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This library is utility library from digipodium

Project description

A python library which can be used to extraxct data from files, pdfs, doc(x) files, as well as save data into these files. This library can be used to scrape and extract webpage data from websites as well.

Installation Requirements and Instructions

Python versions 3.8 or above should be installed. After that open your terminal: For windows users:

pip install dputils

For Mac/Linux users:

pip3 install dputils

Files Modules

Functions from dputils.files:

  1. get_data:

    • To import, use statement:
      from dputils.files import get_data
      
    • Obtains data from files of any extension given as args(supports text files, binary files, pdf, doc for now, more coming!)
    • sample call:
      content = get_data(r"sample.docx")
      print(content)
      
    • Returns a string or binary data depending on the output arg
    • images will not be extracted
  2. save_data:

    • To import, use statement:
      from dputils.files import save_data
      
    • save_data can be used to write and save data into a file of valid extension.
    • sample call:
      pdfContent = save_data("sample.pdf", "Sample text to insert")
      print(pdfContent)
      
    • Returns True if file is successfully accessed and modified. Otherwise False.

Scrape Modules

Functions from dputils.scrape:

  1. get_webpage_data:

    • To import, use statement:
      from dputils.scrape import get_webpage_data
      
    • get_webpage_data can be used to obtain data from any website in the form of BeautifulSoup object
    • sample call:
      soup = get_webpage_data("https://en.wikipedia.org/wiki/Hurricane_Leslie_(2018)")
      print(type(soup))
      
    • Returns data as a BeautifulSoup object
  2. extract_one:

    • extract_one can be used to extract a data item as a dict from data in a given BeautifulSoup object
    • To import, use statement:
      from dputils.scrape import extract_one
      
    • usage:
      soup = get_webpage_data("https://en.wikipedia.org/wiki/Hurricane_Leslie_(2018)")
      
      dataDict = extract_one(soup, title = {'tag' : 'h1', 'attrs' : {'id' : 'firstHeading'}, 'output' : 'text'})
      print(dataDict)
      
    • Output will be of type dict
    example here
    
  3. extract_many:

    import the functions

    from dputils.scrape import extract_many, get_webpage_data
    

    grap your soup

    url = "https://www.flipkart.com/search?q=mobiles&otracker=search&otracker1=search&marketplace=FLIPKART&as-show=on&as=off"
    soup = get_webpage_data(url)
    

    Provide all the parameters in the dict as shown in the example below.

    target = {
    'tag': 'div',
    'attrs':{'class':'_1YokD2 _3Mn1Gg'}
    }
    items = {
        'tag': 'div',
        'attrs':{'class':'_1AtVbE col-12-12'}
    }
    title = {
        'tag': 'div',
        'attrs':{'class':'_4rR01T'}
    }
    price = {
        'tag': 'div',
        'attrs':{'class':'_30jeq3 _1_WHN1'}
    }
    rating = {
        'tag': 'div',
        'attrs':{'class':'_3LWZlK'}
    }
    link = {
        'tag': 'a',
        'attrs':{'class':'_1fQZEK'},
        'output':'href'
    }
    

    call the functions with correct names

    • soup : from get_webpage_data() function
    • target: the subsection where the contents are present (optional)
    • items : the repeating HTML code the contains the items (required)
    • others will be the names and dicts of items to be extracted just link in extract one
    out= extract_many_1(soup, target=target, items=items, title=title, price=price, rating=rating, link=link)
    
    • Output will be a list of dicts
    print(out)
    

    (optional) Convert the data into pandas dataframe

    import pandas as pd
    df = pd.DataFrame(out)
    print(df)
    
  4. extract_urls

    • extract_urls can be used to extract all urls as a list from data in a given BeautifulSoup object
    • To import, use statement:
      from dputils.scrape import extract_urls
      
    • usage:
      soup = get_webpage_data("https://en.wikipedia.org/wiki/Hurricane_Leslie_(2018)")
      
      urlList = extract_urls(soup, target = {'tag' : 'div', 'attrs' : {'class':'s-matching-dir sg-col-16-of-20 sg-col sg-col-8-of-12 sg-col-12-of-16'}})
      print(urlList)
      
    • Output will be list of urls

These functions can used on python versions 3.8 or greater.

References for more help: https://github.com/digipodium/dputils

Thank you for using dputils!

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