AlbertoCuadra / doi_scraper

Digital Object Identifier scraper written in Python

DOI Scraper

The DOI Scraper is a Python script that reads a .bib file, searches for articles without a DOI (Digital Object Identifier), and retrieves the missing DOIs using the Crossref API. It then updates the .bib file with the retrieved DOIs.

Prerequisites

• Python
• requests library

Installation

1. Clone the repository or download the doi_scraper.py file.

2. Install the required dependencies by running the following command:

pip install requests

Usage

Place your input .bib file in the same directory as the doi_scraper.py script.

Open the doi_scraper.py file and modify the following variables according to your needs:

input_file = 'input.bib'   # Name of the input .bib file
output_file = 'output.bib' # Name of the output .bib file
INDENT_PRE = 4             # Number of spaces before the field name
INDENT_POST = 16           # Number of spaces after the field name

Run the script using the following command:

python doi_scraper.py

The script will search for articles without a DOI and retrieve the missing DOIs using the Crossref API. It will then update the output .bib file with the retrieved DOIs.

Once the script completes, you will find the updated .bib file with the retrieved DOIs in the same directory.

Example

Before

@article{Cuadra2020,
title            = {Effect of equivalence ratio fluctuations on planar detonation discontinuities},
author   = {Cuadra, Alberto and Huete, C{\'e}sar and Vera, Marcos},
year    = 2020,
journal  = {Journal of Fluid Mechanics},
publisher    = {Cambridge University Press},
volume       = 903,
pages= {A30 1--39}
}

After

@article{Cuadra2020,
    title            = {Effect of equivalence ratio fluctuations on planar detonation discontinuities},
    author           = {Cuadra, Alberto and Huete, C{\'e}sar and Vera, Marcos},
    year             = 2020,
    journal          = {Journal of Fluid Mechanics},
    publisher        = {Cambridge University Press},
    volume           = 903,
    pages            = {A30 1--39},
    doi              = {10.1017/jfm.2020.651}
}

License

This project is licensed under the MIT License.