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Alex Spinov
Alex Spinov

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OpenAlex Has a Free API — Search 250M+ Research Papers (No API Key Needed)

#python #api #beginners #tutorial

Google Scholar doesn't have an API. Semantic Scholar has rate limits. Web of Science costs $10K+/year.

But there's a free alternative that most researchers don't know about: OpenAlex.

It indexes 250 million research works, 100K+ journals, and 200M+ authors — and the API needs no key, no signup, no payment.

What OpenAlex Gives You

  • 250M+ research papers with abstracts
  • Citation counts and references
  • Author profiles with h-index
  • Institution data
  • Concept/topic classification
  • Open access status
  • Everything downloadable as JSON

Quick Start 

import requests

def search_papers(query, limit=5):
    """Search 250M+ papers. No API key needed."""
    url = "https://api.openalex.org/works"
    params = {
        "search": query,
        "per_page": limit,
        "sort": "cited_by_count:desc"  # Most cited first
    }
    resp = requests.get(url, params=params)
    return resp.json()["results"]

# Search for papers about web scraping
papers = search_papers("web scraping machine learning")
for p in papers:
    print(f'{p["cited_by_count"]:5d} citations | {p["title"]}')
    print(f'      {p["doi"]}')
    print()
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Output:

 1,247 citations | A Survey on Web Scraping Technologies
      https://doi.org/10.1145/xxxxx
   892 citations | Machine Learning for Web Data Extraction
      https://doi.org/10.1007/xxxxx
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5 Useful Queries

Find papers by topic 

# Most cited AI papers published in 2024-2025
params = {
    "search": "large language models",
    "filter": "publication_year:2024-2025",
    "sort": "cited_by_count:desc",
    "per_page": 10
}
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Find papers by author 

# Search for an author
url = "https://api.openalex.org/authors"
params = {"search": "Geoffrey Hinton"}
resp = requests.get(url, params=params)
author = resp.json()["results"][0]
print(f'Name: {author["display_name"]}')
print(f'h-index: {author["summary_stats"]["h_index"]}')
print(f'Total works: {author["works_count"]}')
print(f'Total citations: {author["cited_by_count"]}')
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Find open access papers only 

params = {
    "search": "web scraping",
    "filter": "is_oa:true",  # Open access only
    "per_page": 5
}
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Get paper references 

# Get all papers cited by a specific paper
paper_id = "W2100837269"  # OpenAlex ID
url = f"https://api.openalex.org/works?filter=cites:{paper_id}"
resp = requests.get(url)
print(f'This paper is cited by {resp.json()["meta"]["count"]} papers')
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Analyze trending topics 

# How many papers about LLMs per year?
for year in range(2020, 2027):
    url = f"https://api.openalex.org/works?filter=publication_year:{year}"
    params = {"search": "large language model"}
    resp = requests.get(url, params=params)
    count = resp.json()["meta"]["count"]
    print(f'{year}: count: papers about LLMs')
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OpenAlex vs Alternatives

Feature OpenAlex Google Scholar Semantic Scholar Web of Science
API ✅ Free ❌ None ✅ Free (limited) ✅ Paid ($10K+)
Papers 250M+ Unknown 200M+ 100M+
Rate limit Generous N/A 100 req/5min Varies
API key Not needed N/A Recommended Required
Open data ✅ CC0 ❌ Partial ❌

Rate Limits

  • No API key: ~10 requests/second
  • With mailto param: higher limits (just add your email)
  • Bulk download: full dataset available as snapshot 
# Add your email for better rate limits (recommended)
params["mailto"] = "your@email.com"
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What research APIs do you use?

If you work with academic data, I'd love to know what tools you use. Are you scraping Google Scholar? Using a paid service? Built your own pipeline?

Drop your workflow in the comments — especially if you've found a free alternative I don't know about.

I built tools for academic research: OpenAlex Research Tools

All free APIs: Awesome Free APIs 2026 — 300+ APIs, no key needed

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