Metadata-Version: 1.1
Name: AmeriResumeParser
Version: 1.0.0
Summary: A simple resume parser used for extracting information from resumes
Home-page: https://github.com/ganeshbabu100/pyresparser
Author: Ganesh Babu
Author-email: ganesh.babu@ameri100.com
License: GPL-3.0
Description: pyresparser
        ===========
        
        ::
        
            A simple resume parser used for extracting information from resumes
        
        Built with ❤︎ and :coffee: by `Omkar
        Pathak <https://github.com/OmkarPathak>`__
        
        --------------
        
        |GitHub stars| |PyPI| |Downloads| |GitHub| |PyPI - Python Version| |Say
        Thanks!| |Build Status| |codecov|
        
        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
              }
            ]
        
        References that helped me get here
        ==================================
        
        -  https://www.kaggle.com/nirant/hitchhiker-s-guide-to-nlp-in-spacy
        
        -  https://www.analyticsvidhya.com/blog/2017/04/natural-language-processing-made-easy-using-spacy-%E2%80%8Bin-python/
        
        -  [https://medium.com/@divalicious.priya/information-extraction-from-cv-acec216c3f48](https://medium.com/@divalicious.priya/information-extraction-from-cv-acec216c3f48)
        
        -  **Special thanks** to dataturks for their `annotated
           dataset <https://dataturks.com/blog/named-entity-recognition-in-resumes.php>`__
        
        Donation
        ========
        
        If you have found my softwares to be of any use to you, do consider
        helping me pay my internet bills. This would encourage me to create many
        such softwares :smile:
        
        +-----------+----+
        | PayPal    |    |
        +===========+====+
        | ₹ (INR)   |    |
        +-----------+----+
        
        Stargazer over time
        ===================
        
        |Stargazers over time|
        
        .. |GitHub stars| image:: https://img.shields.io/github/stars/OmkarPathak/pyresparser.svg
           :target: https://github.com/OmkarPathak/pyresparser/stargazers
        .. |PyPI| image:: https://img.shields.io/pypi/v/pyresparser.svg
           :target: https://pypi.org/project/pyresparser/
        .. |Downloads| image:: https://pepy.tech/badge/pyresparser
           :target: https://pepy.tech/project/pyresparser
        .. |GitHub| image:: https://img.shields.io/github/license/omkarpathak/pyresparser.svg
           :target: https://github.com/OmkarPathak/pyresparser/blob/master/LICENSE
        .. |PyPI - Python Version| image:: https://img.shields.io/pypi/pyversions/Django.svg
        .. |Say Thanks!| image:: https://img.shields.io/badge/Say%20Thanks-:D-1EAEDB.svg
           :target: https://saythanks.io/to/OmkarPathak
        .. |Build Status| image:: https://travis-ci.com/OmkarPathak/pyresparser.svg?branch=master
           :target: https://travis-ci.com/OmkarPathak/pyresparser
        .. |codecov| image:: https://codecov.io/gh/OmkarPathak/pyresparser/branch/master/graph/badge.svg
           :target: https://codecov.io/gh/OmkarPathak/pyresparser
        .. |Stargazers over time| image:: https://starchart.cc/OmkarPathak/pyresparser.svg
           :target: https://starchart.cc/OmkarPathak/pyresparser
        
Platform: UNKNOWN
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
