NCBI E-utilities (PubMed)

Use in your agent

Load PubMed search results via E-utilities into pandas and Parquet. Checked against the provider's documentation on Nov 3, 2026.

Access

• No key needed up to 3 requests a second; an NCBI API key (free) allows more and goes in the api_key parameter.
• Send requests to https://eutils.ncbi.nlm.nih.gov with tool and email parameters so NCBI can contact you.

Request

curl 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=heat+wave+mortality&retmode=json&retmax=100&tool=my-loader&email=you@example.org'

Format

ESearch JSON: esearchresult with count and idlist (PubMed IDs). ESummary JSON: result with uids and one object per PMID carrying title, fulljournalname, pubdate, authors and articleids (including doi where present). EFetch returns full PubMed XML.

Load into pandas and Parquet

Needs Python 3 with requests, pandas and pyarrow.

"""PubMed via NCBI E-utilities (ESearch + ESummary) -> pandas -> Parquet. No key needed; at most 3 requests a second."""
import time
import requests
import pandas as pd

BASE = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils"
COMMON = {"db": "pubmed", "retmode": "json", "tool": "my-loader", "email": "you@example.org"}  # use your own tool name and email
s = requests.get(f"{BASE}/esearch.fcgi", params={**COMMON, "term": "heat wave mortality", "retmax": 100,
                 "sort": "pub_date", "datetype": "pdat", "mindate": "2025", "maxdate": "2026"}, timeout=60)
s.raise_for_status()
res = s.json()["esearchresult"]
time.sleep(0.4)
m = requests.get(f"{BASE}/esummary.fcgi", params={**COMMON, "id": ",".join(res["idlist"])}, timeout=60)
m.raise_for_status()
summ = m.json()["result"]
rows = [{
    "pmid": uid,
    "title": summ[uid].get("title"),
    "journal": summ[uid].get("fulljournalname"),
    "pubdate": summ[uid].get("pubdate"),
    "doi": next((i["value"] for i in summ[uid].get("articleids", []) if i.get("idtype") == "doi"), None),
} for uid in summ["uids"]]
df = pd.DataFrame(rows)
df.to_parquet("pubmed_summaries.parquet", index=False)
print(len(df), "PubMed summaries of", res["count"], "matches")

Run by us on 2026-11-03 (python 3.13.5 | pandas 3.1.0 | pyarrow 26.0.0 | requests 2.34.2). Result: 100 PubMed summaries of 106 matches

Limits

• No more than 3 requests per second without a key, counted across all E-utilities from one IP address.
• Run series of more than 100 requests at weekends or between 9 pm and 5 am Eastern Time on weekdays.

Quirks

• ESearch only returns IDs; fetch summaries or records in a second call (ESummary or EFetch).
• pubdate is free text such as 2026 Oct 15 or 2026 Spring; parse it with care.

Terms and attribution

• NLM asks to be acknowledged as the source; some PubMed abstracts may be under copyright held by publishers or authors.
• NCBI's Disclaimer and Copyright notice must be evident to users of a service built on the data.

Sources

• https://www.ncbi.nlm.nih.gov/home/about/policies/: “Make no more than 3 requests every 1 second.”
• https://www.ncbi.nlm.nih.gov/home/about/policies/: “NCBI's Disclaimer and Copyright notice must be evident to users of your service.”
• https://pubmed.ncbi.nlm.nih.gov/download/: “PubMed data are available via our FTP servers and via the E-utilities API.”
• https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/README.txt: “NLM freely provides PubMed data. Please note some abstracts may be protected by copyright.”