plagchecker 1.0.1

plagchecker focuses on using wwww.prepostseo.com plagairism checker facility.

The python package is focused on checking Plagiarism from covered content it is the extension of service offered by prepostseo (https://www.prepostseo.com/plagiarism-checker)

Install

For installation one can proceed to https://pypi.org/project/plagchecker/ or can use

pip install plagchecker

Usage

The package focus on usage for checking plagiarised content and amount of plagiarised content present in the data spread over upto 5000 words or less with non-premium version of https://www.prepostseo.com/plagiarism-checker

Modules

There is 1 module named init.py

Class currently present in module: Checker

initialization of class: Checker()

The constructor takes in 1 manadatry argument i.e the APIKEY provided by www.prepostseo.com by signning up for free version.

Methods: Total of 7 Methods are present in Class: Checker

Method 1: init(self,apiKey):

Method is default constructor of the class Checker and takes in 1 manadatry argument i.e the APIKEY from www.prepostseo.com

Method 2: getDataLen(self,data):

Method returns boolean value based on the count of words present in data if count is less than or equal to 5000 words return True else False.

Method 3: response(self,data):

Method returns 2 (two) values in string format:

1. status code of the querry: i.e 200 for successful execution in string format.
2. json response received upon successful execution or empty string

Method 4: getPlagPercent(self):

The function is used to get the percentage of plagiarised content. It returns the %(percentage) value in string format

Method 5: getUniquePrecent(self):

The function is used to get the precentage of unique content present in the data. It returns the %(percentage) value in string format

Method 6: getSources(self):

The function is used to get the sources from where the content was taken if found plagiarised in the data. It returns sources in the form of a list.

Method 7: getDetails(self):

The function is used to get the additional details of individual querries in data. It returns the additional details in the form of list.

Created & Maintained By

Shrey Patel

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