Update src/streamlit_app.py

src/streamlit_app.py

@@ -3,6 +3,7 @@ import pandas as pd
 import altair as alt
 import json
 import urllib.request
+import os
 
 # 🌟 关键：解除 Altair 5000 行的限制，允许柱状图和折线图使用全量数据渲染
 alt.data_transformers.disable_max_rows()
@@ -21,10 +22,6 @@ st.markdown(
     This interactive article walks you through 2026 Chicago crime data drawn directly from
     the [Chicago Data Portal](https://data.cityofchicago.org/) to help you explore the
     geography, timing, and social context of crime in one of America's largest cities.
-    The dataset records every reported crime incident in 2026, including the exact location,
-    date and time, crime type, and the police district that handled it. Each row is one
-    reported incident. We also include community-level socioeconomic data to examine the
-    relationship between poverty and crime rates across Chicago's neighborhoods.
     """
 )
 
@@ -34,12 +31,25 @@ st.markdown(
 
 @st.cache_data(show_spinner="Loading Chicago crime data from CSV...")
 def load_crime_data():
-    """直接读取上传到 Hugging Face 的 CSV 文件，不再使用 API 循环请求。"""
+    """自动寻找目录下的 Crimes 数据集，彻底告别文件名拼写报错"""
+    
+    # 1. 自动扫描当前文件夹
+    current_files = os.listdir('.')
+    csv_files = [f for f in current_files if 'Crimes' in f and f.endswith('.csv')]
+    
+    # 2. 如果什么都没找到，把当前文件夹里到底有什么打印出来，方便排错
+    if not csv_files:
+        st.error(f"找不到 CSV 文件！当前文件夹里只有这些文件: {current_files}")
+        return pd.DataFrame()
+        
+    # 3. 抓取找到的第一个文件
+    target_file = csv_files[0]
+    st.success(f"自动寻路成功！正在读取: {target_file}")
+    
     try:
-        # 读取本地上传的 CSV 文件
-        df_raw = pd.read_csv("Crimes_-_2026_20260417.csv", low_memory=False)
+        df_raw = pd.read_csv(target_file, low_memory=False)
     except Exception as e:
-        st.error(f"Failed to load CSV file. 请确保文件名准确并已上传到 Hugging Face: {e}")
+        st.error(f"文件找到了，但读取失败: {e}")
         return pd.DataFrame()
 
     df = df_raw.copy()
@@ -115,7 +125,7 @@ districts   = alt.Data(values=district_geojson["features"])
 communities = alt.Data(values=community_geojson["features"])
 
 if df.empty:
-    st.error("Crime data could not be loaded.")
+    st.error("Crime data could not be loaded. Please check the logs.")
     st.stop()
 
 df_geo = df.dropna(subset=["latitude", "longitude"]).copy()