aganitha-intern-task 0.1.0

No project description provided

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

2. 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.