semvec/pypi-packages huggingface dataset:
lluv 1.2.6.dev63
Front end for the linux command DD with a progress bar.
License: MIT
Keywords: python
github
dd
progress
dd-frontend

# L.L.U.V.
The **LLUV** machine (or Linux Live Usb Vending) machine is a service that allows <br />
users to select an image from a repository and write it to a usb storage device with <br />
an easy to use user interface. The backend uses DD so use with care. If the usb device <br />
is allocated and writable, a block size will automatically be generated for  <br />
optimal performance.

**LLUV** was originally designed to run in a kiosk fashion, and read from large lists of images, both <br />
local and remote.<br />

Note: The DD process is completely isolated from LLUV, therefor, if a drive is corrupted, <br />
it was probably DD's alter ego; Disk Destroyer.

# Dependencies
lsscsi - for discovering usb storage devices <br />
DD - for writing the image <br />
Awk - for testing mount location <br />

Note: lluv_simple_cli has no dependencies besides dd itself

# Run
Note:_lluv needs root for storage device access_ <br />

To start the lluv console run:<br />
**sudo lluv.lluvconsole**  This will allow an option of interfaces along with automatic<br />
terminal resizing. <br />

**sudo lluv.cli**  <br />

**sudo lluv.tui** Note: Terminal will not be auto resized without using lluvconsole so<br />
the application may crash if the terminal is to small.<br />

**sudo lluv.simple_cli.py** A simple lluv cli. Basically a simplified dd with a progress bar <br />

# The TUI
Written using the [npyscreen](https://github.com/pfalcon-mirrors/npyscreen "npyscreen") library.
The TUI was designed to be used as a kiosk and therefore has no quit option <br />
(use CTRL-C) and must be used in larger terminal formats.

# Configuration file
Edit values such as the path to the images, drives to ignore, leeway in recommended <br />
drive capacity, and more.

# Image Categories
By default, Images in the image directory specified in the config will be put in the No-Category <br />
category. To create Image categories, create a subdirectory and place images of said category inside. <br />
For example, placing fedora images in the directory /"default img path"/Fedora would render them in the <br />
"Fedora" category. Categories will be sorted alphabetically.

# Compatible Operating Systems
Linux

# Current Version: 1.2
1.2 = 1/26<br />
    - lluv console <br />
    - auto term resize <br />

1.1 = 1/19<br />
    - .lluvrc<br />
    - bug fixes<br />
    - code cleanup<br />

1.0 = 1/18<br />
    - prototype<br />
crawl_trulia 0.0.4
Trulia Crawler Tool Set
License: MIT

.. image:: https://travis-ci.org/MacHu-GWU/crawl_trulia-project.svg?branch=master

.. image:: https://img.shields.io/pypi/v/crawl_trulia.svg

.. image:: https://img.shields.io/pypi/l/crawl_trulia.svg

.. image:: https://img.shields.io/pypi/pyversions/crawl_trulia.svg


Welcome to crawl_trulia Documentation
===============================================================================
This is a small project provide url route, html parse tools to crawl www.trulia.com.


**Quick Links**
-------------------------------------------------------------------------------
- `GitHub Homepage <https://github.com/MacHu-GWU/crawl_trulia-project>`_
- `PyPI download <https://pypi.python.org/pypi/crawl_trulia>`_
- `Install <install_>`_
- `Issue submit and feature request <https://github.com/MacHu-GWU/crawl_trulia-project/issues>`_


**Usage**
-------------------------------------------------------------------------------
A real example:

.. code-block:: python

    >>> from crawl_trulia.urlencoder import urlencoder
    >>> from crawl_trulia.htmlparser import htmlparser
    >>> from crawlib.spider import spider # install crawlib first

    # use address, city and zipcode
    >>> address = "22 Yew Rd"
    >>> city = "Baltimore"
    >>> zipcode = "21221"

    >>> url = urlencoder.by_address_city_and_zipcode(address, city, zipcode)
    >>> html = spider.get_html(url)
    >>> house_detail_data = htmlparser.get_house_detail(html)
    >>> house_detail_data
    {
        "features": {}, 
        "public_records": {
            "AC": "a/c", 
            "basement_type": "improved basement (finished)", 
            "bathroom": 2, 
            "build_year": 1986, 
            "county": "baltimore county", 
            "exterior_walls": "siding (alum/vinyl)", 
            "heating": "heat pump", 
            "lot_size": 7505, 
            "lot_size_unit": "sqft", 
            "partial_bathroom": 1, 
            "roof": "composition shingle", 
            "sqft": 998
        }
    }

    # usually combination of address and zipcode is enough
    >>> address = "2004 Birch Rd"
    >>> zipcode = "21221"

    >>> url = urlencoder.by_address_and_zipcode(address, zipcode)
    >>> html = spider.get_html(url)
    >>> house_detail_data = htmlparser.get_house_detail(html)

    
.. _install:

Install
-------------------------------------------------------------------------------

``crawl_trulia`` is released on PyPI, so all you need is:

.. code-block:: console

    $ pip install crawl_trulia

To upgrade to latest version:

.. code-block:: console

    $ pip install --upgrade crawl_trulia
crawl_zillow 0.0.1
Zillow Crawler Tool Set
License: MIT

.. image:: https://travis-ci.org/MacHu-GWU/crawl_zillow-project.svg?branch=master

.. image:: https://img.shields.io/pypi/v/crawl_zillow.svg

.. image:: https://img.shields.io/pypi/l/crawl_zillow.svg

.. image:: https://img.shields.io/pypi/pyversions/crawl_zillow.svg


Welcome to crawl_zillow Documentation
===============================================================================
This is a small project provide url route, html parse tools to crawl www.zillow.com.


**Quick Links**
-------------------------------------------------------------------------------
- `GitHub Homepage <https://github.com/MacHu-GWU/crawl_zillow-project>`_
- `PyPI download <https://pypi.python.org/pypi/crawl_zillow>`_
- `Install <install_>`_
- `Issue submit and feature request <https://github.com/MacHu-GWU/crawl_zillow-project/issues>`_


.. _install:

Install
-------------------------------------------------------------------------------

``crawl_zillow`` is released on PyPI, so all you need is:

.. code-block:: console

	$ pip install crawl_zillow

To upgrade to latest version:

.. code-block:: console

	$ pip install --upgrade crawl_zillow
python-daily-med 0.1.0b76
Interact with US NLM Daily Med API using Python.
License: MIT

|License MIT| | |Build Status| | |Coveralls Status| | |Codecov Status| | |Code Climate|

================
Python Daily Med
================

This library interacts with the United States National Library of Medicine's Daily
Med API.

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

* Install Python requirements ``pip install -r ./requirements``

Setup
=====

* 

Usage
=====

* `Read The API Documentation <https://laslabs.github.io/python-daily-med>`_

Import and Instantiate
----------------------

Importing an instantiating the Daily Med object:

.. code-block:: python

   from daily_med import DailyMed
   dm = DailyMed()

Structured Product Label Metadata
---------------------------------

`get_spls` mirrors the `/spls` interface as documented `here
<https://dailymed.nlm.nih.gov/dailymed/webservices-help/v2/spls_api.cfm`_.

To get an iterator of all SPLs:

.. code-block:: python

   spl_metas = dm.get_spls()

You can also perform an SPL search using any of the standard query parameters:

.. code-block:: python

   simvastatin_metas = dm.get_spls(drug_name='Simvastatin')

Structured Product Label Documents
----------------------------------

Once you have a `set_id` for an SPL, you can get its document:

.. code-block:: python

   spl_document = dm.get_spl('0be2e371-1f05-48d7-8f2e-f2024f3305f3')

An SPL Document is basically just a dictionary representing the parsed XML
document.

Known Issues / Road Map
=======================

-  SPLDocument is only Python 2 compatible. Generate a Python3 version and integrate
   an import switch for py2/3. Downfall is that this will add another 6mb of code to
   the repo & coverage will be inaccurate because not everything is testable at once.

Credits
=======

Images
------

* LasLabs: `Icon <https://repo.laslabs.com/projects/TEM/repos/odoo-module_template/browse/module_name/static/description/icon.svg?raw>`_.

Contributors
------------

* Dave Lasley <dave@laslabs.com>

Maintainer
----------

.. image:: https://laslabs.com/logo.png
   :alt: LasLabs Inc.
   :target: https://laslabs.com

This module is maintained by LasLabs Inc.

.. |Build Status| image:: https://api.travis-ci.org/LasLabs/python-daily-med.svg?branch=master
   :target: https://travis-ci.org/LasLabs/python-daily-med
.. |Coveralls Status| image:: https://coveralls.io/repos/LasLabs/python-daily-med/badge.svg?branch=master
   :target: https://coveralls.io/r/LasLabs/python-daily-med?branch=master
.. |Codecov Status| image:: https://codecov.io/gh/LasLabs/python-daily-med/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/LasLabs/python-daily-med
.. |Code Climate| image:: https://codeclimate.com/github/LasLabs/python-daily-med/badges/gpa.svg
   :target: https://codeclimate.com/github/LasLabs/python-daily-med
.. |License MIT| image:: https://img.shields.io/badge/license-MIT-blue.svg
   :target: https://opensource.org/licenses/MIT
   :alt: License: AGPL-3