def GetLinks(ids, query=None, url=QueryParams.linkBase, conn=None):
if not conn:
try:
iter(ids)
except TypeError:
ids = [
ids,
]
if not query:
query = QueryParams.details()
query['id'] = ','.join(map(str, ids))
conn = openURL(url, urllib.urlencode(query))
query['cmd'] = 'neighbor'
pubmed = ElementTree.parse(conn)
linkset = pubmed.find('LinkSet/LinkSetDb')
scores = []
scoreNorm = 1.0
for link in linkset.getiterator('Link'):
id = link.findtext('Id')
score = float(link.findtext('Score'))
scores.append([id, score])
# we'll normalize scores by the score for the first of the query ids:
if id == ids[0]:
scoreNorm = score
for i in range(len(scores)):
id, score = scores[i]
scores[i] = id, score / scoreNorm
return tuple(scores)
def GetLinks(ids,query=None,url=QueryParams.linkBase,conn=None):
if not conn:
try:
iter(ids)
except TypeError:
ids = [ids,]
if not query:
query = QueryParams.details()
query['id'] = ','.join(map(str,ids))
conn = openURL(url,urllib.urlencode(query))
query['cmd'] = 'neighbor'
pubmed = ElementTree.parse(conn)
linkset = pubmed.find('LinkSet/LinkSetDb')
scores = []
scoreNorm = 1.0
for link in linkset.getiterator('Link'):
id = link.findtext('Id')
score = float(link.findtext('Score'))
scores.append([id,score])
# we'll normalize scores by the score for the first of the query ids:
if id == ids[0]:
scoreNorm = score
for i in range(len(scores)):
id,score = scores[i]
scores[i] = id,score/scoreNorm
return tuple(scores)
def GetRecords(ids, query=None, url=QueryParams.fetchBase, conn=None):
""" gets a set of document summary records for the ids provided
>>> ids = ['11960484']
>>> recs = GetRecords(ids,conn=open(os.path.join(testDataDir,'records.xml'),'r'))
>>> len(recs)
1
>>> rec = recs[0]
>>> rec.PubMedId
'11960484'
>>> rec.Authors
u'Penzotti JE, Lamb ML, Evensen E, Grootenhuis PD'
>>> rec.Title
u'A computational ensemble pharmacophore model for identifying substrates of P-glycoprotein.'
>>> rec.Source
u'J Med Chem'
>>> rec.Volume
'45'
>>> rec.Pages
'1737-40'
>>> rec.PubYear
'2002'
>>> rec.Abstract[:10]
u'P-glycopro'
We've also got access to keywords:
>>> str(rec.keywords[0])
'Combinatorial Chemistry Techniques'
>>> str(rec.keywords[3])
'Indinavir / chemistry'
and chemicals:
>>> rec.chemicals[0]
'P-Glycoprotein'
>>> rec.chemicals[2]
'Nicardipine <55985-32-5>'
"""
if not conn:
try:
iter(ids)
except TypeError:
ids = [
ids,
]
if not query:
query = QueryParams.details()
query['id'] = ','.join(map(str, ids))
conn = openURL(url, urllib.urlencode(query))
pubmed = ElementTree.parse(conn)
res = []
for article in pubmed.getiterator('PubmedArticle'):
rec = Records.JournalArticleRecord(article)
if rec.PubMedId in ids:
res.append(rec)
return tuple(res)
def GetRecords(ids,query=None,url=QueryParams.fetchBase,conn=None):
""" gets a set of document summary records for the ids provided
>>> ids = ['11960484']
>>> recs = GetRecords(ids,conn=open(os.path.join(testDataDir,'records.xml'),'r'))
>>> len(recs)
1
>>> rec = recs[0]
>>> rec.PubMedId
'11960484'
>>> rec.Authors
u'Penzotti JE, Lamb ML, Evensen E, Grootenhuis PD'
>>> rec.Title
u'A computational ensemble pharmacophore model for identifying substrates of P-glycoprotein.'
>>> rec.Source
u'J Med Chem'
>>> rec.Volume
'45'
>>> rec.Pages
'1737-40'
>>> rec.PubYear
'2002'
>>> rec.Abstract[:10]
u'P-glycopro'
We've also got access to keywords:
>>> str(rec.keywords[0])
'Combinatorial Chemistry Techniques'
>>> str(rec.keywords[3])
'Indinavir / chemistry'
and chemicals:
>>> rec.chemicals[0]
'P-Glycoprotein'
>>> rec.chemicals[2]
'Nicardipine <55985-32-5>'
"""
if not conn:
try:
iter(ids)
except TypeError:
ids = [ids,]
if not query:
query = QueryParams.details()
query['id'] = ','.join(map(str,ids))
conn = openURL(url,urllib.urlencode(query))
pubmed = ElementTree.parse(conn)
res = []
for article in pubmed.getiterator('PubmedArticle'):
rec = Records.JournalArticleRecord(article)
if rec.PubMedId in ids:
res.append(rec)
return tuple(res)
def GetSummaries(ids, query=None, url=QueryParams.summaryBase, conn=None):
""" gets a set of document summary records for the ids provided
>>> ids = ['11960484']
>>> summs = GetSummaries(ids,conn=open(os.path.join(testDataDir,'summary.xml'),'r'))
>>> len(summs)
1
>>> rec = summs[0]
>>> isinstance(rec,Records.SummaryRecord)
1
>>> rec.PubMedId
'11960484'
>>> rec.Authors
'Penzotti JE, Lamb ML, Evensen E, Grootenhuis PD'
>>> rec.Title
'A computational ensemble pharmacophore model for identifying substrates of P-glycoprotein.'
>>> rec.Source
'J Med Chem'
>>> rec.Volume
'45'
>>> rec.Pages
'1737-40'
>>> rec.HasAbstract
'1'
"""
if not conn:
try:
iter(ids)
except TypeError:
ids = [
ids,
]
if not query:
query = QueryParams.details()
ids = map(str, ids)
query['id'] = ','.join(ids)
conn = openURL(url, urllib.urlencode(query))
pubmed = ElementTree.parse(conn)
res = []
for summary in pubmed.getiterator('DocSum'):
rec = Records.SummaryRecord(summary)
if rec.PubMedId in ids:
res.append(rec)
ids.remove(rec.PubMedId)
return tuple(res)
def GetSummaries(ids,query=None,url=QueryParams.summaryBase,conn=None):
""" gets a set of document summary records for the ids provided
>>> ids = ['11960484']
>>> summs = GetSummaries(ids,conn=open(os.path.join(testDataDir,'summary.xml'),'r'))
>>> len(summs)
1
>>> rec = summs[0]
>>> isinstance(rec,Records.SummaryRecord)
1
>>> rec.PubMedId
'11960484'
>>> rec.Authors
'Penzotti JE, Lamb ML, Evensen E, Grootenhuis PD'
>>> rec.Title
'A computational ensemble pharmacophore model for identifying substrates of P-glycoprotein.'
>>> rec.Source
'J Med Chem'
>>> rec.Volume
'45'
>>> rec.Pages
'1737-40'
>>> rec.HasAbstract
'1'
"""
if not conn:
try:
iter(ids)
except TypeError:
ids = [ids,]
if not query:
query = QueryParams.details()
ids = map(str,ids)
query['id'] = ','.join(ids)
conn = openURL(url,urllib.urlencode(query))
pubmed = ElementTree.parse(conn)
res = []
for summary in pubmed.getiterator('DocSum'):
rec = Records.SummaryRecord(summary)
if rec.PubMedId in ids:
res.append(rec)
ids.remove(rec.PubMedId)
return tuple(res)
def CheckForLinks(ids,query=None,url=QueryParams.linkBase,conn=None):
if not conn:
try:
iter(ids)
except TypeError:
ids = [ids,]
if not query:
query = QueryParams.details()
query['id'] = ','.join(map(str,ids))
conn = openURL(url,urllib.urlencode(query))
query['cmd'] = 'ncheck'
pubmed = ElementTree.parse(conn)
checklist = pubmed.find('LinkSet/IdCheckList')
recs = [Records.LinkRecord(x) for x in checklist.getiterator('Id')]
res = {}
for rec in recs:
id = rec.PubMedId
res[id] = rec.HasNeighbor
return res
def CheckForLinks(ids,query=None,url=QueryParams.linkBase,conn=None):
if not conn:
try:
iter(ids)
except TypeError:
ids = [ids,]
if not query:
query = QueryParams.details()
query['id'] = ','.join(map(str,ids))
conn = openURL(url,urllib.urlencode(query))
query['cmd'] = 'ncheck'
pubmed = ElementTree.parse(conn)
checklist = pubmed.find('LinkSet/IdCheckList')
recs = [Records.LinkRecord(x) for x in checklist.getiterator('Id')]
res = {}
for rec in recs:
id = rec.PubMedId
res[id] = rec.HasNeighbor
return res