semvec/pypi-packages huggingface dataset:
fers 0.1.0
Finite Element Method library written in Rust with Python interface
Requires Python: >=3.8

# FERS_core

**FERS_core** is an open-source Finite Element Method (FEM) library written in Rust with a Python interface. It provides the foundational tools and components necessary for performing FEM analysis. This core package is designed for users who need a reliable and efficient FEM solver, while advanced features and optimizations are available in the [FERS_pro](#fers_pro) package.

## Features

- Basic Finite Element Method (FEM) solvers
- Mesh generation and manipulation tools
- Support for various types of finite elements
- Easy-to-use Python interface for integration with existing workflows
- Designed for high performance with Rust

## Installation

You can install `FERS_core` via pip:

```bash
pip install fers_core
pcce-api 1.0rc1
Prisma Cloud Compute Edition API Client
Requires Python: >=3.8.1
Keywords: Prisma Cloud, Prisma Cloud Compute, Palo Alto, CNAPP, API

Welcome to PCCE-API's documentation!
==============================================

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
   :target: https://github.com/psf/black
.. image:: https://img.shields.io/badge/linting-pylint-yellowgreen
   :target: https://github.com/pylint-dev/pylint
.. image:: https://img.shields.io/badge/security-bandit-yellow.svg
   :target: https://github.com/PyCQA/bandit
.. image:: https://gitlab.com/th1nks1mple/pcce-api/badges/main/pipeline.svg
   :target: https://gitlab.com/th1nks1mple/pcce-api/-/commits/main
.. image:: https://gitlab.com/th1nks1mple/pcce-api/badges/main/coverage.svg
   :target: https://gitlab.com/th1nks1mple/pcce-api/-/commits/main
.. image:: https://img.shields.io/pypi/pyversions/pcce-api
   :target: https://pypi.org/project/pcce-api/
.. image:: https://img.shields.io/pypi/v/pcce-api
   :target: https://pypi.org/project/pcce-api/

PCCE-API is a Prisma Cloud Compute Edition API Client.

- Issue Tracker: https://gitlab.com/th1nks1mple/pcce-api/-/issues
- GitLab Repository: https://gitlab.com/th1nks1mple/pcce-api

Features
--------

- Implement the latest Prisma Cloud Compute Edition API.
- Use marshmallow library for validate schema data before send to server.

Installation
------------

To install the most recent published version to pypi, its simply a matter of
installing via pip:

.. code-block:: bash

   pip install pcce-api

If you're looking for bleeding-edge, then feel free to install directly from the
github repository like so:

.. code-block:: bash

   pip install git+git://gitlab.com/th1nks1mple/pcce-api.git#egg=pcce-api

Getting Started
---------------

Lets assume that we want to get the list of users that have been create on our
PCCE application.  Performing this action is as simple as the following:

.. code-block:: python

   from pcce import PCCE
   pcce = PCCE(url='http://console.domain',
                  username='username',
                  password='password')
   for user in pcce.users.list():
      print(user)

Documents
---------

https://pan.dev/compute/api/31-02/

License
-------

The project is licensed under the MIT license.
cumulus-library-covid 2.1.0
SQL generation for cumulus covid symptom analysis
Requires Python: >=3.11

# Cumulus Library - Covid

A collection of tables for generating bioinformatics data for studying COVID-19 symptoms.
Part of the [SMART on FHIR Cumulus Project](https://smarthealthit.org/cumulus/).

For more information, browse the [Cumulus Library documentation](https://docs.smarthealthit.org/cumulus/library).

## Usage

To install the module, simply run `pip install cumulus-library-covid`.

This will add a `covid_symptom` study target to `cumulus-library`.

See [RUNNING.md](RUNNING.md) for more details.

## Publications

The following publications leveraged this module:

__Moving Biosurveillance Beyond Coded Data: AI for Symptom Detection from Physician Notes__
Andrew McMurry, Amy R Zipursky, Alon Geva, Karen L Olson, James Jones, Vlad Ignatov, Timothy Miller, Kenneth D Mandl
medRxiv 2023.09.24.23295960; doi: https://doi.org/10.1101/2023.09.24.23295960

__A computable phenotype for patients with SARS-CoV2 testing that occurred outside the hospital__
Lijing Wang, Amy Zipursky, Alon Geva, Andrew J. McMurry, Kenneth D. Mandl, Timothy A. Miller
JAMIA Open, 2023;, ooad047,doi: https://doi.org/10.1093/jamiaopen/ooad047 

__The SMART Text2FHIR Pipeline__
Timothy A. Miller, Andrew J. McMurry, James Jones, Daniel Gottlieb, Kenneth D. Mandl
medRxiv 2023.03.21.23287499; doi: https://doi.org/10.1101/2023.03.21.23287499 (Preprint)