semvec/pypi-packages huggingface dataset:
link_preview 1.0
Python package to get elements that make link preview
License: MIT
Keywords: preview,link

link\_Preview
=============

A python module that gathers elements required for linkPreview.

Overview
--------

link\_preview is now a fashionable way of sharing links in social media.
The contents of what the preview is made up are:-

::

        1. og.title:-
            Title of the preview. 
            In HTML: <meta property="og.title" content="XYZ">
            Value: XYZ
            
        2. og.description:-
            Description of the preview.
            In HTML: <meta property="og.description" content="XYZ">
            Value: XYZ
            
        3. og.image:-
            Image of the preview.
            In HTML: <meta property="og.image" content="XYZ">
            Value: XYZ
            
        4. title:-
            if 'og:title' is not found, this becomes the Title.
            In HTML: <title>XYZ</title>
            Value: XYZ
            
        5. meta description:-
            if 'og:description' is not found, this becomes the Description.
            In HTML: <meta name="description" content="XYZ">
            Value: XYZ
            
        6. favicon:-
            if 'og:image' is not found, this becomes the Image.
            In HTML: <link rel="shortcut icon" href="XYZ" type="image/x-icon">
            Value: XYZ
            
        7. website:-
            Host website for the link.
            

Reference:- `richpreview <https://richpreview.com>`__ (from where I
learned)

This module fetches all these data and combines those into a dictionary.

A sample WhatsApp link\_preview:-

::

        #######################################
        #   I    #    Title                   #
        #   M    #    Description             #
        #   A    #                            #
        #   G    #    website                 #
        #   E    #                            #
        #######################################

Usage:-

::

        from link_preview import link_preview
        dict_elem = link_preview.generate_dict(url) # this is a dict()
        
        # Access values
        title = dict_elem['title']
        description = dict_elem['description']
        image = dict_elem['image']
        website = dict_elem['website']

Insatallation
-------------

To install from pip, use the following command

::

        pip install link_preview

to update, use

::

        pip install -U link_preview

License
-------

MIT
word2wiz 0.3.1
A tool to create wizard configurations from MS word documents
License: MIT
Keywords: word2wiz document-wizard docwiz spell

# Word2Wiz

Command line tool and web application to convert Word documents to Document
Wizard configurations.

### Requirements

For the command line tool:

- python3
- pip
- spell

To create a server:

- vagrant

To use the converter from the command line you can install the necessary
dependencies with pip:

```
pip install -r requirements.txt
```

To create a server you can run a virtual machine with vagrant (vagrant and
virtualbox are needed):

```
vagrant up
vagrant provision
```

This will download the OS and install dependencies inside that virtual machine.

If you don't want to create a virtual machine, you can also just use the _very
limited_ flask server, runing

```
python3 server.py
```

### How to run it

To run the converter form the 

### How it works

This tool parses an input docx document, looking for text between the marks `«`
and `»`. Then, it generates a Spell file, generating questions based on those
matches. Finally, the spell file is compiled ang an XML is generated with the
Wizard Configuration.

In the case of the web interface, the output will be a zip file containing the
wizard configuration XML, the intermediate Spell and a TXT with the link
between the questions and the metadatas.

### TODO:

- [ ] Remove the zip files after the session is closed.
- [ ] Handle colisions in the uploaded files. Two files can have the same name.
fundoshi 0.0.8
Get manga series & chapter data from various reader sites.
License: MIT

***************************************
Fundoshi: Simple, lean, mean manga API.
***************************************

Fundoshi provides a consistent Python API to extract data from various online
manga reader sites.

=============
Documentation
=============

http://fundoshi.nerdyweekly.com/

=======
License
=======

Fundoshi is released under the MIT license. See `LICENSE`.