scrape-data-cleaner 0.0.21

A package for cleaning forms of scraped data and convert them to normal text.

Scrape Data Cleaner

Clean scraped data fields to recieve your disired text without unicodes,spaces and other unessesary quirks.

Installation

pip install scrape-data-cleaner

Basic Usage

from cleaner import string_cleaner,price_cleaner,remove_char
print(string_cleaner('Iphone 8   plus \  '))
print(price_cleaner(remove_char('USD 100')))

Modules

string_cleaner :

Cleans strings strings encode and re-encode them in ASCII

string_cleaner_array :

Takes an array of strings encode and re-encode them in ASCII then return an array.

string_cleaner_array_wine:

Takes an array of strings encode and re-encode them in ASCII then return an array however during cleaning does not force removing of spaces and tabs.

price_cleaner:

Performs string cleaning from string_cleaner then converts the response to Integer.

remove_special_char :

Removes special characters from string i.e. * - & e.t.c.

remove_char:

Removes all characters and leaves out only integers.

remove_char_special:

Removes all characters and leaves out only integers but first checks for .00 and replaces that with nothing to avoid getting price with extra 00.

cleanhtml:

Extracts text from HTML and returns a string.

cleanhtml_array:

Extracts text from an array of HTML and returns an array of strings.

cleanhtml_array2:

Extracts text from an array of HTML and returns an array of strings however does string_cleaner for each string.

nbsp_replacer:

Replaces unicode \u00a0 with a space.

ratings_extractor:

Extracts ratings from style for stars. Takes style of this format width:80% and converts that to a rating of 1 to 5.

specs_table_gen:

Takes two arrays and combine them with : return one array.

space_tabs_remover:

Removes spaces and tabs i.e if there is \u,\r ,\n . This is more aggressive.

extract_list:

Extracts text in HTML listlifrom a HTML block. Takes raw HTML and returns an array of strings.

gen_link2:

Receives two strings name of store and the link then creates a custom url

i.e

gen_link2('amazon','https://amazon/product/iphone-7.html')

Results: /amazon/iphone-7

extract_from_ldjson:

Extract a value from ld/json. i.e extract_from_ldjson(ld_json,'name') will extract the name value in the ld/json.

table_shaker:

Only works if your using scrapy. Takes the HTML block with the table and an array of the types of data in table. i.e table_shaker(response.css('table'),['td','td']).

Note: Array can be ['th','td'],['th','th'] depending on the table.

get_description :

Extracts description from HTML and returns an array with dictionaries with keys of either text or title. Takes Raw HTML.