semvec/pypi-packages huggingface dataset:
dispatch-generic-harry007 0.0.1
A simple dispatch decorator for generic functions
Requires Python: >=3.9

### dispatch-generic

A simple dispatch decorator for generic functions.
```python
from src import dispatch

@dispatch
def test(i: int):
    print('for int')

@dispatch
def test(s: str):
    print('for str')

test(5)  # for int
test('s') # for str
test() # TypeError
```
sc-stardust 0.1.2
Subcellular-level Tool for the Analysis of RNA Distribution Using optimal Transport
Requires Python: <4.0,>=3.9

# STARDUST 🌌
Imaging-based spatial transcriptomics technologies capture the location of transcripts at subcellular resolution, but established methods represent data at the cell level, ignoring subcellular structure.

STARDUST (Subcellular-level Tool for Analyzing RNA Distribution USing optimal Transport) is a method for analyzing the subcellular spatial distribution of RNA molecules. STARDUST uses the Fused Gromov-Wasserstein distance from the optimal transport problem to model gene transcripts in relation to each other and the cell outline.

### Installation
```
$ pip install sc-stardust
```

### Functionalities
STARDUST includes:

- de_novo_analysis - Identifies the axes of variation in how one or more genes' transcripts are distributed in cells in a dataset. When multiple genes of interest are given, the model distinguishes between transcripts from differen genes and takes into account gene-gene spatial correlations.
    - UMAP_de_novo_analysis_output - Generates an embedding of cells based on the similarity of their subcellular transcript distributions. 
    - barycenters - Cluster cells based on their subcellular transcript distributions and generate barycenters that are representative of each cluster.

- canonical_analysis - Scores cells based on how similar their transcript distributions (for a specific gene of interest) are to user-specified canonical patterns to look for.


For the tutorial and more information, check out https://github.com/emmazchen/STARDUST.
so-file-system 26.4.5
Un sistema de archivos versionado con Copy-on-Write en Python.
Requires Python: >=3.8

# 📂 cow_file_manager

Sistema de archivos versionado usando la técnica **Copy-On-Write (COW)** en Python. Permite crear, escribir, leer y administrar versiones de archivos de cualquier tipo.

---

## 📅 Instalación

1. Clona o descarga el proyecto.
2. Instala las dependencias:

```bash
pip install -r requirements.txt
```

3. (Opcional) Instala el paquete localmente:

```bash
pip install .
```

---

## 📁 Uso básico

```python
from src.cow_file_manager.cow_file_manager import GestorArchivos

# Inicializar el gestor
gestor = GestorArchivos("miarchivo.bin")

# Crear archivo
gestor.create()

# Escribir datos
gestor.write("Hola mundo versionado!")

# Leer la última versión
gestor.read()

# Listar todas las versiones
gestor.listar_versiones()

# Mostrar uso de memoria
gestor.mostrar_uso_memoria()

# Cerrar archivo
gestor.close()
```


---

## 📊 Características principales

- ✅ Versionado automático de archivos.
- ✅ Escritura en bloques comprimidos (zlib nivel 9).
- ✅ Lectura segura de la última versión.
- ✅ Limpieza de bloques huérfanos.
- ✅ Optimizado para archivos de texto o binarios.

---

## 🔧 Comandos para desarrollo

- Ejecutar todos los tests:

```bash
pytest
```

- Correr ejemplo de uso:

```bash
python example.py
```


---

## 📈 Roadmap futuro (opcional)
- ✨ Soporte para rollback de versiones.
- ✨ Exportar versiones específicas.
- ✨ Mejorar eficiencia de lectura masiva.


---

## 👤 Autor
- Proyecto desarrollado por **TuNombre**.


---

## 📘 Licencia
MIT License. Libre de uso para proyectos personales o comerciales.

---

# 🔗 Contribuciones
¡Las contribuciones son bienvenidas! 🚀

```bash
1. Forkea el repositorio.
2. Crea una nueva rama (git checkout -b feature/nueva-feature).
3. Haz commit de tus cambios (git commit -m 'Agrega nueva feature').
4. Haz push a tu rama (git push origin feature/nueva-feature).
5. Abre un Pull Request.
rimecard 0.1.3
Extract vcf vcard contacts to rime pinyin dictionary.
Requires Python: >=3.8
Keywords: dict, dictionary, pinyin, rime, vcard, vcf

# rimecard

Extract vcf vcard contacts to rime pinyin dictionary.

将vcf格式的vcard通讯录里的姓名转换为rime输入法使用的字典格式。

将FN字段中的姓名合并，翻译为拼音，权重提升为1。


## 安装

`pip install rimecard`


## 使用

- `-i`定义输入文件
- `-o`定义输出文件，未定义时屏幕输出
- `-e`定义输出编码（默认utf-8）
- `-l`定义字符数限制（默认3）

`python3 -m rimecard -i vcard.vcf *.vcf [-o OUTPUT] [-e ENCODING] [-l WORDS_LIMIT]`
pandas-bootstrap 0.3.0
Statistical Bootstrap with Pandas made easy
Requires Python: <4.0,>=3.9

# Pandas Bootstrap

[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![Tests](https://github.com/williambdean/pandas-bootstrap/actions/workflows/tests.yml/badge.svg)](https://github.com/williambdean/pandas-bootstrap/actions/workflows/tests.yml)
[![PyPI version](https://badge.fury.io/py/pandas-bootstrap.svg)](https://badge.fury.io/py/pandas-bootstrap)
[![docs](https://github.com/williambdean/pandas-bootstrap/actions/workflows/docs.yml/badge.svg)](https://williambdean.github.io/pandas-bootstrap/)
[![codecov](https://codecov.io/gh/williambdean/pandas-bootstrap/graph/badge.svg?token=WEJBSBMTYN)](https://codecov.io/gh/williambdean/pandas-bootstrap)

Statistical Bootstrap with Pandas made easy.

## Installation

```bash
pip install pandas-bootstrap
```

## Usage

The module is very easy to use.

1. `import bootstrap`
2. define statistic function: `def some_func(df: pd.DataFrame | pd.Series):`
3. get bootstrapped samples: `df.boot.get_samples(bfunc=some_func, B=100)`

Below is a simple example of bootstrapping the mean of two columns.

```python
import pandas as pd

import bootstrap

df = pd.DataFrame({
    'a': [1, 2, 3, 4, 5],
    'b': [6, 7, 8, 9, 10],
})

def mean_of_columns(df):
    return df.mean(numeric_only=True)

sample_kwargs = dict(random_state=42)
df_bootstrap = df.boot.get_samples(bfunc=mean_of_columns, B=5, sample_kwargs=sample_kwargs)
```

which results in:

```text
          a    b
sample
0       3.0  8.0
1       2.6  7.6
2       4.0  9.0
3       3.2  8.2
4       3.0  8.0
```

## Documentation

Read more in the [documentation](https://williambdean.github.io/pandas-bootstrap/)
pygologin 0.1.9
Not official GoLogin python package
Requires Python: >=3.8
Keywords: api, gologin

# pygologin

REST API provides programmatic access to GoLogin App. Create a new browser profile, get a list of all browser profiles, add a browser profile and running.

## Not Official Package

## Getting Started

GoLogin supports Linux, MacOS and Windows platforms.

### Installation

`pip install pygologin`

or clone this repository

`git clone https://github.com/at146/pygologin.git`

### Usage

Where is token? API token is [here](https://app.gologin.com/#/personalArea/TokenApi).
To have an access to the page below you need [register](https://app.gologin.com/#/createUser) GoLogin account.

![Token API in Settings](https://user-images.githubusercontent.com/12957968/146891933-c3b60b4d-c850-47a5-8adf-bc8c37372664.gif)

### Methods

#### Constructor

- `options` <[Object]> Options for profile
  - `autoUpdateBrowser` <[boolean]> do not ask whether download new browser version (default false)
    - `token` <[string]> your API [token](https://gologin.com/#/personalArea/TokenApi)
    - `profile_id` <[string]> profile ID
    - `executablePath` <[string]> path to executable Orbita file. Orbita will be downloaded automatically if not specified.
  - `remote_debugging_port` <[int]> port for remote debugging
    - `vncPort` <[integer]> port of VNC server if you using it
  - `tmpdir` <[string]> path to temporary directore for saving profiles
  - `extra_params` arrayof <[string]> extra params for browser orbita (ex. extentions etc.)
  - `uploadCookiesToServer` <[boolean]> upload cookies to server after profile stopping (default false)
  - `writeCookesFromServer` <[boolean]> download cookies from server and write to profile cookies file (default true)
  - `port` <[integer]> Orbita start port (uncomment out the lines with "random port" and "port" in `gologin-selenium.py` to select a random launch port)

## Full GoLogin API

**Swagger:** [GoLogin Swagger Documentation](https://api.gologin.com/docs)

**Postman:** [link here](https://documenter.getpostman.com/view/21126834/Uz5GnvaL)
generalagents 0.1.1
General Agents client library
Requires Python: >=3.10
Keywords: python

# General Agents Python API client

[![Release](https://img.shields.io/github/v/release/generalagents/generalagents-python)](https://img.shields.io/github/v/release/generalagents/generalagents-python)
[![Build status](https://img.shields.io/github/actions/workflow/status/generalagents/generalagents-python/main.yml?branch=main)](https://github.com/generalagents/generalagents-python/actions/workflows/main.yml?query=branch%3Amain)
[![License](https://img.shields.io/github/license/generalagents/generalagents-python)](https://img.shields.io/github/license/generalagents/generalagents-python)

# Documentation

The REST API documentation: https://docs.generalagents.com/

# Installation

General Agents Python API client is available as a python package on PyPI:

```bash
pip install generalagents
```

# Usage

This client includes both an interface for calling the agent, and a simple computer controller. An example execution
loop:

```python
from generalagents import Agent
from generalagents.macos import Computer

agent = Agent(model="ace-small", api_key='your-api-key-here')
computer = Computer()

instruction = "Star the generalagents-python github repository"
session = agent.start(instruction)
observation = computer.observe()

for _ in range(25):  # max actions
    action = session.plan(observation)
    print(f"Executing: {action}")
    if action.kind == "stop":
        break
    observation = computer.execute(action)
```

# Contributing

See [the contributing documentation](CONTRIBUTING.md).