semvec/pypi-packages huggingface dataset:
print-linkdings 0.1
Print links from Linkding bookmarks including those one hop away.
Requires Python: >=3.10

# print-linkdings

This program sends API requests to the REST API of a Linkding instance on my Tailscale network, gathers the URLs from each unarchived bookmark, gathers URLs one hop away from each bookmark URL, and prints them to standard output.

The Linkding API key must be stored in a plaintext file at `/usr/local/etc/linkding_api_key.txt`.

## Installation

``` shell
pipx install print-linkdings
```

## Usage

``` shell
print-linkdings INSTANCE_URL
```

Example:

``` shell
print-linkdings "https://nas-local.tailnet.ts.net:7000"
```
PyDistSim 2.1.2
A high-level Python library for simulation of distributed algorithms.
Requires Python: >=3.11
Keywords: Networks, Distributed algorithms

PyDistSim
=========

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PyDistSim is a Python package for event-based simulation and evaluation of distributed algorithms. It is a fork of the
deprecated `Pymote <https://github.com/darbula/pymote>`_.

This fork aims at providing new features, redesigned APIs and better documentation. It is being developed by Agustin
Recoba in the context of his grade thesis at `Facultad de Ingeniería, Universidad de la República <https://www.fing.edu.uy/>`_.

Definition of the distributed environment, entities and actions used for making PyDistSim are taken mainly from
`Design and Analysis of Distributed Algorithms <http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0471719978,descCd-description.html>`_
by Nicola Santoro.

PyDistSim's main goal is to provide a framework for fast implementation, easy simulation and data-driven algorithmic
analysis of distributed algorithms.

Currently, PyDistSim supports IPython console or Jupyter notebooks. The gui is still in development and is not recommended
for any type of use.

.. image:: https://raw.githubusercontent.com/agustin-recoba/PyDistSim/main/docs/install/_images/project_showcase.gif
   :align: center
   :alt: PyDistSim console and gui

\

PyDistSim is being developed on top of `NetworkX <https://github.com/networkx/networkx/>`_ and is meant to be used along other scientific packages such as SciPy, NumPy and matplotlib. Currently, gui runs on PySide (Qt bindings) and console is jazzy IPython.

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

For installation instructions please visit `the documentation <https://pydistsim.readthedocs.io/install/installation.html>`_.

Literature
----------

Santoro, N.: *Design and Analysis of Distributed Algorithms*, `2006 <http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0471719978,descCd-description.html>`_

Arbula, D. and Lenac, K.: *Pymote: High Level Python Library for Event-Based Simulation and Evaluation of Distributed Algorithms*, International Journal of Distributed Sensor Networks, Volume `2013 <https://journals.sagepub.com/doi/10.1155/2013/797354>`_

Recoba, A: *PyDistSim: Framework de simulación de algoritmos distribuidos en redes en Python*, 2024
pyfys 0.2.15
A library to speed up physics work
Keywords: python, physics, graphing, constants


<p align="center">
  <img src="https://github.com/nikolaiborbe/PyFys/blob/main/assets/logo.png" width="180" alt="PyFys Logo" />
</p>

<h1 align="center">PyFys</h1>

<p align="center">An opinionated physics library.</p>
<p align="center">
<code>pip install pyfys</code>
</p>
<br />

PyFys is a Python library designed to simplify physics calculations and visualizations. It provides tools for computing common physics quantities and creating graphs.

The philosophy of the project is speed and simplicity. Physics is challenging enough as it is, so PyFys aims to make the programming side of things as easy as possible.

---

## Features
- Calculate physical quantities like kinetic energy, force, and relativistic momentum. (More equations coming soon!)
- Generate and visualize graphs for functions and data.
- Supports scalar and vector inputs for maximum flexibility and speed.

---

## Installation

To install PyFys, run the following command:

```bash
pip install pyfys
```

---

## Quickstart

### Import the Library
Here's an example of how to use PyFys to calculate kinetic energy:

```python
import pyfys

# Example: Calculate kinetic energy
fys = pyfys.fys()
mass = 10
velocity = [5, 10, 15]
energy = fys.kinetic_energy(mass=mass, velocity=velocity)
print(energy)  # Output: [125.0, 500.0, 1125.0]
```

### Generate a Graph
This example demonstrates how to plot multiple functions:

```python
fys.graph((math.sin, math.cos), stop=5)
```

### Plot Data
This example demonstrates how to plot data:

```python
mass = 10
velocity = [5, 10, 15]

fys.plot(fys.kinetic_energy(mass, velocity), velocity)
```

### Bar Chart
This example demonstrates how to create a bar chart from a list of data:

```python
data = ["cat", "dog", "bird", "cat", "dog", "fish", "dog"]
fys.bar(data)
```

---

## Documentation
TODO: Add documentation
"For detailed usage and examples, visit the [official documentation](https://github.com/your-repo-link)."

---

## Contributing

Contributions are welcome!

---

## License

This project is licensed under the MIT License. See the `LICENSE` file for details.

## TODO
- [ ] Add more equations
- [ ] Add more constants
- [ ] Add more unit conversions
- [ ] Create documentation
- [ ] Create a documentation website, where you can search for equations (like the Tailwind documentation)
- [ ] Add integralcalculations for e.g. inertia