From ec3f2c041e135a7ced9dc5b654e364f0bab0765e Mon Sep 17 00:00:00 2001
From: "Eugeniy E. Mikhailov" <evgmik@gmail.com>
Date: Wed, 23 Oct 2024 23:11:25 -0400
Subject: black formatter

---
 toBlackboardCSV.py | 29 +++++++++++++++++++----------
 1 file changed, 19 insertions(+), 10 deletions(-)

diff --git a/toBlackboardCSV.py b/toBlackboardCSV.py
index 3694edc..7804070 100755
--- a/toBlackboardCSV.py
+++ b/toBlackboardCSV.py
@@ -10,32 +10,41 @@ import sqlite3
 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)
+# 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('@.*$', '', regex=True)
-dOut.rename(columns={'UserName':'Username'}, inplace=True)
+dOut["UserName"] = dOut["UserName"].str.replace("@.*$", "", regex=True)
+dOut.rename(columns={"UserName": "Username"}, inplace=True)
 
 # exclude inforows
-dOut = dOut.loc[ dOut['GroupName'].isin(['student']) ]
+dOut = dOut.loc[dOut["GroupName"].isin(["student"])]
 
 # remove unneeded info cols
-infoCol=['FirstName', 'LastName', 'GroupName', 'UserHiddenColums', 'UserHiddenGroups', 'UserHiddenGradeCategories', 'SectionNum', 'IdNum']
+infoCol = [
+    "FirstName",
+    "LastName",
+    "GroupName",
+    "UserHiddenColums",
+    "UserHiddenGroups",
+    "UserHiddenGradeCategories",
+    "SectionNum",
+    "IdNum",
+]
 dOut = dOut.drop(infoCol, axis=1)
 
 # drop non gradable columns
-cCat = (dIn['UserName'] == '_Col_Category_')
+cCat = dIn["UserName"] == "_Col_Category_"
 colToDrop = []
 for c in dOut.columns:
-    if c == 'Username':
+    if c == "Username":
         continue
     category = dIn[cCat][c][0]
-    if category not in ['HomeWork', 'MidTerm', 'FinalExam', 'weighted_column']:
+    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)
+dOut.to_csv("BlackBoard.csv", index=False)
-- 
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