pyresparser 1.0.3

pyresparser

A simple resume parser used for extracting information from resumes

Features

• Extract name

• Extract email

• Extract mobile numbers

• Extract skills

• Extract total experience

• Extract education (not very accurate as of now)

• Extract experience (not very accurate as of now)

Installation

• You can install this package using

pip install pyresparser

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

# spaCy
python -m spacy download en_core_web_sm

# nltk
python -m nltk.downloader words

Supported File Formats

• PDF and DOCx files are supported on all Operating Systems

• If you want to extract DOC files you can install textract for your OS (Linux, MacOS)

• Note: You just have to install textract (and nothing else) and doc files will get parsed easily

CLI

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

usage: pyresparser [-h] [-f FILE] [-d DIRECTORY]

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

For extracting data from a single resume file, use

pyresparser -f <resume_file_path>

For extracting data from several resumes, place them in a directory and then execute

pyresparser -d <resume_directory_path>

For extracting data from remote resumes, execute

pyresparser -r <path_to_remote_resume_file>

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:

[{'education': [('BE', '2014')],
  'email': 'omkarpathak27@gmail.com',
  'experience': [' Schlumberger DATA ENGINEER Pune'],
  'mobile_number': '8087996634',
  'name': 'Omkar Pathak',
  'no_of_pages': 3,
  'skills': ['Python',
             'C',
             'Technical',
             'Linux',
             'Machine learning',
             'System',
             'Html',
             'C++',
             'Security',
             'Testing',
             'Content',
             'Apis',
             'Engineering',
             'Payments',
             'Django',
             'Excel',
             'Admissions',
             'Mysql',
             'Windows',
             'Automation',
             'Opencv',
             'Website',
             'Css',
             'Js',
             'Algorithms',
             'Flask',
             'Programming',
             'Writing',
             'Training',
             'Php',
             'Reports',
             'Photography',
             'Open source',
             'Github',
             'Analytics',
             'Api'],
  'total_experience': 0.58}]

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)

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 :)