Refactor stack analysis logic in Streamlit app for improved readability and maintainability. Consolidate repeated code blocks for handling different stack sizes and ensure consistent data processing before displaying results. Add functionality to export generated tables as CSV.

app.py

@@ -128,151 +128,150 @@ with col1:
 
 with col2:
     stack_hold_container = st.empty()
-    if st.button('Run stack analysis'):
-        comb_list = []
-        if pos_split2 == 'All Positions':
-            raw_baselines = raw_baselines
-        elif pos_split2 != 'All Positions':
-            raw_baselines = raw_baselines[raw_baselines['Position'].str.contains('|'.join(pos_var2))]
-
-        for cur_team in team_var2:
-            working_baselines = raw_baselines
-            working_baselines = working_baselines[working_baselines['Team'] == cur_team]
-            working_baselines = working_baselines[working_baselines['Position'] != 'SP']
-            working_baselines = working_baselines[working_baselines['Position'] != 'P']
-            order_list = working_baselines['Player']
-
-            comb = combinations(order_list, stack_size)
-
-            for i in list(comb):
-                comb_list.append(i)
-
-        comb_DF = pd.DataFrame(comb_list)
-
-        if stack_size == 3:
-            comb_DF['Team'] = comb_DF[0].map(team_dict)
-
-            comb_DF['Proj'] = sum([comb_DF[0].map(proj_dict),
-                    comb_DF[1].map(proj_dict),
-                    comb_DF[2].map(proj_dict)])
-
-            comb_DF['Salary'] = sum([comb_DF[0].map(cost_dict),
-                    comb_DF[1].map(cost_dict),
-                    comb_DF[2].map(cost_dict)])
-
-            comb_DF['Own%'] = sum([comb_DF[0].map(own_dict),
-                    comb_DF[1].map(own_dict),
-                    comb_DF[2].map(own_dict)])
-        elif stack_size == 4:
-            comb_DF['Team'] = comb_DF[0].map(team_dict)
-
-            comb_DF['Proj'] = sum([comb_DF[0].map(proj_dict),
-                    comb_DF[1].map(proj_dict),
-                    comb_DF[2].map(proj_dict),
-                    comb_DF[3].map(proj_dict)])
-
-            comb_DF['Salary'] = sum([comb_DF[0].map(cost_dict),
-                    comb_DF[1].map(cost_dict),
-                    comb_DF[2].map(cost_dict),
-                    comb_DF[3].map(cost_dict)])
-
-            comb_DF['Own%'] = sum([comb_DF[0].map(own_dict),
-                    comb_DF[1].map(own_dict),
-                    comb_DF[2].map(own_dict),
-                    comb_DF[3].map(own_dict)])
-        elif stack_size == 5:
-            comb_DF['Team'] = comb_DF[0].map(team_dict)
-
-            comb_DF['Proj'] = sum([comb_DF[0].map(proj_dict),
-                    comb_DF[1].map(proj_dict),
-                    comb_DF[2].map(proj_dict),
-                    comb_DF[3].map(proj_dict),
-                    comb_DF[4].map(proj_dict)])
-
-            comb_DF['Salary'] = sum([comb_DF[0].map(cost_dict),
-                    comb_DF[1].map(cost_dict),
-                    comb_DF[2].map(cost_dict),
-                    comb_DF[3].map(cost_dict),
-                    comb_DF[4].map(cost_dict)])
-
-            comb_DF['Own%'] = sum([comb_DF[0].map(own_dict),
-                    comb_DF[1].map(own_dict),
-                    comb_DF[2].map(own_dict),
-                    comb_DF[3].map(own_dict),
-                    comb_DF[4].map(own_dict)])
-
-        comb_DF = comb_DF.sort_values(by='Proj', ascending=False)
-        comb_DF = comb_DF.loc[comb_DF['Salary'] <= max_sal2]
-
-        cut_var = 0
-
-        if stack_size == 3:
-            while cut_var <= int(len(comb_DF)):
-                try:
-                    if int(cut_var) == 0:
-                        cur_proj = float(comb_DF.iat[cut_var,4])
+    comb_list = []
+    if pos_split2 == 'All Positions':
+        raw_baselines = raw_baselines
+    elif pos_split2 != 'All Positions':
+        raw_baselines = raw_baselines[raw_baselines['Position'].str.contains('|'.join(pos_var2))]
+
+    for cur_team in team_var2:
+        working_baselines = raw_baselines
+        working_baselines = working_baselines[working_baselines['Team'] == cur_team]
+        working_baselines = working_baselines[working_baselines['Position'] != 'SP']
+        working_baselines = working_baselines[working_baselines['Position'] != 'P']
+        order_list = working_baselines['Player']
+
+        comb = combinations(order_list, stack_size)
+
+        for i in list(comb):
+            comb_list.append(i)
+
+    comb_DF = pd.DataFrame(comb_list)
+
+    if stack_size == 3:
+        comb_DF['Team'] = comb_DF[0].map(team_dict)
+
+        comb_DF['Proj'] = sum([comb_DF[0].map(proj_dict),
+                comb_DF[1].map(proj_dict),
+                comb_DF[2].map(proj_dict)])
+
+        comb_DF['Salary'] = sum([comb_DF[0].map(cost_dict),
+                comb_DF[1].map(cost_dict),
+                comb_DF[2].map(cost_dict)])
+
+        comb_DF['Own%'] = sum([comb_DF[0].map(own_dict),
+                comb_DF[1].map(own_dict),
+                comb_DF[2].map(own_dict)])
+    elif stack_size == 4:
+        comb_DF['Team'] = comb_DF[0].map(team_dict)
+
+        comb_DF['Proj'] = sum([comb_DF[0].map(proj_dict),
+                comb_DF[1].map(proj_dict),
+                comb_DF[2].map(proj_dict),
+                comb_DF[3].map(proj_dict)])
+
+        comb_DF['Salary'] = sum([comb_DF[0].map(cost_dict),
+                comb_DF[1].map(cost_dict),
+                comb_DF[2].map(cost_dict),
+                comb_DF[3].map(cost_dict)])
+
+        comb_DF['Own%'] = sum([comb_DF[0].map(own_dict),
+                comb_DF[1].map(own_dict),
+                comb_DF[2].map(own_dict),
+                comb_DF[3].map(own_dict)])
+    elif stack_size == 5:
+        comb_DF['Team'] = comb_DF[0].map(team_dict)
+
+        comb_DF['Proj'] = sum([comb_DF[0].map(proj_dict),
+                comb_DF[1].map(proj_dict),
+                comb_DF[2].map(proj_dict),
+                comb_DF[3].map(proj_dict),
+                comb_DF[4].map(proj_dict)])
+
+        comb_DF['Salary'] = sum([comb_DF[0].map(cost_dict),
+                comb_DF[1].map(cost_dict),
+                comb_DF[2].map(cost_dict),
+                comb_DF[3].map(cost_dict),
+                comb_DF[4].map(cost_dict)])
+
+        comb_DF['Own%'] = sum([comb_DF[0].map(own_dict),
+                comb_DF[1].map(own_dict),
+                comb_DF[2].map(own_dict),
+                comb_DF[3].map(own_dict),
+                comb_DF[4].map(own_dict)])
+
+    comb_DF = comb_DF.sort_values(by='Proj', ascending=False)
+    comb_DF = comb_DF.loc[comb_DF['Salary'] <= max_sal2]
+
+    cut_var = 0
+
+    if stack_size == 3:
+        while cut_var <= int(len(comb_DF)):
+            try:
+                if int(cut_var) == 0:
+                    cur_proj = float(comb_DF.iat[cut_var,4])
+                    cur_own = float(comb_DF.iat[cut_var,6])
+                elif int(cut_var) >= 1:
+                    check_own = float(comb_DF.iat[cut_var,6])
+                    if check_own > cur_own:
+                        comb_DF = comb_DF.drop([cut_var])
+                        cur_own = cur_own
+                        cut_var = cut_var - 1
+                        comb_DF = comb_DF.reset_index()
+                        comb_DF = comb_DF.drop(['index'], axis=1)
+                    elif check_own <= cur_own:
                         cur_own = float(comb_DF.iat[cut_var,6])
-                    elif int(cut_var) >= 1:
-                        check_own = float(comb_DF.iat[cut_var,6])
-                        if check_own > cur_own:
-                            comb_DF = comb_DF.drop([cut_var])
-                            cur_own = cur_own
-                            cut_var = cut_var - 1
-                            comb_DF = comb_DF.reset_index()
-                            comb_DF = comb_DF.drop(['index'], axis=1)
-                        elif check_own <= cur_own:
-                            cur_own = float(comb_DF.iat[cut_var,6])
-                            cut_var = cut_var
-                    cut_var += 1
-                except:
-                    cut_var += 1
-        elif stack_size == 4:
-            while cut_var <= int(len(comb_DF)):
-                try:
-                    if int(cut_var) == 0:
-                        cur_proj = float(comb_DF.iat[cut_var,5])
+                        cut_var = cut_var
+                cut_var += 1
+            except:
+                cut_var += 1
+    elif stack_size == 4:
+        while cut_var <= int(len(comb_DF)):
+            try:
+                if int(cut_var) == 0:
+                    cur_proj = float(comb_DF.iat[cut_var,5])
+                    cur_own = float(comb_DF.iat[cut_var,7])
+                elif int(cut_var) >= 1:
+                    check_own = float(comb_DF.iat[cut_var,7])
+                    if check_own > cur_own:
+                        comb_DF = comb_DF.drop([cut_var])
+                        cur_own = cur_own
+                        cut_var = cut_var - 1
+                        comb_DF = comb_DF.reset_index()
+                        comb_DF = comb_DF.drop(['index'], axis=1)
+                    elif check_own <= cur_own:
                         cur_own = float(comb_DF.iat[cut_var,7])
-                    elif int(cut_var) >= 1:
-                        check_own = float(comb_DF.iat[cut_var,7])
-                        if check_own > cur_own:
-                            comb_DF = comb_DF.drop([cut_var])
-                            cur_own = cur_own
-                            cut_var = cut_var - 1
-                            comb_DF = comb_DF.reset_index()
-                            comb_DF = comb_DF.drop(['index'], axis=1)
-                        elif check_own <= cur_own:
-                            cur_own = float(comb_DF.iat[cut_var,7])
-                            cut_var = cut_var
-                    cut_var += 1
-                except:
-                    cut_var += 1
-        elif stack_size == 5:
-            while cut_var <= int(len(comb_DF)):
-                try:
-                    if int(cut_var) == 0:
-                        cur_proj = float(comb_DF.iat[cut_var,6])
+                        cut_var = cut_var
+                cut_var += 1
+            except:
+                cut_var += 1
+    elif stack_size == 5:
+        while cut_var <= int(len(comb_DF)):
+            try:
+                if int(cut_var) == 0:
+                    cur_proj = float(comb_DF.iat[cut_var,6])
+                    cur_own = float(comb_DF.iat[cut_var,8])
+                elif int(cut_var) >= 1:
+                    check_own = float(comb_DF.iat[cut_var,8])
+                    if check_own > cur_own:
+                        comb_DF = comb_DF.drop([cut_var])
+                        cur_own = cur_own
+                        cut_var = cut_var - 1
+                        comb_DF = comb_DF.reset_index()
+                        comb_DF = comb_DF.drop(['index'], axis=1)
+                    elif check_own <= cur_own:
                         cur_own = float(comb_DF.iat[cut_var,8])
-                    elif int(cut_var) >= 1:
-                        check_own = float(comb_DF.iat[cut_var,8])
-                        if check_own > cur_own:
-                            comb_DF = comb_DF.drop([cut_var])
-                            cur_own = cur_own
-                            cut_var = cut_var - 1
-                            comb_DF = comb_DF.reset_index()
-                            comb_DF = comb_DF.drop(['index'], axis=1)
-                        elif check_own <= cur_own:
-                            cur_own = float(comb_DF.iat[cut_var,8])
-                            cut_var = cut_var
-                    cut_var += 1
-                except:
-                    cut_var += 1
-
-        with stack_hold_container:
-            stack_hold_container = st.empty()
-            st.dataframe(comb_DF.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
-        st.download_button(
-                label="Export Tables",
-                data=convert_df_to_csv(comb_DF),
-                file_name='MLB_Stack_Options_export.csv',
-                mime='text/csv',
-        )
+                        cut_var = cut_var
+                cut_var += 1
+            except:
+                cut_var += 1
+
+    with stack_hold_container:
+        stack_hold_container = st.empty()
+        st.dataframe(comb_DF.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+    st.download_button(
+            label="Export Tables",
+            data=convert_df_to_csv(comb_DF),
+            file_name='MLB_Stack_Options_export.csv',
+            mime='text/csv',
+    )