Metadata-Version: 2.1
Name: smart_search
Version: 0.0.5
Summary: A search algorithm for efficient searching in PDFs
Home-page: https://github.com/ItsSiddharth/context_search
Author: Siddharth Menon
Author-email: siddharth.menon1@gmail.com
License: UNKNOWN
Description: # Concept-Search
        
        [![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/ItsSiddharth/context_search/blob/master/LICENSE)   [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) 
        
        ## For source code 
        This the my <a href="https://github.com/ItsSiddharth/context_search">Github repo. </a>
        Contact me for support and PRs are welcome.
        
        ## Usage 
        1. Pip install the package.
        ```
        $ pip3 install smart-search
        ```
        * **NOTE** : Please have the pickle file in the same folder as the python script in which you will use our pip package.
        
        > Here i use the <a href="http://nlp.stanford.edu/data/wordvecs/glove.6B.zip">glove.6B.zip</a> file from Standfords Github repository from the hyperlink.
        
        ## Syntax 
        1. Import the library.
        ```
        >> import smart_search
        ```
        2. Create an object of the class, smart_search.model(). Say, `functioncaller`.
        ```
        >> functioncaller = smart_search.model()
        ```
        3. Now to convert a pdf to a list of lists containing page.no and words after stop word removal, we use the built in function `getting_list_of_words()`. This accepts 1 argument, i.e the path to the pdf and returns the required list to be fed to the model.
        ```
        >> pdf_list = functioncaller.getting_list_of_words('path to your pdf')
        ```
        4. Pass this list to the model along with the word you want to get the search result of using the `perform_skip()` function. This accepts 2 variables, i.e the list produced by the previous function and the word you want to search for and retuns the top 5 relevant search locations of the word you searched for.
        ```
        >> location[0:5] = perform_skip(pdf_list, input_word)
        ```
        5. You can use subprocesses library of python to navigate to the page if you want to.
        
        ## LICENSE
        <a href="https://github.com/ItsSiddharth/context_search/blob/master/LICENSE">MIT</a>
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
