semvec/pypi-packages huggingface dataset:
nomad-camels-toolbox 0.4.2
This package provides easy access to data generated with nomad-camels
Requires Python: >=3.10

# NOMAD CAMELS toolbox

This package provides easy access to data generated with [NOMAD CAMELS](https://github.com/FAU-LAP/NOMAD-CAMELS).

Simplify your data evaluation with the NOMAD CAMELS toolbox!
More information about the toolbox can be found in the [documentation of NOMAD CAMELS](https://fau-lap.github.io/NOMAD-CAMELS/doc/nomad_camels_toolbox.html).

## Optional Dependencies
To install the NOMAD CAMELS toolbox, run
```
pip install nomad-camels-toolbox[all]
```
in the Python environment you use for your evaluation. This installs all optional dependencies to use the full functionality. The following options are all included when using `all`.

Single installation options can be installed by using `pip install nomad-camels-toolbox[option-name]` ([see pip install documentation](https://pip.pypa.io/en/stable/cli/pip_install/)). The options are:
- `pandas`: This installs `pandas` as a powerful package for data evaluation along with the toolbox, so the data can be read directly as a [pandas.DataFrame](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html).
- `plotly`: Installs [plotly](https://pypi.org/project/plotly/), [lmfit](https://pypi.org/project/lmfit/) and [pandas](https://pypi.org/project/pandas/). It enables to automatically recreate the plots made in CAMELS, using plotly figures.
- `qt`: Installs [PySide6](https://pypi.org/project/PySide6/) and [pyqtgraph](https://pypi.org/project/pyqtgraph/). This is used to provide a GUI, to quickly investigate data from CAMELS.



# Changelog

### 0.4.2
- fixed broken check for the used camels-suitcase version. If a session name was given in CAMELS it would fail to recreate plots. 

### 0.4.1
Fixes:
- fixed broken import of the modules methods

### 0.4.0
- Can now recreate plots from CAMELS files using suitcase-nomad-camels-hdf5 version > 1.0.0

   Fully supports complex nested protocols and multiple plots with fits. 

   -- BROKEN -- use version 0.4.1

### 0.3.2
- Display data as points and fits as dashed lines

### 0.3.0
- Now compatible with more nested data structure from CAMELS 1.9.0

### 0.2.9
- added direct link to the toolbox documentation

### 0.2.8
- Fixed a bug when using data_set_key

### 0.2.7
- made selection of dataset in reader more intuitive

### 0.2.4
- plots now show legend over the plot, not anymore making the plot tiny
- fixed optional dependencies

### 0.2.3
- fixed plots not being made if two plots had the same name

### 0.2.2
Fixes:
- fixed import problems

### 0.2.1
Features:
- custom plots in qt-viewer

Fixes:
- installation fixed
- qt viewer more stable

## 0.2.0
Features:
- Recreating plots from CAMELS with a single function
- UI tool to view data in a simplified way

### 0.1.2
Fixes:
- fixed returning of dataframes for different shapes of the data
celery-live 0.1.1
A readiness and liveness probe service for Celery
Requires Python: >=3.7

Celery Live
===========

Celery Live is a library for monitoring the health of Celery workers and beat.
Designed to be easy to use with kubernetes, it is heavily based on 
[this blog post](https://medium.com/ambient-innovation/health-checks-for-celery-in-kubernetes-cf3274a3e106)
but packaged for easy deployment.

Usage
=====

In your celery app, add the following code:

```python
from celery import Celery
from celery_live import (
    enable_beat_liveness_checks,
    enable_beat_readiness_checks,
    enable_worker_liveness_checks,
    enable_worker_readiness_checks,
)

app = Celery("ptk_connect")

enable_beat_readiness_checks(app)
enable_worker_readiness_checks(app)
enable_beat_liveness_checks(app)
enable_worker_liveness_checks(app)
```

You can then run these commands to determine liveness or readiness state of beat or worker
 * celery-live beat live
 * celery-live beat ready
 * celery-live worker live
 * celery-live worker ready

this would be configured in kubernetes like
```yaml
    livenessProbe:
      exec:
        command:
        - celery-live
        - worker
        - live
      initialDelaySeconds: 5
      periodSeconds: 5
```
nrp-devtools 1.0.28
NRP repository development tools

# NRP repository development tools

This tool is used to setup and run an Invenio based NRP instance. 

## Prerequisites

- Python 3.10
- node version 16 or greater, npm version 7, 8 or 10
- imagemagick and development packages for imagemagick
- standard build tools (gcc, make, ...), on ubuntu build-essential
- Docker 20.10.10+ and docker-compose 1.17.0+ (or OrbStack on Mac)

## Creating a new repository

1. Download the installer

```bash
curl -sSL https://raw.githubusercontent.com/oarepo/nrp-devtools/main/nrp-installer.sh
```

2. Run the installer with a directory where the repository will be created

```bash 
bash nrp-installer.sh my-repo
```

After asking a couple of questions, the installer will create the
repository in the `my-repo` directory.

It will also initialize git version control system and commit the initial
sources.

3. Go to the my-repo directory and see the README.md file there for further instructions
   (or have a peek at [README.md](https://github.com/oarepo/nrp-devtools/blob/main/src/nrp_devtools/templates/repository/%7B%7Bcookiecutter.repository_name%7D%7D/README.md) )
nezuki 2.2.9
Un pacchetto per la gestione della domotica e servizi server
Requires Python: >=3.12
Keywords: nezuki domotica home-server

# Nezuki

Nezuki è una libreria Python modulare per varie integrazioni relativi all'Home Server con Ubuntu.

Il modulo Nezuki include una serie di funzionalità relative alla gestioned el server ma anche della domotica ed offre funzionalità che possono essere usate anche fuori da questi contesti.

## Caratteristiche

Per visualizzare aggiornamenti, deprecazioni, nuove funzionalità vedere il file CHANGELOG.md

Ogni modulo ha la sua relativa documentazione specifica, per un uso specifico e dettagliato visualizzare la relativa documentazione (README.md), di seguito un uso generale e piccola demo su come installare Nezuki e qualche esempio di funzionamento.

## Installazione

Puoi installare Nezuki tramite pip:

```bash
pip install Nezuki
```

## Esempio