Introduction

pyresumize is a python module to extract useful information from resume and generate a json string out of it. Currently it supports only pdf,docx files as input .

Todo

• Proper Logging to be added
• Support for other formats
• Performance Improvements
• Bug Fixes
• Custom configuration of input data

Notes

The Skills , Employers and Education is given as .csv inputs to the engine and you can see a reference implementation in the data folder.

Design

Class Diagram

Package Diagram

I have changed the Design in such a way that the developers can create own parsing rules and set those to the Parser to bring in flexibility.

Currently we have the below interfaces exposed and the developers can override the process method to bring in custom processing rules.

• EmployerBaseInterface:

Searches for company information in the resume and identifies the employment information from resume. The builtin module uses NER model from a set of 1500+ employers . I already have a plan to list all the employers based on countries (Future Releases)

• EducationBaseInterface

Process Education Details together with universities .Similarly the data is very primitive , I need to update the input csv files based on countries(future releases)

• EmailBaseInterface

Check for email addresses in the resume and returns if found one.

• PhoneBaseInterface

Process phone numbers in the resume text, if there are more than one phone number found , returns a concatenated string with commas.

• NameBaseInterface

Proces the Name of the candidate .

• SkillBaseInterface:

Process the skills section . returns a list of identified skills in a resume. I used a linked in scrapped input for this module.

Sometimes you will be in a need to extend there interfaces , Then create a class like below to have custom parsing.

class RemoteCompaniesChecker (EmployerBaseInterface):
    def process(self,resumetext):
    #Call a remote API and pass the text info
    return list[]

The ResumeEngine class has below member functions and with one of these you can apply your custom engine

set_skills_engine(self, engine):    
set_name_engine(self, engine):    
set_name_engine(self, engine):    
set_email_engine(self, engine):    
set_education_engine(self, engine):    
set_employer_engine(self, engine):

Currently the Engine supports PDF and DOCX File extensions . Incase if you want to use a different parsing mechanism for a particular type of file, you can extend AbstractFileProcessor and use add_custom_text_processor method to register your own text processing features.

Usage

https://pypi.org/project/pyresumize/ . The module can be installed using

pip install pyresumize

Then do the below

python -m spacy download en_core_web_lg    
python -m nltk.downloader words    
python -m nltk.downloader stopwords    
from pyresumize import ResumeEngine    
r_parser=ResumeEngine()    
r_parser.set_custom_keywords_folder("data")    
json=r_parser.process_resume(file)    
print(json)