Bio.Entrez package¶

Submodules¶

Bio.Entrez.Parser module

Module contents¶

Provides code to access NCBI over the WWW.

The main Entrez web page is available at: http://www.ncbi.nlm.nih.gov/Entrez/

Entrez Programming Utilities web page is available at: http://www.ncbi.nlm.nih.gov/books/NBK25501/

This module provides a number of functions like efetch (short for Entrez Fetch) which will return the data as a handle object. This is a standard interface used in Python for reading data from a file, or in this case a remote network connection, and provides methods like .read() or offers iteration over the contents line by line. See also “What the heck is a handle?” in the Biopython Tutorial and Cookbook: http://biopython.org/DIST/docs/tutorial/Tutorial.html http://biopython.org/DIST/docs/tutorial/Tutorial.pdf

Unlike a handle to a file on disk from the open(filename) function, which has a .name attribute giving the filename, the handles from Bio.Entrez all have a .url attribute instead giving the URL used to connect to the NCBI Entrez API.

All the functions that send requests to the NCBI Entrez API will automatically respect the NCBI rate limit (of 3 requests per second without an API key, or 10 requests per second with an API key) and will automatically retry when encountering transient failures (i.e. connection failures or HTTP 5XX codes). By default, Biopython does a maximum of three tries before giving up, and sleeps for 15 seconds between tries. You can tweak these parameters by setting Bio.Entrez.max_tries and Bio.Entrez.sleep_between_tries.

The Entrez module also provides an XML parser which takes a handle as input.

Variables:

email Set the Entrez email parameter (default is not set).

tool Set the Entrez tool parameter (default is biopython).

api_key Personal API key from NCBI. If not set, only 3 queries per second are allowed. 10 queries per seconds otherwise with a valid API key.

max_tries Configures how many times failed requests will be automatically retried on error (default is 3).

sleep_between_tries The delay, in seconds, before retrying a request on error (default is 15).

Functions:

efetch Retrieves records in the requested format from a list of one or more primary IDs or from the user’s environment

epost Posts a file containing a list of primary IDs for future use in the user’s environment to use with subsequent search strategies

esearch Searches and retrieves primary IDs (for use in EFetch, ELink, and ESummary) and term translations and optionally retains results for future use in the user’s environment.

elink Checks for the existence of an external or Related Articles link from a list of one or more primary IDs. Retrieves primary IDs and relevancy scores for links to Entrez databases or Related Articles; creates a hyperlink to the primary LinkOut provider for a specific ID and database, or lists LinkOut URLs and Attributes for multiple IDs.

einfo Provides field index term counts, last update, and available links for each database.

esummary Retrieves document summaries from a list of primary IDs or from the user’s environment.

egquery Provides Entrez database counts in XML for a single search using Global Query.

espell Retrieves spelling suggestions.

ecitmatch Retrieves PubMed IDs (PMIDs) that correspond to a set of input citation strings.
read Parses the XML results returned by any of the above functions. Typical usage is:
>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> handle = Entrez.einfo() # or esearch, efetch, ...
>>> record = Entrez.read(handle)
>>> handle.close()
where record is now a Python dictionary or list.
parse Parses the XML results returned by those of the above functions which can return multiple records - such as efetch, esummary and elink. Typical usage is:
>>> handle = Entrez.esummary(db="pubmed", id="19304878,14630660", retmode="xml")
>>> records = Entrez.parse(handle)
>>> for record in records:
...     # each record is a Python dictionary or list.
...     print(record['Title'])
Biopython: freely available Python tools for computational molecular biology and bioinformatics.
PDB file parser and structure class implemented in Python.
>>> handle.close()
This function is appropriate only if the XML file contains multiple records, and is particular useful for large files.
_open Internally used function.

Bio.Entrez.epost(db, **keywds)¶

Post a file of identifiers for future use.

Posts a file containing a list of UIs for future use in the user’s environment to use with subsequent search strategies.

See the online documentation for an explanation of the parameters: http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EPost

Return a handle to the results.

Raises an IOError exception if there’s a network error.

Bio.Entrez.efetch(db, **keywords)¶

Fetch Entrez results which are returned as a handle.

EFetch retrieves records in the requested format from a list of one or more UIs or from user’s environment.

See the online documentation for an explanation of the parameters: http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EFetch

Return a handle to the results.

Raises an IOError exception if there’s a network error.

Short example:

>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> handle = Entrez.efetch(db="nucleotide", id="AY851612", rettype="gb", retmode="text")
>>> print(handle.readline().strip())
LOCUS       AY851612                 892 bp    DNA     linear   PLN 10-APR-2007
>>> handle.close()

This will automatically use an HTTP POST rather than HTTP GET if there are over 200 identifiers as recommended by the NCBI.

Warning: The NCBI changed the default retmode in Feb 2012, so many databases which previously returned text output now give XML.

Bio.Entrez.esearch(db, term, **keywds)¶

Run an Entrez search and return a handle to the results.

ESearch searches and retrieves primary IDs (for use in EFetch, ELink and ESummary) and term translations, and optionally retains results for future use in the user’s environment.

See the online documentation for an explanation of the parameters: http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ESearch

Return a handle to the results which are always in XML format.

Raises an IOError exception if there’s a network error.

Short example:

>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> handle = Entrez.esearch(db="nucleotide", retmax=10, term="opuntia[ORGN] accD", idtype="acc")
>>> record = Entrez.read(handle)
>>> handle.close()
>>> int(record["Count"]) >= 2
True
>>> "EF590893.1" in record["IdList"]
True
>>> "EF590892.1" in record["IdList"]
True

Bio.Entrez.elink(**keywds)¶

Check for linked external articles and return a handle.

ELink checks for the existence of an external or Related Articles link from a list of one or more primary IDs; retrieves IDs and relevancy scores for links to Entrez databases or Related Articles; creates a hyperlink to the primary LinkOut provider for a specific ID and database, or lists LinkOut URLs and attributes for multiple IDs.

See the online documentation for an explanation of the parameters: http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ELink

Return a handle to the results, by default in XML format.

Raises an IOError exception if there’s a network error.

This example finds articles related to the Biopython application note’s entry in the PubMed database:

>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> pmid = "19304878"
>>> handle = Entrez.elink(dbfrom="pubmed", id=pmid, linkname="pubmed_pubmed")
>>> record = Entrez.read(handle)
>>> handle.close()
>>> print(record[0]["LinkSetDb"][0]["LinkName"])
pubmed_pubmed
>>> linked = [link["Id"] for link in record[0]["LinkSetDb"][0]["Link"]]
>>> "17121776" in linked
True

This is explained in much more detail in the Biopython Tutorial.

Bio.Entrez.einfo(**keywds)¶

Return a summary of the Entrez databases as a results handle.

EInfo provides field names, index term counts, last update, and available links for each Entrez database.

See the online documentation for an explanation of the parameters: http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EInfo

Return a handle to the results, by default in XML format.

Raises an IOError exception if there’s a network error.

Short example:

>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> record = Entrez.read(Entrez.einfo())
>>> 'pubmed' in record['DbList']
True

Bio.Entrez.esummary(**keywds)¶

Retrieve document summaries as a results handle.

ESummary retrieves document summaries from a list of primary IDs or from the user’s environment.

See the online documentation for an explanation of the parameters: http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ESummary

Return a handle to the results, by default in XML format.

Raises an IOError exception if there’s a network error.

This example discovers more about entry 19923 in the structure database:

>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> handle = Entrez.esummary(db="structure", id="19923")
>>> record = Entrez.read(handle)
>>> handle.close()
>>> print(record[0]["Id"])
19923
>>> print(record[0]["PdbDescr"])
Crystal Structure Of E. Coli Aconitase B

Bio.Entrez.egquery(**keywds)¶

Provide Entrez database counts for a global search.

EGQuery provides Entrez database counts in XML for a single search using Global Query.

See the online documentation for an explanation of the parameters: http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EGQuery

Return a handle to the results in XML format.

Raises an IOError exception if there’s a network error.

This quick example based on a longer version from the Biopython Tutorial just checks there are over 60 matches for ‘Biopython’ in PubMedCentral:

>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> handle = Entrez.egquery(term="biopython")
>>> record = Entrez.read(handle)
>>> handle.close()
>>> for row in record["eGQueryResult"]:
...     if "pmc" in row["DbName"]:
...         print(int(row["Count"]) > 60)
True

Bio.Entrez.espell(**keywds)¶

Retrieve spelling suggestions as a results handle.

ESpell retrieves spelling suggestions, if available.

See the online documentation for an explanation of the parameters: http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ESpell

Return a handle to the results, by default in XML format.

Raises an IOError exception if there’s a network error.

Short example:

>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> record = Entrez.read(Entrez.espell(term="biopythooon"))
>>> print(record["Query"])
biopythooon
>>> print(record["CorrectedQuery"])
biopython

Bio.Entrez.ecitmatch(**keywds)¶

Retrieve PMIDs for input citation strings, returned as a handle.

ECitMatch retrieves PubMed IDs (PMIDs) that correspond to a set of input citation strings.

See the online documentation for an explanation of the parameters: http://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ECitMatch

Return a handle to the results, by default in plain text

Raises an IOError exception if there’s a network error.

Short example:

>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> citation_1 = {"journal_title": "proc natl acad sci u s a",
...               "year": "1991", "volume": "88", "first_page": "3248",
...               "author_name": "mann bj", "key": "citation_1"}
>>> handle = Entrez.ecitmatch(db="pubmed", bdata=[citation_1])
>>> print(handle.read().strip().split("|"))
['proc natl acad sci u s a', '1991', '88', '3248', 'mann bj', 'citation_1', '2014248']
>>> handle.close()

Bio.Entrez.read(handle, validate=True, escape=False)¶

Parse an XML file from the NCBI Entrez Utilities into python objects.

This function parses an XML file created by NCBI’s Entrez Utilities, returning a multilevel data structure of Python lists and dictionaries. Most XML files returned by NCBI’s Entrez Utilities can be parsed by this function, provided its DTD is available. Biopython includes the DTDs for most commonly used Entrez Utilities.

If validate is True (default), the parser will validate the XML file against the DTD, and raise an error if the XML file contains tags that are not represented in the DTD. If validate is False, the parser will simply skip such tags.

If escape is True, all characters that are not valid HTML are replaced by HTML escape characters to guarantee that the returned strings are valid HTML fragments. For example, a less-than sign (<) is replaced by <. If escape is False (default), the string is returned as is.

Whereas the data structure seems to consist of generic Python lists, dictionaries, strings, and so on, each of these is actually a class derived from the base type. This allows us to store the attributes (if any) of each element in a dictionary my_element.attributes, and the tag name in my_element.tag.

Bio.Entrez.parse(handle, validate=True, escape=False)¶

Parse an XML file from the NCBI Entrez Utilities into python objects.

This function parses an XML file created by NCBI’s Entrez Utilities, returning a multilevel data structure of Python lists and dictionaries. This function is suitable for XML files that (in Python) can be represented as a list of individual records. Whereas ‘read’ reads the complete file and returns a single Python list, ‘parse’ is a generator function that returns the records one by one. This function is therefore particularly useful for parsing large files.

Most XML files returned by NCBI’s Entrez Utilities can be parsed by this function, provided its DTD is available. Biopython includes the DTDs for most commonly used Entrez Utilities.

If validate is True (default), the parser will validate the XML file against the DTD, and raise an error if the XML file contains tags that are not represented in the DTD. If validate is False, the parser will simply skip such tags.

If escape is True, all characters that are not valid HTML are replaced by HTML escape characters to guarantee that the returned strings are valid HTML fragments. For example, a less-than sign (<) is replaced by <. If escape is False (default), the string is returned as is.

Whereas the data structure seems to consist of generic Python lists, dictionaries, strings, and so on, each of these is actually a class derived from the base type. This allows us to store the attributes (if any) of each element in a dictionary my_element.attributes, and the tag name in my_element.tag.