semvec/pypi-packages huggingface dataset:
spesdebris 0.0.3
Python-based desktop automationand cross-device communication suite

# spesdebris

[![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/) [![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)

/'speÉŞs 'deÉŞbri:/

A Python-based PC automation and cross-device communications suite.

## Disclaimer

This is an experimental package, use at your own risk.

## Prerequisites

- A PC
- A rooted Android device
- Python 3
- [Automate](https://llamalab.com/automate/)
- [Termux](https://termux.com/) and Termux:Task
- A Dropbox account
- NirCmd (preferably installed from [scoop](https://scoop.sh), as it needs to be in PATH)

## Getting started

1. Generate an asymmetric keypair, and
   1. Save both keys to your computer
   1. Save the private key on your phone
1. Obtain your API keys
   1. [Create a Dropbox app](https://www.dropbox.com/developers/apps) and obtain an OAuth2 access token
   1. [Generate an Automate secret](https://llamalab.com/automate/cloud)
1. Install the required flows for Automate and configure them  
   Note: these are not yet available!
1. Install spesdebris with `pip install spesdebris`
1. Configure the package using `python -m spesdebris configure`
1. Run spesdebris with `python -m spesdebris daemon`
filepy 0.17
File converter to different extensions
Keywords: file,convert,extensions,csv,arff

[![Build Status](https://travis-ci.com/KordianD/filepy.svg?branch=master)](https://travis-ci.com/KordianD/filepy)
[![PyPI version](https://badge.fury.io/py/filepy.svg)](https://badge.fury.io/py/filepy)

# Goal
This is a package which converts files to different types.

# Supported extensions 
- CSV
- ARFF

# Installation
``pip install filepy --upgrade`` 

# Usage

This library is mainly divided into 2 ideas, namely writers and readers.
Readers will read your files, writer will write in appropriate format.

# Available classes:
- CsvReader
- CsvWriter
- ArffReader
- ArffWriter


Suppose that you have a csv file: `example1.csv`.

You want to convert this file to an arff format for instance `converted.arff`

    from filepy.csv_reader import CsvReader
    from filepy.arff_writer import ArffWriter
    from filepy.file_converter import convert

    csv_reader = CsvReader('example1.csv', delimiter=';')
    arff_writer = ArffWriter('converted.arff', delimiter=',')

    convert(input_reader=csv_reader, output_writer=arff_writer)

# Additional options

Each writer and reader has additional options to use.

# CsvReader
CsvReader(path_to_file, delimiter = ',', first_line_column_names = True, skip_first_column = False)

    delimiter - how data is separated, can be regex
    first_line_column_names - uses first line to read columns
    skip_first_column - skips first column of data 

After creating object you can get data from it.

    csv_reader = CsvReader('your/path/to/file')
    data = csv_reader.dto.data
    column_names = csv_reader.dto.data

# CsvWriter    
CsvWriter(path_to_file, delimiter = ',', skip_writing_columns = False)

    delimiter - how data will be separated in generated file
    skip_writing_column - whether first line in generated file should have columns names

# ArffReader
ArffReader(path_to_file, delimiter = ',')

    delimiter - how data is separated, can be regex

After creating object you can get data from it.

    csv_reader = CsvReader('your/path/to/file')
    data = csv_reader.dto.data
    column_names = csv_reader.dto.columns

# ArffWriter
ArffWriter(path_to_file, delimiter= ',')

    delimiter - how data will be separated in generated file