semvec/pypi-packages huggingface dataset:
openva-pipeline 0.99
Automate the processing of verbal autopsy data
Requires Python: >=3.8

OpenVA_Pipeline
===============
[![image](https://img.shields.io/pypi/pyversions/openva_pipeline)](https://pypi.org/project/openva_pipeline/)
[![image](http://readthedocs.org/projects/openva-pipeline/badge/)](http://openva-pipeline.readthedocs.io/)
[![Build status](https://ci.appveyor.com/api/projects/status/gsxtxr40r21s0q79?svg=true)](https://ci.appveyor.com/project/jarathomas/openva-pipeline)
[![Coverage](https://codecov.io/gh/verbal-autopsy-software/openva_pipeline/branch/master/graph/badge.svg?token=307LFXDUJ2)](https://codecov.io/gh/verbal-autopsy-software/openva_pipeline)


Automates the processing of verbal autopsy (VA) data from an ODK Aggregate
server, through the openVA Pipeline middleware, and ending with a DHIS2 server
(with the [VA module](https://github.com/verbal-autopsy-software/DHIS2_VA_program)). VA data are
analyzed using the [openVA
package](https://github.com/verbal-autopsy-software/openVA) in **R** (see
[The openVA Toolkit article](https://journal.r-project.org/articles/RJ-2023-020/openVA-RJ-R1.pdf) for
more details).

The documentation for the openVA Pipeline can be found at:
[http://openva-pipeline.readthedocs.io/](http://openva-pipeline.readthedocs.io/)

## Getting Started

The OpenVA Pipeline has been designed for (and tested on) Ubuntu LTS 20.04.
The steps to install and configure the pipeline can be found in
`docs/setup.md`. To make the installation easier, there is also a bash shell
script `ubuntu_installation.sh` that installs all necessary software (the
script requires the `sudo` password).  The script also works for Ubuntu LTS 22.04.

<!-- The documentation can also be found on [Read the Docs](https://openva-pipeline.readthedocs.io/en/latest/): -->

<!-- - [**Software Requirements**](https://openva-pipeline.readthedocs.io/en/latest/software.html)  -->
<!-- - [**Installation Guide**](https://openva-pipeline.readthedocs.io/en/latest/install.html) -->
<!-- - [**Pipeline Configuration**](https://openva-pipeline.readthedocs.io/en/latest/config.html) -->

## License
GNU General Public License v3.0

----

## Licenses for Dependencies (ODK Briefcase and SmartVA-Analyze)

The openva-pipeline package makes use of two external programs:
`ODK-Briefcase-v1.18.0.jar` and `smartva`.  [ODK Briefcase](https://github.com/opendatakit/briefcase) 
is a tool in the Open Data Kit (ODK) Software Suite, and is open-source software available 
under the Apache 2.0 license (see 
[ODK_Briefcase_LICENSE](https://github.com/opendatakit/briefcase/blob/master/LICENSE.md).
`smartva` is an open-source command line interface application for linux (see the 
[SmartVA-Analyze MIT License](https://github.com/ihmeuw/SmartVA-Analyze/blob/master/LICENSE))
that is available for download from the
[ihmeuw/SmartVA-Analyze repository](https://github.com/ihmeuw/SmartVA-Analyze/releases).
**These applications are NOT included under the same license as the OpenVA Pipeline (GPL-3)**.
webdav3-cli 1.0.0.post0
Command line interface for webdav3
Requires Python: >=3.9,<4.0

# webdav3-cli

Simple command-line interface for interacting with a WebDAV server.

This was tested and developed against the WebDAV interface for a [Redmine](https://www.redmine.org/) server.

## Usage

### Configuring

You can configure a set of default values for the optional arguments using the `config` command 

#### Examples:
`webdav3 config set hostname={hostname}`

`webdav3 config set user={username}`

`webdav3 config set pass={password}`


### Uploading files

Files can be uploaded to the WebDAV server using the `upload` command

#### Examples:
`webdav3 upload {local_path} {remote_path} --hostname {server address} --root "/dmsf/webdav" --user {username} --pass {password}`

`webdav3 upload {local_path} {remote_path}`
pycWB 0.17.2
A Python package for coherent gravitational wave burst analysis
Requires Python: >=3.8
Keywords: ligo,physics,gravity,signal processing,gravitational waves,cwb,coherent wave burst

# pycWB

[![Build Status](https://git.ligo.org/yumeng.xu/pycwb/badges/main/pipeline.svg)](https://git.ligo.org/yumeng.xu/pycwb/-/pipelines)
[![Releases](https://git.ligo.org/yumeng.xu/pycwb/-/badges/release.svg)](https://git.ligo.org/yumeng.xu/pycwb/-/releases)
[![PyPI version](https://badge.fury.io/py/pycWB.svg)](https://badge.fury.io/py/pycWB)
[![License](https://img.shields.io/badge/license-GPLv3-blue)](https://git.ligo.org/yumeng.xu/pycwb/-/blob/main/LICENSE)

pycWB is a modularized Python package for gravitational wave burst search based on the core function of cWB.

## Installation

### Install pycWB with pip

pycWB is available on [PyPI](https://pypi.org/project/pycWB/). You can install it with pip.
Some dependencies are required to be installed before installing pycWB with pip. 
The easiest way is to install them with conda.

```bash
conda create -n pycwb "python>=3.9,<3.11"
conda activate pycwb
conda install -c conda-forge root=6.26.10 healpix_cxx=3.81 nds2-client python-nds2-client lalsuite setuptools_scm cmake pkg-config
python3 -m pip install pycwb
```

### Install pycWB from source

```bash
conda create -n pycwb python
conda activate pycwb
conda install -c conda-forge root=6.26.10 healpix_cxx=3.81 nds2-client python-nds2-client lalsuite setuptools_scm cmake pkg-config
git clone git@git.ligo.org:yumeng.xu/pycwb.git
cd pycwb
make install
```

## Usage

Example project can be found in [examples](./examples)

```python
from pycwb.search import search

search('./user_parameters.yaml')
```