Resume Parser & Ranker

Resume Parser | Resume Ranker | Resume Summariser

• Collab Notebook

Features

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

And many more ....

Installation (users)

• You can install this package using

  • pip install sourceparser

• Start Docker Container for runnig the Tika Server

  • docker run --rm -p 9998:9998 logicalspark/docker-tikaserver

Installation (dev)

• You can install this package using

git clone https://github.com/gamingflexer/resume-parser-ranker.git
cd resume-parser-ranker
pip install -e .

• 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
python -m nltk.downloader stopwords

Documentation

Official documentation is available at:

Supported File Formats

• All files Formats are supported on all Operating Systems (Windows, Linux, Mac OS X, etc.) if any unsupported file format is found, please raise an issue.
• If you want to extract DOC files you can install textract for your OS (Linux, MacOS)

Usage

• Import it in your Python project

from sourceparser import SourceParser
parser_obj_file = SourceParser("path/to/file")
print(parser_obj_file)

CLI

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

usage: sourceparser [-h] [-f FILENAME] [-fn FOLDERNAME] [-l] [-sm] [-mb]
                    [-gpu] [-json]

SourceParser

optional arguments:
  -h, --help            show this help message and exit
  -f FILENAME, --filename FILENAME
                        File name to parse
  -fn FOLDERNAME, --foldername FOLDERNAME
                        Folder name to parse files in the folder
  -l, --learner         Uploads the file to the server for learning
  -sm, --summariser     Summarises the file
  -mb, --multiBatch     Multi Batch Summariser
  -gpu, --gpuPresent    Add if GPU Present

Result

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

Donation

For running the Self Learner we need funds. If you like this project and want to support us, you can donate us using the below link:

• Donate