semvec/pypi-packages huggingface dataset:
i3-xkb-switcher 0.2.1
Keyboard layout switcher for i3 windows
License: MIT
Requires Python: >=3.7,<4.0

i3-xkb-switcher
===============

## Description

This app records keyboard layout for a i3 windows when you leave them.
And when you come back it is restore keyboard layout.

## Install

```bash
$ pip install i3-xkb-switcher
```

Also you can download compiled binary from [release page](https://github.com/inn0kenty/i3-xkb-switcher/releases).

## Usage

```bash
$ i3-xkb-switcher
```

To enable debug mode run with `--debug` key.

By default it writes logs to stdout. You can specify path by `--log-path` option.
django-activiti 0.2.0
Activiti/Alfresco Process Services integration for Django.
License: MIT
Keywords: bpmn,process engine,activiti,common ground


.. django-activiti documentation master file, created by startproject.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.

Django-Activiti
===============

:Version: 0.2.0
:Source: https://github.com/maykinmedia/django-activiti
:Keywords: bpmn, process engine, activiti, common ground
:PythonVersion: 3.7

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|python-versions| |django-versions| |pypi-version|

Activiti/Alfresco Process Services integration for Django.

.. contents::

.. section-numbering::

Features
========

* Configure Activiti/APS host with credentials
* List process definitions
* Start process instances

Installation
============

Requirements
------------

* Python 3.7 or above
* setuptools 30.3.0 or above
* Django 2.2 or newer


Install
-------

.. code-block:: bash

    pip install django-activiti


Usage
=====

TODO

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    :target: https://travis-ci.org/maykinmedia/django-activiti

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    :alt: Coverage status

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.. |python-versions| image:: https://img.shields.io/pypi/pyversions/django-activiti.svg

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    :target: https://pypi.org/project/django-activiti/
tidyfasta 1.0.5
Sanitise protein FASTA files / data
License: MIT

# tidyfasta

A python program to tidy and sanitise FASTA sequence files.

It can be imported as a package or used directly from the command line.

If run in non-strict mode (default), any sequence that a breaking issue, such as a non-canonical AA, dangerous characters (any non-alphanumeric character with the exception of `_ -`), or is just an ID without a sequence, will be ignored. 
If run in strict mode then an exception is raised.

When run from the command line interface the script will write a file to the same directory as the input file with the prefix `tidied-` followed by the input file name. 
If there is already an output file, then the prefix will be `tidied-UNIXTIME-` where UNIXTIME is the time at which the script was called.

If imported, after calling the class `ProcessFasta`, two member variables are available. 
`ProcessFasta.fasta_array` returns a minimally validated array of strings, where split lines are combined, excess whitespace is removed, and missing names are added.
`ProcessFasta.validated_array` returns a validated_array of objects, where each object has two variables `id` and `sequence`.
The validated array is checked for non-canonical AA in the sequence and banned characters from the ID. 


## Problems and fixes

| Problem                     | Fix (Strict mode)                       |
|-----------------------------|-----------------------------------------|
| Sequence without ID         | ID name added                           |
| Multiline sequence          | One line per sequence                   |
| ID without sequence         | Sequence ignored (Exception raised)     |
| Non canonical AA            | Sequence ignored (Exception raised)     |
| Dangerous characters in ID  | Sequence ignored (Exception raised)     |
| Lowercase AA                | Converts to uppercase AA                |
| Excessive Whitespace        | Removes excessive whitespace            | 

## Install

    pip install tidyfasta

## Usage

#### Command line interface

    $ tidyfasta --input file.txt

    $ tidyfasta --input file.txt --strict --single

    $ tidyfasta --input file.txt --version

    $ tidyfasta --input file.txt --help


#### Script

    from tidyfasta.common.process import ProcessFasta

    input_file = "sample.txt"

    np = ProcessFasta(input_file, strict=True, single=False)

    fasta_array = np.fasta_array
    print(fasta_array)

    for i in np.validated_array:
        print(i.id+"\n")
        print(i.sequence+"\n")

    np.write_fasta()
nlp-tools-py-lib 0.1.1
simple nlp library
License: MIT
Requires Python: >=3.7,<4.0

# nlp-tools-py-lib
python simple nlp library

## installation

````shell script
pip install nlp-tools-py-lib
````

## usage

````python
# main.py
from nlp_tools.preprocessing import Preprocessing
from nlp_tools.loaders import MdLoader
from nlp_tools.representations import MergedMatrixRepresentation
from nlp_tools.classifiers import ClassificationProcessor, NaiveBayseTfIdfClassifier

TRAIN_PATH = 'demo_training.md'

def build_classifier():
    loader = MdLoader(TRAIN_PATH)
    processor = Preprocessing(loader)
    repres = MergedMatrixRepresentation(processor.data)
    classifier = ClassificationProcessor(NaiveBayseTfIdfClassifier(), repres)
    classifier.train()

    def predict(text: str):
        message = repres.process_new_data(processor.process_sentence(text))
        intent, score = classifier.predict(message)
        return intent, score
    return predict
````

``training.md`` example :

````markdown
# intents

## my_first_intent_name

### responses

- ...

### example

- ...
````