def command_info(cls, id=None, running=None, failed=None):
cmds = {}
if id is not None:
try:
id = int(id)
return jsonreadify(cls.launched_commands[id])
except KeyError:
raise CommandError("No such command with ID %s" % repr(id))
except ValueError:
raise CommandError("Invalid ID %s" % repr(id))
if running is not None:
is_done = not to_boolean(running)
else:
is_done = None
if failed is not None:
failed = to_boolean(failed)
for _id, cmd in cls.launched_commands.items():
if is_done is not None:
# running or done commands (not both)
if cmd.get("is_done") == is_done:
# done + failed (a failed command is always done btw)
if failed is not None and cmd.get("is_done") == True:
if cmd.get("failed") == failed:
cmds[_id] = jsonreadify(cmd)
else:
# don't care if failed or not
cmds[_id] = jsonreadify(cmd)
else:
# If asked is_done=true, it means command _id has is_done=false
# if we get there. So the command is sill running, so we don't
# know if it failed or not, so no need to check failed there,
# it's been handled above.
# If asksed is_done=false, we don't need to check failed,
# same logic applies
continue
else:
# either running or done commands (both)
if failed is not None and cmd.get("is_done") == True:
if cmd.get("failed") == failed:
cmds[_id] = jsonreadify(cmd)
else:
# don't care if failed or not
cmds[_id] = jsonreadify(cmd)
return cmds
def _map_line_to_json(df):
chrom = df['chromosome']
if chrom == 'M':
chrom = 'MT'
ref = df["reference_allele"]
alt = df["tumor_seq_allele1"]
if alt == '-':
HGVS = get_hgvs_from_vcf(chrom,
int(df['start_position']) - 1,
'N' + ref,
'N',
mutant_type=False)
elif ref == '-':
HGVS = get_hgvs_from_vcf(chrom,
int(df['start_position']) - 1,
'N',
'N' + alt,
mutant_type=False)
else:
HGVS = get_hgvs_from_vcf(chrom,
int(df['start_position']),
ref,
alt,
mutant_type=False)
ccle_depmap = {
'gene': {
'id': df['entrez_gene_id'],
'symbol': df['hugo_symbol']
},
'chrom':
chrom,
'hg19': {
'start': df['start_position'],
'end': df['end_position']
},
'strand':
df['strand'],
'class':
df['variant_classification'],
'vartype':
df['variant_type'],
'ref':
df['reference_allele'],
'tumor_seq_allele1':
df['tumor_seq_allele1'],
'dbsnp': {
'rsid': df['dbsnp_rs'],
'val_status': df['dbsnp_val_status']
},
'genome_change':
df['genome_change'],
'annotation_transcript':
df['annotation_transcript'],
'tumor_sample_barcode':
df['tumor_sample_barcode'],
'cdna_change':
df['cdna_change'],
'codon_change':
df['codon_change'],
'protein_change':
df['protein_change'],
'isdeleterious':
to_boolean(df['isdeleterious'],
true_str=[
'TRUE',
],
false_str=[
'FALSE',
]),
'istcgahotspot':
to_boolean(df['istcgahotspot'],
true_str=[
'TRUE',
],
false_str=[
'FALSE',
]),
'tcgahscnt':
df['tcgahscnt'],
'iscosmichotspot':
to_boolean(df['iscosmichotspot'],
true_str=[
'TRUE',
],
false_str=[
'FALSE',
]),
'cosmichscnt':
df['cosmichscnt'],
'exac_af':
df['exac_af'],
'wes_ac':
df['wes_ac'],
'sanger': {
'wes_ac': df['sangerwes_ac'],
'recalibwes_ac': df['sangerrecalibwes_ac']
},
'rnaseq_ac':
df['rnaseq_ac'],
'hc_ac':
df['hc_ac'],
'rd_ac':
df['rd_ac'],
'wgs_ac':
df['wgs_ac'],
'broad_id':
df['broad_id']
}
ccle_depmap = dict_sweep(ccle_depmap)
# load as json data
one_snp_json = {"_id": HGVS, "ccle": ccle_depmap}
one_snp_json = value_convert_to_number(one_snp_json)
one_snp_json['ccle']['chrom'] = str(one_snp_json['ccle']['chrom'])
return one_snp_json
def get(self,name=None):
debug = to_boolean(self.get_query_argument("debug",False))
if name:
self.write(self.get_source(name,debug))
else:
self.write(self.get_sources(debug))