Collectors · Research & science
OpenAlex API in Python
Scholarly works from OpenAlex — title, authors, year, citations, DOI, abstract. Scholar alternative. One POST from Python with query, rows back as JSON with 32 fields, $0.0004 per delivered work. No proxies or parsers to maintain.

First call
Install, call, read the rows.
pip install requestsimport os, requests
r = requests.post(
"https://api.quanticdata.io/v1/scraper/collectors/openalex/run",
headers={"Authorization": f"Bearer {os.environ['QD_API_KEY']}"},
json={
"query": "large language models",
"max_results": 25,
},
timeout=120,
)
r.raise_for_status()
run = r.json()["payload"]
print(run["count"], "rows,", run["cost"]["usd"], "USD")
for row in run["results"]:
print(row.get("id"), row.get("title"), row.get("authors"), row.get("year"))The key comes from an environment variable, never from the code. The run answers in the same request when it finishes in time; payload.results holds the rows and payload.cost what they cost.
Request parameters
What the collector takes.
| Parameter | Type | Required | Meaning |
|---|---|---|---|
query | string | yes | Search terms across title, abstract and metadata. |
year_from | integer | no | Only works published this year or later. |
year_to | integer | no | Only works published up to this year. |
open_access | boolean | no (default false) | Only works with a free full text. |
sort | string: relevance, cited, newest | no (default relevance) | relevance (default), cited (most cited first) or newest. |
max_results | integer | no (default 25) | How many works to deliver at most (1–200). You pay only for delivered works. |
Response fields
32 fields per work.
| Field | Type | What it holds |
|---|---|---|
rank | integer | 1-based position. |
id | string | OpenAlex work id. |
title | string | Paper title. |
authors | string[] | Author names. |
year | integer, nullable | Publication year. |
cited_by_count | integer, nullable | Citation count. |
doi | string, nullable | DOI. |
type | string, nullable | Work type (article, review…). |
venue | string, nullable | Host venue/journal. |
is_open_access | boolean | Open-access flag. |
oa_url | string, nullable | Open-access PDF/landing URL. |
abstract | string, nullable | Abstract (reconstructed). |
url | string | OpenAlex work URL. |
author_count | integer | Number of authors. |
institutions | string[] | Author institutions (up to 10). |
countries | string[] | Author countries (ISO codes). |
publication_date | string, nullable | Publication date (YYYY-MM-DD). |
language | string, nullable | Language code. |
fwci | number, nullable | Field-weighted citation impact (1.0 = field average). |
referenced_works_count | integer, nullable | Number of works cited. |
venue_type | string, nullable | Venue type (journal, repository, conference…). |
issn | string, nullable | Linking ISSN of the venue. |
volume | string, nullable | Volume. |
issue | string, nullable | Issue. |
pages | string, nullable | Page range. |
oa_status | string, nullable | Open-access status (gold, green, hybrid, bronze, closed). |
pdf_url | string, nullable | Direct PDF link, when one is open. |
license | string, nullable | License of the open copy. |
topic | string, nullable | Primary topic. |
field | string, nullable | Field of the primary topic. |
keywords | string[] | Keywords (up to 10). |
is_retracted | boolean | Whether the work was retracted. |
Add ?format=csv to the runs endpoint to get the same rows as CSV.
Long runs
Run in the background, then poll.
A run that needs more time can go to the background: send "async": true, get 202 with the run id, and poll the runs endpoint until the status is done. Reading a run is free.
import os, time, requests
H = {"Authorization": f"Bearer {os.environ['QD_API_KEY']}"}
r = requests.post("https://api.quanticdata.io/v1/scraper/collectors/openalex/run", headers=H,
json={**{"query":"large language models","max_results":25}, "async": True}, timeout=30)
run_id = r.json()["payload"]["run_id"]
while True:
run = requests.get(f"https://api.quanticdata.io/v1/scraper/collectors/runs/{run_id}", headers=H, timeout=30).json()["payload"]
if run["status"] in ("done", "failed"):
break
time.sleep(5)
print(run["status"], run["count"])Errors
What can come back, and what is billed.
| Status | Meaning | Billed |
|---|---|---|
400 | The input does not match the collector (payload.errors) | No |
401 | Missing or wrong API key | No |
402 | Balance and free credit do not cover the run: top up | No |
422 | The input can never resolve; retrying the same input cannot help | No |
424 | The run failed at the source (blocked, timed out, layout changed); safe to retry | No |
429 | Rate limit or a per-account brake; wait for Retry-After | No |
Only delivered rows are billed: a run that delivers nothing costs nothing.
Price
$0.0004 per delivered work.
| Rows | Cost |
|---|---|
| 1 | $0.0004 |
| 1,000 | $0.40 |
| 10,000 | $4.00 |
Up to 200 works per run; split larger jobs into several runs. The $2 free credit every month covers about 5,000 works. No subscription; paid tiers lower the unit price. All collector prices: collector pricing.
Before you run it
Questions developers ask
Is there a free Academic papers (OpenAlex) API?
Every account gets $2 of free usage each month, about 5,000 works of this collector at $0.0004 each, with no card.
Do I have to handle proxies, retries or blocks?
No. The collector runs on our network and handles them; a run blocked at the source returns 424 and is not billed.
How many rows can one run return?
Up to 200 works per run (the max_results input, where the collector has one).
Can an AI agent run it?
Yes: the MCP server exposes it as the run_collector tool, with the same input and price. See the MCP server.
Run it on the free credit.
Create an API key, export it as QD_API_KEY and run the example. $0.0004 per delivered work, no subscription.