Interactive Tutorial

Try ApiLinker in your browser with our interactive Jupyter notebook!

What You'll Learn

This hands-on tutorial demonstrates:

1. Basic API Integration: Connect to NCBI/PubMed and fetch research papers
2. Data Transformation: Map fields and apply transformations
3. Research Workflows: Cross-platform literature search
4. Visualization: Plot citation networks and author collaborations

Running Locally

If you prefer to run the notebook on your local machine:

git clone https://github.com/kkartas/APILinker.git
cd APILinker
pip install -e ".[dev]"
pip install jupyter matplotlib pandas
jupyter notebook examples/ApiLinker_Research_Tutorial.ipynb

Notebook Contents

Section 1: Installation & Setup

Learn how to install ApiLinker and verify the installation.

Section 2: Basic Connectivity

Connect to the PubMed API and fetch your first research paper.

from apilinker.connectors.scientific import NCBIConnector

ncbi = NCBIConnector(email="your-email@university.edu")
results = ncbi.search_pubmed("CRISPR gene editing", max_results=10)

Section 3: Cross-Platform Research

Combine data from multiple research APIs (NCBI, arXiv, Semantic Scholar).

Section 4: Data Visualization

Visualize research trends, citation networks, and co-authorship graphs.

Section 5: Advanced Workflows

Build reproducible research pipelines with scheduling and error handling.

Interactive Features

• Live Code Execution: Run and modify code directly in the browser
• Instant Feedback: See results immediately without installation
• Visualization: Generate charts and graphs
• No Setup Required: Powered by Binder for zero-config execution

Troubleshooting

Binder Not Loading?

If Binder takes too long to build, try:

1. Refresh the page and wait (first build can take 5-10 minutes)
2. Run locally using the instructions above
3. View the notebook on GitHub: ApiLinker_Research_Tutorial.ipynb

Feedback

Found issues with the tutorial? Open an issue on GitHub.