semvec/pypi-packages huggingface dataset:
kalouk 0.1.0
A Python package for creating dataset metadata using Schema.org's Dataset type and sending it to Kalouk's API
Requires Python: >=3.12

# Kalouk Python Package

A Python package for creating dataset metadata using Schema.org's Dataset type and sending it to Kalouk's API.

## Installation

```bash
uv add kalouk
# or
pip install kalouk
```

## Quick Start

```python
from kalouk import Dataset

# Create a new dataset
dataset = Dataset()

# Set metadata using Schema.org Dataset properties
dataset.set_metadata("name", "My Dataset")
dataset.set_metadata("description", "A sample dataset")
dataset.set_metadata("creator", "John Doe")
dataset.set_metadata("dateCreated", "2025-01-01")
dataset.set_metadata("license", "https://creativecommons.org/licenses/by/4.0/")

# Send to Kalouk's API
response = dataset.send_to_kalouk()
print(f"Status: {response.status_code}")
```

## Features

- Create dataset metadata using Schema.org Dataset specification
- Send dataset metadata to Kalouk's API at web.kalouk.xyz/api/datasets
- NumPy-style docstrings with full type hints
- Comprehensive Sphinx documentation with Markdown support

## Documentation

Build the documentation locally:

```bash
cd docs
uv run make html
```

The documentation will be available in `docs/build/html/index.html`.

## Development

This project uses `uv` for dependency management. To set up the development environment:

```bash
uv sync
```

## API Reference

See the full API documentation in the `docs/` directory or build it locally using Sphinx.
KeyboardPaster 0.1.24
A Python package to type text using the keyboard module
Requires Python: >=3.10

# KeyboardPaster

A Python package to type text using the keyboard module. This is useful in situation where copy and paste is prohibited

## Features
- Paste 10 different strings using the keyboard
- Save string for future usage

## Future features
- Paste images as base64 code

## Changes
### v0.1.24
- BUGFIX: Corrected Python requirement

### v0.1.23
- BUGFIX: Corrected Python requirement

### v0.1.22
- FEATURE: Added Python 3.13 support

### v0.1.21
- BUGFIX: Would not correctly load secret settings
- BUGFIX: Multiple profiles would not load

### v0.1.20
- UPDATE: Changed requirement to python version 3.12

### v0.1.19
- BUGFIX: Version Bump

### v0.1.18
- FEATURE: Added a possibility to have multiple profiles.

### v0.1.17
- FEATURE: Added a button to put text into clipboard
- UPDATE: Changed the keyboard paste option into an icon

### v0.1.16
- FEATURE: Changes the launcher to run as a gui application and not show the command line when executed

### v0.1.15
- BUGFIX: Fixed the issue where the app would not start when the saved_inputs could not load

### v0.1.14
- FEATURE: Passwords can not be hidden in the UI

### v0.1.13
- BUGFIX: Python executable was not correctly found by autoupdate

### v0.1.12
- BUGFIX: Moved version to a shared location, and added it to the title

### v0.1.11
- FEATURE: Added autoupdate feature

### v0.1.10
- FEATURE: Added a modifier delay to accommodate slow connects and bad remote applications
- BUGFIX: Fixed the none-working sliders and buttons

### v0.1.9
- FEATURE: Added the ability to send a return press after the text was typed
- BUGFIX: You are not able to click anything in the app if the app does not have focus
stash-basic 1.0.0
The CLI tool for recording all your money related transactions!
Requires Python: >=3.10
Keywords: cli, personal finance, budget, transactions, money

# 💲Stash💲
### The CLI tool for recording all your money related transactions!
---

## 💡Key Features

#### `init`

Initialize the tool by specifying the file path where the data will be stored (in a JSON file). Also set a currency for the accounts.

#### `accounts`
`add` - Add a new account.

`delete` - Delete an existing account.

`summary` - Get details like account holder's **Name**, **Email**, **DOB**, **ID**, **Total Balance** of an existing account.

`statement` - Get the pretty printed tabular format of the transaction of an existing account.

#### `transactions`
`credit` - Add a **credit** transaction to an existing account by providing the account's **ID**, **Credit Amount**, **description**.

`debit` - Add a **debit** transaction to an existing account by providing the account's **ID**, **Debit Amount**, **description**.

`delete` - Delete a transaction from an account by providing the account's **ID** and the **Transaction ID**.

## ⌨️Usage Examples

`stash init D:\stash_data --file_name "stash_db.json --currency €`

This initializes the stash CLI. It is important to initialize the tool before first use. This command will store all
accounts and related data in **stash_db.json** file and the currency will be set to €. This currency is set for all
accounts on Stash. Currently, it is not possible to set individual currencies for accounts.

`stash accounts add "John Doe" "johndoe@gmail.com" 1980-05-01`

This creates an account with the Account holder name as **John Doe**, the email address as **johndoe@gmail.com** and John's DOB as **01-05-1980**. A Unqiue ID is also created for this account. It follows the pattern firstnamelastname_dob. In this example, the Unique ID will be **johndoe_151980**.

`stash accounts summary`

Displays all the accounts on Stash with all details of each account and the account balance.

`stash transactions credit johndoe_151980 1000 --desc "Initial transaction"`

This creates a CREDIT transaction and adds money to John's account. A transaction ID is created (UNIX timestamp). The Date, time, description, type and amount is recorded in every transaction. A Similar command can be used for DEBIT where the money is removed from an account.

`stash accounts statement johndoe_151980`

This displays all the transactions for John's account. All columns mentioned above for the credit example are all displayed in a neat table format.

`stash transactions delete johndoe_151980 1751128581`

This removes a transaction from John's account which has a unique ID **1751128581**. Balance for the account is updated accordingly.

## 📸 CLI Screenshots
![image](https://github.com/user-attachments/assets/4c77b39a-f97d-4f35-922b-bc96b56e2844)

![image](https://github.com/user-attachments/assets/567c9067-0802-4557-8072-4df219e6c8f0)

![image](https://github.com/user-attachments/assets/b02d65bc-6630-451d-ad4d-b9b192810b89)

![image](https://github.com/user-attachments/assets/bab647d5-109f-45bc-9de9-262c49d73c09)


## 🔗Dependencies

python, click, tabular
easygui-win 2.0.0
A super simple Windows GUI library for Python
Requires Python: >=3.7
Keywords: gui windows ui desktop simple easy

# EasyGUI - The Easiest Windows GUI Library

A super simple Windows GUI library for Python — with **no external dependencies**!

---

## 🚀 Features

- ✅ **Super simple API**
- 🔥 **No external dependencies**
- 💨 **Pure Python**, powered by the Windows API
- 🎨 Customizable **colors and styling**
- 🧱 Supports **method chaining**
- ⚡ **Lightweight and fast**

---

## 📦 Installation

```bash
pip install easygui-win
```

---

## 🧪 Quick Start

### Basic Style

```python
import easygui as gui

app = gui.App("My App")
app.text("Hello World!")
app.button("Click me!", lambda: print("Clicked!"))
app.run()
```

### Decorator Style

```python
import easygui as gui

@gui.app("My App")
def my_app():
    gui.text("Welcome!")
    gui.button("OK", gui.close)
```

---

## 🖼️ Examples

Run the included demos:

```bash
easygui-demo
```

---

## 📋 Requirements

- Python **3.7+**
- Windows OS

---

## 📄 License

MIT License — see the `LICENSE` file for details.
ibmoviesdk 0.0.2
SDK Python pour accéder à l’API MovieLens (Data Analysts/Data Scientists friendly)
Requires Python: >=3.11

# MovieLens SDK - `ibmoviesdk`

Un SDK Python simple pour interagir avec l’API REST MovieLens. Il est conçu pour les **Data Analysts** et **Data Scientists**, avec une prise en charge native de **Pydantic**, **dictionnaires** et **DataFrames Pandas**.

[![PyPI version](https://badge.fury.io/py/moviesdk.svg)](https://badge.fury.io/py/moviesdk)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)

---

## Installation

```bash
pip install ibmoviesdk
```

---

## Configuration

```python
from ibmoviesdk import MovieClient, MovieConfig

# Configuration avec l’URL de votre API (Render ou locale)
config = MovieConfig(movie_base_url="https://data-movie-app-back.onrender.com")
client = MovieClient(config=config)
```

---

## Tester le SDK

### 1. Health check

```python
client.health_check()
# Retourne : {"status": "ok"}
```

### 2. Récupérer un film

```python
movie = client.get_movie(1)
print(movie.title)
```

### 3. Liste de films au format DataFrame

```python
df = client.list_movies(limit=5, output_format="pandas")
print(df.head())
```

---

## Modes de sortie disponibles

Toutes les méthodes de liste (`list_movies`, `list_ratings`, etc.) peuvent retourner :

- des objets **Pydantic** (défaut)
- des **dictionnaires**
- des **DataFrames Pandas**

Exemple :

```python
client.list_movies(limit=10, output_format="dict")
client.list_ratings(limit=10, output_format="pandas")
```

---

## Tester en local

Vous pouvez aussi utiliser une API locale :

```python
config = MovieConfig(movie_base_url="http://localhost:8000")
client = MovieClient(config=config)
```

---

## Public cible

- Data Analysts
- Data Scientists
- Étudiants et curieux en Data
- Développeurs Python

---

## Licence

MIT License

---

## Liens utiles

- API Render : [https://data-movie-app-back.onrender.com](https://movie-backend-xelv.onrender.com)
- PyPI : [https://pypi.org/project/ibmoviesdk](https://pypi.org/project/ibmoviesdk)
heyhy 0.1.9.post1
mihomo-hysteria2-inbound manager
Requires Python: >=3.10

# Heyhy <a href = "https://t.me/+V1rQL8WFTNxiMjRh"><img src="https://img.shields.io/static/v1?style=social&logo=telegram&label=chat&message=studio" ></a>

Heyhy 用于快速部署 [hysteria2 server](https://github.com/apernet/hysteria) 并输出客户端最佳实践配置，开箱即用！

**What's features**

| Supported Configuration     | Status |
| --------------------------- | ------ |
| Hysteria2 server            | ✅      |
| NekoRay client proxy        | ✅      |
| sing-box `hy2` outbound     | ✅      |
| Mihomo `hysteria2` outbound | ✅      |
| Hysteria2 client            | ✅      |
| via Cloudflare CDN          | ✅      |

**Prerequisites**

- 在管理员权限下运行
- 提前为你的服务器的 IPv4 解析一个域名 A 纪录

## Get started

一键部署脚本，以 `uv tool` 的方式调度管理工具：

```bash
curl -LsSf https://astral.sh/uv/install.sh | sh && \
source $HOME/.local/bin/env && \
uv tool install heyhy && \
uv run heyhy install -d <填写域名>
```

> 首次安装完毕后，你可以通过别名指令 `heyhy` 或 `uv run heyhy` 调度脚本。

## What's next

安装指令其他参数：

```bash
heyhy install -d [DOMAIN]
```

| 必选参数         | 简介       |
| ---------------- | ---------- |
| `--domain`, `-d` | 绑定的域名 |

| 可选参数           | 简介                                                 |
| ------------------ | ---------------------------------------------------- |
| `--password`, `-p` | 手动指定连接密码 (可选，默认随机生成)                |
| `--ip`             | 手动指定服务器公网 IPv4 (可选，默认自动检测)         |
| `--port`           | 指定监听端口 (可选，默认 4433)                       |
| `--image`          | 指定托管镜像（可选，默认 `metacubex/mihomo:latest`） |

移除所有项目依赖：

```bash
heyhy remove
```

升级脚本：

```bash
heyhy self update
```

输出客户端配置：

根据正在运行的服务配置生成 `mihomo client outbound` 配置。

```bash
heyhy check
```

探索其他指令：

```bash
heyhy --help
```

![image-20250629184651534](./assets/image-20250629184651534.png)

## References

- [Hysteria2](https://v2.hysteria.network/zh/docs/getting-started/Client/) hy2 官方文档

- [sing-box outbound](https://sing-box.sagernet.org/zh/configuration/outbound/hysteria2/) sing-box 客户端出站代理设置

- [mihomo outbound](https://wiki.metacubex.one/config/proxies/hysteria2/#hysteria2) mihomo/clash-meta 客户端出站代理设置

- [MatsuriDayo configuration](https://matsuridayo.github.io/n-extra_core/#_5) nekoray / nekobox 客户端出战代理设置（该项目已停止维护）
divoom-gaming-gate 0.3.1
A PyQt5-based character and screen manager for Divoom gaming devices.
Requires Python: >=3.8

# Divoom Gaming Gate

## What is it?

This is a work in progress designed to allow users to push images to the [ Divoom Times Gate](https://divoom.com/products/time-gate)

It is written in Python and utilizes the PyQt5, Pillow, and requests libraries. 


## How to install and run

You can install the application using pip/pipx/pip3 or any other Python manager that communicates with PyPI. It will take some time to launch on first launch (pycache is being generated), but after that it will launch normally. 

```
pip install divoom-gaming-gate
```
or
```
pipx install divoom-gaming-gate
```
or
```
pip3 install divoom-gaming-gate
```

You may have to ask it to install dependencies like this 

```
pipx install divoom-gaming-gate --include-deps
```

Then just run it from the command line
```
divoom-gaming-gate
```
## Screenshots and description
![image](https://github.com/user-attachments/assets/dbe939a9-b183-4318-af6e-76c9cc03dbd2)



In this screen, you can load any image or animated GIF from either your local machine or Tenor GIF Search. You can skip frames (for sending large GIFs faster) and edit the time between frames. This screen also allows you to change the aspect of the image to Stretch, Fit, or Crop the image for the best fit. You can also save sets of images as themes. 


-------------

![image](https://github.com/user-attachments/assets/c5f4c5e1-7413-49fe-9a7b-7f370e7f33d6)


This screen allows you to send "Themes" to the screens. Themes are collections of 5 mages that are all sent to the screen atthe same time. These allow you to create ambiance for different "scenes" in your adventure. 

-------------

![image](https://github.com/user-attachments/assets/2b6431e4-c73a-4984-bbc7-3cce2fa2080e)


This screen allows you to create character images with backgrounds and character stats. You can use the default system layouts (D&D / Genesys) or roll your own, which you can then save for future use. It allows every stat to be either a single number, an X/Y ,configuration and allows you to add modifiers (like +1 or -2) 

-------------

![image](https://github.com/user-attachments/assets/bfbe22e6-f240-4a24-9748-b2f1f12ee8c9)


This area is mostly self-explanatory and utilizes some of the built-in tools that are part of the Divoom API. There is a stopwatch, a timer, a countdown timer, a scoreboard (red vs blue), a noise meter and an image splitter (for splitting any image into 5 images that can be sent to the screens).  

-------------

![image](https://github.com/user-attachments/assets/4c0a478a-19e3-497b-941f-93737c84ff3b)


a built-in designer that allows you to design new gifs (including animations) and send them to the screens. 

-------------

![image](https://github.com/user-attachments/assets/dff08b21-fd17-43b0-9ed6-e7686362ff29)



Settings for the clock, brightness, and IP address (An IP is required for the app to work) and a place to check for updates.
count-distinct 0.2.1
Use the CVM algorithm to quickly estimate the number of distinct elements in a stream
Requires Python: >=3.10
Keywords: cvm, count-distinct, estimation

# A Python implementation of the CVM Algorithm for Counting Distinct Elements

This library implements the algorithm described in

> Chakraborty, S., Vinodchandran, N. V., & Meel, K. S. (2022). *Distinct Elements in Streams: An Algorithm for the (Text) Book*. 6 pages, 727571 bytes. https://doi.org/10.4230/LIPIcs.ESA.2022.34

The accompanying article in Quanta is here: https://www.quantamagazine.org/computer-scientists-invent-an-efficient-new-way-to-count-20240516/

This Python module leverages the `cvmcount` Rust library: https://github.com/urschrei/cvmcount

## What does that mean
The count-distinct problem, or cardinality-estimation problem refers to counting the number of distinct elements in a data stream with repeated elements. As a concrete example, imagine that you want to count the unique words in a book. If you have enough memory, you can keep track of every unique element you encounter. However, you may not have enough working memory due to resource constraints, or the number of potential elements may be enormous. This constraint is referred to as the bounded-storage constraint in the literature.

In order to overcome this constraint, streaming algorithms have been developed: [Flajolet-Martin](https://en.wikipedia.org/wiki/Flajolet–Martin_algorithm), LogLog, [HyperLogLog](https://en.wikipedia.org/wiki/HyperLogLog). The algorithm implemented by this library is an improvement on these in one particular sense: it is extremely simple. Instead of hashing, it uses a sampling method to compute an [unbiased estimate](https://www.statlect.com/glossary/unbiased-estimator#:~:text=An%20estimator%20of%20a%20given,Examples) of the cardinality.

# What is an Element
Any hashable Python object or primitive. Not `f32` / `f64`, however, as they don't form a total ordering due to the presence of NaN.

## Further Details
Don Knuth has written about the algorithm (he refers to it as **Algorithm D**) at https://cs.stanford.edu/~knuth/papers/cvm-note.pdf, and does a far better job than I do at explaining it.

# Installation
`pip install count_distinct`

# Usage
```python
from count_distinct import CVM

# values for epsilon, delta, and stream size are described in the docstring.
counter = CVM(0.8, 0.1, 1000)
counter.add(2)
counter.add(5)
# keep adding elements
count = counter.calculate_final_result()
# you can keep adding elements if you wish
```

# Perf
## Memory, 10e8 random 7-digit positive integers
Allocation of integer array: 763 MiB

`count_distinct`: 768 MiB

`np.unique`: 1.7 GiB

## Note
If you're thinking about using this library, you presumably know that it only provides an estimate (within the specified bounds), similar to something like HyperLogLog. You are trading accuracy for speed!
napari-mass 0.6.7
Microscopy Array Section Setup napari plugin
Requires Python: >=3.10

# napari-mass

[![License GNU GPL v3.0](https://img.shields.io/pypi/l/napari-mass.svg?color=green)](https://github.com/FrancisCrickInstitute/napari-mass/raw/main/LICENSE)
[![PyPI](https://img.shields.io/pypi/v/napari-mass.svg?color=green)](https://pypi.org/project/napari-mass)
[![Python Version](https://img.shields.io/pypi/pyversions/napari-mass.svg?color=green)](https://python.org)
[![tests](https://github.com/FrancisCrickInstitute/napari-mass/workflows/tests/badge.svg)](https://github.com/FrancisCrickInstitute/napari-mass/actions)
[![codecov](https://codecov.io/gh/FrancisCrickInstitute/napari-mass/branch/main/graph/badge.svg)](https://codecov.io/gh/FrancisCrickInstitute/napari-mass)
[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-mass)](https://napari-hub.org/plugins/napari-mass)

Microscopy Array Section Setup napari plugin: A napari plugin for annotation and guided acquisition working together
with [SBEMimage](https://github.com/SBEMimage/SBEMimage).

----------------------------------

This [napari] plugin was generated with [copier] using the [napari-plugin-template].

<!--
Don't miss the full getting started guide to set up your new package:
https://github.com/napari/napari-plugin-template#getting-started

and review the napari docs for plugin developers:
https://napari.org/stable/plugins/index.html
-->

## Installation

This plugin can be installed via the plugin manager inside napari. For more information on how to install plugins, please refer to the [napari plugin documentation](https://napari.org/stable/plugins/start_using_plugins/finding_and_installing_plugins.html).

Alternatively, you can install `napari-mass` via [pip]:

    pip install napari-mass



To install latest development version :

    pip install git+https://github.com/FrancisCrickInstitute/napari-mass.git


## Contributing

Contributions are very welcome. Tests can be run with [tox], please ensure
the coverage at least stays the same before you submit a pull request.

## License

Distributed under the terms of the [GNU GPL v3.0](LICENSE.md) license,
"napari-mass" is free and open source software

## Issues

If you encounter any problems, please file an issue along with a detailed description.

[napari]: https://github.com/napari/napari
[copier]: https://copier.readthedocs.io/en/stable/
[@napari]: https://github.com/napari
[napari-plugin-template]: https://github.com/napari/napari-plugin-template

[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/