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Get Papers List(Aganiths_Intern_task)

This project fetches research papers from PubMed based on a query, filters out non-academic authors, and generates a CSV file with relevant details.

Project Organization

project/
├── get_papers/
│   ├── fetch_papers.py         # Module to fetch and filter papers
├── scripts/
│   ├── get_papers_list.py      # Command-line program to use the module
├── tests/                      # Directory for test cases
├── README.md                   # Project documentation
├── pyproject.toml              # Poetry configuration
├── dist/                       # Generated distribution files for publishing

Installation

  1. Clone the repository:
    git clone https://github.com/Vighnesh-M-S/Aganitha_Intern_task
    cd Aganitha_Intern_task
    
  2. Install dependencies:
    poetry install
    

Usage

  1. Run the command-line program to fetch papers and generate a CSV file:
    poetry run python3 scripts/get_papers_list.py "<search_query>" -f <output_file> -d
    

Command-Line Arguments

Argument Description Example
query Search query for PubMed "cancer research"
-f, --file Output filename for CSV "output.csv"
-d, --debug Enable debug output N/A
  1. Example:
    poetry run python3 scripts/get_papers_list.py "cancer treatment" -f results.csv -d
    

Output Format

The generated CSV file will have the following columns:

Column Name Description
PubmedID Unique identifier for the paper
Title Title of the paper
Publication Date Date the paper was published
Non-academic Author(s) Names of authors affiliated with non-academic institutions
Company Affiliation(s) Names of pharmaceutical/biotech companies
Corresponding Author Email Email address of the corresponding author

Tools and Libraries Used

The following tools and libraries are used in this project:

  • Python: The programming language used to develop the script.
  • Poetry: For dependency management and packaging. Link
  • Requests: To fetch data from the PubMed API. Link
  • Pandas: For data manipulation and CSV generation. Link
  • Argparse: For command-line argument parsing. Link

Publishing the Module

The module can be published to Test PyPI using the following steps:

Build the package:

poetry build

Upload to Test PyPI:

twine upload --repository-url https://test.pypi.org/legacy/ dist/*

For more information, refer to the Test PyPI Guide.

Troubleshooting

  • Ensure you have an active internet connection to access the PubMed API.
  • If you encounter authentication issues while uploading to Test PyPI, verify your token and credentials.

Metadata

Release files for aganitha-intern-task 0.1.0

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