def _loadNodes(self,ncbiDumpFile):
inp = openCompressed(ncbiDumpFile,'r')
nodes = {}
n_splits = self.nInputFields
#delimRe = re.compile(r"\s*\|\s*")
for rec in inp:
# On profiling, string methods outperformed regexes (compare next two lines):
#values = [ x.strip() for x in rec.split('\t|\t',n_splits)[:n_splits]]
#values = delimRe.split(rec,n_splits)
# This will not split the last field, but we never use it anyway:
values = rec.split("\t|\t")
node = TaxaNode()
node.id = int(values[0])
node.idpar = int(values[1])
node.rank = values[2].replace(' ','_')
node.divid = int(values[4])
#in NCBI file, root node points to itself as a parent.
#We replace it with 0 for consistency with our SQL DB representation, where
#circular self-reference would be inconvenient.
if node.idpar == node.id:
node.idpar = 0
nodes[node.id] = node
assert node.id < ncbiTaxidMax, "We assume that dump file is pristine NCBI file and "+\
"assert that taxonomy ID (%s) < our max limit (%s)" % (node.id,ncbiTaxidMax)
inp.close()
self.nodes = nodes
def load(self):
db = self.db
reader = db.makeBulkReader(sql="select * from %s" % (self.tblNodes,),bufLen=100000)
nodes = {}
for chunk in reader.chunks():
for rec in chunk:
node = TaxaNode()
node.id = rec['id']
node.idpar = rec['idpar']
node.rank = rec['rank']
node.lnest = rec['lnest']
node.rnest = rec['rnest']
node.depth = rec['depth']
node.seq_len = rec['seq_len']
node.seq_len_tot = rec['seq_len_tot']
node.idlevel = rec['idlevel']
node.divid = rec['divid']
nodes[node.id] = node
reader.close()
return dict(nodes=nodes,merged={})
