semvec/pypi-packages huggingface dataset:
manrododex 1.0.5
A manga downloader for mangadex
License: MIT
Keywords: mangadex,manga,downloader

|logo|

**A manga downloader for mangadex using their** `API <https://api.mangadex.org/docs/>`_

|license| |issues| |pyversions| |CI| |PyPI| |rtfd|

Features
========

- Threads support for faster downloads.
- Uses queue for safe threading and better memory usage.
- Creates a series.json file like mylar. (
  see `Komga <https://komga.org/guides/scan-analysis-refresh.html#import-metadata-generated-by-mylar>`_
  and `mylar3 <https://github.com/mylar3/mylar3/wiki/series.json-examples>`_ )
- Can be used to automate the download of manga in combination with crontabs/Scheduled Tasks.
- Manrododex makes it possible to download multiple manga with little to user interaction.
- A possibly wrong Japanese translation of the name.
- Bugs

Inspiration
===========

I might have stolen some ideas from these awesome projects.

- `manga-py <https://github.com/manga-py/manga-py>`_
- `mangadex-dl <https://github.com/frozenpandaman/mangadex-dl>`_
- `MangaDex.py <https://github.com/Proxymiity/MangaDex.py>`_
- `Qtile <https://github.com/qtile/qtile>`_

Maintainer
==========

`@Sydiepus <https://github.com/Sydiepus>`_ GPG: ``BD1D 09DF 8A49 E7A6 C705 3B8A 7D6C DB7E 575A C12A``

.. |logo| image:: https://raw.githubusercontent.com/Sydiepus/Manrododex/main/logo.gif
    :target: https://manrododex.readthedocs.io/en/latest/
.. |license| image:: https://img.shields.io/github/license/Sydiepus/Manrododex.svg
    :target: https://github.com/Sydiepus/Manrododex/blob/main/LICENSE
.. |issues| image:: https://img.shields.io/github/issues/Sydiepus/Manrododex.svg
    :target: https://github.com/Sydiepus/Manrododex/issues
.. |pyversions| image:: https://img.shields.io/pypi/pyversions/manrododex.svg
    :target: https://pypi.org/project/manrododex/
.. |CI| image:: https://github.com/Sydiepus/Manrododex/actions/workflows/CI.yml/badge.svg
    :target: https://github.com/Sydiepus/Manrododex/actions
.. |PyPI| image:: https://img.shields.io/pypi/v/manrododex.svg
    :target: https://pypi.org/project/manrododex/
.. |rtfd| image:: https://readthedocs.org/projects/manrododex/badge/?version=latest
    :target: https://manrododex.readthedocs.io/en/latest/?badge=latest
median-housing-prediction 0.0.4
A module with scripts to download housing data, train machine learning models and analyze their performance
License: MIT
Requires Python: >=3.8

# Median housing value prediction

The housing data can be downloaded from https://raw.githubusercontent.com/ageron/handson-ml/master/. The script has codes to download the data. We have modelled the median house value on given housing data.

The following techniques have been used:

 - Linear regression
 - Decision Tree
 - Random Forest

## Steps performed

 - We prepare and clean the data. We check and impute for missing values.
 - Features are generated and the variables are checked for correlation.
 - Multiple sampling techinuqies are evaluated. The data set is split into train and test.
 - All the above said modelling techniques are tried and evaluated. The final metric used to evaluate is mean squared error.

## Setup for development

## Create conda environment

conda create -n myenv python=3.8
or
conda env create -f env.yml

## Activate

conda activate myenv

# verify the new wnvironment was installed correctly

conda env list

## Usage
## Install package

pip install median-housing-prediction

It will install all the dependencies and the housing package

Python Script

python -m house_pred.ingest_data
python -m house_pred.train
python -m gouse_pred.score
pia-cli 0.1.1
PIA - Python Intelligent Assistant
License: MIT
Requires Python: >=3.6
Keywords: pyton cli assistant

A Python Intelligent Assistant (PIA, pronounced as _piya_) which runs on the command line interface.

## Dependencies
- [typer](https://pypi.org/project/typer/) - To create a CLI application
- [rich](https://pypi.org/project/rich/) - Printing results and errors
- [pytest](https://pypi.org/project/pytest/) - Test cases
pcap-handler 0.1.3
Convert a pcap file into pandas DataFrame or CSV
License: MIT

# import library as:
	from pcap_handler import *
				or
	from pcap_handler import pcapHandler
				or
	from pcap_handler import dfHandler

# Make an object of library
## To convert pcap to pandas DataFrame:
	pcap2df = pcapHandler(file="path to pcap file", verbose=True)
	df = pcap2df.to_DF(head=True)

## To conver DataFrame to CSV:
	df2csv = dfHandler(dataFrame=df, verbose=True)
	df2csv.to_CSV(outputPath="path to save csv")

### Descriptive README soon...