1) refactor, 2) add dockerfile

2025-11-27 19:33:26 +08:00
parent ad753359b0
commit 5e8e51ee82
13 changed files with 406 additions and 290 deletions
--- a/.gitignore
+++ b/.gitignore
@ -8,3 +8,5 @@ wheels/

 # Virtual environments
 .venv
+
+*.tar
--- a/51
+++ b/51
@ -0,0 +1,51 @@
+# Modified by official dockerfile sample(https://github.com/astral-sh/uv-docker-example/blob/main/Dockerfile)
+# Use a Python image with uv pre-installed
+FROM ghcr.io/astral-sh/uv:python3.13-bookworm-slim
+
+# Setup a non-root user
+RUN groupadd --system --gid 999 nonroot \
+    && useradd --system --gid 999 --uid 999 --create-home nonroot
+
+# Install the project into `/app`
+WORKDIR /app
+
+# Enable bytecode compilation
+ENV UV_COMPILE_BYTECODE=1
+
+# Copy from the cache instead of linking since it's a mounted volume
+ENV UV_LINK_MODE=copy
+
+# Ensure installed tools can be executed out of the box
+ENV UV_TOOL_BIN_DIR=/usr/local/bin
+
+# Install the project's dependencies using the lockfile and settings
+RUN --mount=type=cache,target=/root/.cache/uv \
+    --mount=type=bind,source=uv.lock,target=uv.lock \
+    --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
+    uv sync --locked --no-install-project --no-dev
+
+# Then, add the rest of the project source code and install it
+# Installing separately from its dependencies allows optimal layer caching
+COPY ./hiking_assistant /app
+COPY pyproject.toml /app
+COPY uv.lock /app
+RUN --mount=type=cache,target=/root/.cache/uv \
+    uv sync --locked --no-dev
+
+# Place executables in the environment at the front of the path
+ENV PATH="/app/.venv/bin:$PATH"
+
+# Reset the entrypoint, don't invoke `uv`
+ENTRYPOINT []
+
+# Use the non-root user to run our application
+USER nonroot
+
+# Run the Streamlit application by default
+ENV TZ="Asia/Taipei"
+EXPOSE 8504
+CMD ["python", "-m", "streamlit", "run", "app.py", "--server.port=8504", "--server.enableCORS=false", "--server.enableXsrfProtection=false"]
+
+# Build
+# docker build --platform=linux/amd64 -t hiking_assistant:latest .
+# docker save -o hiking_assistant.tar hiking_assistant:latest
--- a/README.md
+++ b/README.md
@ -12,7 +12,8 @@
 ## Installation
 ```bash
 uv sync
-uv run streamlit run hiking_assistant/main.py
+cd hiking_assistant
+uv run streamlit run app.py
 ```

 ## Dirs
--- a/hiking_assistant/app.py
+++ b/hiking_assistant/app.py
@ -0,0 +1,200 @@
+# app.py
+#
+# author: deng
+# date: 20251127
+
+import streamlit as st
+import yaml
+from elevation_profile import ElevationProfileRenderer
+from gpx import GPXProcessor
+from map_render import MapRenderer
+from streamlit_folium import st_folium
+from weather import WeatherFetcher
+
+
+class HikingAssistant:
+    def __init__(self):
+        self._config = self._load_config()
+
+    def _load_config(self):
+        with open('assets/config.yaml', 'r') as f:
+            return yaml.safe_load(f)
+
+    def run(self):
+        """Hiking Assistant application"""
+        # Page configuration
+        st.set_page_config(
+            page_title=self._config['app']['page_title'],
+            page_icon=self._config['app']['page_favicon_path'],
+            layout='wide',
+            initial_sidebar_state='collapsed',
+        )
+
+        # Title and description
+        st.title('⛰️ ' + self._config['app']['page_title'])
+
+        # File uploader
+        uploaded_file = st.file_uploader(
+            '上傳您的 GPX 檔案開始分析路線！',
+            type=['gpx'],
+            help='可以從[健行筆記](https://hiking.biji.co/index.php?q=trail&act=gpx_list)、'
+            '[Hikingbook](https://zh-tw.hikingbook.net/explore/trails?regions=Taiwan)等網站下載 GPX 檔案',
+        )
+
+        if uploaded_file is not None:
+            try:
+                # Process GPX file
+                with st.spinner('正在解析 GPX 檔案...'):
+                    gpx_processor = GPXProcessor(uploaded_file)
+
+                    if not gpx_processor.validate_and_parse():
+                        st.error('❌ GPX 檔案格式錯誤或不包含有效的軌跡點')
+                        return
+
+                    # Calculate statistics
+                    total_distance = gpx_processor.calculate_distance()
+                    elevation_gain, elevation_loss = gpx_processor.calculate_elevation_gain_loss()
+                    min_elevation, max_elevation = gpx_processor.get_min_max_elevation()
+                    start_point, end_point = gpx_processor.get_start_end_points()
+                    all_points = gpx_processor.get_all_points()
+                    distances, elevations = gpx_processor.get_elevation_profile_data()
+                    gradients = gpx_processor.get_gradients()
+                    estimated_time = gpx_processor.calculate_naismith_time()
+
+                # Display statistics section
+                st.header('📊 路線五四三')
+                col1, col2, col3, col4, col5, col6 = st.columns(6)
+
+                with col1:
+                    st.metric(label='總距離', value=f'{total_distance:.1f}km')
+
+                with col2:
+                    st.metric(label='總爬升', value=f'{elevation_gain:.0f}m')
+
+                with col3:
+                    st.metric(label='總下降', value=f'{elevation_loss:.0f}m')
+
+                with col4:
+                    st.metric(label='最高海拔', value=f'{max_elevation:.0f}m')
+
+                with col5:
+                    st.metric(label='最低海拔', value=f'{min_elevation:.0f}m')
+
+                with col6:
+                    st.metric(
+                        label='預估行進時間',
+                        value=f'{estimated_time // 60}h {estimated_time % 60}m',
+                        help='依據[Naismith’s Rule](https://en.wikipedia.org/wiki/Naismith%27s_rule)計算',
+                    )
+
+                # Map section
+                with st.spinner('正在渲染地圖...'):
+                    map_renderer = MapRenderer()
+                    route_map = map_renderer.create_route_map(all_points, start_point, end_point)
+
+                    if route_map:
+                        st_folium(route_map, width=None, height=500, key='route_map', returned_objects=[])
+                    else:
+                        st.error('無法渲染地圖')
+
+                # Create two columns: elevation profile on left, pie chart on right
+                profile_col, pie_col = st.columns([2, 1])
+
+                with profile_col:
+                    with st.spinner('正在繪製海拔剖面圖...'):
+                        profile_renderer = ElevationProfileRenderer()
+                        elevation_fig = profile_renderer.create_elevation_profile(distances, elevations, gradients)
+
+                        if elevation_fig:
+                            # elevation_fig = profile_renderer.add_gradient_legend(elevation_fig)
+                            st.plotly_chart(elevation_fig, width='stretch')
+                        else:
+                            st.error('無法繪製海拔剖面圖')
+
+                with pie_col:
+                    with st.spinner('正在分析坡度分布...'):
+                        pie_fig = profile_renderer.create_gradient_pie_chart(distances, gradients)
+
+                        if pie_fig:
+                            st.plotly_chart(pie_fig, width='stretch')
+                        else:
+                            st.error('無法繪製坡度分布圖')
+
+                st.divider()
+
+                # Weather section
+                st.header('☀️ 天氣安抓')
+
+                if start_point:
+                    with st.spinner('正在獲取天氣資訊...'):
+                        weather_fetcher = WeatherFetcher()
+                        weather_data = weather_fetcher.get_weather(start_point[0], start_point[1])
+
+                        if weather_data:
+                            weather_info = weather_fetcher.format_weather_display(weather_data)
+
+                            if weather_info:
+                                # Current weather
+                                st.subheader('此刻起點天氣')
+                                col1, col2, col3, col4, col5 = st.columns(5)
+
+                                with col1:
+                                    st.metric(label='🌡️ 溫度', value=weather_info['temperature'])
+
+                                with col2:
+                                    st.metric(label='💧 濕度', value=weather_info['humidity'])
+
+                                with col3:
+                                    # Get precipitation probability from weather_data
+                                    precip_prob = weather_data.get('current_precipitation_prob')
+                                    if precip_prob is not None:
+                                        st.metric(label='☔ 降雨機率', value=f'{precip_prob}%')
+                                    else:
+                                        st.metric(label='☔ 降雨機率', value='N/A')
+
+                                with col4:
+                                    st.metric(label='🌧️ 降雨量', value=weather_info['precipitation'])
+
+                                with col5:
+                                    # Get wind direction and convert to flow direction
+                                    wind_dir_degrees = weather_data.get('current_wind_direction')
+                                    wind_dir_text = weather_fetcher.convert_wind_degrees_to_flow_direction(wind_dir_degrees)
+
+                                    # Get wind speed and level indicator
+                                    wind_speed_value = weather_data.get('current_wind_speed')
+                                    wind_level = weather_fetcher.get_wind_speed_indicator(wind_speed_value)
+
+                                    st.metric(
+                                        label='💨 風速與流向',
+                                        value=f'{weather_info["wind_speed"]} {wind_dir_text} {wind_level}',
+                                    )
+
+                                # Forecast
+                                if weather_info['forecast']:
+                                    st.subheader('未來三天預報')
+                                    forecast_cols = st.columns(3)
+
+                                    for idx, forecast in enumerate(weather_info['forecast']):
+                                        with forecast_cols[idx]:
+                                            st.markdown(f'**{forecast["date"]}**')
+                                            st.write(f'🌡️ 高溫: {forecast["temp_max"]}°C')
+                                            st.write(f'🌡️ 低溫: {forecast["temp_min"]}°C')
+                                            st.write(f'☔ 降雨機率: {forecast["precip_prob"]}%')
+                            else:
+                                st.warning('⚠️ 無法格式化天氣資料')
+                        else:
+                            st.warning('⚠️ 無法獲取天氣資訊，請稍後再試')
+                else:
+                    st.warning('⚠️ 無法確定起點位置')
+
+            except Exception as e:
+                st.error(f'❌ 處理檔案時發生錯誤: {str(e)}')
+
+        st.divider()
+        footer_text = f'<div style="text-align:center; font-size: 0.8em"><p>{self._config["app"]["page_footer_text"]}</p></div>'
+        st.markdown(footer_text, unsafe_allow_html=True)
+
+
+if __name__ == '__main__':
+    app = HikingAssistant()
+    app.run()
--- a/hiking_assistant/assets/config.yaml
+++ b/hiking_assistant/assets/config.yaml
@ -0,0 +1,4 @@
+app:
+  page_title: 臺灣登山小幫手
+  page_favicon_path: ./assets/favicon_compressed.jpg
+  page_footer_text: ⚠️ 本服務提供之資訊僅供規劃參考，山區氣候瞬息萬變，請務必依據現場狀況與自身能力進行風險評估<br>Made with ❤️ by <a href="https://gitea.guineapig.love/deng">deng</a>
--- a/hiking_assistant/elevation_profile.py
+++ b/hiking_assistant/elevation_profile.py
@ -8,7 +8,44 @@ class ElevationProfileRenderer:

    def __init__(self):
        """Initialize elevation profile renderer."""
-        pass
+        self.color = {
+            'steep_ascent': 'rgb(139, 69, 19)',
+            'gentle_ascent': 'rgb(210, 180, 140)',
+            'steep_descent': 'rgb(34, 139, 34)',
+            'gentle_descent': 'rgb(154, 205, 50)',
+        }
+
+        self.slope = {
+            'steep_ascent': [15, float('inf')],
+            'gentle_ascent': [0, 15],
+            'steep_descent': [float('-inf'), -20],
+            'gentle_descent': [-20, 0],
+        }
+
+        self.label = {
+            'steep_ascent': '陡上坡 (>= 15%)',
+            'gentle_ascent': '緩上坡 (< 15%)',
+            'steep_descent': '陡下坡 (<= -20%)',
+            'gentle_descent': '緩下坡 (> -20%)',
+        }
+
+    def _get_gradient_category(self, gradient):
+        """Determine gradient category based on slope thresholds.
+
+        Args:
+            gradient: Gradient value in percentage
+
+        Returns:
+            str: Category key ('steep_ascent', 'gentle_ascent', 'steep_descent', 'gentle_descent')
+        """
+        if gradient >= self.slope['steep_ascent'][0]:
+            return 'steep_ascent'
+        elif gradient >= self.slope['gentle_ascent'][0]:
+            return 'gentle_ascent'
+        elif gradient <= self.slope['steep_descent'][1]:
+            return 'steep_descent'
+        else:
+            return 'gentle_descent'

    def _downsample_data(self, distances, elevations, gradients, max_points=800):
        """Downsample data if there are too many points.
@ -84,23 +121,10 @@ class ElevationProfileRenderer:
        while i < len(distances) - 1:
            gradient = gradients_extended[i + 1]

-            # Determine color based on gradient thresholds (earth-tone palette)
-            if gradient > 0:  # Ascending
-                if gradient >= 15:
-                    # Steep ascent: dark red-brown (brick/terracotta)
-                    color = 'rgb(139, 69, 19)'  # Saddle brown
-                else:
-                    # Gentle ascent: light red-brown (sandy/tan)
-                    color = 'rgb(210, 180, 140)'  # Tan
-                is_ascending = True
-            else:  # Descending
-                if gradient <= -20:
-                    # Steep descent: dark green (forest green)
-                    color = 'rgb(34, 139, 34)'  # Forest green
-                else:
-                    # Gentle descent: light green (sage/olive)
-                    color = 'rgb(154, 205, 50)'  # Yellow green
-                is_ascending = False
+            # Determine color based on gradient category
+            category = self._get_gradient_category(gradient)
+            color = self.color[category]
+            is_ascending = gradient > 0

            # Collect consecutive points with similar direction (ascending/descending)
            segment_x = [distances[i]]
@ -179,14 +203,15 @@ class ElevationProfileRenderer:
            if i + 1 < len(distances):
                segment_distance = distances[i + 1] - distances[i]
                gradient = gradients[i]
+                category = self._get_gradient_category(gradient)

-                if gradient >= 15:
+                if category == 'steep_ascent':
                    steep_ascent_km += segment_distance
-                elif gradient > 0:
+                elif category == 'gentle_ascent':
                    gentle_ascent_km += segment_distance
-                elif gradient <= -20:
+                elif category == 'steep_descent':
                    steep_descent_km += segment_distance
-                else:  # gradient < 0 and > -20
+                else:  # gentle_descent
                    gentle_descent_km += segment_distance

        return {
@ -211,33 +236,23 @@ class ElevationProfileRenderer:
        if not stats:
            return None

-        # Prepare data
-        labels = ['陡上坡 (≥15%)', '緩上坡 (<15%)', '陡下坡 (≤-20%)', '緩下坡 (>-20%)']
-        values = [stats['steep_ascent'], stats['gentle_ascent'], stats['steep_descent'], stats['gentle_descent']]
-        colors = [
-            'rgb(139, 69, 19)',  # Steep ascent - dark brown
-            'rgb(210, 180, 140)',  # Gentle ascent - tan
-            'rgb(34, 139, 34)',  # Steep descent - forest green
-            'rgb(154, 205, 50)',  # Gentle descent - yellow green
-        ]
-
        # Create pie chart
        fig = go.Figure(
            data=[
                go.Pie(
-                    labels=labels,
-                    values=values,
-                    marker=dict(colors=colors),
+                    labels=list(self.label.values()),
+                    values=list(stats.values()),
+                    marker=dict(colors=list(self.color.values())),
                    textinfo='label+percent',
                    textposition='inside',
-                    hovertemplate='%{label}<br>%{value:.2f} km<br>%{percent}<extra></extra>',
+                    hovertemplate='%{value:.2f} km<extra></extra>',
                    showlegend=False,  # Don't show legend as requested
                )
            ]
        )

        fig.update_layout(
-            title='坡度分布',
+            title='',
            height=400,
            margin=dict(l=20, r=20, t=40, b=20),
        )
@ -259,8 +274,8 @@ class ElevationProfileRenderer:
                x=[None],
                y=[None],
                mode='lines',
-                line=dict(color='rgb(139,69,19)', width=3),
-                name='陡上坡 (≥15%)',
+                line=dict(color=self.color['steep_ascent'], width=3),
+                name=self.label['steep_ascent'],
            )
        )

@ -269,8 +284,8 @@ class ElevationProfileRenderer:
                x=[None],
                y=[None],
                mode='lines',
-                line=dict(color='rgb(210,180,140)', width=3),
-                name='緩上坡 (<15%)',
+                line=dict(color=self.color['gentle_ascent'], width=3),
+                name=self.label['gentle_ascent'],
            )
        )

@ -279,8 +294,8 @@ class ElevationProfileRenderer:
                x=[None],
                y=[None],
                mode='lines',
-                line=dict(color='rgb(34,139,34)', width=3),
-                name='陡下坡 (≤-20%)',
+                line=dict(color=self.color['steep_descent'], width=3),
+                name=self.label['steep_descent'],
            )
        )

@ -289,8 +304,8 @@ class ElevationProfileRenderer:
                x=[None],
                y=[None],
                mode='lines',
-                line=dict(color='rgb(154,205,50)', width=3),
-                name='緩下坡 (>-20%)',
+                line=dict(color=self.color['gentle_descent'], width=3),
+                name=self.label['gentle_descent'],
            )
        )

--- a/hiking_assistant/gpx.py
+++ b/hiking_assistant/gpx.py
@ -1,4 +1,7 @@
-"""GPX file processing module for hiking route analysis."""
+# gpx.py
+#
+# author: deng
+# date: 20251127

 import gpxpy
 import gpxpy.gpx
@ -165,3 +168,31 @@ class GPXProcessor:
            gradients.append(gradient)

        return gradients
+
+    def calculate_naismith_time(self):
+        """Calculate estimated hiking time using Naismith's Rule.
+
+        Naismith's Rule:
+        - Base time: 1 hour per 5 km of horizontal distance
+        - Add time: 1 hour per 600 meters of ascent
+
+        Returns:
+            int: Estimated time in minutes
+        """
+        if len(self.points) < 2:
+            return 0
+
+        # Get total distance and elevation gain
+        total_distance = self.calculate_distance() if not self.distances else self.distances[-1]
+        elevation_gain, _ = self.calculate_elevation_gain_loss()
+
+        # Naismith's Rule calculation
+        # 1 hour per 5 km = 0.2 hours per km
+        time_for_distance = total_distance * 0.2
+
+        # 1 hour per 600 meters of ascent
+        time_for_ascent = elevation_gain / 600.0
+
+        total_time = int((time_for_distance + time_for_ascent) * 60)
+
+        return total_time
--- a/hiking_assistant/main.py
+++ b/hiking_assistant/main.py
@ -1,182 +0,0 @@
-"""台灣登山路線規劃輔助系統 - Streamlit Web Application"""
-
-import streamlit as st
-from elevation_profile import ElevationProfileRenderer
-from gpx import GPXProcessor
-from map_render import MapRenderer
-from streamlit_folium import st_folium
-from weather import WeatherFetcher
-
-
-def main():
-    """Main Streamlit application."""
-    # Page configuration
-    st.set_page_config(
-        page_title='臺灣登山路線分析小幫手',
-        page_icon='assets/favicon_compressed.jpg',
-        layout='wide',
-        initial_sidebar_state='collapsed',
-    )
-
-    # Title and description
-    st.title('⛰️ 臺灣登山路線分析小幫手')
-    st.markdown('上傳您的 GPX 檔案開始分析路線！')
-
-    # File uploader
-    uploaded_file = st.file_uploader(
-        '上傳檔案',
-        type=['gpx'],
-        help='請上傳包含登山路線的 GPX 檔案',
-    )
-
-    if uploaded_file is not None:
-        try:
-            # Process GPX file
-            with st.spinner('正在解析 GPX 檔案...'):
-                gpx_processor = GPXProcessor(uploaded_file)
-
-                if not gpx_processor.validate_and_parse():
-                    st.error('❌ GPX 檔案格式錯誤或不包含有效的軌跡點')
-                    return
-
-                # Calculate statistics
-                total_distance = gpx_processor.calculate_distance()
-                elevation_gain, elevation_loss = gpx_processor.calculate_elevation_gain_loss()
-                min_elevation, max_elevation = gpx_processor.get_min_max_elevation()
-                start_point, end_point = gpx_processor.get_start_end_points()
-                all_points = gpx_processor.get_all_points()
-                distances, elevations = gpx_processor.get_elevation_profile_data()
-                gradients = gpx_processor.get_gradients()
-
-            # Display statistics section
-            st.header('📊 路線統計資訊')
-            col1, col2, col3, col4, col5 = st.columns(5)
-
-            with col1:
-                st.metric(label='總距離', value=f'{total_distance:.2f}', delta='公里')
-
-            with col2:
-                st.metric(label='總爬升', value=f'{elevation_gain:.0f}', delta='公尺')
-
-            with col3:
-                st.metric(label='總下降', value=f'{elevation_loss:.0f}', delta='公尺')
-
-            with col4:
-                st.metric(label='最高海拔', value=f'{max_elevation:.0f}', delta='公尺')
-
-            with col5:
-                st.metric(label='最低海拔', value=f'{min_elevation:.0f}', delta='公尺')
-
-            st.divider()
-
-            # Map and Elevation profile section (no divider between them)
-            st.header('🗺️ 路線地圖')
-
-            # Map section
-            with st.spinner('正在渲染地圖...'):
-                map_renderer = MapRenderer()
-                route_map = map_renderer.create_route_map(all_points, start_point, end_point)
-
-                if route_map:
-                    st_folium(route_map, width=None, height=500)
-                else:
-                    st.error('無法渲染地圖')
-
-            # Elevation profile section (directly below map, no divider)
-            # st.markdown('🔴 **紅色**表示上升路段（顏色越深坡度越陡） | 🟢 **綠色**表示下降路段（顏色越深坡度越陡）')
-
-            # Create two columns: elevation profile on left, pie chart on right
-            profile_col, pie_col = st.columns([2, 1])
-
-            with profile_col:
-                with st.spinner('正在繪製海拔剖面圖...'):
-                    profile_renderer = ElevationProfileRenderer()
-                    elevation_fig = profile_renderer.create_elevation_profile(distances, elevations, gradients)
-
-                    if elevation_fig:
-                        # Add legend
-                        elevation_fig = profile_renderer.add_gradient_legend(elevation_fig)
-                        st.plotly_chart(elevation_fig, width='stretch')
-                    else:
-                        st.error('無法繪製海拔剖面圖')
-
-            with pie_col:
-                with st.spinner('正在分析坡度分布...'):
-                    pie_fig = profile_renderer.create_gradient_pie_chart(distances, gradients)
-
-                    if pie_fig:
-                        st.plotly_chart(pie_fig, width='stretch')
-                    else:
-                        st.error('無法繪製坡度分布圖')
-
-            st.divider()
-
-            # Weather section
-            st.header('☀️ 起點天氣預報')
-
-            if start_point:
-                with st.spinner('正在獲取天氣資訊...'):
-                    weather_fetcher = WeatherFetcher()
-                    weather_data = weather_fetcher.get_weather(start_point[0], start_point[1])
-
-                    if weather_data:
-                        weather_info = weather_fetcher.format_weather_display(weather_data)
-
-                        if weather_info:
-                            # Current weather
-                            st.subheader('當前天氣')
-                            col1, col2, col3, col4 = st.columns(4)
-
-                            with col1:
-                                st.metric(label='🌡️ 溫度', value=weather_info['temperature'])
-
-                            with col2:
-                                st.metric(label='💧 濕度', value=weather_info['humidity'])
-
-                            with col3:
-                                st.metric(label='🌧️ 降雨量', value=weather_info['precipitation'])
-
-                            with col4:
-                                st.metric(label='💨 風速', value=weather_info['wind_speed'])
-
-                            # Forecast
-                            if weather_info['forecast']:
-                                st.subheader('未來三天預報')
-                                forecast_cols = st.columns(3)
-
-                                for idx, forecast in enumerate(weather_info['forecast']):
-                                    with forecast_cols[idx]:
-                                        st.markdown(f'**{forecast["date"]}**')
-                                        st.write(f'🌡️ 高溫: {forecast["temp_max"]}°C')
-                                        st.write(f'🌡️ 低溫: {forecast["temp_min"]}°C')
-                                        st.write(f'🌧️ 降雨機率: {forecast["precip_prob"]}%')
-                        else:
-                            st.warning('⚠️ 無法格式化天氣資料')
-                    else:
-                        st.warning('⚠️ 無法獲取天氣資訊，請稍後再試')
-            else:
-                st.warning('⚠️ 無法確定起點位置')
-
-        except Exception as e:
-            st.error(f'❌ 處理檔案時發生錯誤: {str(e)}')
-
-    else:
-        # # Show instructions when no file is uploaded
-        # st.info('👆 請上傳 GPX 檔案開始分析')
-        # st.markdown(
-        #     """
-        # ### 使用說明
-        # 1. 點擊上方的「選擇 GPX 檔案」按鈕
-        # 2. 選擇您的登山路線 GPX 檔案
-        # 3. 系統將自動分析並顯示：
-        #    - 📊 路線統計資訊（距離、爬升、海拔等）
-        #    - 🗺️ 互動式路線地圖
-        #    - 📈 海拔剖面圖（顏色顯示坡度變化）
-        #    - ☀️ 起點天氣預報
-        # """
-        # )
-        pass
-
-
-if __name__ == '__main__':
-    main()
--- a/hiking_assistant/map_render.py
+++ b/hiking_assistant/map_render.py
@ -1,4 +1,7 @@
-"""Map rendering module using Folium for interactive maps."""
+# map_render.py
+#
+# author: deng
+# date: 20251127

 import folium

--- a/hiking_assistant/weather.py
+++ b/hiking_assistant/weather.py
@ -1,4 +1,7 @@
-"""Weather data fetching module using Open-Meteo API."""
+# weather.py
+#
+# author: deng
+# date: 20251127

 import requests

@ -8,7 +11,44 @@ class WeatherFetcher:

    def __init__(self):
        """Initialize weather fetcher."""
-        self.base_url = 'https://api.open-meteo.com/v1/forecast'
+        self.api_url = 'https://api.open-meteo.com/v1/forecast'
+        self.request_timeout = 8  # unit: second
+
+    def convert_wind_degrees_to_flow_direction(self, degrees):
+        """Convert wind direction from degrees to flow direction emoji.
+
+        Args:
+            degrees: Wind direction in degrees (0-360)
+
+        Returns:
+            str: Flow direction as emoji arrow (pointing where wind is blowing to)
+        """
+        if degrees is None:
+            return 'N/A'
+        directions = ['⬇️', '↙️', '⬅️', '↖️', '⬆️', '↗️', '➡️', '↘️']
+        index = round(degrees / 45) % 8
+        return directions[index]
+
+    def get_wind_speed_indicator(self, wind_speed):
+        """Get wind speed level indicator based on speed.
+
+        Args:
+            wind_speed: Wind speed in km/h
+
+        Returns:
+            str: Emoji indicator (🟢/🟡/🟠/🔴)
+        """
+        if wind_speed is None:
+            return ''
+
+        if wind_speed < 20:
+            return '🟢'  # Safe
+        elif wind_speed < 40:
+            return '🟡'  # Caution
+        elif wind_speed < 60:
+            return '🟠'  # Alert
+        else:
+            return '🔴'  # Dangerous

    def get_weather(self, latitude, longitude):
        """Fetch weather data for given coordinates.
@ -25,18 +65,18 @@ class WeatherFetcher:
            params = {
                'latitude': latitude,
                'longitude': longitude,
-                'current': 'temperature_2m,relative_humidity_2m,precipitation,wind_speed_10m',
+                'current': 'temperature_2m,relative_humidity_2m,precipitation,wind_speed_10m,wind_direction_10m',
                'daily': 'temperature_2m_max,temperature_2m_min,precipitation_probability_max',
-                'timezone': 'Asia/Taipei',
+                'timezone': 'auto',
                'forecast_days': 3,
            }

-            response = requests.get(self.base_url, params=params, timeout=10)
+            response = requests.get(self.api_url, params=params, timeout=self.request_timeout)
            response.raise_for_status()

            data = response.json()

-            # Parse current weather
+            # Parse weather data
            current = data.get('current', {})
            daily = data.get('daily', {})

@ -44,7 +84,9 @@ class WeatherFetcher:
                'current_temperature': current.get('temperature_2m'),
                'current_humidity': current.get('relative_humidity_2m'),
                'current_precipitation': current.get('precipitation'),
+                'current_precipitation_prob': daily.get('precipitation_probability_max', [None])[0],  # Today's rain probability
                'current_wind_speed': current.get('wind_speed_10m'),
+                'current_wind_direction': current.get('wind_direction_10m'),
                'daily_temp_max': daily.get('temperature_2m_max', []),
                'daily_temp_min': daily.get('temperature_2m_min', []),
                'daily_precipitation_prob': daily.get('precipitation_probability_max', []),
--- a/pyproject.toml
+++ b/pyproject.toml
@ -13,6 +13,7 @@ dependencies = [
    "requests>=2.32.3",
    "geopy>=2.4.1",
    "streamlit-plotly-events>=0.0.6",
+    "pyyaml>=6.0.3",
 ]

 [dependency-groups]
--- a/test_hehuan.gpx
+++ b/test_hehuan.gpx
@ -1,54 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<gpx version="1.1" creator="Hiking Assistant Test" 
-  xmlns="http://www.topografix.com/GPX/1/1"
-  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
-  xsi:schemaLocation="http://www.topografix.com/GPX/1/1 http://www.topografix.com/GPX/1/1/gpx.xsd">
-  <metadata>
-    <name>合歡山主峰測試路線</name>
-    <desc>從合歡山主峰登山口到山頂的測試路線</desc>
-  </metadata>
-  <trk>
-    <name>合歡山主峰路線</name>
-    <trkseg>
-      <trkpt lat="24.1400" lon="121.2720">
-        <ele>3150</ele>
-      </trkpt>
-      <trkpt lat="24.1405" lon="121.2725">
-        <ele>3180</ele>
-      </trkpt>
-      <trkpt lat="24.1410" lon="121.2730">
-        <ele>3210</ele>
-      </trkpt>
-      <trkpt lat="24.1415" lon="121.2735">
-        <ele>3250</ele>
-      </trkpt>
-      <trkpt lat="24.1420" lon="121.2740">
-        <ele>3290</ele>
-      </trkpt>
-      <trkpt lat="24.1425" lon="121.2745">
-        <ele>3320</ele>
-      </trkpt>
-      <trkpt lat="24.1430" lon="121.2750">
-        <ele>3350</ele>
-      </trkpt>
-      <trkpt lat="24.1435" lon="121.2755">
-        <ele>3360</ele>
-      </trkpt>
-      <trkpt lat="24.1438" lon="121.2758">
-        <ele>3380</ele>
-      </trkpt>
-      <trkpt lat="24.1440" lon="121.2760">
-        <ele>3400</ele>
-      </trkpt>
-      <trkpt lat="24.1442" lon="121.2762">
-        <ele>3410</ele>
-      </trkpt>
-      <trkpt lat="24.1444" lon="121.2764">
-        <ele>3416</ele>
-      </trkpt>
-      <trkpt lat="24.1445" lon="121.2765">
-        <ele>3417</ele>
-      </trkpt>
-    </trkseg>
-  </trk>
-</gpx>
--- a/uv.lock
+++ b/uv.lock
@ -234,6 +234,7 @@ dependencies = [
    { name = "geopy" },
    { name = "gpxpy" },
    { name = "plotly" },
+    { name = "pyyaml" },
    { name = "requests" },
    { name = "streamlit" },
    { name = "streamlit-folium" },
@ -253,6 +254,7 @@ requires-dist = [
    { name = "geopy", specifier = ">=2.4.1" },
    { name = "gpxpy", specifier = ">=1.6.2" },
    { name = "plotly", specifier = ">=5.24.1" },
+    { name = "pyyaml", specifier = ">=6.0.3" },
    { name = "requests", specifier = ">=2.32.3" },
    { name = "streamlit", specifier = ">=1.51.0" },
    { name = "streamlit-folium", specifier = ">=0.23.1" },