def timeseries(client, dataset):
# create
ts = TimeSeries('Human EEG')
assert not ts.exists
dataset.add(ts)
assert ts.exists
assert ts in dataset
assert ts.type == 'TimeSeries'
assert ts.name.startswith(
'Human EEG') #starts with bc duplicate names are appended
ts2 = client.get(ts.id)
assert ts2.id == ts.id
assert ts2.name == ts.name
assert ts2.type == 'TimeSeries'
del ts2
# provide to other tests
yield ts
# streaming credentials
cred = ts.streaming_credentials()
assert cred
# remove
dataset.remove(ts)
assert not ts.exists
assert ts not in dataset
def timeseries(client, dataset):
# create
ts = TimeSeries('Human EEG')
assert not ts.exists
dataset.add(ts)
assert ts.exists
assert ts in dataset
assert ts.type == 'TimeSeries'
assert ts.name == 'Human EEG'
ts2 = client.get(ts.id)
assert ts2.id == ts.id
assert ts2.name == ts.name
assert ts2.type == 'TimeSeries'
del ts2
# provide to other tests
yield ts
# update ts: change name
ts.name = 'Monkey EEG'
ts.update()
ts2 = client.get(ts.id)
assert ts2.id == ts.id
assert ts2.name == ts.name
assert ts2.type == 'TimeSeries'
# streaming credentials
cred = ts.streaming_credentials()
assert cred
# remove
dataset.remove(ts)
assert not ts.exists
assert ts not in dataset
def test_search(client, dataset):
# create
ts = TimeSeries('Human EEG')
assert not ts.exists
dataset.add(ts)
assert ts.exists
assert ts in dataset
assert ts.type == 'TimeSeries'
assert ts.name == 'Human EEG'
ts2 = client.get(ts.id)
assert ts2.id == ts.id
assert ts2.name == ts.name
assert ts2.type == 'TimeSeries'
del ts2
t = Tabular('Some tabular data')
assert not t.exists
assert t.schema is None
# create
dataset.add(t)
assert t.exists
assert t.schema is None
schema = [
TabularSchemaColumn(name='',
display_name='index',
datatype='Integer',
primary_key=True,
internal=True),
TabularSchemaColumn(name='',
display_name='email',
datatype='String',
primary_key=False,
internal=False),
]
s = TabularSchema(name="schema", column_schema=schema)
t.set_schema(s)
assert t.name == 'Some tabular data'
assert t.exists
a = t.get_schema()
assert a.exists
a = client.search('email')
def timeseries(client, dataset):
# create
ts = TimeSeries("Human EEG")
assert not ts.exists
dataset.add(ts)
assert ts.exists
assert ts in dataset
assert ts.type == "TimeSeries"
assert ts.name.startswith(
"Human EEG") # starts with bc duplicate names are appended
ts2 = client.get(ts.id)
assert ts2.id == ts.id
assert ts2.name == ts.name
assert ts2.type == "TimeSeries"
del ts2
# provide to other tests
yield ts
# remove
dataset.remove(ts)
assert not ts.exists
assert ts not in dataset
def test_stream_upload(use_dev, client, dataset):
# can only run against dev server :-(
if not use_dev: return
# generate data
freq = 100
df = generate_dataframe(minutes=1, freq=100)
# create timeseries
ts = TimeSeries('My Test TimeSeries')
dataset.add(ts)
assert ts.exists
print(ts)
# create channels
channels = [TimeSeriesChannel(c, rate=freq) for c in df.columns]
ts.add_channels(*channels)
for ch in channels:
assert ch.exists
assert ch.rate == freq
assert ch.name in df.columns
print("channels =", ts.channels)
# stream data up
ts.stream_data(df)
# wait a bit -- let server write data
time.sleep(10)
# retrieve data
for chunk in ts.get_data_iter():
assert len(chunk) > 0
assert chunk.columns == df.columns
assert chunk.index[-1] == df.index[-1]
# make sure channel times were updated
for ch in ts.channels:
assert ch.start_datetime == df.index[0]
assert ch.end_datetime == df.index[-1]
def timeseries2(client, dataset):
ts = TimeSeries("Animal EEG")
dataset.add(ts)
assert ts.exists
yield ts
dataset.remove(ts)