semvec/pypi-packages huggingface dataset:
st-contextmap-cs 0.0.2
Streamlit component based on Cytoscape.js that allows for creation and editing of context maps
Requires Python: >=3.7

# streamlit-custom-component

Streamlit component based on Cytoscape.js that allows for creation and editing of context maps


## Installation instructions

```sh
pip install st-contextmap-cs
```

## Usage instructions

```python
import streamlit as st

from contextmap_component import contextmap_component
```
drex 0.0.247
DRex package
Requires Python: >=3.8

# Reproducibility repository of the paper "D-Rex: Adaptive Erasure Coding for Efficient Data Storage on Wide-Area Heterogeneous Storage Systems"

All the information are in this depot:

```bash
~$ git clone https://github.com/dynostore/D-rex.git
```

You will find in this repository our schedulers, the state-of-the art algorithms, the simulator of data replications and the informations of the input data nodes used.
You can re-create the figure and result in the tables of the paper using our simulation.

## Simulation

In order to produce figures 5, 7, 8 and 9 one can run:

```bash
~/D-rex$ bash test/all_drex_only.sh
```

Then
```bash
~/D-rex$
```

The results are then in the folder D-rex/plot/combined
wbBase 0.2.13
Base package for WorkBench applications.
Requires Python: >=3.8
Keywords: workbench, wxPython, GUI

# wbBase

This is the base package for WorkBench applications.
Workbench is a plugin based RAD framework for platform independent GUI applications
based on [wxPython](https://pypi.org/project/wxPython/).

## Installation

```shell
pip install wbBase
```

## Documentation

For details read the [Documentation](https://workbench2.gitlab.io/wbbase/).

## Plugins
The following plugins are currently available as individual packages.

- [wbpOutput](https://pypi.org/project/wbpoutput/), 
    an output panel for Workbench applications.
- [wbpShell](https://pypi.org/project/wbpshell/), 
    a shell panel for Workbench applications.
- [wbpLoglist](https://pypi.org/project/wbploglist/),
    a log list panel for Workbench applications.
- [wbpNamespace](https://pypi.org/project/wbpnamespace/),
    a namespace panel for Workbench applications.
- [wbpWidgetinspector](https://pypi.org/project/wbpwidgetinspector/)
    integrates the Widgetinspector in Workbench applications.
- [wbpFilebrowser](https://pypi.org/project/wbpfilebrowser/),
    a file browser panel for Workbench applications.
- [wbpTextedit](https://pypi.org/project/wbptextedit/),
    document templates to create, view and edit some text file types.
- [wbpUItools](https://pypi.org/project/wbpuitools/),
    collection of some useful functions for user interaction in Python scripts.
- [wbpHTMLpanel](https://pypi.org/project/wbpHTMLpanel/),
    a panel to display arbitrary html.
tl-bot 0.1.4
upload files to your telegram channel or group with your telegram bot
Requires Python: >=3
Keywords: telegram, t-bot, telegram-api, telegram-api-bot, telegram-file-upload, telegram-upload

# t-bot

Upload files to your Telegram channel or group with your telegram bot

 [![PyPI version](https://badge.fury.io/py/tl-bot.svg)](https://pypi.org/project/tl-bot/)
 [![Downloads](https://pepy.tech/badge/tl-bot/month)](https://pepy.tech/project/tl-bot)
 [![Downloads](https://static.pepy.tech/personalized-badge/tl-bot?period=total&units=international_system&left_color=green&right_color=blue&left_text=Total%20Downloads)](https://pepy.tech/project/tl-bot)
 ![GitHub Contributors](https://img.shields.io/github/contributors/jakbin/t-bot)
 ![GitHub commit activity](https://img.shields.io/github/commit-activity/m/jakbin/t-bot)
 ![GitHub last commit](https://img.shields.io/github/last-commit/jakbin/t-bot)
 ![Python 3.6](https://img.shields.io/badge/python-3.6-yellow.svg)


## Features
- Progress bar
- You can change file name before upload on telegram

Note : Bot can upload only 50 MB file (with default telegram bot api server url).


## Installation

```sh
pip3 install tl-bot
```

## Usage 
```sh
t-bot setup               # setup your telegram credentials
t-bot setup --cahtid -1001234567890 --token 1234:asdfgjkl --server http://127.0.0.1:8081      # setup your telegram credentials
t-bot reset               # reset to default your telegram credentials
t-bot test                # test telegram bot token
t-bot getid               # get chat id of your connected group or channel
t-bot up {file_name} -c file_caption       # upload Telegram channel or group
t-bot d {url} -c caption                   # download and upload file to your Telegram channel or group
```

# API

The anonfile-upload client is also usable through an API (for test integration, automation, etc)

### tl_bot.test_token(bot_token)

```py
from tl_bot import test_token

test_token(bot_token)   # bot_token type str
```

### tl_bot.uploader(bot_token: str, chat_id: str, file_name: str, server_url: str, caption: str)

```py
from tl_bot import uploader

uploader(bot_token, chat_id, file_name, server_url, caption)    # all arguments must be str
```

### tl_bot.download(url:str, bot_token:str, chat_id:str, caption:str)

```py
from tl_bot import download

download(url, bot_token, chat_id, caption)    # all arguments must be str
```
pc-information 1.0.0
A PC info tool for displaying system information and managing processes
Requires Python: >=3.11
Keywords: system, info, monitoring, processes, pc

<div align="center">

# PC Info

[![DevSkim](https://github.com/wfxey/PC-Info/actions/workflows/devskim.yml/badge.svg)](https://github.com/wfxey/PC-Info/actions/workflows/devskim.yml) ![Python](https://img.shields.io/badge/Python-14354C?style=flat&logo=python&logoColor=white) [![License](https://img.shields.io/badge/License-MIT-blue)](#license)

[![Discord](https://img.shields.io/badge/Discord-5865F2?style=flat&logo=discord&logoColor=white)](https://discord.gg/rfrMnA4XCc)

Our program displays all Informations from your pc and gives you the ability to just export it and send it to the support for an example!

</div>

## Note

More infos can be found in the README file, in doubt just place your questions by direct messages @iv32. or @wfxey. In the case that you can not sent us a message, contact us via our Discord Server (https://discord.gg/t4mYGbErAn).
Please don't directly judge us if we've got something wrong with Licenses if you contact us we will directly solve the issue!

## Installation

- You need:
    - Python
    - Windows 11 or Linux Mint (optional,tested)
odm-api 1.61.0
ODM API
Keywords: OpenAPI, OpenAPI-Generator, ODM API

    This swagger page describes the variantUser API endpoints for ODM. These are typically used to find and retrieve variant data and metadata.  Before carrying out any API calls you will need an API token. API tokens can be obtained under your profile within the Genestack software.  To try out calls in this swagger page:  1.  Click the &#39;Authorize&#39; button below to enter your API token 2.  Scroll to the &#39;Parameters&#39; section for the method you wish to try out and click the &#39;Try it out&#39; button 3.  Enter parameter values that you wish to try 4.  Scroll to the bottom of the Parameters section and click the &#39;Execute&#39; bar that appears    The server response will be in the section that follows.
smtp-tlsa-verify 0.1.1
A small library, command-line utility and JSON/HTTP/FastAPI service to check DANE/TLSA-RRs against SMTP servers.
Requires Python: >=3.11

# smtp-tlsa-verify

## Installing and running the FastAPI-based HTTP/JSON service

Install using the `fastapi` extra option:

```
pip install smtp-tlsa-verify[fastapi]
```

or if using the `uv` package manager:

```
uv add smtp-tlsa-verify --extra fastapi
```

## Installing as a command line utility using pipx

```
pipx install smpt-tlsa-verify
```

After installation you can run the following command to verify: `danesmtp mail.example.com`


## Using as a library

```
pip install smtp-tlsa-verify
```

```
from smtp_tlsa_verify import verify

result = verify("mail.example.com")
print(result)
```
ccobra 1.5.0
The CCOBRA framework.

# Cognitive COmputation for Behavioral Reasoning Analysis (CCOBRA) Framework

[![](https://img.shields.io/pypi/v/ccobra.svg)](https://pypi.org/pypi/ccobra/)
[![](https://img.shields.io/pypi/pyversions/ccobra.svg)](https://pypi.org/pypi/ccobra/)
[![GitHub license](https://img.shields.io/github/license/CognitiveComputationLab/ccobra.svg)](https://github.com/CognitiveComputationLab/ccobra/blob/master/LICENSE)
[![DOI](https://zenodo.org/badge/144011537.svg)](https://zenodo.org/badge/latestdoi/144011537)

[[API Documentation]](https://www.pva.tu-chemnitz.de/ccobra/ccobra-doc/)

## Installation

### PyPi

CCOBRA is available via `pip`. To install the current version, run the following command:

```
$> pip install ccobra
```

to update your installation, run `pip install -U ccobra`.

### Development Version

It is also possible to install a development version of CCOBRA. The difference to the standard version is that changes to the local copy of the repository are directly reflected in the module loaded from Python via `import`. To install the develop version, download a local copy of the repository and run the following commands:

```
$> cd /path/to/repository/
$> python -m pip install --editable .
```

### Running CCOBRA

When installed, CCOBRA can be run on a benchmark file:

```
$> cd /path/to/repository/
$> ccobra benchmark.json
```

Alternatively, the runner script `run_ccobra.py` can be run instead:

```
$> cd /path/to/repository/
$> python run_ccobra.py benchmark.json
```
jaxpy 0.0.0
Add your description here
Requires Python: >=3.10

<div align="center">
<img src="images/jaxpy.png" width="400" alt="logo"></img>
</div>

-----------------

jaxpy is a python package that:
+ makes jax easier to use with full functionality (from a pytorch user point of view)
+ automatic reproducible global random generator
+ integrated with the statefull class implementation of flax nnx


It integrates jax, flax and optax all in one package.

### Install
```bash
pip install jaxpy
```
staaax 1.0.0
Jax based S-matrix stack solver.
Requires Python: >=3.11

# Staaax v1.0.0

![Logo](./docs/assets/logo2.svg)

`staaax` is a convenience wrapper for `sax`, that allows evaluating scattering matrices (S-matrices) for stacks of layered media (also called stratified media).

```{code-cell} ipython3
import staaax
import numpy as np

ns = [1, 2, 3+0.001j, 1]
ds = [1, 0.5]

wl = 1.5
theta_0=np.deg2rad(20)
k0 = 2*np.pi/wl
kx = k0*np.sin(theta_0)

stack, info = staaax.stratified(
  ds, ns, k0, kx, pol="s"
)

S = stack()
S
```