def find_batch_runs(kive, batch_name, batch_size):
run_map = {} # {sample_name: status}
run_count = 0
for i in range(1, 201):
response = kive.get('/api/runs/status/',
params={
'page_size': 25,
'page': i
})
response.raise_for_status()
json = response.json()
for entry in json['results']:
text_status = entry['run_progress']['status']
pipeline_id = entry['pipeline']
if (re.match(r'^\*+-\*+$', text_status) is None
or pipeline_id not in kive_pipelines):
continue
display_match = re.match(r'^MiSeq - ([^_]*_S\d+)$',
entry['display_name'])
if display_match is not None:
if batch_name not in entry['runbatch_name']:
continue
sample_name = display_match.group(1)
else:
status_response = kive.get(entry['run_status'])
status_response.raise_for_status()
status_json = status_response.json()
is_match = False
sample_name = None
for input_dataset_name in map(itemgetter('dataset_name'),
status_json['inputs'].values()):
if input_dataset_name.endswith('_quality.csv'):
is_match = batch_name in input_dataset_name
elif input_dataset_name.endswith('.fastq.gz'):
sample_name = '_'.join(
input_dataset_name.split('_')[:2])
if not is_match or sample_name is None:
continue
status = RunStatus(entry, kive)
status.json = entry
run_map[sample_name] = status
run_count = len(run_map)
print('Found {} of {} runs after {} pages.'.format(
run_count, batch_size, i))
if run_count >= batch_size:
break
if run_count < batch_size:
raise Exception('Expected {} samples, but only found {}.'.format(
batch_size, run_count))
runs = list(run_map.items())
runs.sort()
return runs
def find_batch_runs(kive, batch_name, batch_size):
run_map = {} # {sample_name: status}
for i in range(1, 201):
response = kive.get('/api/runs/status/',
params={
'page_size': 25,
'page': i
})
response.raise_for_status()
json = response.json()
for entry in json['results']:
text_status = entry['run_progress']['status']
pipeline_id = entry['pipeline']
if re.match(r'^\*+-\*+$',
text_status) is None or pipeline_id != 167:
continue
display_match = re.match(r'^MiSeq - ([^_]*_S\d+) \((.*)\)$',
entry['display_name'])
if display_match is not None:
if display_match.group(2) != batch_name:
continue
sample_name = display_match.group(1)
else:
status_response = kive.get(entry['run_status'])
status_response.raise_for_status()
status_json = status_response.json()
quality_filename = status_json['inputs']['1']['dataset_name']
if quality_filename != '{}_quality.csv'.format(batch_name):
continue
sample_filename = status_json['inputs']['2']['dataset_name']
sample_name = '_'.join(sample_filename.split('_')[:2])
status = RunStatus(entry, kive)
status.json = entry
run_map[sample_name] = status
run_count = len(run_map)
print('Found {} of {} runs after {} pages.'.format(
run_count, batch_size, i))
if run_count >= batch_size:
break
if run_count < batch_size:
raise StandardError('Expected {} samples, but only found {}.'.format(
batch_size, run_count))
runs = run_map.items()
runs.sort()
return runs
def find_old_runs(kive, **kwargs):
params = {}
param_count = 0
for key, val in kwargs.items():
if val is not None:
params['filters[{}][key]'.format(param_count)] = key
params['filters[{}][val]'.format(param_count)] = val
param_count += 1
response = kive.get('/api/runs/status/', params=params)
response.raise_for_status()
json = response.json()
runs = []
for entry in json:
status = RunStatus(entry, kive)
status.json = entry
status_response = kive.get(entry['run_status'])
status_response.raise_for_status()
sample_filename = status_response.json()['inputs']['2']['dataset_name']
sample_name = '_'.join(sample_filename.split('_')[:2])
runs.append((sample_name, status))
runs.sort()
return runs
def find_old_runs(kive, **kwargs):
params = {}
param_count = 0
for key, val in kwargs.iteritems():
if val is not None:
params["filters[{}][key]".format(param_count)] = key
params["filters[{}][val]".format(param_count)] = val
param_count += 1
response = kive.get("/api/runs/status/", params=params)
response.raise_for_status()
json = response.json()
runs = []
for entry in json:
status = RunStatus(entry, kive)
status.json = entry
status_response = kive.get(entry["run_status"])
status_response.raise_for_status()
sample_filename = status_response.json()["inputs"]["2"]["dataset_name"]
sample_name = "_".join(sample_filename.split("_")[:2])
runs.append((sample_name, status))
runs.sort()
return runs
def find_batch_runs(kive, batch_name, batch_size):
run_map = {} # {sample_name: status}
for i in range(1, 201):
response = kive.get("/api/runs/status/", params={"page_size": 25, "page": i})
response.raise_for_status()
json = response.json()
for entry in json["results"]:
text_status = entry["run_progress"]["status"]
pipeline_id = entry["pipeline"]
if re.match(r"^\*+-\*+$", text_status) is None or pipeline_id != 167:
continue
display_match = re.match(r"^MiSeq - ([^_]*_S\d+) \((.*)\)$", entry["display_name"])
if display_match is not None:
if display_match.group(2) != batch_name:
continue
sample_name = display_match.group(1)
else:
status_response = kive.get(entry["run_status"])
status_response.raise_for_status()
status_json = status_response.json()
quality_filename = status_json["inputs"]["1"]["dataset_name"]
if quality_filename != "{}_quality.csv".format(batch_name):
continue
sample_filename = status_json["inputs"]["2"]["dataset_name"]
sample_name = "_".join(sample_filename.split("_")[:2])
status = RunStatus(entry, kive)
status.json = entry
run_map[sample_name] = status
run_count = len(run_map)
print("Found {} of {} runs after {} pages.".format(run_count, batch_size, i))
if run_count >= batch_size:
break
if run_count < batch_size:
raise StandardError("Expected {} samples, but only found {}.".format(batch_size, run_count))
runs = run_map.items()
runs.sort()
return runs
