Hi there. I'm new to GitHub so the issue I cover below may not be as detailed as you may be used to.
Currently, "report.py" handles COUNT 5 'TR_J1' data in similar ways as a COUNTER 4 'JR1' data. However, because the columns are different in a TR_J1 report, the data I extract is offset. Please find a reproducible example below.
I am running Python 3.7, pycounter Release v2.1.4, on an Apple Macbook Pro (10.15.6)
Source
please see attached file
TestFile_COP5-TR_J1-report.txt
Commands
import pycounter
report = pycounter.report.parse('TestFile_COP5-TR_J1-report.txt')
for journal in report:
for item in journal:
print(item)
Output
MonthsUsage(month=datetime.date(2017, 10, 1), metric='Total_Item_Requests', usage=25)
Expected output
MonthsUsage(month=datetime.date(2017, 10, 1), metric='Total_Item_Requests', usage=0)
Thank you so much for your contributions to pycounter. They have been very useful to me. Best - Ian
Hi there. I'm new to GitHub so the issue I cover below may not be as detailed as you may be used to.
Currently, "report.py" handles COUNT 5 'TR_J1' data in similar ways as a COUNTER 4 'JR1' data. However, because the columns are different in a TR_J1 report, the data I extract is offset. Please find a reproducible example below.
I am running Python 3.7, pycounter Release v2.1.4, on an Apple Macbook Pro (10.15.6)
Source
please see attached file
TestFile_COP5-TR_J1-report.txt
Commands
import pycounterreport = pycounter.report.parse('TestFile_COP5-TR_J1-report.txt')for journal in report:for item in journal:print(item)Output
MonthsUsage(month=datetime.date(2017, 10, 1), metric='Total_Item_Requests', usage=25)Expected output
MonthsUsage(month=datetime.date(2017, 10, 1), metric='Total_Item_Requests', usage=0)Thank you so much for your contributions to pycounter. They have been very useful to me. Best - Ian