def test_multiple_persons_by_npa():
persons = 100
timestamp = int(time.time())
npa = 3240
for id in range(0,persons):
doc_id = str(uuid.uuid4())[0:10]
print(doc_id)
report = IndividualReportModel(
document_id=doc_id,
diagnostic=random.randint(0, 4),
locator=npa,
session_id=str(uuid.uuid4()),
timestamp=timestamp,
analysis_done=False
)
session.add(report)
session.commit()
analysis_next_report(persons)
_date = datetime.fromtimestamp(timestamp)
print(_date)
q = session.query(DailyDiagnosticChangeModel)
daily_change = q.filter_by(locator=npa, year=_date.year, month=_date.month, day=_date.day).first()
total = daily_change.diagnostic_0 + \
daily_change.diagnostic_1 + \
daily_change.diagnostic_2 + \
daily_change.diagnostic_3 + \
daily_change.diagnostic_4
assert persons == total
def test_one_person_update():
nb_update = 1000
timestamps = range(1584892474, 1584892474 + nb_update)
session_id = str(uuid.uuid4())
npa = 1246
for timestamp in timestamps:
doc_id = str(uuid.uuid4())[0:10]
print(doc_id)
report = IndividualReportModel(
document_id=doc_id,
diagnostic=random.randint(0, 4),
locator=npa,
session_id=session_id,
timestamp=timestamp,
analysis_done=False
)
session.add(report)
session.commit()
analysis_next_report(nb_update)
_date = datetime.fromtimestamp(timestamps[0])
q = session.query(DailyDiagnosticChangeModel)
daily_change = q.filter_by(locator=npa, year=_date.year, month=_date.month, day=_date.day).first()
total = daily_change.diagnostic_0 + \
daily_change.diagnostic_1 + \
daily_change.diagnostic_2 + \
daily_change.diagnostic_3 + \
daily_change.diagnostic_4
print(total)
assert total == 1
def build(json_object):
seconds = json_object["data"]["timestamp"]["_seconds"]
nanoseconds = json_object["data"]["timestamp"]["_nanoseconds"]
timestamp = (seconds +
nanoseconds / 1000000000) * 1000 # to milliseconds
return IndividualReportModel(
document_id=json_object["id"],
diagnostic=json_object["data"]["diagnostic"],
locator=json_object["data"]["locator"],
session_id=json_object["data"]["sessionId"],
timestamp=timestamp,
analysis_done=False,
symptoms=str(json_object["data"]["symptoms"]))
def test_insert_speed():
timestamps = range(1584892474, 1584892474 + 1000)
npa = 1240
start_time = time.time()
for timestamp in timestamps:
doc_id = str(uuid.uuid4())[0:10]
report = IndividualReportModel(
document_id=doc_id,
diagnostic=random.randint(0, 4),
locator=npa,
session_id=str(uuid.uuid4()),
timestamp=timestamp
)
session.add(report)
session.commit()
print('Insertion time:',time.time() - start_time)
def build(json_object):
seconds = json_object["data"]["timestamp"]["_seconds"]
nanoseconds = json_object["data"]["timestamp"]["_nanoseconds"]
timestamp = (seconds +
nanoseconds / 1000000000) * 1000 # to milliseconds
symptoms = json_object["data"]["symptoms"]
return IndividualReportModel(
document_id=json_object["id"],
diagnostic=json_object["data"]["diagnostic"],
locator=json_object["data"]["locator"],
session_id=json_object["data"]["sessionId"],
timestamp=timestamp,
analysis_done=False,
# FIXME: need to be changed if the website is updated with new
# questions based on 1177 guidelines
symptoms=str(symptoms),
temp="mid" if "fever" in symptoms else "low",
cough="sometimes" if "cough" in symptoms else "no",
breathless="sometimes" if "dyspnea" in symptoms else "no",
energy="tired" if "weakness" in symptoms else "normal")
def insert_fake_inidividual_reports():
from_day = '2020-03-10'
to_day = '2020-03-15'
sample_per_day = 1000
person_list = gen_fake_person_list(sample_per_day)
from_date = datetime.strptime(from_day, DAY_FORMAT)
to_date = datetime.strptime(to_day, DAY_FORMAT)
_from = int(datetime.strptime(from_day, DAY_FORMAT).timestamp())
_to = int(datetime.strptime(to_day, DAY_FORMAT).timestamp())
current_day = from_date
while current_day <= to_date:
timestamp = current_day.timestamp()
start_time = time.time()
for sample in range(0, sample_per_day):
person = random_list_element(person_list)
doc_id = str(uuid.uuid4())[0:20]
report = IndividualReportModel(
document_id=doc_id,
diagnostic=random.randint(0, 4),
locator=person['npa'],
session_id=person['session_id'],
timestamp=(timestamp + sample) * 1000, # to millisecond
analysis_done=False)
# print(report.timestamp)
session.add(report)
session.commit()
spend_time = time.time() - start_time
print(
str(current_day) + ': uploaded ' + str(sample_per_day) +
' samples in ' + str(spend_time) + 's')
current_day = current_day + timedelta(days=1)
def insert_fake_inidividual_reports():
from_day = '2020-03-10'
to_day = '2020-03-15'
sample_per_day = 1000
person_list = gen_fake_person_list(sample_per_day)
from_date = datetime.strptime(from_day, DAY_FORMAT)
to_date = datetime.strptime(to_day, DAY_FORMAT)
_from = int(datetime.strptime(from_day, DAY_FORMAT).timestamp())
_to = int(datetime.strptime(to_day, DAY_FORMAT).timestamp())
def random_bool():
return random.randint(0, 1)
current_day = from_date
while current_day <= to_date:
timestamp = current_day.timestamp()
start_time = time.time()
for sample in range(0, sample_per_day):
person = random_list_element(person_list)
doc_id = str(uuid.uuid4())[0:20]
has_comorbid = random_bool()
comorbid = Comorbid(
hypertension = random_bool(),
cardiovascular = random_bool(),
pulmonary = random_bool(),
cancer = random_bool(),
diabetes = random_bool(),
renal = random_bool(),
neurological = random_bool(),
respiratory = random_bool(),
)
report = IndividualReportModel(
# Metadata
document_id=doc_id,
diagnostic=random.randint(0, 4),
locator=person['npa'],
session_id=person['session_id'],
timestamp=(timestamp + sample ) * 1000, # to millisecond
analysis_done=False,
# Actual data
temp=enum.Scale3(random.randint(1, 3)).name,
cough=enum.Scale4(random.randint(0, 3)).name,
breathless=enum.Scale4(random.randint(0, 3)).name,
energy=enum.Energy(random.randint(0, 4)).name,
exposure=enum.Exposure(random.randint(0, 2)).name,
has_comorbid=has_comorbid,
comorbid=comorbid,
compromised_immune=random_bool(),
age=enum.Scale3(random.randint(1, 3)).name,
)
# print(report.timestamp)
session.add(report)
session.commit()
spend_time = time.time() - start_time
print(str(current_day) + ': uploaded ' + str(sample_per_day) + ' samples in ' + str(spend_time) + 's')
current_day = current_day + timedelta(days=1)