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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.

A Python requests snippet that posts {
A Python requests call to the openalex collector returns one dict per work, at $0.0004 each.

First call

Install, call, read the rows.

pip install requests
The only dependency.
import 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"))
Python: one Academic papers (OpenAlex) run (Ricerca), printing id, title, authors, 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.

Input of the Academic papers (OpenAlex) collector
ParameterTypeRequiredMeaning
querystringyesSearch terms across title, abstract and metadata.
year_fromintegernoOnly works published this year or later.
year_tointegernoOnly works published up to this year.
open_accessbooleanno (default false)Only works with a free full text.
sortstring: relevance, cited, newestno (default relevance)relevance (default), cited (most cited first) or newest.
max_resultsintegerno (default 25)How many works to deliver at most (1–200). You pay only for delivered works.

Response fields

32 fields per work.

Fields of each row (work)
FieldTypeWhat it holds
rankinteger1-based position.
idstringOpenAlex work id.
titlestringPaper title.
authorsstring[]Author names.
yearinteger, nullablePublication year.
cited_by_countinteger, nullableCitation count.
doistring, nullableDOI.
typestring, nullableWork type (article, review…).
venuestring, nullableHost venue/journal.
is_open_accessbooleanOpen-access flag.
oa_urlstring, nullableOpen-access PDF/landing URL.
abstractstring, nullableAbstract (reconstructed).
urlstringOpenAlex work URL.
author_countintegerNumber of authors.
institutionsstring[]Author institutions (up to 10).
countriesstring[]Author countries (ISO codes).
publication_datestring, nullablePublication date (YYYY-MM-DD).
languagestring, nullableLanguage code.
fwcinumber, nullableField-weighted citation impact (1.0 = field average).
referenced_works_countinteger, nullableNumber of works cited.
venue_typestring, nullableVenue type (journal, repository, conference…).
issnstring, nullableLinking ISSN of the venue.
volumestring, nullableVolume.
issuestring, nullableIssue.
pagesstring, nullablePage range.
oa_statusstring, nullableOpen-access status (gold, green, hybrid, bronze, closed).
pdf_urlstring, nullableDirect PDF link, when one is open.
licensestring, nullableLicense of the open copy.
topicstring, nullablePrimary topic.
fieldstring, nullableField of the primary topic.
keywordsstring[]Keywords (up to 10).
is_retractedbooleanWhether 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"])
Python: background run and polling

Errors

What can come back, and what is billed.

Collector run errors
StatusMeaningBilled
400The input does not match the collector (payload.errors)No
401Missing or wrong API keyNo
402Balance and free credit do not cover the run: top upNo
422The input can never resolve; retrying the same input cannot helpNo
424The run failed at the source (blocked, timed out, layout changed); safe to retryNo
429Rate limit or a per-account brake; wait for Retry-AfterNo

Only delivered rows are billed: a run that delivers nothing costs nothing.

Price

$0.0004 per delivered work.

What Academic papers (OpenAlex) rows cost at list price
RowsCost
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.