semvec/pypi-packages huggingface dataset:
mcpauth 0.2.0b1
Plug-and-play auth for Python MCP servers.
Requires Python: <4.0,>=3.10
Keywords: authentication, authorization, mcp, modelcontextprotocol, oauth2, openid-connect, oidc

# MCP Auth Python SDK

[![GitHub branch check runs](https://img.shields.io/github/check-runs/mcp-auth/python/master)](https://github.com/mcp-auth/python/actions?query=branch%3Amaster)
[![codecov](https://codecov.io/gh/mcp-auth/python/graph/badge.svg?token=JXZ4C50SCV)](https://codecov.io/gh/mcp-auth/python)
[![Stable Version](https://img.shields.io/pypi/v/mcpauth?label=stable)][PyPI Releases]
[![Required Python Version](https://img.shields.io/python/required-version-toml?tomlFilePath=https%3A%2F%2Fraw.githubusercontent.com%2Fmcp-auth%2Fpython%2Fmaster%2Fpyproject.toml)][PyPI]
[![PyPI - License](https://img.shields.io/pypi/l/mcpauth)](https://github.com/mcp-auth/python/blob/master/LICENSE)

[Website]: https://mcp-auth.dev/
[PyPI]: https://pypi.org/project/mcpauth/
[PyPI Releases]: https://pypi.org/project/mcpauth/#history

The MCP spec [requires OAuth 2.1 and other RFCs](https://modelcontextprotocol.io/specification/2025-03-26/basic/authorization) for auth. Instead of spending weeks on them, use MCP Auth to connect to an trusted provider with a few lines of code.

## Get started

### Is my provider supported?

Check out the [MCP-compatible providers](https://mcp-auth.dev/provider-list) to see which providers are supported. It also includes a tool for real-time checking of provider compatibility.

### Installation

```bash
pip install mcpauth
```

Or use your package manager of choice, such as `poetry` or `uv`.

See [the documentation](https://mcp-auth.dev/docs) for the full guide.

## Join the discussion

Join the [MCP Auth org discussion](https://github.com/orgs/mcp-auth/discussions) to ask questions or share your feedback.
cfcli-py-tool 1.0.2
A CLI tool for interacting with the Codeforces API
Requires Python: >=3.8

# CFCli
A cli tool for codeforces

## Installation

Head to [the pypi page](https://pypi.org/project/cfcli-py-tool/) and copy the command at the top.

In our case it will be `pip install cfcli-py-tool`.

Open your terminal (or command line if you're using windows) and paste the following:

```bash
pip install cfcli-py-tool
```

If this gives an error, please try:

```bash
pip3 install cfcli-py-tool
```

This will install CFCli from the PyPi package manager.

In order to test your installation, please run:

```bash
cf-cli
```

## Requirements

Since the project is a pip (python package manager) package, you are required to have the following in order for it to work.
- Python 3.8+
- Latest Pip version

## Setup

The setup for cf-cli is very minimal. Since there are parts of the [Codeforces API](https://codeforces.com/apiHelp) that require authentication, it is the only environment variable that is needed.

# For the rest of the documenation, please visit the [official site](https://compprogtools.github.io/CFCli/)
obk 0.10.0
This is a pre-release/alpha version for initial feedback and CI testing. Not for production use.
Requires Python: >=3.11

# obk

> ⚠️ This project is in early development (pre-release/alpha).
> APIs and behavior will change rapidly as features are added.

OBK is a programmable system for documenting, validating, and querying project
knowledge via structured prompts validated with XSD and stored for later
analysis.

## Installation

```bash
pip install obk
```

## Quickstart

```bash
obk hello-world
obk divide 4 2
obk trace-id
```

## Features

* `hello-world` prints a greeting
* `divide` divides numbers with zero-checking
* `greet` greets by name; `fail` triggers a fatal error
* `validate-*` validates prompt files; `harmonize-*` normalizes them
* `trace-id` generates unique trace IDs

## Usage

For help on any command:

```bash
obk --help
```

## Contributing

See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.

## License

MIT
MorphLink 1.0.7
MorphLink: Bridging Cell Morphological Behaviors and Molecular Dynamics in Multi-modal Spatial Omics
Requires Python: >=3.6

# MorphLink

## MorphLink: Bridging Cell Morphological Behaviors and Molecular Dynamics in Multi-modal Spatial Omics

### Jing Huang, Chenyang Yuan, Jiahui Jiang, Jianfeng Chen, Sunil S. Badve, Yesim Gokmen-Polar, Rossana L. Segura, Xinmiao Yan, Alexander Lazar, Jianjun Gao, Michael Epstein, Linghua Wang,*, Jian Hu,*

MorphLink is a computational framework to systematically extract and link interpretable morphological features with molecular measurements in multi-model spatial omics analyses. The identified linkages provide a transparent depiction of cellular behaviors that drive transcriptomic heterogeneity and immune diversity across different regions within diseased tissues. Moreover, MorphLink is scalable and robust against cross-sample batch effects, making it an efficient method for integrating spatial omics data analysis across samples, cohorts, and modalities, and enhancing the interpretation of results for large-scale studies. MorphLink is applicable to various types of spatial omics data, including spatial transcriptomics (Spatial Transcriptomics, 10x Visium, 10x Xenium, and MERFISH), spatial proteomics (CODEX and IMS), and the simultaneous measurement of proteins and transcriptome (spatial CITE-seq and CosMx).
For more info, please go to: 
https://github.com/jianhuupenn/MorphLink