semvec/pypi-packages huggingface dataset:
tendril-connector-stytch 0.1.0
Stytch Connector for Tendril
Requires Python: !=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7
Keywords: tendril



.. image:: https://img.shields.io/pypi/v/tendril-connector-stytch.svg?logo=pypi
    :target: https://pypi.org/project/tendril-connector-stytch

.. image:: https://img.shields.io/pypi/pyversions/tendril-connector-stytch.svg?logo=pypi
    :target: https://pypi.org/project/tendril-connector-stytch

.. image:: https://img.shields.io/travis/tendril-framework/tendril-connector-stytch.svg?logo=travis
    :target: https://travis-ci.org/tendril-framework/tendril-connector-stytch

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    :target: https://coveralls.io/github/tendril-framework/tendril-connector-stytch

.. image:: https://img.shields.io/codacy/grade/363acc44e8c240dc9db79935860191b4?logo=codacy
    :target: https://www.codacy.com/app/chintal/tendril-connector-stytch

.. image:: https://img.shields.io/requires/github/tendril-framework/tendril-connector-stytch.svg
    :target: https://requires.io/github/tendril-framework/tendril-connector-stytch/requirements

.. image:: https://img.shields.io/pypi/l/tendril-connector-stytch.svg
    :target: https://www.gnu.org/licenses/agpl-3.0.en.html



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Introduction
------------

TODO Some brief introduction


Package Information
-------------------

The latest version of the documentation, including installation, usage, and
API/developer notes can be found at
`ReadTheDocs <https://tendril-connector-stytch.readthedocs.io/en/latest/index.html>`_.

The latest version of the sources can be found at
`GitHub <https://github.com/tendril-framework/tendril-connector-stytch>`_. Please use 
GitHub's features to report bugs, request features, or submit pull/merge requests.

The principle author for ``tendril-connector-stytch`` is Chintalagiri Shashank. The 
author can be contacted if necessary via the information on the
`author's github profile <https://github.com/chintal>`_ . See the AUTHORS file
for a full list of collaborators and/or contributing authors, if any.

``tendril-connector-stytch`` is distributed under the terms of the
`AGPLv3 license <https://www.gnu.org/licenses/agpl-3.0.en.html>`_ .
A copy of the text of the license is included along with the sources.
mcp-server-hcp4 1.1.0
Excel MCP Server for manipulating Excel files
Requires Python: >=3.10

A Model Context Protocol (MCP) server that enables structured interactions with Microsoft Excel workbooks. Use it to read, write, query, and transform spreadsheet data via MCP-compliant clients.

### **Features**
1. Open and manage Excel workbooks and worksheets
2. Read/write cell ranges, rows, and columns
3. Append data and create tables
4. Evaluate formulas and recalculate sheets
5. Find/replace, filter, and basic data validation

### **MCP Capabilities**
1. open_workbook(path, mode="r|rw") -> { workbookId, sheets }
2. list_workbooks(root=?) -> [paths]
3. list_sheets(workbook) -> [names]
4. read_range(workbook, sheet, range) -> { values, types? }
5. write_range(workbook, sheet, range, values) -> { updated: count }
6. append_rows(workbook, sheet, rows) -> { appended: count }
7. find(workbook, sheet, query, matchCase=?, wholeCell=?) -> [addresses]
8. replace(workbook, sheet, query, replace, all=?) -> { replaced: count }
9. export_csv(workbook, sheet, range=?, path=?) -> { path }
10. export_json(workbook, sheet, range=?, path=?) -> { path }
11. save(workbook, path=?) -> { path }
12. close_workbook(workbook, save=?)

### **Resources**
1. workbook:list
2. sheet:list
openg2p-fastapi-auth 1.1.4
OpenG2P Library for initializing authn and authz for defined APIs
Requires Python: >=3.7

# OpenG2P FastAPI Auth

[![Pre-commit Status](https://github.com/OpenG2P/openg2p-fastapi-common/actions/workflows/pre-commit.yml/badge.svg?branch=1.1)](https://github.com/OpenG2P/openg2p-fastapi-common/actions/workflows/pre-commit.yml?query=branch%3A1.1)
[![Build Status](https://github.com/OpenG2P/openg2p-fastapi-common/actions/workflows/test.yml/badge.svg?branch=1.1)](https://github.com/OpenG2P/openg2p-fastapi-common/actions/workflows/test.yml?query=branch%3A1.1)
[![codecov](https://codecov.io/gh/OpenG2P/openg2p-fastapi-common/branch/1.1/graph/badge.svg)](https://codecov.io/gh/OpenG2P/openg2p-fastapi-common)
[![PyPI](https://img.shields.io/pypi/v/openg2p-fastapi-auth?label=pypi%20package)](https://pypi.org/project/openg2p-fastapi-auth)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/openg2p-fastapi-auth)](https://pypi.org/project/openg2p-fastapi-auth)

This package contains components required to bootstrap the authn & authz aspects for APIs defined.
openg2p-fastapi-common 1.1.4
OpenG2P Library for initializing common API Backend components
Requires Python: >=3.7

# OpenG2P FastAPI Common

[![Pre-commit Status](https://github.com/OpenG2P/openg2p-fastapi-common/actions/workflows/pre-commit.yml/badge.svg?branch=1.1)](https://github.com/OpenG2P/openg2p-fastapi-common/actions/workflows/pre-commit.yml?query=branch%3A1.1)
[![Build Status](https://github.com/OpenG2P/openg2p-fastapi-common/actions/workflows/test.yml/badge.svg?branch=1.1)](https://github.com/OpenG2P/openg2p-fastapi-common/actions/workflows/test.yml?query=branch%3A1.1)
[![codecov](https://codecov.io/gh/OpenG2P/openg2p-fastapi-common/branch/1.1/graph/badge.svg)](https://codecov.io/gh/OpenG2P/openg2p-fastapi-common)
[![PyPI](https://img.shields.io/pypi/v/openg2p-fastapi-common?label=pypi%20package)](https://pypi.org/project/openg2p-fastapi-common)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/openg2p-fastapi-common)](https://pypi.org/project/openg2p-fastapi-common)

This package contains can be used to bootstrap the common components API, API Models, ORM, Configs, etc.

## Usage

TBD
pyfwapi 0.2.8
Work with the Fotoware API in Python
Requires Python: >=3.12

# `pyfwapi`

Work with the Fotoware API in Python.

## Examples

```py
>>> from pyfwapi import Tenant
... fw = Tenant("https://tenant.example.org", client_id="abd123", client_secret="sekret")
...
... async for archive in fw.archives():
...     print(a.name)
Marketing
Technical docs
```

## Design considerations

The API responses are parsed using Pydantic.
It's a hefty dependency, but -- for now -- allows easy parsing of the JSON responses.
And it also enables easy integration with FastAPI.

Explorations of `attrs`, `cattrs`, and `msgspec` failed to quickly result in satisfactory objects from the API JSON responses.
rfdetr-doclayout 0.1.0
Add your description here
Requires Python: >=3.12

# RF-DETR For Document Layout Analysis

This is a repository for RF-DETR For Document Layout Analysis training with DocLayNet dataset.

This repository is based on [rf-detr-onnx](https://github.com/PierreMarieCurie/rf-detr-onnx).

|Original Image|Result Image|
|---|---|
|![academic](./assets/academic.jpg) | ![academic_result](./assets/academic_result.jpg) |
|![textbook](./assets/textbook.jpg) | ![textbook_result](./assets/textbook_result.jpg) |

## Installation

```bash
pip install rfdetr-doclayout
```

## Quick Start

```python
from rfdetr_doclayout.rfdetr import RfDetrDoclayout
import time

# Initialize the model
model = RfDetrDoclayout()

# Run inference and get detections
_, labels, boxes, masks = model.predict("path/to/image.jpg")
model.save_detections("path/to/image.jpg", boxes, labels, masks, "path/to/output.jpg")
```


## Training

```bash
git clone https://github.com/neka-nat/rfdetr-doclayout.git
cd rfdetr-doclayout
uv sync --extra train
```

### Download Dataset

```bash
wget https://codait-cos-dax.s3.us.cloud-object-storage.appdomain.cloud/dax-doclaynet/1.0.0/DocLayNet_core.zip
unzip DocLayNet_core.zip -d DocLayNet_core
```

Convert dataset to RF-DETR format.

```bash
uv run scripts/convert_dataset.py --src DocLayNet_core --dst dataset
```

### Training Locally

```bash
uv run scripts/doclaynet_train.py --dataset_dir dataset --output_dir models/rfdetr-doclayout
```

### Training on AWS SageMaker

```bash
aws s3 sync dataset/  s3://<your-bucket-name>/dataset
touch .env
echo "AWS_BUCKET_NAME=<your-bucket-name>" >> .env
echo "AWS_SAGEMAKER_ROLE_NAME=<your-role-name>" >> .env
uv run scripts/deploy_train.py
```
rocket-amjebenamjed 1.0.0
A Python package modeling Rockets, Shuttles, and Circular Rockets with distance, area, and circumference calculations.
Requires Python: >=3.7

# package_name

`rocket` is a Python library for Creating and move rockets in a 2D space, Compare rocket equality by position, Calculate distances between rockets and Specialized CircleRocket class with area and circumference calculations

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install `rocket`.

```bash
pip install rocket
```

## Usage

```python
from rocket import Rocket, CircleRocket

# Create a basic Rocket object
r1 = Rocket(0, 0)
r2 = Rocket(3, 4)

# Move a rocket
r1.move_rocket(1, 2)
print(r1)  # prints new position

# Compare two rockets
print(r1 == r2)  # checks if positions are equal

# Measure distance between rockets
print(r1.get_distance(r2))

# Create a CircleRocket (inherits from Rocket)
cr1 = CircleRocket(0, 0, 10)
print(cr1.get_area())          # prints area of the circular rocket
print(cr1.get_circumference()) # prints circumference
```

## License
[MIT]("C:\Users\nabil\Downloads\AI DS\SEDS_Lab3\rocket\rocket\LICENCE.txt")