Rename main.py to app.py

main.py → app.py

@@ -1,124 +1,124 @@
-from flask import Flask, jsonify, render_template, request
-import pandas as pd
-import re
-from datetime import datetime, timedelta
-
-app = Flask(__name__)
-
-# 加载 Excel 数据
-grade_files = {
-    "22级": r"D:\论文项目\喜鹊儿类似产品\数据表\22级.xlsx",
-    "23级": r"D:\论文项目\喜鹊儿类似产品\数据表\23级.xlsx",
-    "24级": r"D:\论文项目\喜鹊儿类似产品\数据表\24级.xlsx",
-}
-
-# 预加载所有年级数据
-dataframes = {}
-for grade, file_path in grade_files.items():
-    df = pd.read_excel(file_path)
-    df["grade"] = grade  # 添加年级字段
-    dataframes[grade] = df
-
-all_data = pd.concat(dataframes.values(), ignore_index=True)
-
-# 第一周的开始日期
-first_week_start_date = datetime(2024, 9, 2)  # 第一周星期一的日期
-
-# 周次解析函数
-def parse_weeks(weeks_str):
-    if not weeks_str or pd.isna(weeks_str):
-        return set()
-    weeks = set()
-    for part in weeks_str.split(","):
-        try:
-            if "-" in part:
-                start, end = map(int, part.split("-"))
-                weeks.update(range(start, end + 1))
-            else:
-                weeks.add(int(part))
-        except ValueError:
-            print(f"跳过无效周次: {part}")
-            continue
-    return weeks
-
-
-# 星期与节次解析函数
-def parse_day_and_period(period_str):
-    if not period_str or pd.isna(period_str):
-        return None
-    try:
-        day_match = re.search(r"[一二三四五六日]", period_str)
-        period_match = re.search(r"\[(\d+)-(\d+)节\]", period_str)
-
-        if day_match and period_match:
-            day = "一二三四五六日".index(day_match.group()) + 1
-            start, end = map(int, period_match.groups())
-            periods = list(range(start, end + 1))
-            return day, periods
-    except Exception as e:
-        print(f"解析失败: {period_str}, 错误: {e}")
-    return None
-
-# 根据周次和星期计算实际日期
-def calculate_date(week, day):
-    days_from_start = (week - 1) * 7 + (day - 1)  # 从第一周开始的天数差
-    return first_week_start_date + timedelta(days=days_from_start)
-
-@app.route("/")
-def index():
-    return render_template("index.html")
-
-
-@app.route("/api/courses")
-def get_courses():
-    week = request.args.get("week", 1)
-    grade = request.args.get("grade", None)
-    admin_class = request.args.get("admin_class", None)
-
-    # 筛选数据
-    filtered_data = all_data
-    if grade:
-        filtered_data = filtered_data[filtered_data["grade"] == grade]
-    if admin_class:
-        filtered_data = filtered_data[filtered_data["行政班级"].str.contains(admin_class, na=False)]
-
-    # 筛选课程类型：只要必修课
-    filtered_data = filtered_data[filtered_data["课程类别"].str.contains("必修课", na=False)]
-
-    if week:
-        week = int(week)
-        filtered_data = filtered_data[
-            filtered_data["周次"].apply(lambda x: week in parse_weeks(x) if pd.notna(x) else False)
-        ]
-
-    # 解析课程信息
-    results = []
-    for _, row in filtered_data.iterrows():
-        day_and_period = parse_day_and_period(row["节次"])
-        if day_and_period:
-            day, periods = day_and_period
-            course_date = calculate_date(week, day)  # 计算课程日期
-            results.append({
-                "课程": row["课程"],
-                "教师": row["教师"],
-                "地点": row["地点"],
-                "星期": day,
-                "日期": course_date.strftime("%Y-%m-%d"),  # 格式化为字符串
-                "节次": periods,
-                "节次范围": f"第{periods[0]}-{periods[-1]}节",
-                "周次": row["周次"]
-            })
-
-    # 按星期和节次排序
-    results = sorted(results, key=lambda x: (x["星期"], x["节次"][0]))
-    return jsonify(results)
-
-
-@app.route("/api/classes")
-def get_classes():
-    classes = all_data["行政班级"].dropna().unique().tolist()
-    return jsonify(sorted(classes))
-
-
-if __name__ == "__main__":
-    app.run(debug=True)
+from flask import Flask, jsonify, render_template, request
+import pandas as pd
+import re
+from datetime import datetime, timedelta
+
+app = Flask(__name__)
+
+# 加载 Excel 数据
+grade_files = {
+    "22级": r"数据表\22级.xlsx",
+    "23级": r"数据表\23级.xlsx",
+    "24级": r"数据表\24级.xlsx",
+}
+
+# 预加载所有年级数据
+dataframes = {}
+for grade, file_path in grade_files.items():
+    df = pd.read_excel(file_path)
+    df["grade"] = grade  # 添加年级字段
+    dataframes[grade] = df
+
+all_data = pd.concat(dataframes.values(), ignore_index=True)
+
+# 第一周的开始日期
+first_week_start_date = datetime(2024, 9, 2)  # 第一周星期一的日期
+
+# 周次解析函数
+def parse_weeks(weeks_str):
+    if not weeks_str or pd.isna(weeks_str):
+        return set()
+    weeks = set()
+    for part in weeks_str.split(","):
+        try:
+            if "-" in part:
+                start, end = map(int, part.split("-"))
+                weeks.update(range(start, end + 1))
+            else:
+                weeks.add(int(part))
+        except ValueError:
+            print(f"跳过无效周次: {part}")
+            continue
+    return weeks
+
+
+# 星期与节次解析函数
+def parse_day_and_period(period_str):
+    if not period_str or pd.isna(period_str):
+        return None
+    try:
+        day_match = re.search(r"[一二三四五六日]", period_str)
+        period_match = re.search(r"\[(\d+)-(\d+)节\]", period_str)
+
+        if day_match and period_match:
+            day = "一二三四五六日".index(day_match.group()) + 1
+            start, end = map(int, period_match.groups())
+            periods = list(range(start, end + 1))
+            return day, periods
+    except Exception as e:
+        print(f"解析失败: {period_str}, 错误: {e}")
+    return None
+
+# 根据周次和星期计算实际日期
+def calculate_date(week, day):
+    days_from_start = (week - 1) * 7 + (day - 1)  # 从第一周开始的天数差
+    return first_week_start_date + timedelta(days=days_from_start)
+
+@app.route("/")
+def index():
+    return render_template("index.html")
+
+
+@app.route("/api/courses")
+def get_courses():
+    week = request.args.get("week", 1)
+    grade = request.args.get("grade", None)
+    admin_class = request.args.get("admin_class", None)
+
+    # 筛选数据
+    filtered_data = all_data
+    if grade:
+        filtered_data = filtered_data[filtered_data["grade"] == grade]
+    if admin_class:
+        filtered_data = filtered_data[filtered_data["行政班级"].str.contains(admin_class, na=False)]
+
+    # 筛选课程类型：只要必修课
+    filtered_data = filtered_data[filtered_data["课程类别"].str.contains("必修课", na=False)]
+
+    if week:
+        week = int(week)
+        filtered_data = filtered_data[
+            filtered_data["周次"].apply(lambda x: week in parse_weeks(x) if pd.notna(x) else False)
+        ]
+
+    # 解析课程信息
+    results = []
+    for _, row in filtered_data.iterrows():
+        day_and_period = parse_day_and_period(row["节次"])
+        if day_and_period:
+            day, periods = day_and_period
+            course_date = calculate_date(week, day)  # 计算课程日期
+            results.append({
+                "课程": row["课程"],
+                "教师": row["教师"],
+                "地点": row["地点"],
+                "星期": day,
+                "日期": course_date.strftime("%Y-%m-%d"),  # 格式化为字符串
+                "节次": periods,
+                "节次范围": f"第{periods[0]}-{periods[-1]}节",
+                "周次": row["周次"]
+            })
+
+    # 按星期和节次排序
+    results = sorted(results, key=lambda x: (x["星期"], x["节次"][0]))
+    return jsonify(results)
+
+
+@app.route("/api/classes")
+def get_classes():
+    classes = all_data["行政班级"].dropna().unique().tolist()
+    return jsonify(sorted(classes))
+
+
+if __name__ == "__main__":
+    app.run(debug=True)