semvec/pypi-packages huggingface dataset:
captcha_prune 1.0.0
A tool to protect formulaire from spam.
Requires Python: <4.0,>=3.12
Keywords: captcha, django, code-quality

# Prune's Captcha

## What is it for?

Captcha helps prevent robots from spamming using your forms.

## Prerequisites

-   To be installed on a Prune Django project that uses poetry or UV

## UV project

### Installation

Run the following command in the console:

```bash
uv add captcha_prune
```

### Running the captcha

To run the package, simply enter in the console:

```bash
captcha_prune
```

### Updating the captcha

Don't hesitate to regularly run `uv sync --upgrade`, as the captcha evolves with time and our practices!

## Poetry project

### Installation

Run the following command:

```bash
poetry add captcha_prune
```

### Running the captcha

```bash
poetry run captcha_prune
```

### Updating the captcha

Don't hesitate to regularly run `poetry update`, as the captcha evolves with time and our practices!

## Captcha Integration

Once the project is launched, the application's URLs need to be linked to the form.

-   When making a **GET** request to the form page, the API must be called via the **creation endpoint**. The response will contain the necessary information to display the captcha.
-   When submitting the form via **POST**, the API must be called via the **verification endpoint**. The response will indicate whether the captcha is valid or not.

## Captcha Display

To display the captcha correctly, use the data received in the response from the creation request. This data includes:

-   the captcha's width and height,
-   the piece's width and height,
-   the current position of the piece,
-   the target position (where the piece should be placed),
-   the expected precision (captcha difficulty level).

# Available Versions

| Version | Date       | Notes                                  |
| ------- | ---------- | -------------------------------------- |
| 1.0.0   | 2025-03-14 | First version of the `captcha` package |
openg2p-spar-self-service-api 1.1.0
OpenG2P SPAR Self Service API
Requires Python: >=3.7

# OpenG2P SPAR Self Service API
[![Pre-commit Status](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/pre-commit.yml/badge.svg?branch=develop)](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/pre-commit.yml?query=branch%3Adevelop)
[![Build Status](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/test.yml/badge.svg?branch=develop)](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/test.yml?query=branch%3Adevelop)
[![codecov](https://codecov.io/gh/OpenG2P/openg2p-spar-self-service/branch/develop/graph/badge.svg)](https://codecov.io/gh/OpenG2P/openg2p-spar-self-service)
[![PyPI](https://img.shields.io/pypi/v/openg2p-spar-self-service-api?label=pypi%20package)](https://pypi.org/project/openg2p-spar-self-service-api)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/openg2p-spar-self-service-api)](https://pypi.org/project/openg2p-spar-self-service-api)

SPAR Self Service API

## Licenses

This repository is licensed under [MPL-2.0](LICENSE).
openg2p-spar-g2pconnect-mapper-connector-lib 1.1.0
OpenG2P SPAR Self Service G2PConnect Mapper Connector Library
Requires Python: >=3.7

# OpenG2P SPAR Self Service G2PConnect Mapper Connector Library
[![Pre-commit Status](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/pre-commit.yml/badge.svg?branch=develop)](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/pre-commit.yml?query=branch%3Adevelop)
[![Build Status](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/test.yml/badge.svg?branch=develop)](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/test.yml?query=branch%3Adevelop)
[![codecov](https://codecov.io/gh/OpenG2P/openg2p-spar-self-service/branch/develop/graph/badge.svg)](https://codecov.io/gh/OpenG2P/openg2p-spar-self-service)
[![PyPI](https://img.shields.io/pypi/v/openg2p-spar-g2pconnect-mapper-connector-lib?label=pypi%20package)](https://pypi.org/project/openg2p-spar-g2pconnect-mapper-connector-lib)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/openg2p-spar-g2pconnect-mapper-connector-lib)](https://pypi.org/project/openg2p-spar-g2pconnect-mapper-connector-lib)

G2PConnect Mapper Connector Library for SPAR Self Service

## Licenses

This repository is licensed under [MPL-2.0](LICENSE).
openg2p-spar-mapper-interface-lib 1.1.0
OpenG2P SPAR Self Service Mapper Interface Library
Requires Python: >=3.7

# OpenG2P SPAR Self Service Mapper Interface Library
[![Pre-commit Status](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/pre-commit.yml/badge.svg?branch=develop)](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/pre-commit.yml?query=branch%3Adevelop)
[![Build Status](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/test.yml/badge.svg?branch=develop)](https://github.com/OpenG2P/openg2p-spar-self-service/actions/workflows/test.yml?query=branch%3Adevelop)
[![codecov](https://codecov.io/gh/OpenG2P/openg2p-spar-self-service/branch/develop/graph/badge.svg)](https://codecov.io/gh/OpenG2P/openg2p-spar-self-service)
[![PyPI](https://img.shields.io/pypi/v/openg2p-spar-mapper-interface-lib?label=pypi%20package)](https://pypi.org/project/openg2p-spar-mapper-interface-lib)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/openg2p-spar-mapper-interface-lib)](https://pypi.org/project/openg2p-spar-mapper-interface-lib)

Mapper Interface Library for SPAR Self Service

## Licenses

This repository is licensed under [MPL-2.0](LICENSE).
gadfastetcd 0.0.1
A FastAPI integration with Etcd for managing configuration settings via a RESTful API
Requires Python: >=3.8

<p align="center">
  <a href="https://github.com/AlexDemure/gadfastetcd">
    <a href="https://ibb.co/ZzpzbS7g"><img src="https://i.ibb.co/pjBjkQ5K/logo.png" alt="logo" border="0"></a>
  </a>
</p>

<p align="center">
  A FastAPI integration with Etcd for managing configuration settings via a RESTful API
</p>

---

### Installation

```
pip install gadfastetcd
```

### Usage

#### API
Set
```curl
curl -X 'PUT' \
  'http://127.0.0.1:8000/-/etcd' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "test": 1
}
```
Get
```
curl -X 'GET' \
  'http://127.0.0.1:8000/-/etcd' \
  -H 'accept: application/json'

{
  "test": 1
}
```

#### Code
```python
import pydantic

import fastapi

from gadfastetcd import Etcd

class Settings(pydantic.BaseModel):
    class Config:
        extra = "allow"

settings = Settings()

etcd = Etcd(url="localhost:2379", storage="/{service_name}/{environment}", settings=settings)

app = fastapi.FastAPI()

app.include_router(etcd.router)

>>> settings.test
```
bemyeyes-django-cte 1.3.4
Common Table Expressions (CTE) for Django
Requires Python: >=3.9

# Common Table Expressions with Django

[![PyPI version](https://badge.fury.io/py/bemyeyes-django-cte.svg)](https://badge.fury.io/py/bemyeyes-django-cte)

## Installation

```
pip install bemyeyes-django-cte
```

## Documentation

Fork of [django-cte documentation](https://dimagi.github.io/django-cte/) that doesn't support recursive CTEs

## Publishing a new version to PyPI

```
[create new tag]
uv pip install build
rm -rf dist/ build/ *.egg-info
uv run python -m build
uv pip install twine
uv run twine check dist/*
uv run twine upload dist/*
```
tgedr-ds 0.0.7
data science related code
Requires Python: >=3.11
Keywords: ai, data science, ml, mlops

[![pipelines](https://github.com/jtviegas/datascience/actions/workflows/pipeline.yml/badge.svg)](https://github.com/jtviegas/datascience/actions/workflows/pipeline.yml)

# datascience
data science experiments


## tweaks

### torch install

`pip install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu`
pytest-everyfunc 0.1.3
A pytest plugin to detect completely untested functions using coverage

pytest-everyfunc
================

A pytest plugin to detect completely untested functions using coverage.

Motivation
----------

If you add pytest-everyfunc to your CI, you can prevent yourself from
checking in code that adds functions without tests.

Installation
------------

::

    $ pip install pytest-everyfunc

Usage
-----

::

    $ pytest --cov=mypackage --fail-on-untested
    ...
    tests/test_script.py ........      [100%]
    mypackage/foo.py:253: untested function: rv_logpdf
    mypackage/bar.py:717: untested function: norms
    mypackage/baz.py:86: untested function: prior_predictive_check_plot
    Exit: Untested functions found.


The output shows the functions that were not called.

If --fail-on-untested is set, then the exit code is 32 (regardless whether tests succeed).

::

    $ echo $?
    32

git hook
--------

add to .git/hooks/pre-commit the pytest command above.
gadasyncblock 0.0.2
Event loop lock detector for Python
Requires Python: >=3.8

<p align="center">
  <a href="https://github.com/AlexDemure/gadasyncblock">
    <a href="https://ibb.co/4gMDDpK7"><img src="https://i.ibb.co/JF2bbHmK/logo.png" alt="logo" border="0"></a>
  </a>
</p>

<p align="center">
  Event loop lock detector for Python.
</p>

---

### Installation

```
pip install gadasyncblock
```

### Usage

```python
import contextlib

from fastapi import FastAPI

from gadasyncblock import AsyncBlock
# logger: asyncio.detector

detector = AsyncBlock(timeout=1)

@contextlib.asynccontextmanager
async def lifespan(_: FastAPI):
    detector.start()
    yield
    detector.shutdown()


app = FastAPI(lifespan=lifespan)

@app.post("/run")
async def run():
    time.sleep(2)
    return {"message": "Blocked"}
```
get-bibtex 2.0.1
A Python tool for fetching citations from multiple sources.
Requires Python: >=3.10

# get-bibtex

A Python tool for fetching citations from multiple sources.

[![PyPI version](https://badge.fury.io/py/get-bibtex.svg)](https://badge.fury.io/py/get-bibtex)
[![Python Version](https://img.shields.io/pypi/pyversions/get-bibtex.svg)](https://pypi.org/project/get-bibtex/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

[中文文档](README_CN.md)

## Features

- Multiple data sources (CrossRef, DBLP, Google Scholar)
- Smart workflow and fallback mechanism
- Batch processing
- Detailed error handling and logging

## Quick Start

### Installation

```bash
pip install get-bibtex
```

### Basic Usage

```python
from apiModels import CrossRefBibTeX

# Using CrossRef
fetcher = CrossRefBibTeX(email="your.email@example.com")
bibtex = fetcher.get_bibtex("10.3390/s22197244")  # FedMSA paper
print(bibtex)
```

### Using Workflow

```python
from apiModels import WorkflowBuilder, CrossRefBibTeX, DBLPBibTeX

# Create workflow
workflow = WorkflowBuilder()
workflow.add_fetcher(CrossRefBibTeX(email="your.email@example.com"))
workflow.add_fetcher(DBLPBibTeX())

# Batch processing
queries = [
    "ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks",
    "CBAM: Convolutional Block Attention Module"
]
results = workflow.get_multiple_bibtex(queries)
```

## Using Google Scholar

### Getting SerpAPI Key

1. Visit [SerpAPI](https://serpapi.com/) and sign up
2. Get API key from Dashboard
3. Initialize Google Scholar fetcher with API key

```python
from apiModels import GoogleScholarBibTeX

fetcher = GoogleScholarBibTeX(api_key="your-serpapi-key")
bibtex = fetcher.get_bibtex("Attention Is All You Need")
print(bibtex)
```

### Notes

- Free plan limited to 100 searches per month
- Use environment variables for API key
- Prefer CrossRef and DBLP when possible

## Examples

### Fetching Attention Mechanism Papers

```python
from apiModels import CrossRefBibTeX

fetcher = CrossRefBibTeX(email="your.email@example.com")

# Get ECA-Net paper citation
bibtex = fetcher.get_bibtex("10.1109/cvpr42600.2020.01155")
print(bibtex)
```

### File Processing

```python
from apiModels import WorkflowBuilder

workflow = WorkflowBuilder()
workflow.add_fetcher(CrossRefBibTeX(email="your.email@example.com"))
workflow.add_fetcher(DBLPBibTeX())

# Read queries from file and save results
workflow.process_file("papers.txt", "references.bib")
```

## Documentation

For detailed documentation, see [blog_cn.md](blog_cn.md)

## Contributing

Pull requests and issues are welcome!

## License

MIT
ditidy 2.1.0
Formatting utility for C
Requires Python: >=3

# Di Tidy

This project is a formatting/linting utility for various languages

## Development

```sh
pip install -e .
```

To run the specific module

```sh
export PYTHONPATH=src
python -m ditidy.[module name]
```

## Linting

```sh
hatch run lint
```

## Testing

```sh
hatch test
```

## Releasing

```sh
python -m build
twine upload --repository pypi dist/*
```
django-polls52 0.1
A Django app to conduct web-based polls.
Requires Python: >=3.13

==============
django-polls52
==============

django-polls52 is a Django app to conduct web-based polls. For each
question, visitors can choose between a fixed number of answers.

Detailed documentation is in the "docs" directory.

Quick start
-----------

1. Add "polls" to your INSTALLED_APPS setting like this::

    INSTALLED_APPS = [
        ...,
        "django_polls",
    ]

2. Include the polls URLconf in your project urls.py like this::

    path("polls/", include("django_polls.urls")),

3. Run ``python manage.py migrate`` to create the models.

4. Start the development server and visit the admin to create a poll.

5. Visit the ``/polls/`` URL to participate in the poll.
mcp-auto-builder 0.1.0
Final unified interface for global users
Requires Python: >=3.7

# mcp-auto_builder

Final unified interface for global users. Just describe your server, paste your API key (Claude/OpenAI/Grok), and this library will build, test, and deploy the full MCP server locally or remotely.

## Features

- Unified UI or CLI interface
- Takes one input: server description + key
- Auto-generates MCP server via internal libraries
- Claude Desktop auto-configuration
- Production and dev modes available

## Installation

```bash
pip install mcp-auto_builder
```

## Usage

```python
from mcp_auto_builder import Mcp_auto_builder

# Initialize the library
mcp_auto_builder_instance = Mcp_auto_builder()

# Use the library functions
# Example usage will be added in future versions
```

## License

MIT
mita-client 0.0.7
Mita client for Python.
Requires Python: >=3.6
Keywords: monitoring, logging

# Mita

Mita, named as Multi-Tangled, is a web application for monitoring runtime status and data of multiple machines 
(clients).

Demo: [https://mita-demo.controlnet.space](https://mita-demo.controlnet.space)

<img src=".github/demo.png" style="max-height: 480px">

## Get Started

### Run Server

The server is used to accept client post data and host the web UI.

#### Docker
```bash
docker run \
  -p <PORT>:9000 \
  -e MITA_PASSWORD=<PASSWORD> \
  [-e MITA_GUEST_PASSWORD=<GUEST_PASSWORD>] \
  controlnet/mita[:<VERSION>]
```

#### Environment Variables

- `MITA_PASSWORD`: Password for **admin** accessing the api and web for read/write.
- `MITA_GUEST_PASSWORD`: Password for **guest** accessing the api and web for read only.
- `REACT_APP_PASSWORD`: _Optional_, set the default password for the frontend.
- `MITA_SECRET_KEY`: _Optional_, Server secret key for CRSF token.
- `MITA_TOKEN_SECRET`: _Optional_, Server secret key for JWT authentication token.

### Run Client

The client is the interface to post data to the server.

Now the python client is available. The other clients (nodejs, java, cli, ...) are in plan.

#### Python Client

Install the client from pypi:
```bash
pip install mita_client
```

Use the tqdm integrated client (require `tqdm` for progress bar):
```python
from mita_client import mita_tqdm
import time

for i in mita_tqdm(range(1000), ADDRESS, PASSWORD):
    time.sleep(0.1)
```

Use the fully client:
```python
from mita_client.client import Mita
from mita_client.component import *
from mita_client.view import View

# initialize components
view = View("python_view")
logger = Logger("python_logger")
line_chart = LineChart("python_line_chart")
progress_bar = ProgressBar("python_progress_bar", total=100)
var = Variable("python_var", 100)

# register components to view
view.add(
    var,
    progress_bar,
    logger,
    line_chart
)

# update data in the runtime, and post to the client
with Mita(ADDRESS, PASSWORD) as client:
    client.add(view)

    for i in range(10):
        logger.log(f"some msg {i}")
        line_chart.add(1 + i, 1 + i, "pos")
        line_chart.add(1 + i, 3.5 - i, "neg")
        progress_bar.set(i * 8 + 1)
        
        client.push()
```

## License

| Module | License                        |
|--------|--------------------------------|
| server | [AGPL](./LICENSE)              |
| client | [MIT](./client/python/LICENSE) |
dsm-mcp-time-server 0.1.0
MCP 服务器，提供获取当前时间功能
Requires Python: >=3.13

# MCP 时间服务器

一个基于 Model Context Protocol (MCP) 的时间服务器，提供获取当前时间功能，支持各种时区。

## 功能特点

- 获取当前 UTC 时间或指定时区时间
- 同时获取多个时区的当前时间
- 提供常用时区列表资源
- 通过stdio或SSE传输方式运行

## 安装

```bash
pip install mcp-timeserver