semvec/pypi-packages huggingface dataset:
MICView 1.0.0
Open-source GUI for visualization of multimodal medical images and segmentations viewing
Requires Python: >=3.8

# MICView
This project is an open-source API of a GUI for visualization of multimodal medical images and segmentations viewing. It was produced in a scenario of need for the assistance of graphical tools for the study of deep-learning neural networks for segmenting medical images, and also as the final project of my Bachelor's degree on Computer Engineering in FEEC-Unicamp. The project was made using Tkinter, and designed in a MVC software architecture (Model View Controller).

## Requirements
The software was developed and tested in Ubuntu 22.04, and tested on Windows. The minimum required version of Python is 3.8, others required libs are described in [requirements](./requirements.txt)

## Installation
It is suggested to create a Python environment with Conda:

    conda create -n micview python=3.8
    conda activate micview

To download the package, do:

    git clone https://github.com/MICLab-Unicamp/micview
    cd micview
    pip install . 

## Using
You can use the API calling inside a terminal, and calling functions of micview inside your Python code, to call micview inside a terminal do:

    micview

You can also pass arguments as the file path, the mask path, and if you want to see the image in the original shape or in a squared shape.

    micview --input 'filepath' --mask 'maskpath' --resized

In the above example the GUI will open with an image and segmentation loaded, and in a squared shape. To call the GUI inside your Python code, you can use the functions:

    micview.open() #Opens the GUI
    micview.openfile(file='filepath', mask: optional ='maskpath', resized: optional = False (default)) #Opens the GUI with an image

Pay attention that if you call this functions inside a Python code, the programm will block in this line until you closes the MICView window, it occurs because the Tkinter mainloop is a blocking process.
edgegap-migrate 1.6.1
The Edgegap library to handle migrations. It is designed for use within the Edgegap organization.
Requires Python: <4.0,>=3.10

# Edgegap Scheduling Library

This is the README for the Edgegap Scheduling Helper, which is part of the Edgegap suite of helpers.
This library provides utilities for helping with Scheduling Task.

## Table of Contents

- [Overview](#overview)
- [Installation](#installation)
- [Usage](#usage)
- [Running Tests](#running-tests)
- [Uploading Package](#uploading-package)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)

## Overview

The Edgegap Scheduling library includes various tools and helpers for helping with Scheduling Task. It is
designed for use within the Edgegap organization.

## Installation

To install this library, ensure you have Python and `poetry` installed. Then, use the following command:

```bash
poetry add edgegap-scheduling
```

Ensure you have the necessary permissions to install and use this library, as it is intended for Edgegap employees only.

## Usage

Please consult Obsidian Documentation for Usage

## Running Tests

To run tests for this library, you need to have pytest installed. You can install dev dependencies with:

```bash
poetry install --with=dev
```

then run

```bash
pytest
```

This will execute all the tests in the tests folder.

## Uploading Package

To upload the distribution to pypi, you will need an API token from Pypi

```bash
poetry config pypi-token.pypi <your-api-token>
poetry version x.x.x
poetry publish --build
```

## Contributing

If you'd like to contribute to this library and you're an Edgegap employee, please follow these steps:

- Fork the repository.
- Create a new branch for your changes (e.g., feature/my-feature).
- Commit your changes with a clear message.
- Push your branch to your fork.
- Open a Pull Request, explaining the changes and providing any necessary context.

## License

This software is proprietary to Edgegap. Only current Edgegap employees are allowed to use this library. Refer to the
LICENSE file for detailed licensing information.

## Contact

For support or questions related to this library, please contact support@edgegap.com.

## Acknowledgements

Thanks to the Edgegap development team for creating and maintaining this library.
juan-stats 2.1
Probability density or mass function calculator for Binomial and Gaussian distributions

<p align="center">
  <img src="https://drive.google.com/uc?id=10F8iwc-wW0PTSe3C3sia579Jl2ll5jfP" alt="logo" width="430">
</p>


Python module that calculates the probability density  or mass function, along with the median and standard deviation
for numerical datasets exhibiting Gaussian or Binomial distributions.


### Installation
```
pip install juan-stats
from juan_stats import *
```
### Demo in Google Colab
Look the package in action [here](https://colab.research.google.com/drive/1LDSrWoDuMq_DDGVm8y6ilCBCLXjQDEEY?usp=sharing)

### Features Gaussian Distribution
- Read numerical datasets from a CSV file or  a Python list
```
gaussian_one = Gaussian()
gaussian_one.read_data_file("numbers.csv")

#another option is to read the data from a list
gaussian_one.data = [10,10,10,19,15,15,12,12,2,9,8,8,5] 
```

- Calculate the mean, standard deviation, and relative probability density at a specific point in a Gaussian distribution
```
print(gaussian_one.calculate_mean())
print(gaussian_one.calculate_stdev())
print(gaussian_one.pdf(49))
```

- Plot Histogram of the data or the Normalized histogram along with the probability density function 
```
gaussian_one.plot_histogram()
gaussian_one.plot_histogram_pdf()
```

### Features Binomial Distribution
- Calculate the mean, and standard deviation given some probability p and number of trials n
```
Binomial(0.4, 25)
#or
Binomial(p=0.4, n=25)
```

- Read numerical datasets from a CSV file or a Python list. The dataset should be composed of 0 and 1.
- Calculate the mean, standard deviation, and probability mass at a specific point in a Binomial distribution
```
binomial_one.data = [0,1,0,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1] 
print(binomial_one.calculate_mean())
print(binomial_one.calculate_stdev())
print(binomial_one.pdf(5))
```

- Plot the probability mass function of the binomial distribution
```
binomial_one.plot_bar_pdf()
```

#### Contributing
Submit a pull request to this [Github repository](https://github.com/juandavidp9/juan-stats) and add other distributions you may like!
EnglishLanguageAPI 1.0.1
A CLI tool for looking up the meanings of things.
Requires Python: >=3.11

# Lab-93 Dictionary API & Linguistic Analysis Tools
This package offers a simple command-line command for scraping the definition of a word from `dictionary.com`
and returning it to the user.

It also provides a mechanism for building your own in-house dictionary from a list of over 50,000 words.


## Installation
The module is available on Pip, to install to a virtual environment type:
```
pip install EnglishLanguageAPI
```


### Single-Case Usage
To look up the definition of a single word, use the `--word={$WORD}` flag, where $WORD is the word to search for.
```
EnglishLanguageAPI --word={word}
```


### Dictionary Database Builder
The library also includes a system for building an offline dictionary by automating the process of selecting
random words to look up and then writing the word and its definition to a sqlite3 database file.

- `--database`: Write the definition to as many random words as time allows for.
- `--resume`: Keep track of what words haven't been entered into the database.
- `--disposable-wordlist`: A consumable copy of the 50000-wordlist.txt file, for keeping track
                           of what still needs to be defined.
- `--wordlist`: Filepath to the local hardcopy of the 50000-wordlist.txt file.
scrapkit 2.2
WebScrapping in 3 lines of code

# ScrapKit 2.2 - WebScrapping is now easy

## Usage

In ScrapKit 2.2 We added a Function from which Now you can scrape multiple pages of a website that you can print or save to any type of file. Also we added two more functions `cleanedText` and `getAttributeFromElements` 

## Syntax

```python
import scrapkit as sk

# Example URL
url = "https://en.wikipedia.org"

# Get attributes (example: get all 'src' attributes from 'img' tags)
image_src_attributes = sk.getAttributeFromElements(url, 'img', 'src')
sk.saveFile (image_src_attributes, filename = 'att.txt')
# OR
print (image_src_attributes)

# Scrape multiple pages
base_url = "https://pypi.org/"
num_pages = 3
all_links = sk.scrapeMultiplePages(base_url, num_pages)
sk.saveFile (all_links, filename = 'links.txt')
# OR
print (all_links)

# Clean text
dirty_text = "<p>Hello <b>world</b>!</p>"
cleaned_text = sk.cleanText(dirty_text)
sk.saveFile (f'cleaned text: {cleaned_text}', filename = 'cleaned.txt')
# OR
print (cleaned_text)
```

# Founder

ScrapKit is a very useful python package that is made by "Ali Lodhi". Ali Lodhi is from Pakistan, He loves to write code in python and to ease people's work. Recently Ali Lodhi is working on the next update of this package

# Versions

## ScrapKit 1 (Old)

- ScrapKit 1.0 - It provide you to fetch whole HTML of the website
- ScrapKit 1.1 - It provides you to fetch HTML, Title and the Text of the website
- ScrapKit 1.2 - You can save the Fetched HTML in a `.html` file
- ScrapKit 1.3 - Bug Fixes
- ScrapKit 1.4 - You can fetch the links given in any website
- ScrapKit 1.5 - You can fetch the URL of the image on the webpage
- ScrapKit 1.6 - Now you can get Elements data by using their IDs and Classes
- ScrapKit 1.7 - Bug Fixes

## ScrapKit 2 (Latest)

- ScrapKit 2.0 - Added 4 new functions
- ScrapKit 2.1 - Added `saveFile` function
- ScrapKit 2.2 - Added 3 new functions