Add duplicate removal for player lineups in init_DK_lineups and init_FD_lineups functions to ensure unique entries based on key positions, enhancing data integrity.

src/streamlit_app.py

@@ -259,6 +259,8 @@ def init_DK_lineups(type_var, slate_var, prio_var, prio_mix, db_translation, lin
             else:
                 cursor = collection.find().sort(prio_var, -1).limit(lineup_num)
                 raw_display = pd.DataFrame(list(cursor))
+            
+            raw_display = raw_display.drop_duplicates(subset=['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'])
 
             raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
             dict_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
@@ -299,6 +301,8 @@ def init_DK_lineups(type_var, slate_var, prio_var, prio_mix, db_translation, lin
                 cursor = collection.find().sort(prio_var, -1).limit(lineup_num)
                 raw_display = pd.DataFrame(list(cursor))
 
+            raw_display = raw_display.drop_duplicates(subset=['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'])
+
             raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
             dict_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
             # Map names
@@ -338,6 +342,8 @@ def init_DK_lineups(type_var, slate_var, prio_var, prio_mix, db_translation, lin
                 cursor = collection.find().sort(prio_var, -1).limit(lineup_num)
                 raw_display = pd.DataFrame(list(cursor))
 
+            raw_display = raw_display.drop_duplicates(subset=['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'])
+
             raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
             dict_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
             # Map names
@@ -371,6 +377,8 @@ def init_DK_lineups(type_var, slate_var, prio_var, prio_mix, db_translation, lin
             cursor = collection.find().sort(prio_var, -1).limit(lineup_num)
             raw_display = pd.DataFrame(list(cursor))
 
+        raw_display = raw_display.drop_duplicates(subset=['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'])
+
         raw_display = raw_display[['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
         for column in ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']:
             raw_display[column] = raw_display[column].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(raw_display[column])
@@ -422,6 +430,8 @@ def init_FD_lineups(type_var, slate_var, prio_var, prio_mix, db_translation, lin
                 cursor = collection.find().sort(prio_var, -1).limit(lineup_num)
                 raw_display = pd.DataFrame(list(cursor))
 
+            raw_display = raw_display.drop_duplicates(subset=['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'])
+
             raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
             dict_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
             # Map names
@@ -461,6 +471,8 @@ def init_FD_lineups(type_var, slate_var, prio_var, prio_mix, db_translation, lin
                 cursor = collection.find().sort(prio_var, -1).limit(lineup_num)
                 raw_display = pd.DataFrame(list(cursor))
 
+            raw_display = raw_display.drop_duplicates(subset=['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'])
+
             raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
             dict_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
             # Map names
@@ -500,6 +512,8 @@ def init_FD_lineups(type_var, slate_var, prio_var, prio_mix, db_translation, lin
                 cursor = collection.find().sort(prio_var, -1).limit(lineup_num)
                 raw_display = pd.DataFrame(list(cursor))
 
+            raw_display = raw_display.drop_duplicates(subset=['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'])
+
             raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
             dict_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
             # Map names
@@ -534,6 +548,8 @@ def init_FD_lineups(type_var, slate_var, prio_var, prio_mix, db_translation, lin
             cursor = collection.find().sort(prio_var, -1).limit(lineup_num)
             raw_display = pd.DataFrame(list(cursor))
 
+        raw_display = raw_display.drop_duplicates(subset=['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'])
+
         raw_display = raw_display[['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
         for column in ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']:
             raw_display[column] = raw_display[column].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(raw_display[column])