CVParser

Python library for parsing resumes using natural language processing and machine learning.

Setup

Installation on Linux and Mac OS

• Follow the guide here on how to clone or fork a repo

• Follow the guide here on how to create virtualenv

• To create a normal virtualenv (example myvenv) and activate it (see Code below).

  $ virtualenv --python=python3 myvenv
  
  $ source myvenv/bin/activate
  
  (myvenv) $ pip install -r requirements.txt
  
  

Usage

from cvparser.parser import CVParser

CVParser.download_nlk_data()


parser = CVParser(file_path="path/to/file.[pdf|doc|docx|png|jpeg]")
parser.parse()
print(parser.json())

Re-training the Model

• cd into the train folder.
• Delete the folder model and the file train.json.
• Copy your new training data into the train folder. The train data must be in json. This can be generated using the data annotation tool called Dataturk. The file containing the training data must be named train.json.
• Then, start re-training the model by execute the python script in the train folder named manual_training.py.
• Then test your new model by #usage .