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Alex Spinov
Alex Spinov

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5 Free Academic APIs Every Developer Should Know (No Key Required)

#python #api #research #tutorial

Last week I shared 5 Free APIs That Changed How I Build Side Projects. It got way more attention than I expected.

Several people asked about research and academic APIs — so here are 5 more free APIs, focused on scholarly data.

All of them are completely free, require no API key, and return real, verified data (not AI-generated).

1. Crossref — 150M+ Scholarly Articles

Crossref is the official DOI registry. Every DOI ever assigned has metadata here.

import requests

resp = requests.get("https://api.crossref.org/works", params={
    "query": "machine learning",
    "rows": 3,
    "mailto": "you@email.com"  # polite pool = 10x faster
})

for item in resp.json()["message"]["items"]:
    print(f"{item['title'][0]}")
    print(f"  Cited by {item['is-referenced-by-count']} papers")
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Best for: Citation analysis, bibliography generation, DOI resolution
Docs: https://api.crossref.org

2. OpenAlex — 250M+ Academic Works

The successor to Microsoft Academic Graph. Completely open.

resp = requests.get("https://api.openalex.org/works", params={
    "search": "CRISPR gene therapy",
    "per_page": 3,
    "sort": "cited_by_count:desc"
})

for work in resp.json()["results"]:
    print(f"{work['title']}")
    print(f"  {work['cited_by_count']} citations | {work['publication_year']}")
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Best for: Large-scale bibliometrics, author networks, institutional research
Docs: https://docs.openalex.org

3. PubMed (E-utilities) — 36M+ Medical Papers

The gold standard for biomedical literature. Run by NIH.

# Search
search = requests.get("https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi", params={
    "db": "pubmed", "term": "covid vaccine efficacy",
    "retmax": 3, "retmode": "json"
})
ids = search.json()["esearchresult"]["idlist"]

# Fetch details
details = requests.get("https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi", params={
    "db": "pubmed", "id": ",".join(ids), "retmode": "json"
})
for uid in ids:
    paper = details.json()["result"][uid]
    print(f"{paper['title'][:80]}...")
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Best for: Medical research, clinical trials, drug discovery
Docs: https://www.ncbi.nlm.nih.gov/books/NBK25501/

4. arXiv — 2M+ Preprints

Where cutting-edge research appears first — before peer review.

import urllib.parse

query = urllib.parse.quote("all:transformer attention mechanism")
resp = requests.get(f"http://export.arxiv.org/api/query?search_query={query}&max_results=3")

import xml.etree.ElementTree as ET
root = ET.fromstring(resp.text)
ns = {"atom": "http://www.w3.org/2005/Atom"}

for entry in root.findall("atom:entry", ns):
    title = entry.find("atom:title", ns).text.strip()
    print(title[:80])
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Best for: AI/ML papers, physics, math, CS — latest research before publication
Docs: https://info.arxiv.org/help/api

5. CORE — 300M+ Open Access Articles

The world's largest collection of open access research papers. Full text included.

# CORE requires a free API key (quick signup)
resp = requests.get("https://api.core.ac.uk/v3/search/works", params={
    "q": "renewable energy storage",
    "limit": 3
}, headers={"Authorization": "Bearer YOUR_KEY"})

for work in resp.json()["results"]:
    print(f"{work['title']}")
    print(f"  Full text: {'Yes' if work.get('fullText') else 'Abstract only'}")
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Best for: Full-text analysis, open access research, text mining
Docs: https://core.ac.uk/services/api

Quick Comparison

API Records Key? Best For
Crossref 150M+ No DOIs, citations
OpenAlex 250M+ No Bibliometrics
PubMed 36M+ No Medical research
arXiv 2M+ No Preprints (AI/Physics)
CORE 300M+ Free key Full text

Open Source Toolkits

I built Python toolkits for each of these:

All MIT licensed. Use them however you want.

Which academic API are you using? Or is there one I missed? Drop a comment — I'm building more toolkits based on what people need.

Need custom research data pipelines? Check my GitHub or email me.

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