# retrieve from our database
if not _force_update:
existing = Study.retrieve(ncts)
for ex in existing:
trials[ex.nct] = ex
# loop trials
for nct in ncts:
if not nct:
continue
# get the trial fresh via web
if nct in trials:
trial = trials[nct]
else:
trial = lilly.get_trial(nct)
if trial is None:
raise Exception("No trial for %s" % nct)
trial.store()
# skip if not in the US
countries = getattr(trial, 'location_countries')
if countries is None or 0 == len(countries) or u'United States' not in countries.get('country', []):
# print '--> Skipping %s (%s)' % (nct, countries)
continue
# print '==> Using %s' % nct
first_y = trial.entered
last_y = trial.last_updated
# collect trial attributes
# retrieve from our database
if not _force_update:
existing = Study.retrieve(ncts)
for ex in existing:
trials[ex.nct] = ex
# loop trials
for nct in ncts:
if not nct:
continue
# get the trial fresh via web
if nct in trials:
trial = trials[nct]
else:
trial = lilly.get_trial(nct)
if trial is None:
raise Exception("No trial for %s" % nct)
trial.store()
# skip if not in the US
countries = getattr(trial, 'location_countries')
if countries is None or 0 == len(
countries) or u'United States' not in countries.get(
'country', []):
# print '--> Skipping %s (%s)' % (nct, countries)
continue
# print '==> Using %s' % nct
first_y = trial.entered
last_y = trial.last_updated
# open output file
csv_new = "%s-auto-updated.csv" % os.path.splitext(
csv_path)[0].replace('-manual', '')
with codecs.open(csv_new, 'w') as w_handle:
lilly = LillyCOI()
# ref_date = datetime.datetime(2013, 7, 30) # this can NOT be used against date last updated, of course
ref_date = datetime.datetime.now()
writer = csv.writer(w_handle)
header.pop(idx_drop)
writer.writerow(header)
# loop trials
for row in reader:
trial = lilly.get_trial(row[idx_nct])
# date calculations
first = trial.date('firstreceived_date')
first_y = round((ref_date - first[1]).days / 365.25 *
10) / 10 if first[1] else 99
last = trial.date('lastchanged_date')
last_y = round((ref_date - last[1]).days / 365.25 *
10) / 10 if last[1] else 99
comp = trial.date('primary_completion_date')
comp_y = round((ref_date - comp[1]).days / 365.25 *
10) / 10 if comp[1] else 99
veri = trial.date('verification_date')
veri_y = round((ref_date - veri[1]).days / 365.25 *
10) / 10 if veri[1] else 99
idx_last = header.index('last update yrs ago')
# open output file
csv_new = "%s-auto-updated.csv" % os.path.splitext(csv_path)[0].replace('-manual', '')
with codecs.open(csv_new, 'w') as w_handle:
lilly = LillyCOI()
# ref_date = datetime.datetime(2013, 7, 30) # this can NOT be used against date last updated, of course
ref_date = datetime.datetime.now()
writer = csv.writer(w_handle)
header.pop(idx_drop)
writer.writerow(header)
# loop trials
for row in reader:
trial = lilly.get_trial(row[idx_nct])
# date calculations
first = trial.date('firstreceived_date')
first_y = round((ref_date - first[1]).days / 365.25 * 10) / 10 if first[1] else 99
last = trial.date('lastchanged_date')
last_y = round((ref_date - last[1]).days / 365.25 * 10) / 10 if last[1] else 99
comp = trial.date('primary_completion_date')
comp_y = round((ref_date - comp[1]).days / 365.25 * 10) / 10 if comp[1] else 99
veri = trial.date('verification_date')
veri_y = round((ref_date - veri[1]).days / 365.25 * 10) / 10 if veri[1] else 99
# write updated row
row[idx_first] = first_y
row[idx_last] = last_y
row.pop(idx_drop)
