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#!/usr/bin/python3
import sys
import pandas as pd
import numpy as np
import os
import sqlite3
# infile = 'gb.db'
infile = sys.argv[1]
con = sqlite3.connect(infile)
# dIn=pd.read_sql("Select * from 'GradesTable' where GroupName='student'", con)
dIn = pd.read_sql("Select * from 'GradesTable'", con)
dOut = dIn.copy()
# replacing user names in accordance with BlackBoard
dOut["UserName"] = dOut["UserName"].str.replace("@.*$", "", regex=True)
dOut.rename(columns={"UserName": "Username"}, inplace=True)
# exclude inforows
dOut = dOut.loc[dOut["GroupName"].isin(["student"])]
# remove unneeded info cols
infoCol = [
"FirstName",
"LastName",
"GroupName",
"UserHiddenColums",
"UserHiddenGroups",
"UserHiddenGradeCategories",
"SectionNum",
"IdNum",
]
dOut = dOut.drop(infoCol, axis=1)
# drop non gradable columns
cCat = dIn["UserName"] == "_Col_Category_"
colToDrop = []
for c in dOut.columns:
if c == "Username":
continue
category = dIn[cCat][c][0]
if category not in ["HomeWork", "MidTerm", "FinalExam", "weighted_column"]:
colToDrop.append(c)
dOut = dOut.drop(colToDrop, axis=1)
dOut.to_csv("BlackBoard.csv", index=False)
print(f"Data was exported to {fout}")
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