teams-report-converter 0.2.0

Description:

teamsreportconverter 0.2.0

Teams Attendance Report Converter
This tool is a simple script that converts basic attendance reports generated from MS Teams events into calculated attendance spreadsheets.
Instalation
You can install this converter from PyPI:
pip install teams-report-converter

How to use
This converter can be used as a command line application as well as a package imported by your own python application.
Using as command line application:
convert-teams-report -f <path-to-original-csv> -s <datetime-event-start> -e <datetime-event-end> -tz <timezone-event> -o <path-to-resulting-spreadsheet>

In this scenario the converter uses the following parameters:

-f: path of attendance report generated by MS Teams for a live event (usually called "AttendeeReport.csv")
-s: datetime of event start in the format "%Y-%m-%d %H:%M:%S" (you must use double quotes)
-e: datetime of event end in the format "%Y-%m-%d %H:%M:%S" (you must use double quotes)
-o: path of resulting spreadsheet
-tz: timezone of event start and event end (for reference use TZ database name)

Note that this is the unique scenario that outputs a ready to use resulting spreadsheet.
Using as package imported by your python application
You can still use the converter as a package only for processing the original report e apply your own calculations. In this scenario, the Converter class outputs three dataframes that you can handle:
from teams_report_converter import Converter

converter = Converter(report_content='AttendeeReport.csv',
event_start='2021-11-03 15:00:00',
event_end='2021-11-03 17:00:00',
local_tz='America/Sao_Paulo')

From this point, you can call converter.data for accessing the original data. Calling converter.sessions outputs another dataframe listing all joins and lefts paired by sessions and converter.attendance outputs the dataframe that contains the total of valid minutes accumulated by each participant.
How the tool calculates attendance
The below table shows how the timestamps from original data are processed in different scenarios:



Join Timestamp
Left Timestamp
Truncated Joined
Truncated Left
Attendance Calculation




before event start
no record
set to event start
set to event end
[event end] - [event start]


before event start
before event start
set to left timestamp
left timestamp
[set to zero]


before event start
between event start and event end
set to event start
left timestamp
[left timestamp] - [event start]


before event start
after event end
set to event start
set to event end
[event end] - [event start]


after event start
no record
join timestamp
set to event end
[event end] - [join timestamp]


after event start
before event end
join timestamp
left timestamp
[left timestamp] - [join timestamp]


after event start
after event end
join timestamp
set to event end
[event end] - [join timestamp]


after event end
no record
join timestamp
set to join timestamp
[set to zero]


after event end
after event end
join timestamp
set to join timestamp
[set to zero]