Package Entrez

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/entrez/query/static/epost_help.html

Return a handle to the results.

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

Fetches 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/entrez/query/static/efetch_help.html

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="57240072", rettype="gb", retmode="text")
>>> print handle.readline().strip()
LOCUS       AY851612                 892 bp    DNA     linear   PLN 10-APR-2007
>>> handle.close()

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

ESearch runs an Entrez search and returns 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/entrez/query/static/esearch_help.html

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")
>>> record = Entrez.read(handle)
>>> handle.close()
>>> record["Count"] >= 2
True
>>> "156535671" in record["IdList"]
True
>>> "156535673" in record["IdList"]
True

ELink checks for linked external articles and returns 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/entrez/query/static/elink_help.html

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.

EInfo returns a summary of the Entez 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/entrez/query/static/einfo_help.html

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

ESummary retrieves 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/entrez/query/static/esummary_help.html

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 30367 in the journals database:

>>> from Bio import Entrez
>>> Entrez.email = "Your.Name.Here@example.org"
>>> handle = Entrez.esummary(db="journals", id="30367")
>>> record = Entrez.read(handle)
>>> handle.close()
>>> print record[0]["Id"]
30367
>>> print record[0]["Title"]
Computational biology and chemistry

EGQuery provides 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/entrez/query/static/egquery_help.html

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 row["Count"] > 60
True

ESpell retrieves spelling suggestions, returned in 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/entrez/query/static/espell_help.html

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

Parses 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.

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.

Parses 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.

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.