semvec/pypi-packages huggingface dataset:
phystool 5.4.0
Exercise database manager for LaTeX files
Requires Python: >=3.13

# Phystool

This package is there to help managing physics lecture notes, exercises,
tests... It is based on four complementary elements:

1. **phystool**: Manages a database of LaTeX documents with additional metadata
2. **physnoob**: Provides some the of **phystool**'s functionalities in a GUI
3. _optional_ **[physvim](https://bitbucket.org/jdufour/physvim/src/master/)** or **[phystool.nvim](https://bitbucket.org/jdufour/phystool.nvim/src/master/)**: Implements vim commands to interact with **phystool**
5. _optional_ **[phystex](https://bitbucket.org/jdufour/phystex/src/main/)**: LaTeX classes and packages that are compatible with **phystool**

Among other things, this package provides:

+ a clean way to compile LaTeX documents without cluttering your directories
+ a neat and user-friendly log LaTeX compilation messages
+ an automatic LaTeX recompilation when/if required


# Development tools

The following tools are used during development:

+ [uv](https://docs.astral.sh/uv/): manages the python dependencies, build and publish new releases
+ [just](https://just.systems/): provides a set of commands
+ [direnv](https://direnv.net/): automatically loads the `.envrc`  when the directory is entered so that
    + the envrironment variables are set
    + the virtual envrironment is synchronized and activated
navigator-auth 0.17.4
Navigator Auth is an Authentication/Authorization Toolkit for aiohttp.
Requires Python: >=3.9.16

# Navigator Auth #

Navigator Auth is an Authentication/Authorization toolkit for aiohttp or Navigator, based on Asyncio.

[![pypi](https://img.shields.io/pypi/v/asyncdb?style=plastic)](https://pypi.org/project/asyncdb/)
[![versions](https://img.shields.io/pypi/pyversions/blacksheep.svg?style=plastic)](https://github.com/phenobarbital/navigator-auth)
[![Apache 2.0 licensed](https://img.shields.io/github/license/phenobarbital/navigator-auth?style=plastic)](https://raw.githubusercontent.com/phenobarbital/navigator-auth/master/LICENSE)


---

## Introduction

* Quick summary
* Version
* [Learn Markdown](https://bitbucket.org/tutorials/markdowndemo)

### Getting Started ###

* Installation
* Configuration
* Dependencies
* Database configuration
* How to run tests
* Deployment instructions

### Requirements ###

* Python >= 3.9
* asyncio (https://pypi.python.org/pypi/asyncio/)
* aiohttp >= 3.8
* Navigator-API >= 2.1

### License ###

Navigator_Auth is copyright of Jesus Lara (https://phenobarbital.info) and is under Apache 2 license. I am providing code in this repository under an open source license, remember, this is my personal repository; the license that you receive is from me and not from my employeer.
lalamo 0.6.8
JAX library for optimization and export of models for use with the UZU inference engine.
Requires Python: <4,>=3.12

<p align="center">
  <picture>
    <img alt="Mirai" src="https://artifacts.trymirai.com/social/github/lalamo-header.jpg" style="max-width: 100%;">
  </picture>
</p>

<a href="https://artifacts.trymirai.com/social/about_us.mp3"><img src="https://img.shields.io/badge/Listen-Podcast-red" alt="Listen to our podcast"></a>
<a href="https://docsend.com/v/76bpr/mirai2025"><img src="https://img.shields.io/badge/View-Deck-red" alt="View our deck"></a>
<a href="https://discord.com/invite/trymirai"><img src="https://img.shields.io/discord/1377764166764462120?label=Discord" alt="Discord"></a>
<a href="mailto:contact@getmirai.co?subject=Interested%20in%20Mirai"><img src="https://img.shields.io/badge/Send-Email-green" alt="Contact us"></a>
<a href="https://docs.trymirai.com/overview/lalamo"><img src="https://img.shields.io/badge/Read-Docs-blue" alt="Read docs"></a>
[![License](https://img.shields.io/badge/License-MIT-blue)](LICENSE)

# lalamo

A set of tools for adapting Large Language Models to on-device inference using the [uzu](https://github.com/trymirai/uzu) inference engine.

## Quick Start

To get the list of [supported models](https://trymirai.com/models), run:

```bash
uv run lalamo list-models
```

To convert a model, run:

```bash
uv run lalamo convert MODEL_REPO
```

Note: on some CPU platform you may be getting an error saying `The precision 'F16_F16_F32' is not supported by dot_general on CPU`. This is due to a bug in XLA, which causes matmuls inside `jax.jit` not work correctly on CPUs. The workaround is to set the environment variable `JAX_DISABLE_JIT=1` when running the conversion.

After that, you can find the converted model in the `models` folder. For more options see `uv run lalamo convert --help`.

## Model Support

To add support for a new model, write the corresponding [ModelSpec](lalamo/model_import/model_specs), as shown in the example below:

```python
ModelSpec(
    vendor="Google",
    family="Gemma-3",
    name="Gemma-3-1B-Instruct",
    size="1B",
    quantization=None,
    repo="google/gemma-3-1b-it",
    config_type=HFGemma3TextConfig,
    weights_type=WeightsType.SAFETENSORS,
)
```

## Optional Features

### PyAudio

PyAudio enables audio playback for TTS models and is used as an optional Lalamo feature because it requires [PortAudio](https://www.portaudio.com/) to be installed. 

How to:

- **macOS**: `brew install portaudio` ([formula](https://formulae.brew.sh/formula/portaudio))
- **Debian/Ubuntu**: `apt-get install portaudio19-dev python-all-dev`
- **Other Linux**: [PortAudio build instructions](https://www.portaudio.com/docs/v19-doxydocs/compile_linux.html)

Then run :

```bash
uv run --with  pyaudio lalamo path/to/model --replay
```
winnow-ml 1.0.1
An intelligent feature selection library for Machine Learning
Requires Python: >=3.8

# 🌾 Winnow

[![Python Version](https://img.shields.io/badge/python-3.8%2B-blue.svg)](https://www.python.org/)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)
[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](http://makeapullrequest.com)
[![Maintainability](https://img.shields.io/badge/maintainability-A-brightgreen.svg)](https://github.com/)

**The Intelligent Feature Selection Library for Machine Learning**

Winnow is a high-performance, modular Python library designed to separate the signal from the noise in your data. It provides both classic statistical criteria and state-of-the-art selection techniques like BorutaSHAP and mRMR, all wrapped in a clean, developer-friendly API.

---

## 🎯 Why Winnow?

In data science, more data isn't always better. Irrelevant or redundant features can lead to overfitting, slow training times, and poor model interpretability. Winnow helps you "winnow the wheat from the chaff," leaving you with only the most impactful features.

### ✨ Key Features

*   **⚡ Base Selection**: Correlation-based pruning, variance thresholding, and target relevancy.
*   **🧠 Advanced Techniques**: 
    *   **mRMR**: Minimum Redundancy Maximum Relevance for diverse feature sets.
    *   **BorutaSHAP**: Rigorous statistical selection using shadow features and SHAP values.
    *   **PCA Contribution**: Filter features based on their influence on principal components.
*   **🛠️ Custom Logic**: Easily register your own selection criteria into the pipeline.
*   **📊 Transparency**: Comprehensive reporting of why each feature was kept or removed.

---

## 📦 Installation

```bash
pip install winnow-ml
```

---

## 🚀 Quick Start

### Basic Selection

```python
import pandas as pd
from winnow import BaseSelector

# Load your data
df = pd.read_csv("data.csv")

# Initialize and transform
selector = BaseSelector(correlation_threshold=0.85)
result = selector.fit_transform(df, target_column='target')

print(f"Selected features: {result.selected_features}")
```

### Advanced Selection (Boruta + mRMR)

```python
from winnow import AdvancedSelector

selector = AdvancedSelector(
    use_borutashap=True, 
    n_boruta_trials=20,
    use_mrmr=True,
    n_mrmr_features=10
)

result = selector.fit_transform(X, y)
```

---

## 📁 Project Structure

```
winnow/
├── winnow/               # Core source code
│   ├── base_selector.py  # Core selection logic
│   ├── advanced_selector.py # Boruta, mRMR, and PCA
│   └── logger.py         # Centralized logging
├── examples/             # Real-world usage examples
├── tests/                # Robust test suite
└── README.md
```

---

## 📄 License

Winnow is released under the **MIT License**.
llvm-lnt 0.4.9
LLVM Nightly Test Infrastructure
Requires Python: >=3.10
Keywords: web, testing, performance, development, llvm

LNT: LLVM Nightly Test Infrastructure
=====================================

About
-----

LNT is an infrastructure for performance testing. The software itself
consists of two main parts, a web application for accessing and visualizing
performance data, and command line utilities to allow users to generate and
submit test results to the server.

The package was originally written for use in testing LLVM compiler
technologies, but is designed to be usable for the performance testing of any
software.


Documentation
-------------

The official LNT documentation is available online at: https://llvm.org/docs/lnt


Source
------

The LNT source is available in the llvm-lnt repository: https://github.com/llvm/llvm-lnt


Contributing
------------

To get started, please look at the [Developer Guide](https://llvm.org/docs/lnt/developer_guide.html) in the official documentation.
iflow-mcp_jiayao-mcp-chess 0.1.9
MCP server for playing chess against AI
Requires Python: >=3.11

# MCP Chess Server

This MCP let's you play chess against any LLM.

## Installation

To use this chess server, add the following configuration to your MCP config:

```json
{
  "mcpServers": {
    "chess": {
      "command": "uvx",
      "args": [
        "mcp-chess"
      ]
    }
  }
}
```

## Usage

Play a game:
![Chess starting position with black pieces](screenshots/start_black.png)

![A few moves later](screenshots/acc_dragon.png)

Find a position in a PGN for game analysis:

![Find a position in a PGN](screenshots/find_position.png)

## Available Tools

The server provides the following tools:

*   `get_board_visualization()`: Provides the current state of the chessboard as an image. The board orientation automatically flips based on the user's assigned color.
*   `get_turn()`: Indicates whose turn it is ('white' or 'black').
*   `get_valid_moves()`: Lists all legal moves for the current player in UCI notation (e.g., 'e2e4', 'g1f3'). Returns an empty list if the game is over.
*   `make_move(move_san: str)`: Makes a move on the board using Standard Algebraic Notation (SAN) (e.g., 'e4', 'Nf3', 'Bxe5'). Returns the move in SAN and UCI, the new board FEN, and game status.
*   `new_game(user_plays_white: bool = True)`: Starts a new game, resetting the board. By default, the user plays white. Sets the user's color for board orientation. Returns a confirmation message.
*   `find_position_in_pgn(pgn_string: str, condition: str)`: Finds the first board position in a PGN string matching a condition (e.g., "bishop on a3") and returns an image of that board state. The condition format is "piece_type on square_name". Valid piece types are "pawn", "knight", "bishop", "rook", "queen", "king".
RG 0.0.76
Ryan's go-to Python functions

Miscellaneous functions:    
    
Miscellaneous functions:    
reset, loatmat, xlsread    
    
Work with data:    
regress, R2, VIF, lags, pcorrcoef, correlated_matrix, interactions, SAM    
    
Dynamic time warping:    
DTW,DTW_batch    
    
Plot data:    
colorspectra,axaline,corr_reorder    
    
Statistical functions    
normplot    
    
Multivariate data analysis    
PCA, PLS, VIP, mbPLS, LDA, PCA_ellipse, ICA, MCR, NPLS_cal, NPLS_val    
    
Spectral pretreatments    
center, autoscale, SNV, MSC, EMSC, Savitzky Golay, detrend, baseline
cryptography 46.0.5
cryptography is a package which provides cryptographic recipes and primitives to Python developers.
Requires Python: !=3.9.0,!=3.9.1,>=3.8

pyca/cryptography
=================

.. image:: https://img.shields.io/pypi/v/cryptography.svg
    :target: https://pypi.org/project/cryptography/
    :alt: Latest Version

.. image:: https://readthedocs.org/projects/cryptography/badge/?version=latest
    :target: https://cryptography.io
    :alt: Latest Docs

.. image:: https://github.com/pyca/cryptography/actions/workflows/ci.yml/badge.svg
    :target: https://github.com/pyca/cryptography/actions/workflows/ci.yml?query=branch%3Amain

``cryptography`` is a package which provides cryptographic recipes and
primitives to Python developers. Our goal is for it to be your "cryptographic
standard library". It supports Python 3.8+ and PyPy3 7.3.11+.

``cryptography`` includes both high level recipes and low level interfaces to
common cryptographic algorithms such as symmetric ciphers, message digests, and
key derivation functions. For example, to encrypt something with
``cryptography``'s high level symmetric encryption recipe:

.. code-block:: pycon

    >>> from cryptography.fernet import Fernet
    >>> # Put this somewhere safe!
    >>> key = Fernet.generate_key()
    >>> f = Fernet(key)
    >>> token = f.encrypt(b"A really secret message. Not for prying eyes.")
    >>> token
    b'...'
    >>> f.decrypt(token)
    b'A really secret message. Not for prying eyes.'

You can find more information in the `documentation`_.

You can install ``cryptography`` with:

.. code-block:: console

    $ pip install cryptography

For full details see `the installation documentation`_.

Discussion
~~~~~~~~~~

If you run into bugs, you can file them in our `issue tracker`_.

We maintain a `cryptography-dev`_ mailing list for development discussion.

You can also join ``#pyca`` on ``irc.libera.chat`` to ask questions or get
involved.

Security
~~~~~~~~

Need to report a security issue? Please consult our `security reporting`_
documentation.


.. _`documentation`: https://cryptography.io/
.. _`the installation documentation`: https://cryptography.io/en/latest/installation/
.. _`issue tracker`: https://github.com/pyca/cryptography/issues
.. _`cryptography-dev`: https://mail.python.org/mailman/listinfo/cryptography-dev
.. _`security reporting`: https://cryptography.io/en/latest/security/
amberflow 0.6.0
Python workflow to run Free Energy calculations
Requires Python: >=3.10

=========
amberflow
=========


.. image:: https://img.shields.io/pypi/v/amberflow.svg
        :target: https://pypi.python.org/pypi/amberflow

.. image:: https://readthedocs.org/projects/locuaz/badge/?version=latest
        :target: https://locuaz.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status

.. image:: https://zenodo.org/badge/502907107.svg
        :target: https://zenodo.org/doi/10.5281/zenodo.10937388


* Free software: MIT license
* Documentation: not yet publicly available.

Documentation
-------------

If you just want to check the documentation, it's currentl being hosted on
chardonnay. Just forward it using ``ssh``::

    ssh -L 8888:127.0.0.1:8000 yorkgroup@chardonnay.rutgers.edu

And then go to ``localhost:8888`` on your browser.

Install
--------

Clone this repo::

    git clone git@github.com:/pgbarletta/amberflow

Change dir into the project and create conda environment::
   
    mamba env create -f conda/dev_environment.yaml

Install this project::
   
    git clone git@github.com:/pgbarletta/amberflow

Build it in editable mode using pip::

    pip install -e .

Build the documentation::

    sphinx-build -b html docs/source/ docs/build/html/

Access the docs locally on your browser::

    PATH/amberflow/docs/build/html/index.html


Development
------------

To release a new version, just tag the main brand and push::

    git tag 0.2.8
    git push --tags
fastmcp-tool 0.1.3
Command line tool for interacting with MCP servers
Requires Python: >=3.12
Keywords: cli, fastmcp, mcp

# fastmcp-tool

A command line tool for interacting with MCP (Model Context Protocol) servers.

## Installation

```bash
pip install fastmcp-tool
```

Or with uv:

```bash
uv pip install fastmcp-tool
```

## Usage

### Connecting to a Server

Use the `--server` option to specify an MCP server. This can be either:

- An HTTP/HTTPS URL for streamable HTTP transport
- A shell command for stdio transport

```bash
# HTTP server
fastmcp-tool --server https://mcp.example.com/sse <command>

# Stdio server (runs command via bash)
fastmcp-tool --server "python my_mcp_server.py" <command>
```

### Commands

#### List Tools

List all available tools on the MCP server:

```bash
fastmcp-tool --server https://mcp.example.com/sse tools
```

#### Call a Tool

Call a specific tool with optional JSON parameters:

```bash
# Pass parameters as a JSON string
fastmcp-tool --server https://mcp.example.com/sse call my_tool --params '{"key": "value"}'

# Or read parameters from a JSON file
fastmcp-tool --server https://mcp.example.com/sse call my_tool --params-file params.json
```

The `--params` and `--params-file` options are mutually exclusive.

#### List Resources

List all available resources:

```bash
fastmcp-tool --server https://mcp.example.com/sse resources
```

#### List Prompts

List all available prompts:

```bash
fastmcp-tool --server https://mcp.example.com/sse prompts
```

### Options

| Option | Description |
|--------|-------------|
| `--server` | MCP server URL or stdio command |
| `--debug` | Enable debug logging |
| `--bearer-token` | Bearer token for HTTP server authentication |
| `--help` | Show help message |

### Call Options

| Option | Description |
|--------|-------------|
| `--params` | JSON string of parameters to pass to the tool |
| `--params-file` | Path to a JSON file containing parameters |

## Examples

```bash
# List tools from a local stdio server
fastmcp-tool --server "uv run my_server.py" tools

# Call a tool with parameters
fastmcp-tool --server https://api.example.com/mcp call search --params '{"query": "hello"}'

# Call a tool with parameters from a file
fastmcp-tool --server https://api.example.com/mcp call search --params-file search_params.json

# List resources with debug output
fastmcp-tool --server "python server.py" --debug resources
```

## License

Apache License 2.0 - see [LICENSE](LICENSE) for details.
bootsec 0.9.2
Security baseline for your project. One command, you're set.
Requires Python: >=3.10
Keywords: bootstrap, gitignore, pre-commit, secrets, security

# Bootsec

Security baseline for your project. One command, you're set.

## The Problem

You're shipping fast. Security? "We'll add it later."

Later never comes. Then some bot finds your AWS keys on GitHub at 3am.

## The Fix

```bash
pip install bootsec
bootsec go
```

That's it. 60 seconds. Done.

You now have:
- `.gitignore` that actually blocks secrets
- `SECURITY.md` so people can report vulns
- `docs/security-checklist.md` for pre-launch
- `.pre-commit-config.yaml` that catches mistakes before you commit

No config files. No 200-page docs. No BS.

## Commands

| Command | What it does |
|---------|--------------|
| `bootsec go` | Setup everything |
| `bootsec guard` | Pre-commit check (<1 sec) |
| `bootsec peek` | Preview before applying |
| `bootsec packs` | See available packs |

## How It Works

1. **Scans** your repo (Node? Python? Flutter? We got you)
2. **Generates** security docs for your stack
3. **Guards** your commits so you don't push secrets
4. **Merges** with your existing files (never overwrites)

## What You Get

| File | Why |
|------|-----|
| `.gitignore` | Blocks secrets, build junk |
| `.env.example` | Template for env vars |
| `SECURITY.md` | Vuln reporting |
| `docs/security-checklist.md` | Pre-launch checklist |
| `.pre-commit-config.yaml` | Commit guard |

## Examples

```bash
bootsec go           # basic setup
bootsec go --ci      # + GitHub Actions
bootsec peek         # just preview, no changes
```

## Design

- Merge, don't overwrite
- No network calls
- Pure Python, zero deps
- Fast. Like, actually fast.

---

## Want More?

**[Bootsec Pro](https://beatdown0x.gumroad.com/l/vytstl)** unlocks the good stuff:

| Command | What it does |
|---------|--------------|
| `bootsec check` | Security audit with score (0-100) |
| `bootsec scan` | Find vulnerable deps |
| `bootsec deps` | Audit npm/pip/cargo/go/ruby/php |
| `bootsec sbom` | Generate SBOM |
| `bootsec ai` | AI fix suggestions |

Plus: **85+ secret patterns**, Docker/K8s checks, supply chain security.

**[Get Pro](https://beatdown0x.gumroad.com/l/vytstl)**

---

## Requirements

- Python 3.10+
- Git

## License

MIT

---

*Code audited by my buddy Claude. He finds bugs at 3am without complaining. Truly built different.*
kitconcept.solr 2.0.0a12
An opinionated Solr integration for Plone.
Requires Python: >=3.12
Keywords: CMS, Plone, Python

# kitconcept.solr

An opinionated Solr integration for Plone.

## Features

TODO: List our awesome features

## Installation

Install kitconcept.solr with uv.

```shell
uv add kitconcept.solr
```

Create the Plone site.

```shell
make create-site
```

## Contribute

- [Issue tracker](https://github.com/kitconcept/kitconcept-solr/issues)
- [Source code](https://github.com/kitconcept/kitconcept-solr/)

### Prerequisites ✅

-   An [operating system](https://6.docs.plone.org/install/create-project-cookieplone.html#prerequisites-for-installation) that runs all the requirements mentioned.
-   [uv](https://6.docs.plone.org/install/create-project-cookieplone.html#uv)
-   [Make](https://6.docs.plone.org/install/create-project-cookieplone.html#make)
-   [Git](https://6.docs.plone.org/install/create-project-cookieplone.html#git)
-   [Docker](https://docs.docker.com/get-started/get-docker/) (optional)

### Installation 🔧

1.  Clone this repository.

    ```shell
    git clone git@github.com:kitconcept/kitconcept-solr.git
    cd kitconcept.solr/backend
    ```

2.  Install this code base.

    ```shell
    make install
    ```


### Add features using `plonecli` or `bobtemplates.plone`

This package provides markers as strings (`<!-- extra stuff goes here -->`) that are compatible with [`plonecli`](https://github.com/plone/plonecli) and [`bobtemplates.plone`](https://github.com/plone/bobtemplates.plone).
These markers act as hooks to add all kinds of features through subtemplates, including behaviors, control panels, upgrade steps, or other subtemplates from `bobtemplates.plone`.
`plonecli` is a command line client for `bobtemplates.plone`, adding autocompletion and other features.

To add a feature as a subtemplate to your package, use the following command pattern.

```shell
make add <template_name>
```

For example, you can add a content type to your package with the following command.

```shell
make add content_type
```

You can add a behavior with the following command.

```shell
make add behavior
```

```{seealso}
You can check the list of available subtemplates in the [`bobtemplates.plone` `README.md` file](https://github.com/plone/bobtemplates.plone/?tab=readme-ov-file#provided-subtemplates).
See also the documentation of [Mockup and Patternslib](https://6.docs.plone.org/classic-ui/mockup.html) for how to build the UI toolkit for Classic UI.
```

## License

The project is licensed under GPLv2.

## Credits and acknowledgements 🙏

Generated from the [`cookieplone-templates`  template](https://github.com/plone/cookieplone-templates/tree/main/) on 2025-07-22 22:24:40.. A special thanks to all contributors and supporters!