For comparison, here is an example showing how to query and review similar data using the Script Console (Designer) and the system.tag.queryTagHistory function.
myTagPaths = [ '[default]Station Power/Station 4/PM-04-04/Energy' ]
myColumnNames = [ 'PM-04-04' ]
myEndDateTime = system.date.parse("2022-08-03 00:00:00", "yyyy-MM-dd HH:mm:ss")
myStartDateTime = system.date.addHours(myEndDateTime, -24)
print myEndDateTime
print myStartDateTime
#======================================================================
#======================================================================
def printDataSet(datasetIn):
# Get Row and Column counts
nrows = datasetIn.getRowCount()
ncols = datasetIn.getColumnCount()
# Get max length of row labels
rowLen = len(max(['row']+[unicode(i) for i in range(nrows)], key=len))
# Get column names
colNames = datasetIn.getColumnNames()
# initialize lists to process columns
headerList = []
colData = []
maxLen = []
# Process columns
for i, col in zip(range(ncols), colNames):
# Get column as list, converting all elemenst to unicode strings
colIn = ([unicode(element) for element in list(datasetIn.getColumnAsList(i))])
# Get max lentgh of the column, including the column name
maxLen = len(max([col]+colIn, key=len))
# Append data as left justified strings.
# ljust() will automatically pad to the max string length
colData.append([element.ljust(maxLen) for element in colIn])
# Append column name, also using the max string length
headerList.append(col.ljust(maxLen))
# Concatenate the header string and print it.
headerString= 'row'.ljust(rowLen) + ' | ' + ' | '.join(headerList)
print headerString
# Print a bunch of dashes the same length as the header string
print'-' * len(headerString)
# Print the rows
for row in enumerate(zip(*colData)):
print unicode(row[0]).ljust(rowLen) + ' | ' + ' | '.join(row[1])
#======================================================================
#======================================================================
data = system.tag.queryTagHistory(
paths=myTagPaths
, startDate=myStartDateTime
, endDate=myEndDateTime
# , returnSize = 0
# , aggregationMode="LastValue"
# , returnFormat
, columnNames=myColumnNames
# , intervalHours
# , intervalMinutes
# , rangeHours
# , rangeMinutes
# , aggregationModes
# , includeBoundingValues=1
# , validateSCExec
, noInterpolation=1 # prevent the return of rows that are interpolated
# , ignoreBadQuality
, timeout = 10000
# , intervalSeconds
# , rangeSeconds
)
printDataSet(data)
Results:
>>> Wed Aug 03 00:00:00 UTC 2022 Tue Aug 02 00:00:00 UTC 2022 row | t_stamp | PM-04-04 -------------------------------------------------- 0 | Tue Aug 02 00:06:17 UTC 2022 | 17.8490009308 1 | Tue Aug 02 01:06:23 UTC 2022 | 18.2940006256 2 | Tue Aug 02 02:06:29 UTC 2022 | 18.7299995422 3 | Tue Aug 02 03:06:33 UTC 2022 | 19.1550006866 4 | Tue Aug 02 04:06:37 UTC 2022 | 19.577999115 5 | Tue Aug 02 05:06:43 UTC 2022 | 19.9960002899 6 | Tue Aug 02 06:06:49 UTC 2022 | 20.4130001068 7 | Tue Aug 02 07:06:55 UTC 2022 | 20.8269996643 8 | Tue Aug 02 08:07:00 UTC 2022 | 21.2390003204 9 | Tue Aug 02 09:07:06 UTC 2022 | 21.6520004272 10 | Tue Aug 02 10:07:13 UTC 2022 | 22.0620002747 ...
To me this actually seems quite a bit less versatile than querying the database directly but it does have the advantage of transparently handling the history data partitioned across database tables.
There is probably a way, but it is not immediately apparent, how one might use localized time in the query and show localized time in the returned data.
The printDataSet function was lifted from a forum post by @JordanCClark, (thank you).