semvec/pypi-packages huggingface dataset:
xarray-validate 0.0.5
A lightweight xarray validation library
Requires Python: >=3.8

# xarray-validate

[![PyPI version](https://img.shields.io/pypi/v/xarray-validate?color=blue)](https://pypi.org/project/xarray-validate)
[![GitHub Workflow Status (branch)](https://img.shields.io/github/actions/workflow/status/leroyvn/xarray-validate/ci.yml?branch=main)](https://github.com/leroyvn/xarray-validate/actions/workflows/ci.yml)
[![Documentation Status](https://img.shields.io/readthedocs/xarray-validate)](https://xarray-validate.readthedocs.io)
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://docs.astral.sh/uv/)
[![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)

## Motivation

> This is a maintained refactor of
> [xarray-schema](https://github.com/xarray-contrib/xarray-schema).
> I needed an xarray validation engine for one of my projects. I saw in the
> xarray-schema library a good start, but both its maintenance status and the
> foreseen integration of its feature set into the much larger Pandera library
> seemed uncertain. I therefore decided to fork the project, refactor it and add
> the features I was missing.

## Features

* ⬆️ DataArray and Dataset validation
* ⬆️ Basic Python type serialization / deserialization
* Construct schema from existing xarray data
* 🚫 ~~JSON roundtrip~~ (not guaranteed to work)

⬆️ Inherited from xarray-schema
🚫 Won't do / won't fix

## License

This project is distributed under the terms of the
[MIT license](https://choosealicense.com/licenses/mit/).

## About

xarray-validate is maintained by [Vincent Leroy](https://github.com/leroyvn).

The xarray-validate maintainers acknowledge the work of the xarray-schema
project creators and maintainers.
integrityguard-cli 1.1.3
Tool to detect Privilege Escalation and Data Tampering risks in Docker environments
Requires Python: >=3.10

# IntegrityGuard: Docker Security Assessment Tool

[![PyPI version](https://badge.fury.io/py/integrityguard-cli.svg)](https://badge.fury.io/py/integrityguard-cli)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

**IntegrityGuard** is a security tool designed to detect **Privilege Escalation** and **Data Tampering** risks in multi-user Docker environments.

It implements the methodology described in the research *"Segurança em Docker Multiusuário: Avaliação de Riscos"*, focusing on the dangers of exposing the Docker socket (`/var/run/docker.sock`) to non-privileged users.

## 🚀 Key Features

* **Vulnerability Diagnosis:** Checks if the current user is improperly added to the `docker` group or has write access to the socket.
* **Safe Proof-of-Concept (PoC):** Simulates a "Host Breakout" attack by attempting to mount the host filesystem and write a harmless test file, proving the viability of Data Tampering without damaging the system.
* **IEVI Score Calculation:** Quantifies the risk using the **Integrity Violation Exposure Index (IEVI)**, a metric derived from the **DREAD** threat modeling framework.
* **SonarQube-like Reporting:** Generates visual HTML dashboards or JSON output for CI/CD integration.

## 📦 Installation

Install the tool directly from PyPI:

```bash
pip install integrityguard-cli
````

## 🛠️ Usage

Once installed, the `integrity-guard` command is available globally.

### 1\. Standard Analysis (Console Output)

Runs the diagnosis and prints the findings and IEVI score to the terminal.

```bash
integrity-guard
```

### 2\. Generate HTML Dashboard

Creates a visual report (`integrity_scan_report.html`) containing the risk score, DREAD breakdown, and detailed findings.

```bash
integrity-guard --html
```

### 3\. JSON Output (DevOps/CI)

Outputs the raw data in JSON format for parsing by other tools.

```bash
integrity-guard --json
```

## 📊 How It Works (Methodology)

The tool operates in three phases:

1.  **Diagnosis:** It inspects user permissions and group memberships. Adding a user to the `docker` group is equivalent to granting them `root` access.
2.  **Simulation:** It attempts to spin up a container with `-v /:/mnt/host` to verify if the host filesystem is writable.
3.  **Scoring:** It calculates the **IEVI** (Integrity Violation Exposure Index).
      * **Score \> 40:** Indicates a **Critical** risk where an attacker can modify `/etc/passwd` or other sensitive files.
      * **Score \< 40:** Indicates a **Tolerable** risk (e.g., Rootless Docker).

## 🛡️ Mitigation

If **IntegrityGuard** reports a critical vulnerability, the recommended mitigation is to migrate to **Docker Rootless** mode or remove the user from the `docker` group.

## 📝 License

This project is licensed under the MIT License.
pynbody 2.4.1
Astronomical N-body/SPH analysis for python
Requires Python: >=3.11

pynbody
=======
[![Build Status](https://github.com/pynbody/pynbody/actions/workflows/build-test.yaml/badge.svg?branch=master)](https://github.com/pynbody/pynbody/actions)

[Pynbody](https://github.com/pynbody/pynbody) is an analysis framework for
N-body and hydrodynamic astrophysical simulations supporting PKDGRAV/Gasoline,
Gadget, Gadget4/Arepo, N-Chilada and RAMSES AMR outputs. 
Python version support adheres roughly to [SPEC0](https://scientific-python.org/specs/spec-0000/).

### Documentation

The documentation is at [readthedocs](https://pynbody.readthedocs.io). To get a first sense of what pynbody
can do, try the [quick-start tutorial](https://pynbody.readthedocs.io/latest/tutorials/quickstart.html) or
[images tutorial](https://pynbody.readthedocs.io/latest/tutorials/images.html).


### Getting started

Binary wheels are provided for Linux, MacOS and, from version 2.2, Windows. 

If python and the standard pip package manager is installed and properly configured, you can simply do:

```
$ pip install pynbody
```

If this fails, you may need some more detailed [installation
instructions](https://pynbody.readthedocs.io/latest/installation.html). 

### Contributing

Help us make *pynbody* better! As you develop analysis for your science with pynbody, consider making your code available 
for everyone else to use. You can do this by creating a [tutorial](https://pynbody.readthedocs.io/latest/tutorials/tutorials.html) 
or by adding your code to the relevant sub-module and submitting a pull request (make a fork first — see 
https://help.github.com/articles/using-pull-requests).


### Acknowledging the code

When using pynbody, please acknowledge it by citing the [Astrophysics Source Code Library entry](http://adsabs.harvard.edu/abs/2013ascl.soft05002P). Optionally you can also cite the Zenodo DOI for the specific version of pynbody that you are using, which may be found [here](https://doi.org/10.5281/zenodo.1297087).

### Support and Contact

If you have trouble with Pynbody or you have feature requests/suggestions you can [submit an issue](https://github.com/pynbody/pynbody/issues),
and/or send us an email on the [Usergroup mailing list](https://groups.google.com/forum/?fromgroups#!forum/pynbody-users).