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resumeparser's Introduction

ResumeParser

A utility to make handling many resumes easier by automatically pulling contact information, required skills and custom text fields. These results are then surfaced as a convenient summary CSV.

Quick Start Guide

This assumes you've installed Anaconda (as discussed in Python Environment)

# Create Python virtual enviornment
conda env create -f environment.yml

# Activate Python virtual environment
source activate resume

#Retrieve language model from spacy
python -m spacy download en

# Run code (with default configurations)
cd bin/
python main.py

# Review output
open ../data/output/resume_summary.csv

Getting started

Repo structure

  • bin/main.py: Code entry point
  • confs/confs.yaml.template: Configuration file template
  • data/input/example_resumes: Example resumes, which are parsed w/ default configurations
  • data/output/resume_summary.csv: Results from parsing example resumes

Python Environment

Python code in this repo utilizes packages that are not part of the common library. To make sure you have all of the appropriate packages, please install Anaconda, Python 2.7 Version, and install the environment described in environment.yml (Instructions here, under Creating an environment from an environment.yml file, and Activating an environment).

Once Anaconda is installed, you can follow the steps described in the Quick Start Guide

Configuration file

This program utilizes a configuration file to set program parameters. You can run this program with the default parameters view sample output, but you'll probably want to create a config file and modify it to get the most value from this program.

# Create configuration file from template
scp confs/confs.yaml.template confs/confs.yaml

# Modify confs to match your needs
open confs/confs.yaml

The configuration file has a few parameters you can tweak:

  • resume_directory: A directory containing resumes you'd like to parse
  • summary_output_directory: Where to place the .csv file, summarizing your resumes
  • data_schema_dir: The directory to store table schema. This is mostly for development purposes
  • skills: A YAML list of skills. Each element in this list can either be a string (e.g. skill1 or machine learning), or a list aliases for the same skill (e.g. [skill2_alias_A, skill2_alias_B] or [ml, machine learning, machine-learning])
  • universities: A YAML list of universities you'd like to search for

Contact

Feel free to contact me at 13herger <at> gmail <dot> com

resumeparser's People

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