Search NCBI databases using Biopython Bio.Entrez. Use when finding records by keyword, building complex search queries, discovering database structure, or getting global query counts across databases.
Reference examples tested with: BioPython 1.83+, Entrez Direct 21.0+
Before using code patterns, verify installed versions match. If versions differ:
pip show <package> then help(module.function) to check signaturesIf code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Search NCBI databases using Biopython's Entrez module (ESearch, EInfo, EGQuery utilities).
"Search NCBI for records" → Query any NCBI database by keyword, organism, or field-qualified terms and retrieve matching record IDs.
Entrez.esearch(db=..., term=...) (BioPython)esearch -db nucleotide -query "term" (Entrez Direct)from Bio import Entrez
Entrez.email = '[email protected]' # Required by NCBI
Entrez.api_key = 'your_api_key' # Optional, raises rate limit 3->10 req/sec
Search any NCBI database and get matching record IDs.
handle = Entrez.esearch(db='nucleotide', term='human[orgn] AND BRCA1[gene]')
record = Entrez.read(handle)
handle.close()
print(f"Found {record['Count']} records")
print(f"IDs: {record['IdList']}") # First 20 IDs by default
Key Parameters:
| Parameter | Description | Default |
|---|---|---|
db | Database to search | Required |
term | Search query | Required |
retmax | Max IDs to return | 20 |
retstart | Starting index (pagination) | 0 |
usehistory | Store results on server | 'n' |
sort | Sort order | database-specific |
datetype | Date field to search | 'pdat' |
reldate | Records from last N days | None |
mindate | Start date (YYYY/MM/DD) | None |
maxdate | End date (YYYY/MM/DD) | None |
ESearch Result Fields:
record['Count'] # Total matching records (string)
record['IdList'] # List of record IDs
record['RetMax'] # Number of IDs returned
record['RetStart'] # Starting index
record['QueryKey'] # For history server (if usehistory='y')
record['WebEnv'] # For history server (if usehistory='y')
record['TranslationSet'] # Query translations applied
record['QueryTranslation'] # Final translated query
Get information about available databases or specific database fields.
# List all available databases
handle = Entrez.einfo()
record = Entrez.read(handle)
handle.close()
print(record['DbList']) # ['pubmed', 'protein', 'nucleotide', ...]
# Get info about specific database
handle = Entrez.einfo(db='nucleotide')
record = Entrez.read(handle)
handle.close()
print(f"Description: {record['DbInfo']['Description']}")
print(f"Record count: {record['DbInfo']['Count']}")
# List searchable fields
for field in record['DbInfo']['FieldList']:
print(f"{field['Name']}: {field['Description']}")
Database Info Fields:
record['DbInfo']['DbName'] # Database name
record['DbInfo']['Description'] # Database description
record['DbInfo']['Count'] # Total records in database
record['DbInfo']['LastUpdate'] # Last update date
record['DbInfo']['FieldList'] # Searchable fields
record['DbInfo']['LinkList'] # Available links to other databases
Search across all NCBI databases simultaneously.
handle = Entrez.egquery(term='CRISPR')
record = Entrez.read(handle)
handle.close()
for result in record['eGQueryResult']:
if int(result['Count']) > 0:
print(f"{result['DbName']}: {result['Count']} records")
NCBI uses a specific query syntax:
# Search specific fields using [field_name]
term = 'BRCA1[gene]' # Gene name field
term = 'human[orgn]' # Organism field
term = 'Homo sapiens[ORGN]' # Full organism name
term = 'NM_007294[accn]' # Accession number
term = 'Smith J[auth]' # Author (PubMed)
term = 'Nature[jour]' # Journal (PubMed)
term = '1000:5000[slen]' # Sequence length range
term = 'mRNA[fkey]' # Feature key
term = 'BRCA1 AND human' # Both terms
term = 'cancer OR tumor' # Either term
term = 'human NOT mouse' # Exclude term
term = '(BRCA1 OR BRCA2) AND human' # Grouping
# Using date parameters
handle = Entrez.esearch(
db='pubmed',
term='CRISPR',
datetype='pdat', # Publication date
mindate='2023/01/01',
maxdate='2024/12/31'
)
# Or in query string
term = 'CRISPR AND 2024[pdat]'
term = 'CRISPR AND 2023:2024[pdat]'
term = 'immun*' # Wildcard
term = '"breast cancer"[title]' # Exact phrase
| Database | db value | Common Fields |
|---|---|---|
| PubMed | pubmed | [auth], [title], [jour], [pdat] |
| Nucleotide | nucleotide | [orgn], [gene], [accn], [slen] |
| Protein | protein | [orgn], [gene], [accn], [molwt] |
| Gene | gene | [orgn], [sym], [chr] |
| SRA | sra | [orgn], [platform], [strategy] |
| Taxonomy | taxonomy | [scin], [comn], [rank] |
| Assembly | assembly | [orgn], [level], [refseq] |
from Bio import Entrez
Entrez.email = '[email protected]'
def search_ncbi(db, term, max_results=100):
handle = Entrez.esearch(db=db, term=term, retmax=max_results)
record = Entrez.read(handle)
handle.close()
return record['IdList'], int(record['Count'])
ids, total = search_ncbi('nucleotide', 'human[orgn] AND insulin[gene]')
print(f'Retrieved {len(ids)} of {total} total records')
Goal: Retrieve all matching record IDs when the result set exceeds the default return limit.
Approach: First query with retmax=0 to get the total count, then page through results in batches using retstart offsets.
def search_all_ids(db, term, batch_size=10000):
all_ids = []
handle = Entrez.esearch(db=db, term=term, retmax=0)
record = Entrez.read(handle)
handle.close()
total = int(record['Count'])
for start in range(0, total, batch_size):
handle = Entrez.esearch(db=db, term=term, retstart=start, retmax=batch_size)
record = Entrez.read(handle)
handle.close()
all_ids.extend(record['IdList'])
return all_ids
Goal: Store search results on the NCBI server for efficient subsequent batch fetching without re-sending IDs.
Approach: Run esearch with usehistory='y' to get a WebEnv session key and QueryKey, then pass those to efetch for server-side retrieval.
# Store results on NCBI server for subsequent fetching
handle = Entrez.esearch(db='nucleotide', term='human[orgn] AND mRNA[fkey]', usehistory='y')
record = Entrez.read(handle)
handle.close()
webenv = record['WebEnv']
query_key = record['QueryKey']
total = int(record['Count'])
# Use webenv and query_key with efetch for batch downloads
# See batch-downloads skill for details
# Records from last 30 days
handle = Entrez.esearch(db='pubmed', term='CRISPR', reldate=30, datetype='pdat')
record = Entrez.read(handle)
handle.close()
def get_search_fields(db):
handle = Entrez.einfo(db=db)
record = Entrez.read(handle)
handle.close()
return [(f['Name'], f['Description']) for f in record['DbInfo']['FieldList']]
fields = get_search_fields('nucleotide')
for name, desc in fields[:10]:
print(f'{name}: {desc}')
handle = Entrez.esearch(db='nucleotide', term='human BRCA1')
record = Entrez.read(handle)
handle.close()
# See how NCBI interpreted your query
print(f"Your query was translated to: {record['QueryTranslation']}")
# e.g., '"homo sapiens"[Organism] AND BRCA1[All Fields]'
| Error | Cause | Solution |
|---|---|---|
HTTPError 429 | Rate limit exceeded | Add delays or use API key |
HTTPError 400 | Invalid query syntax | Check field names and operators |
| Empty IdList | No matches or typo | Check QueryTranslation field |
RuntimeError | Missing email | Set Entrez.email |
Need to search NCBI?
├── Finding records in one database?
│ └── Use Entrez.esearch()
├── Search across all databases?
│ └── Use Entrez.egquery()
├── Need database field names?
│ └── Use Entrez.einfo(db='database')
├── List all available databases?
│ └── Use Entrez.einfo() (no db argument)
├── Results > 10,000 records?
│ └── Use usehistory='y', then batch fetch
└── Need to fetch actual records?
└── See entrez-fetch skill