semvec/pypi-packages huggingface dataset:
mxcubecore 2.4.0
Core libraries for the MXCuBE application
Requires Python: <3.12,>=3.10
Keywords: mxcube, mxcube3, mxcubecore

[![License: LGPL v3](https://img.shields.io/badge/License-LGPL%20v3-blue.svg)](https://www.gnu.org/licenses/lgpl-3.0)
[![Test and build](https://github.com/mxcube/mxcubecore/actions/workflows/tests.yml/badge.svg)](https://github.com/mxcube/mxcubecore/actions/workflows/tests.yml)
![PyPI](https://img.shields.io/pypi/v/mxcubecore)

# Backend of MXCuBE

`mxcubecore` is the back-end library for
[MXCuBE Qt](https://github.com/mxcube/mxcubeqt/)
and [MXCuBE Web](https://github.com/mxcube/mxcubeweb/).
It allows access to the beamline control system and instrumentation.
It acts as a container of single Python objects (called "hardware objects").

Please read the
[contributing guidelines](https://mxcubecore.readthedocs.io/en/stable/dev/contributing.html)
before submitting your code to the repository.

## License

MXCuBE is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

MXCuBE is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License
along with MXCuBE. If not, see <https://www.gnu.org/licenses/>.

## Installation

Installation of the `mxcubecore` module is commonly done as a dependency of either
[MXCuBE Web](https://github.com/mxcube/mxcubeweb/)
or [MXCuBE Qt](https://github.com/mxcube/mxcubeqt/).

Standalone installation of the `mxcubecore` for development purposes can be done
via Poetry with `poetry install`
or via pip with `python -m pip install --editable .` (don't forget the trailing dot `.`).

`mxcubecore` depends on `python-ldap` that in turn depends on the `openldap` system library.
It can be installed in a conda environment: `conda install openldap`
or on systems using the apt package manager (Debian and derivatives, including Ubuntu):
`sudo apt-get install -y libldap2-dev libsasl2-dev`.
See [python-ldap](https://www.python-ldap.org/en/python-ldap-3.4.3/installing.html#debian)
for more information.

See [Developer documentation](https://mxcubecore.readthedocs.io/)
for more information on working with mxcubecore.
londonaicentre-mesa-local 1.3.1
Serve MESA models locally
Requires Python: >=3.12

# MESA local

Serve MESA models locally.

- ⬇️ Downloads weights from S3

- 📦 Unpacks

- 🚀 Serves via a local OpenAI-compatible server

## Prerequisites

### Software

- Python 3.12

### Hardware

- A GPU with >=24GB VRAM (tested on NVIDIA A30)

### Configuration

- Create a file called `.env` in the directory where you intend to run this package.
Populate it with the details you have been provided with in the following format:

```text
MODEL_NAME=
WEIGHTS_ID=
WEIGHTS_KEY=
```

## Installation

1. (Recommended) Create a virtual environment and activate it:

    ```python
    python -m venv .venv
    source .venv/bin/activate
    ```

2. Install this package: `pip install londonaicentre-mesa-local`.

## Usage

### CLI

1. Note command line arguments:

    | Argument | Description |
    | --- | --- |
    | -v, --verbose | Enable debug output (optional) |

2. Start the server as follows: `mesalocal [args]`.

## Clients

### OpenAI (example with _Oncollama_)

1. Interact with the server using the [OpenAI client](https://pypi.org/project/openai) in python:

    ```python
    from openai import OpenAI
    from oncoschema.prompt_builder import PromptBuilder # pip install londonaicentre-oncoschema

    client = OpenAI(
        base_url="http://localhost:5000/v1",
        api_key="blank" 
    )

    response = client.chat.completions.create(
        model="oncollama3betav01",
        messages=[
            {"role": "system", "content": PromptBuilder().build_main_prompt()},
            {"role": "user", "content": "Diagnosis 01/01/26..."}
        ]
    )

    print(response.choices[0].message.content)
    ```

## License

This project uses a proprietary license (see [LICENSE](LICENSE.md)).
check_zpool_scrub 3.0.0a0
Monitoring plugin to check how long ago the last ZFS scrub was performed.
Requires Python: <4,>=3.10

.. image:: http://img.shields.io/pypi/v/check-zpool-scrub.svg
    :target: https://pypi.org/project/check-zpool-scrub
    :alt: This package on the Python Package Index

.. image:: https://github.com/Josef-Friedrich/check_zpool_scrub/actions/workflows/tests.yml/badge.svg
    :target: https://github.com/Josef-Friedrich/check_zpool_scrub/actions/workflows/tests.yml
    :alt: Tests

Command line interface
----------------------

:: 

    check_zpool_scrub v2.0
    Copyright (c) 2016-2026 Josef Friedrich <josef@friedrich.rocks>

    Monitoring plugin to check how long ago the last ZFS scrub was performed.

    Usage: check_zpool_scrub <options>

    Options:
     -c, --critical=OPT_CRITICAL
        Interval in seconds for critical state.
     -p,--pool=OPT_POOL
        Name of the pool. If this option is omitted all pools are checked.
     -h, --help
        Show this help.
     -s, --short-description
        Show a short description / summary.
     -v, --version
        Show the version number.
     -w, --warning=OPT_WARNING
        Interval in seconds for warning state. Must be lower than -c.

    Performance data:

    POOL is the name of the pool

     - POOL_last_ago
        Time interval in seconds for last scrub.
     - POOL_progress
        Percent 0 - 100
     - POOL_speed
        MB per second.
     - POOL_time
        Time to go in seconds.

    Details about the implementation of this monitoring plugin:

    This monitoring plugin grabs the last scrub date from the command
    'zpool status POOL'.

Project pages
-------------

* https://github.com/Josef-Friedrich/check_zpool_scrub
* https://exchange.icinga.com/joseffriedrich/check_zpool_scrub
* https://exchange.nagios.org/directory/Plugins/System-Metrics/File-System/check_zpool_scrub/details
oas-patch 0.6.0
A complete cli/lib to apply overlays to OpenAPI documents, powering your ci/cd and API lifecycle

# OAS Patcher

A powerful command-line tool and Python library for working with OpenAPI Specification (OAS) Overlays. Modify and enhance your OpenAPI documents using a declarative overlay approach - no manual editing of large spec files needed!

[![Documentation](https://img.shields.io/badge/docs-online-blue)](https://mcroissant.github.io/oas_patcher/)
[![PyPI version](https://badge.fury.io/py/oas-patch.svg)](https://badge.fury.io/py/oas-patch)

[![Overlay Spec](https://img.shields.io/badge/Overlay-1.0%20%7C%201.1-green)](https://github.com/OAI/Overlay-Specification)

## Key Features

🎯 **Overlay System** - Apply targeted modifications to OpenAPI documents  
📋 **Copy Action** - Duplicate schemas and components within your API (Overlay 1.1)  
📦 **Bundle Management** - Organize multiple overlays into reusable bundles  
🌍 **Environment Support** - Different configurations for dev, staging, production  
🔧 **Template Engine** - Use variables and dynamic content with Jinja2  
✅ **Validation** - Comprehensive validation for overlays and configurations  

**Supports OpenAPI Overlay Specification 1.0 and 1.1** - Use the latest features or maintain backward compatibility.

[View all features in documentation →](https://mcroissant.github.io/oas_patcher/core-concepts/overlays/)

## Quick Start

### Installation

```bash
pip install oas-patch
```

### Basic Usage

1. **Apply an Overlay**
```bash
oas-patch overlay openapi.yaml overlay.yaml -o modified.yaml
```

2. **Generate an Overlay (Diff)**
```bash
oas-patch diff original.yaml modified.yaml -o overlay.yaml
```

3. **Validate an Overlay**
```bash
oas-patch validate overlay.yaml
```

## Example

```yaml
# overlay.yaml
overlay: 1.1.0
info:
  title: Production Environment Overlay
  version: 1.0.0
  description: Configures the API for production use
actions:
  # Update server URL

  - target: "$"
    update:
      servers:
        - url: https://api.production.com
  
  # Copy a schema to create a new one (Overlay 1.1 feature)
  - target: "$.components.schemas.AdminUser"
    copy: "$.components.schemas.User"
    description: Create AdminUser schema based on User schema

```


## Documentation

- 📚 [Full Documentation](https://mcroissant.github.io/oas_patcher/)
- 🚀 [Getting Started Guide](https://mcroissant.github.io/oas_patcher/getting-started/quick-start/)
- 💡 [Core Concepts](https://mcroissant.github.io/oas_patcher/core-concepts/overlays/)

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.