.

## Instalação

### Pré-requisitos (considerando o uso do Conda para gerenciar o ambiente python)

- [Miniforge 3](https://conda-forge.org/download/): O Miniforge é uma distribuição mínima do conda, que é um gerenciador de pacotes e ambientes virtuais. Ele será usado para criar um ambiente virtual para instalar as dependências do projeto.

### Criando o ambiente virtual

1. Uma vez instalado o Conda, abra o terminal e digite o seguinte comando:

```bash
conda create -n eagle python=3.10
```

2. Após a criação do ambiente, ative-o com o comando:

```bash
conda activate eagle
```

3. Instale a versão mais recente do Poetry com o comando:

```bash
pip install poetry==1.8.5
```

1. Instale as dependências do projeto com o comando:

```bash
poetry install
```

## Testes
Para executar os testes, execute os seguintes passos:

1. Ative o ambiente virtual com o comando:

```bash
conda activate eagle
```

2. Copie o arquivo `sample.test.env` para `.test.env` e preencha as variáveis de ambiente com as informações necessárias para o seu amnbiente de testes.

```bash
cp sample.test.env .test.env
```

### Ponto de Atenção

Os testes e exemplos dos notebooks estão baseados nos modelos `AzureChatOpenAI` para os LLMs e `AzureOpenAIEmbeddings` para os embeddings. Caso seja necessário utilizar outros nomes de modelos, tipos ou ajustar as relações com as variáveis de ambiente, essas alterações podem ser feitas na pasta [`tests/models`](tests/models).

## Exemplos de uso das funcionalidades

A pasta `notebooks` contém exemplos de uso das ferramentas. Para executar os exemplos:

1. Ative o ambiente virtual com o comando:

```bash
conda activate eagle
```

2. Ative a extensão de widgets do jupyter com o comando:

```bash
jupyter nbextension enable --py widgetsnbextension
```

3. Ative o jupyter lab com o comando:

```bash
jupyter lab
```

4. Abra o browser e execute os notebooks da pasta `notebooks`.
pandas-render 0.4.0
A pandas extension for rendering DataFrames
Requires Python: >=3.9

<p align="center">
  <img src="https://raw.githubusercontent.com/nok/pandas-render/refs/heads/main/assets/pandas-render.png" alt="pandas-render" height=130>
</p>

<h1 align="center">pandas-render</h1>

<p align="center">Render <a href="https://github.com/pandas-dev/pandas" target="_pandas">pandas</a> or <a href="https://github.com/pola-rs/polars" target="_polars">polars</a> DataFrames and Series as HTML tables with flexibility for formatting and styling.</p>

<div align="center">

![GitHub Repo stars](https://img.shields.io/github/stars/nok/pandas-render)
[![Ko-fi](https://img.shields.io/badge/Ko--fi-FF5E5B?logo=ko-fi&logoColor=white)](https://ko-fi.com/nok)

</div>


## Installation

```bash
pip install "pandas-render[pandas]"
```

```bash
pip install "pandas-render[polars]"
```


## Usage

This is a simple example that demonstrates the basic functionality. The column names are used to match individual [Jinja2](https://github.com/pallets/jinja) templates. And `{{ content }}` is the placeholder for the content of the original cell.

```python
from pandas_render import pandas as pd

df = pd.DataFrame(
    [
        dict(name="Alice", age=25, hobbies=["coding"]),
        dict(name="Bob", age=30, hobbies=["reading", "hiking"]),
    ]
)

df.render(
    templates=dict(
        name="<strong>{{ content }}</strong>",
        age="{{ content }} years old",
        hobbies="<em>{{ content|join(', ') }}</em>",
    ),
    table_column_names=["Name", "Age", "Hobbies"],
)
```

The result is a rendered dataframe:

<table class="dataframe"><thead><tr><th>Name</th><th>Age</th><th>Hobbies</th></tr></thead><tbody><tr><td><strong>Alice</strong></td><td>25 years old</td><td><em>coding</em></td></tr><tr><td><strong>Bob</strong></td><td>30 years old</td><td><em>reading, hiking</em></td></tr></tbody></table>


## Examples

Exciting and more powerful features can be explored and learned in the [Getting Started](examples/01_getting_started.ipynb) notebook.

List of all notebooks with examples:

- [Getting Started](examples/01_getting_started.ipynb) ✨
- [Components](examples/02_components.ipynb)


## Support

Do you like this project? Fuel it with a ☕ coffee on [Ko-fi](https://ko-fi.com/nok). Every little bit helps and means a lot!


## Contributing

We encourage you to contribute to this project! Please check out the [contributing guidelines](CONTRIBUTING.md) about how to proceed.


## License

This package is Open Source Software released under the [BSD-3-Clause](LICENSE) license.
ksd-metric 0.2.0
Kernel Stein Discrepancy
Requires Python: >=3.10

<p align="center">
  <img src="assets/logo.svg" alt="ksd-metric logo" width="300"/>
</p>

[![PyPI version](https://img.shields.io/pypi/v/ksd-metric.svg)](https://pypi.org/project/ksd-metric/)

<p align="center">
  A lightweight library for computing Kernel Stein Discrepancy (KSD) with JAX support
</p>

## Install

### Pypi

```{bash}
pip install ksd-metric
```

### Build from Source

```{bash}
# Install uv first
uv python install 3.10
uv sync
uv pip install .
```

## Examples

[Quick Start](https://congyewang.github.io/ksd/examples/auto.html)

[Customized Using Interface](https://congyewang.github.io/ksd/examples/custom.html)
method-flowchart 0.1.0
Generate Mermaid flowcharts from Python methods
Keywords: mermaid flowchart ast code analysis documentation

# Method Flowchart

Generate Mermaid flowcharts from Python methods or class methods via a command-line interface.

## Installation

Install the package (from source):

```bash
pip install .
```

## Usage (CLI)

After installation, use the CLI tool `method-flowchart`:

```bash
method-flowchart <python_file> <function_or_Class.method> [-o output_file]
```

- `<python_file>`: Path to the Python file containing the function or class method you want to analyze.
- `<function_or_Class.method>`: Name of the function (e.g., `my_function`) or class method (e.g., `MyClass.my_method`).
- `-o, --output`: (Optional) Output file for the Mermaid diagram. Defaults to `<function_or_Class.method>_flow.mmd`.

### Example

Suppose you have a file `example.py`:

```python
def foo():
    bar()
    print("Hello")

def bar():
    pass
```

To generate a flowchart for `foo`:

```bash
method-flowchart example.py foo -o foo_flow.mmd
```

To generate a flowchart for a class method:

```bash
method-flowchart example.py MyClass.my_method -o my_method_flow.mmd
```

The output will be a Mermaid diagram file you can visualize with Mermaid tools.

## Notes
- The CLI dynamically imports the specified file, so ensure it is importable and does not have side effects on import.
- The decorator-based API is deprecated in favor of the CLI.
AutoChrome 0.1.10
基于 DrissionPage 封装的自用API，用于网页自动化。
Requires Python: >=3.10

# AutoChrome

> AutoChrome 是基于 [DrissionPage](https://drissionpage.cn/) 封装的浏览器自动化工具，支持自动下载
> Chrome、丰富的页面操作、元素操作、网络监听、文件下载、日志管理等功能，适用于数据采集、自动化测试等场景。

注意：AutoChrome 是一个自用模块，部分功能 `未进行充分测试`，请谨慎使用！

## ✨ 主要功能

- 🛠️ 支持自动安装 `Chromium`，解决了打包环境缺失的问题
- 🍪 cookies 的获取与设置
- 🔄 封装了常见的 `网页翻页` 功能
- 👀 封装了 `网络监听` 功能
- ⬇️ 将浏览器下载和 requests 下载进行了封装
- ⬆️ 封装 `文件上传` 功能
- 🧬 `AutoChrome` 继承于 `DrissionPage`，支持 `DrissionPage` 的源方法和参数
- 📚 `源码`包含详细的参数和功能说明，包含 `DrissionPage` 源文档链接
- 🐞 模块是个人使用的一个工具，当初写的比较急，代码较为粗糙🤐...

---

## 📒 说明文档 📒

- [https://blog.csdn.net/xiaoqiangclub/article/details/148529468](https://blog.csdn.net/xiaoqiangclub/article/details/148529468)

---

## 💬 联系与支持

* 👨‍💻 作者：Xiaoqiang
* 📢 微信公众号：**XiaoqiangClub**
* 📧 反馈与建议请通过邮件联系：**[xiaoqiangclub@hotmail.com](mailto:xiaoqiangclub@hotmail.com)**
* ☕ **请我喝咖啡支持项目发展：**

![请我喝咖啡](https://gitee.com/xiaoqiangclub/xiaoqiangapps/raw/master/images/xiaoqiangclub_ad.png)
precice-config-visualizer-gui 1.0.0
A GUI tool for visualizing a preCICE configuration file as a dot file.
Requires Python: >=3.8
Keywords: preCICE, dot, graphviz, XML, interactive, configuration, visualization

# preCICE Config-Visualizer GUI

The `config-visualizer` is a tool meant to help visualize and debug precice configuration xml files. This tool produces a dot file as output, which visualizes the various participants, communicators and meshes defined in the configuration file and the movement of data between them.
This GUI offers an interactive way to quickly inspect, explore and study preCICE configuration files.

## Installation options

Install directly from PyPi using [pipx](https://pipx.pypa.io/stable/) or via pip:

```
pipx install precice-config-visualizer-gui
```

## Usage

```
precice-config-visualizer-gui [CONFIG-FILE]
```

You can launch the GUI directly from the command line.
Passing the path to a configuration file is optional.
All further adjustments are made directly in the GUI.

## System integration

Until existing tools provide an automatic way to integrate applications into the system, this has to be done manually.

For pipx users, run the following command [which downloads this file](https://gist.githubusercontent.com/fsimonis/a08c3771abf808b0534d658bcb563f90/raw/10717f5b2afbf2d3c05ecb9f5c7eeaae4bbe868a/org.precice.configvisualizer.desktop)

```console
mkdir -p ~/.local/share/applications && wget -O ~/.local/share/applications/org.precice.configvisualizer.desktop https://gist.githubusercontent.com/fsimonis/a08c3771abf808b0534d658bcb563f90/raw/10717f5b2afbf2d3c05ecb9f5c7eeaae4bbe868a/org.precice.configvisualizer.desktop
```

You may have to logout and login for your desktop environment to detect the file.
Now you can open XML files directly with the config-visualizer and see the application in your launcher.

## Licensing

The license was changed from GPLv3 to MIT in approval of the copyright holder Frédéric Simonis (@fsimonis frederic.simonis@ipvs.uni-stuttgart.de) decided on 24. June 2025 12:40 CET.
precice-config-visualizer 2.0.0
A tool for visualizing a preCICE configuration file as a dot file.
Requires Python: >=3.8
Keywords: preCICE, dot, graphviz, XML, configuration, visualization

# preCICE Config-Visualizer

The `config-visualizer` is a tool meant to help visualize and debug precice configuration xml files. This tool produces a dot file as output, which visualizes the various participants, communicators and meshes defined in the configuration file and the movement of data between them.

## Installation options

Install directly from PyPi using [pipx](https://pipx.pypa.io/stable/) or via pip:

```
pipx install precice-config-visualizer
```

To also install [the GUI](https://pypi.org/project/precice-config-visualizer-gui/), run:

```
pipx install 'precice-config-visualizer[gui]'
```

## Usage

```
precice-config-visualizer --help
precice-config-visualizer [OPTIONS] [-o OUTFILE] [<CONFIG-FILE>]
```

The command line version of the tool transforms the XML configuration file into a dot graph and either outputs it to the terminal or writes it to a file.
If the extension of the output file is `.png`, `.pdf`, `.svg`, or `.jpg`, then the tool will render the output using `graghviz`.
The dot output is especially useful if the output needs to be altered for various reasons.
To edit the dot version of the graph, displaying it using a dot viewer such as [xdot](https://pypi.org/project/xdot/) can be helpful.

The tool reads from stdin if no configuration file is given as an argument and the output is printed to stdout if no output filename if specified using the `-o` option.

To generate `graph.dot` from `precice-config.xml` use:

```
precice-config-visualizer precice-config.xml > graph.dot
precice-config-visualizer -o graph.dot precice-config.xml
```

To generate an image from `precice-config.xml` use:

```
precice-config-visualizer -o graph.png precice-config.xml
precice-config-visualizer -o graph.pdf precice-config.xml
precice-config-visualizer -o graph.svg precice-config.xml
```

To modify the dot graph from `precice-config.xml` yourself use:

```
precice-config-visualizer precice-config.xml > graph.dot
# Edit graph.dot here
dot -Tpdf -o graph.pdf graph.dot
```

Further options can be used to control the output appearance. Some information can be turned off or merged.
For a full list of options, run:

```
precice-config-visualizer --help
```

## Licensing

The license was changed from GPLv3 to MIT in approval of all contributors at the point of change:

| Contributor | Approved when |
| --- | --- |
|`Benjamin Rodenberg <benjamin.rodenberg@cit.tum.de>` | 23.06.2025 16:30 CET |
|`Benjamin Uekermann <benjamin.uekermann@gmail.com` | 23.06.2025 16:59 CET |
|`Frédéric Simonis <simonisfrederic@gmail.com` | 23.06.2025 17:56 CET |
|`Gerasimos Chourdakis <makishourdakis@gmail.com` | 23.06.2025 16:53 CET |
|`Keefe Huang <huangq1234553@gmail.com` | 23.06.2025 17:51 CET |