semvec/pypi-packages huggingface dataset:
jupyter-trame-proxy 0.2.0
ParaView trame proxy for JupyterLab
Requires Python: >=3.9
Keywords: jupyter,trame,paraview,jupyterhub,jupyter-server-proxy

# jupyter-trame-proxy
Integrates [trame](https://github.com/Kitware/trame) in your Jupyter environment using [ParaView Visualizer](https://github.com/Kitware/paraview-visualizer).  

## Requirements
- Python **3.9+**
- ParaView **5.10+**
- Jupyter Notebook 6.0+
- JupyterLab 2.1+

This extension will start the `pv_visualizer` package. You must make sure it is on the PYTHONPATH! Adjust [launch_trame.sh](jupyter_trame_proxy/share/launch_trame.sh) to ensure this.

## Install 

#### Create and Activate Environment
```
virtualenv -p python3 venv
source venv/bin/activate
```

#### Install jupyter-trame-proxy
```
pip install git+https://github.com/jwindgassen/jupyter-trame-proxy.git
```

#### Enable jupyter-trame-proxy Extensions
For Jupyter Classic, activate the jupyter-server-proxy extension:
```
jupyter serverextension enable --sys-prefix jupyter_server_proxy
```

For Jupyter Lab, install the @jupyterlab/server-proxy extension:
```
jupyter labextension install @jupyterlab/server-proxy
jupyter lab build
```

## Starting
Click on the *ParaView trame* icon from the Jupyter Lab Launcher or the *ParaView trame* item from the new dropdown in Jupyter Classic.  

### Jupyter-Server-Proxy
[Jupyter-Server-Proxy](https://jupyter-server-proxy.readthedocs.io) lets you run arbitrary external processes alongside your notebook and provide web access to them. After installing this proxy, you can start trame using the *ParaView trame* entry in the launcher. It will start the server (which might take a few seconds) and open the website in a new tab.

## License
This software is provided under the BSD 3-Clause
divipy 1.0.2
Perfect and Cool package for developers.
Requires Python: >=3.7

# Divipy

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install Divipy

```diff
pip install -i https://test.pypi.org/simple/ divipy
```

## Import

```python
import divipy
```

## Use

```python
from divipy import sum
sum(1,50)

# >> 51
```
[View more examples](https://github.com/pandaxyz-xd/divipy/examples)

## License
[MIT](https://choosealicense.com/licenses/mit/)
compy 1.0.4
A package for reading CoMPASS directories into Python
Requires Python: >=3.6

# Compy: The CoMPASS Python Companion

## Introduction

Compy is a Python package for easily accessing and analyzing data acquired using CAEN Multi-PArameter Spectroscopy Software (CoMPASS). Compy takes as input the CoMPASS directories where experimental data is stored and processes the settings, spectra, and data files, storing them in a CompassRun object. Compy currently can only process data saved as either .csv or .bin files. Compy enables user filtering of data by energy and/or PSD cut and easy plotting of un/filtered energy/TOF/PSD spectra.

## Scripts

Included with the compy package are several scripts for commonly desired processes, such as plotting CoMPASS spectra, manually calculating TOF from signal and reference channels, and enabling user cuts.

### compy-run

The compy-run script provides a quick way of reading in CoMPASS data, merging related runs, plotting spectra, and saving the CoMPASS data to a pickle file for easy access later in Python.