Search NCBI databases using Biopython Bio.Entrez (ESearch, EInfo, EGQuery, ESpell). Use when finding records by keyword, building reproducible field-qualified queries, navigating the Entrez Query Translator, exploiting the history server for large result sets, handling retmax caps, or interpreting weekly index lag. Covers PubMed, Nucleotide, Protein, Gene, SRA, GEO, Assembly, Taxonomy, ClinVar, dbSNP.
Search NCBI databases using Biopython Bio.Entrez (ESearch, EInfo, EGQuery, ESpell). Use when finding records by keyword, building reproducible field-qualified queries, navigating the Entrez Query Translator, exploiting the history server for large result sets, handling retmax caps, or interpreting weekly index lag. Covers PubMed, Nucleotide, Protein, Gene, SRA, GEO, Assembly, Taxonomy, ClinVar, dbSNP.
tool_type
python
primary_tool
Bio.Entrez
Version Compatibility
Reference examples tested with: BioPython 1.83+, Entrez Direct 21.0+
Before using code patterns, verify installed versions match. If versions differ:
Python: pip show biopython then help(Bio.Entrez.esearch) to check signatures
CLI: esearch -version then esearch -help to confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.
Entrez Search
"Find NCBI records matching a query" -> ESearch returns matching record UIDs (not full records) from one NCBI database; EGQuery returns counts across all databases; EInfo describes a database's searchable fields and update timestamp.
The single most important fact: ESearch returns UIDs (PMIDs, GI numbers, gene IDs, etc.), not records. To get content the agent must call EFetch or ESummary. Forgetting this is the most common Entrez mistake.
from Bio import Entrez
import time
Entrez.email = 'researcher@institution.edu'# NCBI requires; sets User-Agent
Entrez.api_key = 'YOUR_KEY'# 3 -> 10 req/sec; get at ncbi.nlm.nih.gov/account/settings/
Entrez.tool = 'project-name'# appears in NCBI usage logs; helps if rate-throttled
What ESearch actually does
ESearch sends the query string through the Entrez Query Translator (EQT), which rewrites unqualified terms into the canonical term[field] form, then runs the rewritten query against the per-database index. The result is a list of UIDs plus a QueryTranslation string showing exactly what was searched. Reproducible work always inspects QueryTranslation and builds queries that are translation-stable from the start.
handle = Entrez.esearch(db='nucleotide', term='human BRCA1')
record = Entrez.read(handle)
handle.close()
print(record['QueryTranslation'])
# '("homo sapiens"[Organism] OR human[All Fields]) AND (BRCA1[Gene Name] OR BRCA1[All Fields])'
The translator may expand human to the full taxonomy subtree, or coerce a gene symbol to [All Fields] if the symbol isn't unambiguous. Use field-qualified terms (Homo sapiens[ORGN] AND BRCA1[Gene Name]) for any query that will be re-run later.
Decision table: which utility for which question
Question
Utility
Returns
Cost
"How many records match X in PubMed?"
ESearch with retmax=0
Count + WebEnv
1 call
"Give me 20 matching UIDs"
ESearch
UIDs
1 call
"Give me ALL matching UIDs (>10K)"
ESearch + usehistory='y'
WebEnv/QueryKey
1 call (then EFetch chunks server-side)
"Does record X exist in db Y?"
ESearch with term='X[Accn]'
UIDs
1 call
"Which NCBI databases mention X at all?"
EGQuery
Counts across every db
1 call
"What searchable fields does db Y have?"
EInfo with db=Y
FieldList
1 call
"Last update timestamp for db Y?"
EInfo with db=Y
LastUpdate
1 call
"Did the user misspell X?"
ESpell
Spelling suggestion
1 call
EGQuery has been semi-deprecated since the 2022 site refactor — it still works but counts can lag the per-database indexes by 1-2 days. For authoritative cross-database counts, loop ESearch over a curated db list instead.
retmax silent caps
Endpoint behavior
Cap
Workaround
Default retmax
20
Set explicitly
Legacy esearch.fcgi (no usehistory)
9,999 silent cap
Use history server
usehistory='y' + ESearch
100,000 per page
Page with retstart against the WebEnv
EPost (to push IDs server-side)
200 IDs per call
Chunk to multiple EPost calls; union with QueryKey
The 9,999 cap is the bug that has shipped in countless lab pipelines: query returns "Count: 78,432" but IdList has 9,999 entries and there is no error. Always set retmax explicitly and either page or move to usehistory='y' whenever Count > retmax.
History server (WebEnv/QueryKey) semantics
Property
Value
TTL
8 hours absolute (per NCBI E-utils help, 2024)
Idle eviction
Empirically ~15 min under load; can be shorter
Chaining
Run another ESearch against WebEnv with term='#1 AND #2' to intersect prior QueryKeys
Persistence
Session is per WebEnv string; do NOT share across processes when isolation matters
Failure mode
Expired session returns HTTP 200 with <ERROR>WebEnv not found</ERROR> — must parse body, not status
Chaining example:
h1 = Entrez.esearch(db='pubmed', term='CRISPR[Title]', usehistory='y')
r1 = Entrez.read(h1); h1.close()
webenv = r1['WebEnv']
h2 = Entrez.esearch(db='pubmed', term='2024[PDAT]', usehistory='y', WebEnv=webenv)
r2 = Entrez.read(h2); h2.close()
# Intersect QueryKey #1 (CRISPR) AND #2 (2024) into a new key
h3 = Entrez.esearch(db='pubmed', term=f'#{r1["QueryKey"]} AND #{r2["QueryKey"]}',
usehistory='y', WebEnv=webenv)
r3 = Entrez.read(h3); h3.close()
print(f'CRISPR & 2024: {r3["Count"]}')
Index lag
NCBI's Entrez indexer runs nightly (US Eastern). Records submitted Monday morning typically appear in ESearch results Wednesday at earliest. PubMed has additional MEDLINE indexing lag (1-3 weeks for full MeSH terms). For freshly-deposited data the more reliable check is EFetch on the known accession or NCBI Datasets API for genomes.
# Curated RefSeq mRNA only, human, between 500 and 5000 nt
term = 'Homo sapiens[ORGN] AND srcdb_refseq[PROP] AND biomol_mrna[PROP] AND 500:5000[SLEN]'# Reviewed SwissProt human kinases
term = 'Homo sapiens[ORGN] AND swissprot[Filter] AND kinase[Protein Name]'# PubMed: human studies in last 30 days, full-text in PMC
term = 'CRISPR[Title] AND humans[MeSH Terms] AND last 30 days[EDAT] AND pubmed pmc[sb]'
Organism field gotcha
[Organism] (and the alias [ORGN]) is taxonomy-walked: searching mammalia[ORGN] returns records from every species in Mammalia. To get records tagged at exactly that node use [Organism:exp] (no taxonomic expansion). Most workflows want the default walk, but multi-species queries that "blow up" by 100x are almost always a missing :exp.
Code patterns
Single search with explicit retmax
Goal: Get matching UIDs for a focused query without hitting silent caps.
Approach: Set retmax explicitly to the maximum the caller wants; if Count > retmax either page or switch to history server.
Reference (BioPython 1.83+):
defsearch_ncbi(db, term, max_results=100):
handle = Entrez.esearch(db=db, term=term, retmax=max_results)
record = Entrez.read(handle); handle.close()
count = int(record['Count'])
if count > max_results:
print(f'WARNING: {count} matched, returning first {max_results}; use history server for full set')
return record['IdList'], count, record['QueryTranslation']
Paged retrieval (only when enumeration without fetching is required)
Goal: Stream all matching UIDs to a file when downstream work can't use the history server.
Approach: Page through retstart increments; respect rate limit; stop at total.
defstream_all_ids(db, term, batch_size=10000):
h = Entrez.esearch(db=db, term=term, retmax=0)
total = int(Entrez.read(h)['Count']); h.close()
delay = 0.1if Entrez.api_key else0.34for start inrange(0, total, batch_size):
h = Entrez.esearch(db=db, term=term, retstart=start, retmax=batch_size)
r = Entrez.read(h); h.close()
for uid in r['IdList']:
yield uid
time.sleep(delay)
For any download workflow, history-server retrieval is strictly better — see batch-downloads skill.
History server for downstream EFetch
Goal: Push a large result set to NCBI servers so EFetch can pull it in batches without re-sending IDs.
Approach: ESearch with usehistory='y'; capture WebEnv and QueryKey; pass to EFetch.
Reference (BioPython 1.83+):
h = Entrez.esearch(db='nucleotide',
term='Homo sapiens[ORGN] AND srcdb_refseq[PROP] AND biomol_mrna[PROP]',
usehistory='y', retmax=0)
r = Entrez.read(h); h.close()
webenv, query_key, count = r['WebEnv'], r['QueryKey'], int(r['Count'])
print(f'{count} mRNAs queued on history server; use webenv/query_key with efetch')
Inspect the translation before trusting a query
Goal: Catch translator misinterpretation before producing publication results.
Approach: Always print QueryTranslation for new queries and lock the rewritten string into the codebase as the canonical query.
h = Entrez.esearch(db='pubmed', term='covid vaccine efficacy 2024', retmax=0)
r = Entrez.read(h); h.close()
print(r['QueryTranslation'])
# '("covid 19 vaccines"[MeSH Terms] OR ("covid 19"[All Fields] AND ...# Now use this rewritten string explicitly to guarantee reproducibility.
Discover fields for a database
deflist_fields(db):
h = Entrez.einfo(db=db); r = Entrez.read(h); h.close()
return [(f['Name'], f['FullName'], f['Description']) for f in r['DbInfo']['FieldList']]
Spell-check before searching (catches typo-driven empty results)
h = Entrez.espell(db='pubmed', term='breast canser')
r = Entrez.read(h); h.close()
print(r['CorrectedQuery']) # 'breast cancer'
Failure modes
Silent retmax cap
Trigger:Count > 9999 with no usehistory='y'; IdList capped at 9999.
Mechanism: Legacy esearch.fcgi enforces a 9999 cap for non-history responses.
Symptom: Pipeline returns "the first 9999" with no error; downstream stats are wrong.
Fix: Always check int(record['Count']) <= len(record['IdList']); switch to history server above ~5000.
Query translation mismatch
Trigger: Unqualified ambiguous term (e.g. MARCH1 — Excel-renamed gene vs month abbreviation).
Mechanism: EQT falls back to [All Fields] when no unambiguous mapping is found.
Symptom: Either zero hits (gene symbol not in [All Fields]) or huge non-specific hits.
Fix: Use field-qualified terms; for gene symbols, use HGNC ID via gene db lookup first.
WebEnv expiration mid-pipeline
Trigger: Long-running batch job; session > 8 hours or idle > 15 min.
Mechanism: Server evicts WebEnv; subsequent EFetch returns <ERROR> body with HTTP 200.
Symptom: Silent empty results halfway through a download.
Fix: Parse error bodies (not just status codes); re-run ESearch and resume from retstart.
Index lag for fresh deposits
Trigger: Querying a record submitted < 48h ago.
Mechanism: Indexer is batch (Tue/Fri primary); record exists but not searchable.
Symptom: ESearch by accession returns empty; direct EFetch by accession succeeds.
Fix: If the accession is known, use EFetch directly; only use ESearch for content-based discovery.
Organism over-expansion
Trigger:[ORGN] query on a higher taxon (e.g. Vertebrata[ORGN]).
Mechanism: Default behavior walks the entire taxonomy subtree.
Symptom: 1000x more hits than intended.
Fix: Use [Organism:exp] to disable the walk, or constrain to a specific species/genus.
Empty IdList with no error
Trigger: Misspelled field name ([gene] works; [gene_name] returns nothing).
Mechanism: Unknown field is silently coerced to [All Fields] — but combined with AND of a real field, the AND prunes everything.
Symptom: Query that "should" match gets 0 results.
Fix: Run EInfo on the db first to confirm field names; check QueryTranslation.
Rate-limit math
Auth
req/sec allowed
Sleep between calls
Bulk-friendly?
Email only
3
0.34 s
Use history server, not parallel calls
Email + API key
10
0.10 s
Modest parallelism (4 workers) is safe
Institutional bulk
Email eutilities@ncbi.nlm.nih.gov
Negotiated
For >100K queries; courtesy expected
NCBI's terms of use ask that heavy automated queries run outside US weekday business hours (9 AM-5 PM ET). For genuinely bulk work, prefer the history server over parallel API calls — chunking against one session is faster and friendlier than scaling out.
Common errors
Error / symptom
Cause
Solution
HTTPError 429
Rate limit exceeded
Add time.sleep(0.34) or use API key
HTTPError 400
Field name or bracket malformed
Inspect EInfo field list; check brackets
RuntimeError: ... email
Missing Entrez.email
Set globally before any call
Empty IdList, large Count
Hit retmax cap
Set retmax explicitly or use history
<ERROR>WebEnv not found</ERROR> (HTTP 200)
Session expired
Re-run ESearch; parse XML body for errors
Query gives wildly wrong count
EQT misinterpretation
Print QueryTranslation; use field-qualified terms
References
Sayers EW et al. (2024) Database resources of the National Center for Biotechnology Information in 2024. Nucleic Acids Res 52:D33-D43.
Kans J. (2024) Entrez Direct: E-utilities on the Unix Command Line. NCBI Bookshelf NBK179288.
NCBI. E-utilities In-Depth: Parameters, Syntax and More. NBK25499 (online manual; check current revision).
Cock PJ et al. (2009) Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 25:1422-1423.
Related Skills
entrez-fetch - Retrieve actual records once UIDs are in hand
