def search(self,start,end):
search_command = 'Search'
search_database = 'Protein'
return_format = 'GenPept'
Protein_gi_line = re.compile(r'Protein\<\/a\>')
CDS_gi_line = re.compile(r'CDS\<\/a\>')
pattern_gi = re.compile(r'val=(\d*)')
j=1
if start<1:
start =1
if end >len(self.accs) or end == 0:
end = len(self.accs)
for k in range(start-1,end):
sys.stderr.write("No " + repr(j) + ": " + self.accs[k] +'\n')
j=j+1
try :
result_handle = NCBI.query(search_command, search_database, term=self.accs[k], doptcmdl = return_format)
tmp=result_handle.readline()
sys.stdout.write(tmp)
while tmp:
sys.stdout.write(tmp)
if Protein_gi_line.search(tmp):
protein_gi=pattern_gi.search(tmp).group(1)
sys.stderr.write( "fetching "+protein_gi + '\n')
protein_handle=NCBI.query('Text',search_database, uid=protein_gi,dopt=return_format)
proteinfile.write(protein_handle.read())
if CDS_gi_line.search(tmp):
CDS_gi=pattern_gi.search(tmp).group(1)
#sys.stderr.write( "fetching " + CDS_gi + '\n')
#CDS_handle=NCBI.query('Text','nucleotide', uid=CDS_gi,dopt='GenBank')
#CDSfile.write(CDS_handle.read())
tmp = result_handle.readline()
except:
print "Entrez query error"
def find_related(pmid):
"""find_related(pmid) -> ids
Search PubMed for a list of citations related to pmid. pmid can
be a PubMed ID, a MEDLINE UID, or a list of those.
"""
class ResultParser(sgmllib.SGMLParser):
# Parse the ID's out of the HTML-formatted page that PubMed
# returns. The format of the page is:
# [...]
# <Link>
# <Id>######</Id>
# <Score>######</Score>
# [...]
# </Link>
# [...]
def __init__(self):
sgmllib.SGMLParser.__init__(self)
self.ids = []
self.in_link = 0
self.in_id = 0
def start_id(self, attributes):
self.in_id = 1
def end_id(self):
self.in_id = 0
def start_link(self, attributes):
self.in_link = 1
def end_link(self):
self.in_link = 0
_not_pmid_re = re.compile(r'\D')
def handle_data(self, data):
if not self.in_link or not self.in_id:
return
# Everything here should be a PMID. Check and make sure
# data really is one. A PMID should be a string consisting
# of only integers. Should I check to make sure it
# meets a certain minimum length?
if self._not_pmid_re.search(data):
raise ValueError, \
"I expected an ID, but '%s' doesn't look like one." % \
repr(data)
self.ids.append(data)
parser = ResultParser()
if type(pmid) is type([]):
pmid = string.join(pmid, ',')
h = NCBI.elink(dbfrom='pubmed', id=pmid)
parser.feed(h.read())
return parser.ids
def __getitem__(self, id):
"""S.__getitem__(id) -> object
Return the Medline entry. id is either the Medline Unique ID
or the Pubmed ID of the article. Raises a KeyError if there's an
error.
"""
# First, check to see if enough time has passed since my
# last query.
self.limiter.wait()
try:
handle = NCBI.efetch(
db="pubmed", id=id, retmode='text', rettype='medlars')
except IOError, x:
# raise a KeyError instead of an IOError
# XXX I really should distinguish between a real IOError and
# if the id is not in the database.
raise KeyError, x
See http://www.ncbi.nlm.nih.gov/entrez/query/static/linking.html for
more help understanding the parameters passed.
This also requires a web browser to run -- either netscape or lynx
are supported in this example."""
# standard library
import os
# biopython
from Bio.WWW import NCBI
search_command = 'Search'
search_database = 'Nucleotide'
return_format = 'FASTA'
search_term = 'Cypripedioideae'
my_browser = 'lynx'
result_handle = NCBI.query(search_command, search_database, term = search_term,
doptcmdl = return_format)
result_file_name = os.path.join(os.getcwd(), 'results.html')
result_file = open(result_file_name, 'w')
result_file.write(result_handle.read())
result_file.close()
if my_browser == 'lynx':
os.system('lynx -force_html ' + result_file_name)
elif my_browser == 'netscape':
os.system('netscape file:' + result_file_name)
def download_many(ids, callback_fn, broken_fn=None, delay=120.0, faildelay=5.0,
batchsize=500, parser=None):
"""download_many(ids, callback_fn[, broken_fn][, delay][, faildelay][, batchsize])
Download many records from PubMed. ids is a list of either the
Medline Unique ID or the PubMed ID's of the articles. Each time a
record is downloaded, callback_fn is called with the text of the
record. broken_fn is an optional function that is called with the
id of records that were not able to be downloaded. delay is the
number of seconds to wait between requests. batchsize is the
number of records to request each time.
"""
# parser is an undocumented parameter that allows people to
# specify an optional parser to handle each record. This is
# dangerous because the results may be malformed, and exceptions
# in the parser may disrupt the whole download process.
if batchsize > 500 or batchsize < 1:
raise ValueError, "batchsize must be between 1 and 500"
limiter = RequestLimiter(delay)
current_batchsize = batchsize
# Loop until all the ids are processed. We want to process as
# many as possible with each request. Unfortunately, errors can
# occur. Some id may be incorrect, or the server may be
# unresponsive. In addition, one broken id out of a list of id's
# can cause a non-specific error. Thus, the strategy I'm going to
# take, is to start by downloading as many as I can. If the
# request fails, I'm going to half the number of records I try to
# get. If there's only one more record, then I'll report it as
# broken and move on. If the request succeeds, I'll double the
# number of records until I get back up to the batchsize.
nsuccesses = 0
while ids:
if current_batchsize > len(ids):
current_batchsize = len(ids)
id_str = ','.join(ids[:current_batchsize])
# Make sure enough time has passed before I do another query.
if not nsuccesses:
limiter.wait(faildelay)
else:
limiter.wait()
try:
# Query PubMed. If one or more of the id's are broken,
# this will raise an IOError.
handle = NCBI.efetch(
db="pubmed", id=id_str, retmode='text', rettype='medlars')
# I'm going to check to make sure PubMed returned the same
# number of id's as I requested. If it didn't then I'm going
# to raise an exception. This could take a lot of memory if
# the batchsize is large.
results = handle.read()
num_ids = 0
for x in Medline.Iterator(File.StringHandle(results)):
num_ids = num_ids + 1
if num_ids != current_batchsize:
raise IOError
handle = File.StringHandle(results)
except IOError: # Query did not work.
if current_batchsize == 1:
# There was only 1 id in the query. Report it as
# broken and move on.
id = ids.pop(0)
if broken_fn is not None:
broken_fn(id)
else:
# I don't know which one is broken. Try again with
# fewer id's.
current_batchsize = current_batchsize / 2
nsuccesses = 0
continue
nsuccesses = nsuccesses + 1
# Iterate through the results and pass the records to the
# callback.
idnum = 0
for rec in Medline.Iterator(handle, parser):
callback_fn(ids[idnum], rec)
idnum = idnum + 1
ids = ids[current_batchsize:]
# If I'm not downloading the maximum number of articles,
# double the number for next time.
if nsuccesses >= 2 and current_batchsize < batchsize:
current_batchsize = current_batchsize * 2
if current_batchsize > batchsize:
current_batchsize = batchsize
def search_for(search, reldate=None, mindate=None, maxdate=None,
batchsize=100, delay=2, callback_fn=None,
start_id=0, max_ids=None):
"""search_for(search[, reldate][, mindate][, maxdate]
[, batchsize][, delay][, callback_fn][, start_id][, max_ids]) -> ids
Search PubMed and return a list of the PMID's that match the
criteria. search is the search string used to search the
database. reldate is the number of dates prior to the current
date to restrict the search. mindate and maxdate are the dates to
restrict the search, e.g. 2002/01/01. batchsize specifies the
number of ids to return at one time. By default, it is set to
10000, the maximum. delay is the number of seconds to wait
between queries (default 2). callback_fn is an optional callback
function that will be called as passed a PMID as results are
retrieved. start_id specifies the index of the first id to
retrieve and max_ids specifies the maximum number of id's to
retrieve.
XXX The date parameters don't seem to be working with NCBI's
script. Please let me know if you can get it to work.
"""
class ResultParser(sgmllib.SGMLParser):
# Parse the ID's out of the XML-formatted page that PubMed
# returns. The format of the page is:
# [...]
# <Id>...</Id>
# [...]
def __init__(self):
sgmllib.SGMLParser.__init__(self)
self.ids = []
self.in_id = 0
def start_id(self, attributes):
self.in_id = 1
def end_id(self):
self.in_id = 0
_not_pmid_re = re.compile(r'\D')
def handle_data(self, data):
if not self.in_id:
return
# If data is just whitespace, then ignore it.
data = string.strip(data)
if not data:
return
# Everything here should be a PMID. Check and make sure
# data really is one. A PMID should be a string consisting
# of only integers. Should I check to make sure it
# meets a certain minimum length?
if self._not_pmid_re.search(data):
raise ValueError, \
"I expected an ID, but %s doesn't look like one." % \
repr(data)
self.ids.append(data)
params = {
'db' : 'pubmed',
'term' : search,
'reldate' : reldate,
'mindate' : mindate,
'maxdate' : maxdate
}
for k, v in params.items():
if v is None:
del params[k]
limiter = RequestLimiter(delay)
ids = []
while max_ids is None or len(ids) < max_ids:
parser = ResultParser()
# Check to make sure enough time has passed before my
# last search. If not, then wait.
limiter.wait()
start = start_id + len(ids)
max = batchsize
if max_ids is not None and max > max_ids - len(ids):
max = max_ids - len(ids)
params['retstart'] = start
params['retmax'] = max
h = NCBI.esearch(**params)
parser.feed(h.read())
ids.extend(parser.ids)
if callback_fn is not None:
# Call the callback function with each of the new ID's.
for id in parser.ids:
callback_fn(id)
if len(parser.ids) < max or not parser.ids: # no more id's to read
break
return ids
more help understanding the parameters passed.
This also requires a web browser to run -- either netscape or lynx
are supported in this example."""
# standard library
import os
# biopython
from Bio.WWW import NCBI
search_command = 'Search'
search_database = 'Nucleotide'
return_format = 'FASTA'
search_term = 'Cypripedioideae'
my_browser = 'lynx'
result_handle = NCBI.query(search_command,
search_database,
term=search_term,
doptcmdl=return_format)
result_file_name = os.path.join(os.getcwd(), 'results.html')
result_file = open(result_file_name, 'w')
result_file.write(result_handle.read())
result_file.close()
if my_browser == 'lynx':
os.system('lynx -force_html ' + result_file_name)
elif my_browser == 'netscape':
os.system('netscape file:' + result_file_name)