Metadata-Version: 2.1
Name: electivegroup
Version: 1.0.61
Summary: A simple resume parser used for extracting information from resumes
Home-page: https://github.com/electivetechnology/cv-parser-python
Author: Chris Dixon
Author-email: chris@recii.io
License: GPL-3.0
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
License-File: LICENSE

pyresparser
===========

::

    A simple resume parser used for extracting information from resumes

Forked from Omkar Pathak (https://github.com/OmkarPathak/pyresparser) 
Customised by [Chris Dixon](https://github.com/chris-wm)

Features
========

-  Extract name
-  Extract email
-  Extract mobile numbers
-  Extract skills
-  Extract total experience
-  Extract college name
-  Extract degree
-  Extract designation
-  Extract company names

Installation
============

-  You can install this package using

.. code:: bash

    pip install pyresparser

-  For NLP operations we use spacy and nltk. Install them using below
   commands:

.. code:: bash

    # spaCy
    python -m spacy download en_core_web_sm

    # nltk
    python -m nltk.downloader words

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

Official documentation is available at:
https://www.omkarpathak.in/pyresparser/

Supported File Formats
======================

-  PDF and DOCx files are supported on all Operating Systems
-  If you want to extract DOC files you can install
   `textract <https://textract.readthedocs.io/en/stable/installation.html>`__
   for your OS (Linux, MacOS)
-  Note: You just have to install textract (and nothing else) and doc
   files will get parsed easily

Usage
=====

-  Import it in your Python project

.. code:: python

    from pyresparser import ResumeParser
    data = ResumeParser('/path/to/resume/file').get_extracted_data()

CLI
===

For running the resume extractor you can also use the ``cli`` provided

.. code:: bash

    usage: pyresparser [-h] [-f FILE] [-d DIRECTORY] [-r REMOTEFILE]
                       [-re CUSTOM_REGEX] [-sf SKILLSFILE] [-e EXPORT_FORMAT]

    optional arguments:
      -h, --help            show this help message and exit
      -f FILE, --file FILE  resume file to be extracted
      -d DIRECTORY, --directory DIRECTORY
                            directory containing all the resumes to be extracted
      -r REMOTEFILE, --remotefile REMOTEFILE
                            remote path for resume file to be extracted
      -re CUSTOM_REGEX, --custom-regex CUSTOM_REGEX
                            custom regex for parsing mobile numbers
      -sf SKILLSFILE, --skillsfile SKILLSFILE
                            custom skills CSV file against which skills are
                            searched for
      -e EXPORT_FORMAT, --export-format EXPORT_FORMAT
                            the information export format (json)

Notes:
======

-  If you are running the app on windows, then you can only extract
   .docs and .pdf files

Result
======

The module would return a list of dictionary objects with result as
follows:

::

    [
      {
        'college_name': ['Marathwada Mitra Mandal’s College of Engineering'],
        'company_names': None,
        'degree': ['B.E. IN COMPUTER ENGINEERING'],
        'designation': ['Manager',
                        'TECHNICAL CONTENT WRITER',
                        'DATA ENGINEER'],
        'email': 'omkarpathak27@gmail.com',
        'mobile_number': '8087996634',
        'name': 'Omkar Pathak',
        'no_of_pages': 3,
        'skills': ['Operating systems',
                  'Linux',
                  'Github',
                  'Testing',
                  'Content',
                  'Automation',
                  'Python',
                  'Css',
                  'Website',
                  'Django',
                  'Opencv',
                  'Programming',
                  'C',
                  ...],
        'total_experience': 1.83
      }
    ]
