Update app.py

app.py

@@ -1,16 +1,12 @@
 import streamlit as st
 import pandas as pd
 import plotly.graph_objects as go
-import os
 from zipfile import ZipFile
 import plotly.io as pio
 from io import BytesIO
-import numpy as np
-import shutil
 
-# 中文字体配置（核心修改部分）
+# ================== 中文字体配置 ==================
 def setup_chinese_font():
-    # 列出多个备选中文字体
     chinese_fonts = [
         "Microsoft JhengHei",
         "Noto Sans CJK TC",
@@ -20,26 +16,18 @@ def setup_chinese_font():
     ]
     return ", ".join(chinese_fonts)
 
-# 初始化全局字体设置
 CHINESE_FONT = setup_chinese_font()
 
-try:
-    import kaleido
-except ImportError:
-    st.error("請安裝 'kaleido' 套件以啟用圖像導出功能：\n\n    $ pip install kaleido")
-
+# ================== 数据加载函数 ==================
 def load_data(uploaded_file):
-    """改进的数据加载函数，增加数据验证"""
     try:
         df = pd.read_csv(uploaded_file, encoding='utf-8').dropna(how='all')
         
-        # 数据验证
-        required_columns = ['姓名']
-        for col in required_columns:
-            if col not in df.columns:
-                raise ValueError(f"CSV文件中缺少必要欄位：{col}")
-                
-        # 动态识别数值列（改进点）
+        # 验证必要字段
+        if '姓名' not in df.columns:
+            raise ValueError("CSV文件中缺少'姓名'欄位")
+            
+        # 动态识别数值列
         numeric_columns = []
         potential_numeric = ['平均', '總分', '國文', '英文', '數學', '自科', 
                            '社會', '地理', '歷史', '公民', '物理', '化學', '生物']
@@ -49,18 +37,18 @@ def load_data(uploaded_file):
                     df[col] = pd.to_numeric(df[col], errors='coerce')
                     numeric_columns.append(col)
                 except:
-                    pass
+                    continue
                     
         if not numeric_columns:
-            raise ValueError("CSV文件中未找到有效的數值欄位")
+            raise ValueError("未找到有效的數值欄位")
             
         return df, numeric_columns
     except Exception as e:
         st.error(f"數據加載錯誤：{str(e)}")
         return None, None
 
+# ================== 雷达图生成函数 ==================
 def create_radar_chart(df, selected_rows, selected_columns, student_name=""):
-    """改进的雷达图生成函数"""
     line_styles = ['solid', 'dot', 'dash', 'longdash', 'dashdot']
     colors = ['#1F77B4', '#FF7F0E', '#2CA02C', '#D62728', '#9467BD']
 
@@ -83,7 +71,6 @@ def create_radar_chart(df, selected_rows, selected_columns, student_name=""):
 
     max_value = df[selected_columns].max().max() * 1.1 if selected_columns else 100
 
-    # 统一字体设置
     fig.update_layout(
         polar=dict(
             radialaxis=dict(
@@ -115,27 +102,23 @@ def create_radar_chart(df, selected_rows, selected_columns, student_name=""):
     )
     return fig
 
+# ================== 字体强制设置 ==================
 def apply_font_settings(fig):
-    """强化字体设置"""
     fig.update_layout(
         font_family=CHINESE_FONT,
         title_font_family=CHINESE_FONT,
         legend_font_family=CHINESE_FONT
     )
-    fig.update_polars(
-        angularaxis_tickfont_family=CHINESE_FONT,
-        radialaxis_tickfont_family=CHINESE_FONT
-    )
     return fig
 
+# ================== 图片生成函数 ==================
 def generate_radar_image(fig):
-    """改进的图片生成函数"""
-    # 配置kaleido的字体设置
     pio.kaleido.scope.default_format = "png"
     pio.kaleido.scope.default_width = 800
     pio.kaleido.scope.default_height = 600
     return pio.to_image(fig, format="png", engine="kaleido")
 
+# ================== 主程序 ==================
 def main():
     st.title('學生成績雷達圖產生器')
     uploaded_file = st.file_uploader("上傳CSV檔案", type=['csv'])
@@ -144,11 +127,12 @@ def main():
         df, numeric_columns = load_data(uploaded_file)
         
         if df is not None and numeric_columns:
+            # ===== 单次比较模式 =====
             st.write("### 選擇要比較的欄位")
             selected_columns = st.multiselect(
                 '選擇科目',
                 numeric_columns,
-                default=numeric_columns[:3]  # 默认选择前三个
+                default=numeric_columns[:3]
             )
 
             st.write("### 選擇要比較的對象")
@@ -163,15 +147,24 @@ def main():
                 except Exception as e:
                     st.error(f"生成雷達圖錯誤：{str(e)}")
 
+            # ===== 批量下载模式 =====
             st.write("### 批次下載全班學生雷達圖")
             comparison_items = st.multiselect("選擇比較基準", all_students)
 
             if comparison_items:
+                # 计算有效学生数量
+                valid_students = [s for s in all_students if s not in comparison_items]
+                total_students = len(valid_students)
+                
+                if total_students == 0:
+                    st.warning("比較基準已包含所有學生，請至少保留一個非基準學生")
+                    return
+                
                 progress_bar = st.progress(0)
                 image_bytes = {}
-                total_students = len(all_students) - len(comparison_items)
-                
-                for idx, student in enumerate(all_students):
+                processed_count = 0
+
+                for student in all_students:
                     if student in comparison_items:
                         continue
                         
@@ -184,10 +177,13 @@ def main():
                         )
                         fig = apply_font_settings(fig)
                         image_bytes[student] = generate_radar_image(fig)
+                        
+                        # 更新进度条
+                        processed_count += 1
+                        progress_bar.progress(processed_count / total_students)
+                        
                     except Exception as e:
                         st.error(f"生成 {student} 圖表失敗：{str(e)}")
-                        
-                    progress_bar.progress((idx+1)/total_students)
 
                 # 显示预览
                 cols = st.columns(3)
@@ -197,7 +193,7 @@ def main():
                         st.caption(f"{student} 與 {', '.join(comparison_items)} 的比較")
 
                 # 打包下载
-                if st.button("打包下載全部圖表"):
+                if image_bytes:
                     zip_buffer = BytesIO()
                     with ZipFile(zip_buffer, "w") as zip_file:
                         for student, img in image_bytes.items():