semvec/pypi-packages huggingface dataset:
mylistanalyzer 0.1.2
package to fetch and conduct ETL on your anime list from myanimelist
License: MIT
Requires Python: <4.0,>=3.12

This is a [Next.js](https://nextjs.org/) project bootstrapped with [`create-next-app`](https://github.com/vercel/next.js/tree/canary/packages/create-next-app).

## Getting Started

First, run the development server:

```bash
npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev
```

Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.

You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file.

This project uses [`next/font`](https://nextjs.org/docs/basic-features/font-optimization) to automatically optimize and load Inter, a custom Google Font.

## Learn More

To learn more about Next.js, take a look at the following resources:

- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API.
- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial.

You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js/) - your feedback and contributions are welcome!

## Deploy on Vercel

The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js.

Check out our [Next.js deployment documentation](https://nextjs.org/docs/deployment) for more details.
pymodaq-plugins-MozzaSpectro 0.1.1
some word about your plugin
License: MIT

pymodaq_plugins_template
########################

.. the following must be adapted to your developed package, links to pypi, github  description...

.. image:: https://img.shields.io/pypi/v/pymodaq_plugins_template.svg
   :target: https://pypi.org/project/pymodaq_plugins_template/
   :alt: Latest Version

.. image:: https://readthedocs.org/projects/pymodaq/badge/?version=latest
   :target: https://pymodaq.readthedocs.io/en/stable/?badge=latest
   :alt: Documentation Status

.. image:: https://github.com/PyMoDAQ/pymodaq_plugins_template/workflows/Upload%20Python%20Package/badge.svg
   :target: https://github.com/PyMoDAQ/pymodaq_plugins_template
   :alt: Publication Status

.. image:: https://github.com/PyMoDAQ/pymodaq_plugins_template/actions/workflows/Test.yml/badge.svg
    :target: https://github.com/PyMoDAQ/pymodaq_plugins_template/actions/workflows/Test.yml


Use this template to create a repository on your account and start the development of your own PyMoDAQ plugin!


Authors
=======

* First Author  (myemail@xxx.org)
* Other author (myotheremail@xxx.org)

.. if needed use this field

    Contributors
    ============

    * First Contributor
    * Other Contributors

.. if needed use this field

  Depending on the plugin type, delete/complete the fields below


Instruments
===========

Below is the list of instruments included in this plugin

Actuators
+++++++++

* **yyy**: control of yyy actuators
* **xxx**: control of xxx actuators

Viewer0D
++++++++

* **yyy**: control of yyy 0D detector
* **xxx**: control of xxx 0D detector

Viewer1D
++++++++

* **yyy**: control of yyy 1D detector
* **xxx**: control of xxx 1D detector


Viewer2D
++++++++

* **yyy**: control of yyy 2D detector
* **xxx**: control of xxx 2D detector


PID Models
==========


Extensions
==========


Installation instructions
=========================

* PyMoDAQâ€™s version.
* Operating systemâ€™s version.
* What manufacturerâ€™s drivers should be installed to make this plugin run?
SplitFVM 0.2
1D Finite-Volume Split Newton Solver
License: MIT
Keywords: amr newton python finite-volume armijo optimization pseudotransient splitting

# SplitFVM

[![Downloads](https://pepy.tech/badge/splitfvm)](https://pepy.tech/project/splitfvm)

![img](https://github.com/gpavanb1/SplitFVM/blob/main/assets/logo.jpg)

1D [Finite-Volume](https://en.wikipedia.org/wiki/Finite_volume_method) with [adaptive mesh refinement](https://en.wikipedia.org/wiki/Adaptive_mesh_refinement) and steady-state solver using Newton and [Split-Newton](https://github.com/gpavanb1/SplitNewton) approach

## What does 'split' mean?

The system is divided into two and for ease of communication, let's refer to first set of variables as "outer" and the second as "inner".

* Holding the outer variables fixed, Newton iteration is performed till convergence using the sub-Jacobian

* One Newton step is performed for the outer variables with inner held fixed (using its sub-Jacobian)

* This process is repeated till convergence criterion is met for the full system (same as in Newton)

## How to install and execute?

Just run 
```
pip install splitfvm
```

There is an [examples](https://github.com/gpavanb1/SplitFVM/examples) folder that contains a test model - [Advection-Diffusion](https://en.wikipedia.org/wiki/Convection%E2%80%93diffusion_equation)

You can define your own equations by simply creating a derived class from `Model` and adding to the `_equations` using existing or custom equations!

A basic driver program is as follows
```
# Define the problem
m = AdvectionDiffusion(c=0.2, nu=0.001)

# Define the domain and variables
# ng stands for ghost cell count
d = Domain.from_size(20, 2, ["u", "v", "w"]) # nx, ng, variables

# Set IC and BC
ics = {"u": "gaussian", "v": "rarefaction"}
bcs = {
    "u": {
        "left": "periodic",
        "right": "periodic"
    },
    "v": {
        "left": {"dirichlet": 3},
        "right": {"dirichlet": 4}
    },
    "w": {
        "left": {"dirichlet": 2},
        "right": "periodic"
    }
}
s = Simulation(d, m, ics, bcs)

# Advance in time or to steady state
s.evolve(dt=0.1)
bounds = [[-1., -2., 0.], [5., 4., 3.]]
iter = s.steady_state(split=True, split_loc=1, bounds=bounds)

# Visualize
draw(d, "label")
```

## Whom to contact?

Please direct your queries to [gpavanb1](http://github.com/gpavanb1)
for any questions.

## Acknowledgements

Do visit its [Finite-Difference](https://github.com/gpavanb1/SplitFDM) cousin

Special thanks to [Cantera](https://github.com/Cantera/cantera) and [WENO-Scalar](https://github.com/comp-physics/WENO-scalar) for serving as an inspiration for code architecture
python-pptx 1.0.2
Create, read, and update PowerPoint 2007+ (.pptx) files.
License: MIT
Requires Python: >=3.8
Keywords: powerpoint, ppt, pptx, openxml, office

*python-pptx* is a Python library for creating, reading, and updating PowerPoint (.pptx)
files.

A typical use would be generating a PowerPoint presentation from dynamic content such as
a database query, analytics output, or a JSON payload, perhaps in response to an HTTP
request and downloading the generated PPTX file in response. It runs on any Python
capable platform, including macOS and Linux, and does not require the PowerPoint
application to be installed or licensed.

It can also be used to analyze PowerPoint files from a corpus, perhaps to extract search
indexing text and images.

In can also be used to simply automate the production of a slide or two that would be
tedious to get right by hand, which is how this all got started.

More information is available in the `python-pptx documentation`_.

Browse `examples with screenshots`_ to get a quick idea what you can do with
python-pptx.

.. _`python-pptx documentation`:
   https://python-pptx.readthedocs.org/en/latest/

.. _`examples with screenshots`:
   https://python-pptx.readthedocs.org/en/latest/user/quickstart.html