def test_read(Client, read_type, size):
if read_type == "SNAPSHOT":
df = Client.read(
TAGS["Float32"],
read_type=getattr(ReaderType, read_type),
)
else:
df = Client.read(
TAGS["Float32"],
start_time=START_TIME,
end_time=STOP_TIME,
ts=SAMPLE_TIME,
read_type=getattr(ReaderType, read_type),
)
if read_type not in ["SNAPSHOT", "RAW"]:
assert df.shape == (size, 1)
assert df.index[0] == ensure_datetime_with_tz(START_TIME)
assert df.index[-1] == df.index[0] + (size - 1) * pd.Timedelta(
SAMPLE_TIME, unit="s"
)
elif read_type in "RAW":
# Weirdness for test-tag which can have two different results,
# apparently depending on the day of the week, mood, lunar cycle...
assert df.shape == (size, 1) or df.shape == (size - 1, 1)
assert df.index[0] >= ensure_datetime_with_tz(START_TIME)
assert df.index[-1] <= ensure_datetime_with_tz(STOP_TIME)
def test_generate_tag_read_query(read_type):
starttime = ensure_datetime_with_tz(START_TIME)
stoptime = ensure_datetime_with_tz(STOP_TIME)
ts = pd.Timedelta(SAMPLE_TIME, unit="s")
if read_type == "SNAPSHOT":
res = AspenHandlerODBC.generate_read_query(
"thetag", None, None, None, None, getattr(ReaderType, read_type))
else:
res = AspenHandlerODBC.generate_read_query(
"thetag", None, starttime, stoptime, ts,
getattr(ReaderType, read_type))
expected = {
"RAW":
('SELECT ISO8601(ts) AS "time", value AS "value" FROM history WHERE '
"name = 'thetag' AND (request = 4) "
"AND (ts BETWEEN '2018-01-17T15:00:00Z' AND '2018-01-17T16:00:00Z') "
"ORDER BY ts"),
"INT":
('SELECT ISO8601(ts) AS "time", value AS "value" FROM history WHERE '
"name = 'thetag' AND (period = 600) AND (request = 7) "
"AND (ts BETWEEN '2018-01-17T15:00:00Z' AND '2018-01-17T16:00:00Z') "
"ORDER BY ts"),
"MIN":
('SELECT ISO8601(ts_start) AS "time", min AS "value" FROM aggregates WHERE '
"name = 'thetag' AND (period = 600) AND (request = 1) "
"AND (ts BETWEEN '2018-01-17T15:00:00Z' AND '2018-01-17T16:00:00Z') "
"ORDER BY ts"),
"MAX":
('SELECT ISO8601(ts_start) AS "time", max AS "value" FROM aggregates WHERE '
"name = 'thetag' AND (period = 600) AND (request = 1) "
"AND (ts BETWEEN '2018-01-17T15:00:00Z' AND '2018-01-17T16:00:00Z') "
"ORDER BY ts"),
"RNG":
('SELECT ISO8601(ts_start) AS "time", rng AS "value" FROM aggregates WHERE '
"name = 'thetag' AND (period = 600) AND (request = 1) "
"AND (ts BETWEEN '2018-01-17T15:00:00Z' AND '2018-01-17T16:00:00Z') "
"ORDER BY ts"),
"AVG":
('SELECT ISO8601(ts_start) AS "time", avg AS "value" FROM aggregates WHERE '
"name = 'thetag' AND (period = 600) AND (request = 1) "
"AND (ts BETWEEN '2018-01-17T15:00:00Z' AND '2018-01-17T16:00:00Z') "
"ORDER BY ts"),
"STD":
('SELECT ISO8601(ts_start) AS "time", std AS "value" FROM aggregates WHERE '
"name = 'thetag' AND (period = 600) AND (request = 1) "
"AND (ts BETWEEN '2018-01-17T15:00:00Z' AND '2018-01-17T16:00:00Z') "
"ORDER BY ts"),
"VAR":
('SELECT ISO8601(ts_start) AS "time", var AS "value" FROM aggregates WHERE '
"name = 'thetag' AND (period = 600) AND (request = 1) "
"AND (ts BETWEEN '2018-01-17T15:00:00Z' AND '2018-01-17T16:00:00Z') "
"ORDER BY ts"),
"SNAPSHOT":
('SELECT ISO8601(IP_INPUT_TIME) AS "time", IP_INPUT_VALUE AS "value" '
'FROM "thetag"'),
}
assert expected[read_type] == res
def test_generate_tag_read_query(PIHandler, read_type):
starttime = utils.ensure_datetime_with_tz(START_TIME)
stoptime = utils.ensure_datetime_with_tz(STOP_TIME)
ts = pd.Timedelta(SAMPLE_TIME, unit="s")
if read_type == "SNAPSHOT":
res = PIHandler.generate_read_query("thetag", None, None, None,
getattr(ReaderType, read_type))
else:
res = PIHandler.generate_read_query("thetag", starttime, stoptime, ts,
getattr(ReaderType, read_type))
expected = {
"RAW":
("SELECT TOP 100000 CAST(value as FLOAT32) AS value, time "
"FROM [piarchive]..[picomp2] WHERE tag='thetag' "
"AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') "
"ORDER BY time"),
"INT":
("SELECT CAST(value as FLOAT32) AS value, time "
"FROM [piarchive]..[piinterp2] WHERE tag='thetag' "
"AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') "
"AND (timestep = '60s') ORDER BY time"),
"MIN":
("SELECT CAST(value as FLOAT32) AS value, time "
"FROM [piarchive]..[pimin] WHERE tag='thetag' "
"AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') "
"AND (timestep = '60s') ORDER BY time"),
"MAX":
("SELECT CAST(value as FLOAT32) AS value, time "
"FROM [piarchive]..[pimax] WHERE tag='thetag' "
"AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') "
"AND (timestep = '60s') ORDER BY time"),
"RNG":
("SELECT CAST(value as FLOAT32) AS value, time "
"FROM [piarchive]..[pirange] WHERE tag='thetag' "
"AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') "
"AND (timestep = '60s') ORDER BY time"),
"AVG":
("SELECT CAST(value as FLOAT32) AS value, time "
"FROM [piarchive]..[piavg] WHERE tag='thetag' "
"AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') "
"AND (timestep = '60s') ORDER BY time"),
"STD":
("SELECT CAST(value as FLOAT32) AS value, time "
"FROM [piarchive]..[pistd] WHERE tag='thetag' "
"AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') "
"AND (timestep = '60s') ORDER BY time"),
"VAR":
("SELECT POWER(CAST(value as FLOAT32), 2) AS value, time "
"FROM [piarchive]..[pistd] WHERE tag='thetag' "
"AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') "
"AND (timestep = '60s') ORDER BY time"),
"SNAPSHOT": ("SELECT CAST(value as FLOAT32) AS value, time "
"FROM [piarchive]..[pisnapshot] WHERE tag='thetag'"),
}
assert expected[read_type] == res
def test_genreadquery_long_sampletime(PIHandler):
starttime = ensure_datetime_with_tz(START_TIME)
stoptime = ensure_datetime_with_tz(STOP_TIME)
ts = pd.Timedelta(86410, unit="s")
(url, params) = PIHandler.generate_read_query(
PIHandler.tag_to_webid("alreadyknowntag"),
starttime,
stoptime,
ts,
ReaderType.INT,
)
assert params["interval"] == f"{86410}s"
def test_genreadquery_long_sampletime(AspenHandler):
start_time = utils.ensure_datetime_with_tz("2020-06-24 17:00:00")
stop_time = utils.ensure_datetime_with_tz("2020-06-24 18:00:00")
ts = pd.Timedelta(86401, unit="s")
res = AspenHandler.generate_read_query("ATCAI", None, start_time,
stop_time, ts, ReaderType.INT)
expected = ('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>1</RT><S>0</S><P>86401</P><PU>3</PU></Tag></Q>")
assert expected == res
def test_generate_read_query(PIHandler, read_type): # TODO: Move away from test*connect
starttime = ensure_datetime_with_tz(START_TIME)
stoptime = ensure_datetime_with_tz(STOP_TIME)
ts = pd.Timedelta(SAMPLE_TIME, unit="s")
(url, params) = PIHandler.generate_read_query(
PIHandler.tag_to_webid("alreadyknowntag"),
starttime,
stoptime,
ts,
getattr(ReaderType, read_type),
)
if read_type != "SNAPSHOT":
assert params["startTime"] == "01-Apr-20 09:05:00"
assert params["endTime"] == "01-Apr-20 10:05:00"
assert params["timeZone"] == "UTC"
if read_type == "INT":
assert url == f"streams/{PIHandler.webidcache['alreadyknowntag']}/interpolated"
assert (
params["selectedFields"] == "Links;Items.Timestamp;Items.Value;Items.Good"
)
assert params["interval"] == f"{SAMPLE_TIME}s"
elif read_type in ["AVG", "MIN", "MAX", "RNG", "STD", "VAR"]:
assert url == f"streams/{PIHandler.webidcache['alreadyknowntag']}/summary"
assert (
params["selectedFields"]
== "Links;Items.Value.Timestamp;Items.Value.Value;Items.Value.Good"
)
assert {
"AVG": "Average",
"MIN": "Minimum",
"MAX": "Maximum",
"RNG": "Range",
"STD": "StdDev",
"VAR": "StdDev",
}.get(read_type) == params["summaryType"]
assert params["summaryDuration"] == f"{SAMPLE_TIME}s"
elif read_type == "SNAPSHOT":
assert url == f"streams/{PIHandler.webidcache['alreadyknowntag']}/value"
assert (
params["selectedFields"] == "Timestamp;Value;Good"
)
assert len(params) == 3
elif read_type == "RAW":
assert url == f"streams/{PIHandler.webidcache['alreadyknowntag']}/recorded"
assert (
params["selectedFields"] == "Links;Items.Timestamp;Items.Value;Items.Good"
)
assert params["maxCount"] == 10000
def test_genreadquery_long_sampletime(PIHandler):
starttime = utils.ensure_datetime_with_tz(START_TIME)
stoptime = utils.ensure_datetime_with_tz(STOP_TIME)
ts = pd.Timedelta(86401, unit="s")
res = PIHandler.generate_read_query("thetag", starttime, stoptime, ts,
ReaderType.INT)
expected = (
"SELECT CAST(value as FLOAT32) AS value, time "
"FROM [piarchive]..[piinterp2] WHERE tag='thetag' "
"AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') "
"AND (timestep = '86401s') ORDER BY time")
assert expected == res
def test_genreadquery_long_sampletime():
starttime = ensure_datetime_with_tz(START_TIME)
stoptime = ensure_datetime_with_tz(STOP_TIME)
ts = pd.Timedelta(86401, unit="s")
res = AspenHandlerODBC.generate_read_query("thetag", None, starttime,
stoptime, ts, ReaderType.INT)
expected = (
'SELECT ISO8601(ts) AS "time", value AS "value" FROM history WHERE '
"name = 'thetag' AND (period = 864010) AND (request = 7) "
"AND (ts BETWEEN '2018-01-17T15:00:00Z' AND '2018-01-17T16:00:00Z') "
"ORDER BY ts")
assert expected == res
def test_read(Client, read_type, size):
if read_type == "SNAPSHOT":
df = Client.read(TAGS["Float32"], read_type=getattr(ReaderType, read_type))
else:
df = Client.read(
TAGS["Float32"],
start_time=START_TIME,
end_time=STOP_TIME,
ts=SAMPLE_TIME,
read_type=getattr(ReaderType, read_type),
)
assert df.shape == (size, 1)
if read_type not in ["SNAPSHOT", "RAW"]:
assert df.index[0] == ensure_datetime_with_tz(START_TIME)
assert df.index[-1] == df.index[0] + (size - 1) * pd.Timedelta(
SAMPLE_TIME, unit="s"
)
elif read_type in "RAW":
assert df.index[0] >= ensure_datetime_with_tz(START_TIME)
assert df.index[-1] <= ensure_datetime_with_tz(STOP_TIME)
def test_cache_proper_fill_up(PIClientWeb):
PIClientWeb.cache = SmartCache(PI_DS)
if os.path.exists(PI_DS + ".h5"):
os.remove(PI_DS + ".h5")
df_int_1 = PIClientWeb.read(
PI_TAG, PI_START_TIME, PI_END_TIME, TS, read_type=ReaderType.INT
)
df_int_2 = PIClientWeb.read(
PI_TAG, PI_START_TIME_2, PI_END_TIME_2, TS, read_type=ReaderType.INT
)
assert len(df_int_1) == 16
assert len(df_int_2) == 16
df_cached = PIClientWeb.cache.fetch(
PI_TAG,
ReaderType.INT,
TS,
ensure_datetime_with_tz(PI_START_TIME),
ensure_datetime_with_tz(PI_END_TIME_2),
)
assert len(df_cached) == 32
def test_ensure_is_datetime():
assert ensure_datetime_with_tz("10. jan. 2018 13:45:15") == timezone(
"Europe/Oslo"
).localize(datetime.datetime(2018, 1, 10, 13, 45, 15))
assert ensure_datetime_with_tz("02.01.03 00:00:00") == timezone(
"Europe/Oslo"
).localize(datetime.datetime(2003, 1, 2, 0, 0, 0))
assert ensure_datetime_with_tz("02.01.03 00:00:00") == ensure_datetime_with_tz(
"2003-02-01 0:00:00am"
)
assert ensure_datetime_with_tz(
"02.01.03 00:00:00", "America/Sao_Paulo"
) == timezone("America/Sao_Paulo").localize(datetime.datetime(2003, 1, 2, 0, 0, 0))
assert ensure_datetime_with_tz("02.01.03 00:00:00", tz="Brazil/East") == timezone(
"Brazil/East"
).localize(datetime.datetime(2003, 1, 2, 0, 0, 0))
assert ensure_datetime_with_tz(
timezone("Brazil/East").localize(datetime.datetime(2003, 1, 2, 0, 0, 0)),
tz="Europe/Oslo",
) == timezone("Brazil/East").localize(datetime.datetime(2003, 1, 2, 0, 0, 0))
def test_generate_tag_read_query(AspenHandler, read_type):
start_time = utils.ensure_datetime_with_tz("2020-06-24 17:00:00")
stop_time = utils.ensure_datetime_with_tz("2020-06-24 18:00:00")
ts = pd.Timedelta(SAMPLE_TIME, unit="s")
res = AspenHandler.generate_read_query("ATCAI", None, start_time,
stop_time, ts,
getattr(ReaderType, read_type))
expected = {
"RAW": ('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>0</RT><X>100000</X><O>0</O></Tag></Q>"),
"SHAPEPRESERVING":
('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>2</RT><X>100000</X><O>0</O><S>0</S></Tag></Q>"),
"INT": ('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>1</RT><S>0</S><P>60</P><PU>3</PU></Tag></Q>"),
"MIN": ('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>14</RT><O>0</O><S>0</S><P>60</P><PU>3</PU><AM>0</AM>"
"<AS>0</AS><AA>0</AA><DSA>0</DSA></Tag></Q>"),
"MAX": ('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>13</RT><O>0</O><S>0</S><P>60</P><PU>3</PU><AM>0</AM>"
"<AS>0</AS><AA>0</AA><DSA>0</DSA></Tag></Q>"),
"RNG": ('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>15</RT><O>0</O><S>0</S><P>60</P><PU>3</PU><AM>0</AM>"
"<AS>0</AS><AA>0</AA><DSA>0</DSA></Tag></Q>"),
"AVG": ('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>12</RT><O>0</O><S>0</S><P>60</P><PU>3</PU><AM>0</AM>"
"<AS>0</AS><AA>0</AA><DSA>0</DSA></Tag></Q>"),
"VAR": ('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>18</RT><O>0</O><S>0</S><P>60</P><PU>3</PU><AM>0</AM>"
"<AS>0</AS><AA>0</AA><DSA>0</DSA></Tag></Q>"),
"STD": ('<Q f="d" allQuotes="1"><Tag><N><![CDATA[ATCAI]]></N>'
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<HF>0</HF><St>1593010800000</St><Et>1593014400000</Et>"
"<RT>17</RT><O>0</O><S>0</S><P>60</P><PU>3</PU><AM>0</AM>"
"<AS>0</AS><AA>0</AA><DSA>0</DSA></Tag></Q>"),
"COUNT": ("whatever"),
"GOOD": ("whatever"),
"BAD": ("whatever"),
"TOTAL": ("whatever"),
"SUM": ("whatever"),
"SNAPSHOT": ('<Q f="d" allQuotes="1" rt="1593014400000" uc="0">'
"<Tag><N><![CDATA[ATCAI]]></N>"
"<D><![CDATA[sourcename]]></D><F><![CDATA[VAL]]></F>"
"<VS>1</VS><S>0</S></Tag></Q>"),
}
assert expected[read_type] == res
def test_ensure_is_datetime_datetime():
dt = datetime.datetime(2018, 1, 10, 13, 45, 15)
dt_with_tz = timezone("Europe/Oslo").localize(dt)
assert ensure_datetime_with_tz(dt_with_tz) == dt_with_tz
assert ensure_datetime_with_tz(dt) == dt_with_tz
def test_ensure_is_datetime_pd_timestamp():
ts = pd.Timestamp(2018, 1, 10, 13, 45, 15)
ts_with_tz = timezone("Europe/Oslo").localize(ts)
assert ensure_datetime_with_tz(ts_with_tz) == ts_with_tz
assert ensure_datetime_with_tz(ts) == ts_with_tz
