semvec/pypi-packages huggingface dataset:
elvia-vault 0.1.1
elvia-vault Python package

# [elvia-vault](https://pypi.org/project/elvia-vault): Authenticate against an Elvia vault and fetch secrets

## To install:

`pip install elvia-vault`

## Usage:

`from elvia_vault import VaultClient`

```
vault = VaultClient()
vault.get_value(secret_path)
```

## Environment variables that need to be set up before use

- `VAULT_ADDR`: The vault endpoint
- `GITHUB_TOKEN`: If Github is the preferred authentication method

## Publishing a new version to PyPI

Run these from the repo root folder. It requires [setting up an account](https://pypi.org/account/register/) on PyPI, the Python Package Index. [See the package publishing guide here](https://packaging.python.org/tutorials/packaging-projects)

```
python3 -m pip install --upgrade build
python3 -m build
python3 -m pip install --user --upgrade twine
python3 -m twine upload dist/*
```
badges-io 1.0.8
Uploads total coverage for displaying badge
Keywords: badge,shield,shields.io

# badges_io

Uploads total badge data to an online service running at https://badges.vidstige.se/

## Usage
Just issue

    python3 -m badges_io coverage 97%

Here the "coverage" is a subject appearing to the left in the badge, while
"97%" here is the status of the badge, appearing to the right.

The color of the badge will be auto computed from the status. A third argument
will override the color, e.g. "green".

to upload coverage to the badges service. `badges_io` will try to autodetect the
repo slug (e.g. "user/repo") by first looking at the origin remote of the
current git repo, and also using environment variables if run on Travis CI.

## Author
Samuel Carlsson
ProText 0.0.4
A text Preprocessing & Feature extraction package for NLP applications
Requires Python: >=3.6

# ProText makes your Text Preprocessing & Feature extraction tasks easy for NLP applications

A Helper pip package for text prepocessing & feature extraction. 

This pip package helps you execute **text cleaning** like 

   + General cleaning (Removal of URL, @username, addtional whitespaces, Hashtags, punctuations..etc)
   + Stopword removal
   + Adding more stop words to "stopwords.words" library list
   + Stemming, 
   + lemmatiing, 
   + Removal of single or two character word, 
   + Converting to lower case,
   + Removal of digits
   + Spell correction
   + Creating of Wordcloud & line graph

All of these can be executed in a single line of command sequentially in any prefered order or can be executed in multiline.

Also feature extrations like **CountVectorizer & TfidfVectorizer**

> Package can be executed on both panda DataFrames and single line of text

This tool can be really helpful and No one neither needs to rememebr various syntax associated with processing nor packages.

This packages reuses functions from nltk, Textblob and wordcloud for the above operations.

### Assumptions:
   - Assuming python is installed on your system.
   - nltk, Textblob and wordcloud installed on your system

Install `ProText` on your system using :

   ``` 
    pip install ProText 
   ```

## Text Preprocessing user guide on df or text

   + Importing library
       
       ``` 
       from ProText import *        
       ```
        or
       ``` 
       from ProText import gen, low, dig,stopw, lemma, stem, spell, clean_len, WCloud, countvec, tfidf       
       ```

   + Execution of single preprocessing property on dataframe
   
      ```
       dfcleaned['tweets'] = dfcleaned['tweets'].apply(gen)   
      ```
   
   + Adding more stop words to "stopwords.words" library list
   
      ```
       stopadd = ['sample', 'much', 'thank']
      
       df['tweet']= df['tweet'].apply(stopw, args=(stopadd,))
                           or
       df['tweet']= df['tweet'].apply(stopw, args=(['sample', 'much', 'thank'],))
       ```
 
> If there are multiple lines, better convert to Dataframe

 
###  Sequential operation in a single line of command
```
       dfcleaned['tweets'] = dfcleaned['tweets'].apply(gen).apply(low).apply(low).apply(stopw).apply(lemma)
```

### Finally WordCloud
   ```
       WCloud(dfcleaned.tweets)
   ```
## Feature extraction user guide on df or list
+ For CountVectorizer
```
       cv_vect, cv_feature, cvdf = countvec(dfcleaned)
```
+ For TfidfVectorizer
```
       tfidf_vect, tfidf_feature, tfidfdf = tfidf(dfcleaned)
```
tinyjambu 0.0.1
A sample Python project
Requires Python: >=3.6, <4
Keywords: sample,setuptools,development

# A sample Python project

![Python Logo](https://www.python.org/static/community_logos/python-logo.png "Sample inline image")

A sample project that exists as an aid to the [Python Packaging User
Guide][packaging guide]'s [Tutorial on Packaging and Distributing
Projects][distribution tutorial].

This project does not aim to cover best practices for Python project
development as a whole. For example, it does not provide guidance or tool
recommendations for version control, documentation, or testing.

[The source for this project is available here][src].

Most of the configuration for a Python project is done in the `setup.py` file,
an example of which is included in this project. You should edit this file
accordingly to adapt this sample project to your needs.

----

This is the README file for the project.

The file should use UTF-8 encoding and can be written using
[reStructuredText][rst] or [markdown][md use] with the appropriate [key set][md
use]. It will be used to generate the project webpage on PyPI and will be
displayed as the project homepage on common code-hosting services, and should be
written for that purpose.

Typical contents for this file would include an overview of the project, basic
usage examples, etc. Generally, including the project changelog in here is not a
good idea, although a simple “What's New” section for the most recent version
may be appropriate.

[packaging guide]: https://packaging.python.org
[distribution tutorial]: https://packaging.python.org/tutorials/packaging-projects/
[src]: https://github.com/pypa/sampleproject
[rst]: http://docutils.sourceforge.net/rst.html
[md]: https://tools.ietf.org/html/rfc7764#section-3.5 "CommonMark variant"
[md use]: https://packaging.python.org/specifications/core-metadata/#description-content-type-optional
xoodyak 0.0.1
A sample Python project
Requires Python: >=3.6, <4
Keywords: sample,setuptools,development

# A sample Python project

![Python Logo](https://www.python.org/static/community_logos/python-logo.png "Sample inline image")

A sample project that exists as an aid to the [Python Packaging User
Guide][packaging guide]'s [Tutorial on Packaging and Distributing
Projects][distribution tutorial].

This project does not aim to cover best practices for Python project
development as a whole. For example, it does not provide guidance or tool
recommendations for version control, documentation, or testing.

[The source for this project is available here][src].

Most of the configuration for a Python project is done in the `setup.py` file,
an example of which is included in this project. You should edit this file
accordingly to adapt this sample project to your needs.

----

This is the README file for the project.

The file should use UTF-8 encoding and can be written using
[reStructuredText][rst] or [markdown][md use] with the appropriate [key set][md
use]. It will be used to generate the project webpage on PyPI and will be
displayed as the project homepage on common code-hosting services, and should be
written for that purpose.

Typical contents for this file would include an overview of the project, basic
usage examples, etc. Generally, including the project changelog in here is not a
good idea, although a simple “What's New” section for the most recent version
may be appropriate.

[packaging guide]: https://packaging.python.org
[distribution tutorial]: https://packaging.python.org/tutorials/packaging-projects/
[src]: https://github.com/pypa/sampleproject
[rst]: http://docutils.sourceforge.net/rst.html
[md]: https://tools.ietf.org/html/rfc7764#section-3.5 "CommonMark variant"
[md use]: https://packaging.python.org/specifications/core-metadata/#description-content-type-optional
anilistpy 0.1.0
python API wrapper for anilist.co
Requires Python: >=3.6

# Anilistpy ![anilistpy](https://avatars3.githubusercontent.com/u/75199724?s=30&v=4)

![Test](https://github.com/anilistpy/anilistpy/workflows/Test/badge.svg)
[![CodeFactor](https://www.codefactor.io/repository/github/anilistpy/anilistpy/badge)](https://www.codefactor.io/repository/github/anilistpy/anilistpy)
![PyPI - Downloads](https://img.shields.io/pypi/dm/anilistpy)
[![pypi verison](https://img.shields.io/pypi/v/anilistpy.svg)](https://pypi.org/project/anilistpy/)
[![GitHub license](https://img.shields.io/github/license/anilistpy/anilistpy)](https://github.com/anilistpy/anilistpy/blob/master/license)

An easy to use python3 wrapper for anilist.co APIv2 (UNOFFICIAL)

# Installing

## Installing from pypi
```
pip install anilistpy
```

## Build Requirements:

- Rust Toolchain (rustc cargo) 
- Python Toolchain (pip wheel setuptools setuptools-rust)

## NOTE FOR WINDOWS/MAC USERS:

i will only provide binaries for gnu/linux starting from v0.1.x, if you want to use this library on these platforms, you will have to compile from source or install v0.0.5.x, which wont get new features but get bug fixes.

 
Documenation and Examples [here](https://anilistpy.github.io/) 
(note: the Documenation is not complete, if you need help make a issue)

# Change log 0.5.x -> 0.1.x

- moving to rust for better performance 

![agpl3](https://upload.wikimedia.org/wikipedia/commons/thumb/0/06/AGPLv3_Logo.svg/200px-AGPLv3_Logo.svg.png)