Open climbjh opened 4 years ago
Since you're already working with csv files and exporting the final result to csv, the easiest approach might be to create a csv with cost multiplier data and another for pay rate data, and use pandas to read that data. Unless you would prefer to use a database just to get some experience working with SQL, in which case I think SQLite makes the most sense.
I do think a valuable next step once this is all functional is to move this code into the cloud. You could create a very simple web interface with Azure Static Web Apps, move your python code into Azure Functions, and store all the data in CosmosDb.
Need to import the created CSV to an SQL database, then link the created table to 2 other tables which hold data for cost multiplier which corresponds to cost code as well as pay rate for each employee (username). The data from these two external tables should be dropped into the main table based on employee name and cost code, then a CSV file (or XLSX table) should be exported as the final result and placed into the created folder.