25级数应四班第五次实验（34）

学号	姓名	是否提交作业
2025010133	王子涵	是
2025010134	赵雯佳	是
2025010136	屈雨蒙	是
2025010137	刘柯凡	是
2025010139	潘佳乐	是
2025010140	杨亚洲	是
2025010141	王嘉伟	是
2025010142	杨旭洁	是
2025010143	肖雅楠	是
2025010144	张博洋	是
2025010145	黄冰冰	是
2025010146	顾芳菲	是
2025010147	刘芝怡	否
2025010148	岳嘉瑞	是
2025010149	马相淼	是
2025010150	唐景泽	是
2025010151	侯益波	是
2025010152	刘金惺	是
2025010153	范鹏展	是
2025010154	洪关瑞	是
2025010155	王状	是
2025010157	闫宸熙	是
2025010158	陈文洁	是
2025010159	成哲煜	是
2025010160	韩俊杰	是
2025010161	朱星月	是
2025010162	刘奕桐	是
2025010163	刘志杰	是
2025010164	李朋祖	是
2025010165	赵子月	是
2025010166	蒋子凡	是
2025010167	杨书宇	是
2025010168	袁艺伦	是
2025010169	闵子怡	是
2025010170	张家祺	是
2025010171	陈宣汝	是
2025010172	张景悦	是
2025010173	杨云飞	是
2025010174	刘研	是
2025010175	孙兰妮	是

2025010133王子涵

import pandas as pd     #导入pandas库# 读取销售明细表，指定openpyxl来读取
sale_df = pd.read_excel("销售明细表.xlsx", engine="openpyxl")# 用字典定义商品单价
price_map = {"中性笔": 1.5,"笔记本": 5,"文件夹": 7.2
}# 计算单价和单笔销售额
sale_df["单价"] = sale_df["商品名称"].map(price_map)  #p根据字典把商品名称换成对应的单价，s_d新增一列单价
sale_df["单笔销售额"] = sale_df["销售数量"] * sale_df["单价"]# 按销售人员汇总（用字典传参避免括号语法问题）
summary_df = sale_df.groupby("销售人员").agg({     #g把同一个人的订单归为一组"销售数量": "sum",                             #对分组数据合计"单笔销售额": "sum"
}).rename(columns={"销售数量": "总销售数量","单笔销售额": "总销售额(元)"
}).reset_index()# 金额保留2位小数
summary_df["总销售额(元)"] = summary_df["总销售额(元)"].round(2)# 导出汇总表
summary_df.to_excel("人员总销售额汇总表.xlsx", index=False, engine="openpyxl")# 打印结果
print("✅ 汇总完成！")
print(summary_df)

 2025010134 赵雯佳

 列表转字典

 

def lists_to_dict(keys, values):"""将两个列表转换为字典，并自动处理长度不匹配的情况"""# 1. 判断长度是否不相等if len(keys) != len(values):print(f"⚠️ 警告：键列表长度({len(keys)})与值列表长度({len(values)})不匹配！")# 情况 A：键比值多 (Key > Value) -> 补 Noneif len(keys) > len(values):print("👉 键列表较长，缺失的值将用 None 填充。")result = {}for i in range(len(keys)):if i < len(values):result[keys[i]] = values[i]else:result[keys[i]] = Nonereturn result# 情况 B：值比键多 (Value > Key) -> 截断值else:print("👉 值列表较长，多出的值将被舍弃。")result = {}for i in range(len(keys)):result[keys[i]] = values[i]return result# 2. 否则 (长度相等)else:print("✅ 两个列表长度匹配，直接转换。")return dict(zip(keys, values))# --- 测试代码 ---# 示例1：长度相等
keys1 = ['姓名', '年龄', '城市']
values1 = ['小明', 18, '西安']
print(lists_to_dict(keys1, values1), "\n")# 示例2：值比键多 (你图中的示例2)
keys3 = ['语文', '数学']
values3 = [95, 100, 88, 76]
print(lists_to_dict(keys3, values3), "\n")# 示例3：键比值多
keys4 = ['a', 'b', 'c', 'd']
values4 = [1, 2]
print(lists_to_dict(keys4, values4))

 

 

 

2025010136 屈雨蒙
加载马鞍图

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D  # 这里改成正确导入# 解决中文乱码、字体警告

plt.rcParams["axes.unicode_minus"] = False  # 解决负号显示问题# 生成x、y网格
x = np.linspace(-5, stop=5, num=100)
y = np.linspace(-5, stop=5, num=100)
X, Y = np.meshgrid(x, y)# 马鞍面 z = x² - y²
Z = X ** 2 - Y ** 2# 3D画布
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')ax.plot_surface(X, Y, Z, cmap='coolwarm', alpha=0.8)ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')  # 补上z轴标签
plt.show()

 

2025010137 刘柯凡
角度加减

# 角度加法函数
def jia(du1,fen1,miao1,du2,fen2,miao2):miao = miao1 + miao2fen = fen1 + fen2du = du1 + du2# 秒进位if miao >= 60:miao -= 60fen += 1# 分进位if fen >= 60:fen -= 60du += 1return du,fen,miao# 角度减法函数
def jian(du1,fen1,miao1,du2,fen2,miao2):miao = miao1 - miao2fen = fen1 - fen2du = du1 - du2# 秒不够减借位if miao < 0:miao += 60fen -= 1# 分不够减借位if fen < 0:fen += 60du -= 1return du,fen,miao# 手动输入数据
print("=====角度加减计算器=====")
print("请输入第一个角度：")
d1=int(input("度："))
f1=int(input("分："))
m1=int(input("秒："))print("请输入第二个角度：")
d2=int(input("度："))
f2=int(input("分："))
m2=int(input("秒："))# 调用函数
add_du,add_fen,add_miao = jia(d1,f1,m1,d2,f2,m2)
sub_du,sub_fen,sub_miao = jian(d1,f1,m1,d2,f2,m2)# 输出结果
print("\n加法结果：",add_du,"度",add_fen,"分",add_miao,"秒")
print("减法结果：",sub_du,"度",sub_fen,"分",sub_miao,"秒")

 

 

2025010139 潘佳乐
判断等比等差数列

def check_sequence(sequence):     #接受数列if len(sequence) < 2:return "数列长度不足，无法判断"# ===== 判断 等差数列 =====is_arithmetic = Truecommon_diff = sequence[1] - sequence[0]for i in range(2, len(sequence)):if sequence[i] - sequence[i - 1] != common_diff:is_arithmetic = Falsebreak# ===== 判断 等比数列 =====is_geometric = Truefor num in sequence:if num == 0:is_geometric = Falsebreakif is_geometric:common_ratio = sequence[1] / sequence[0]for i in range(2, len(sequence)):# 处理浮点数精度问题，允许微小误差if abs(sequence[i] / sequence[i - 1] - common_ratio) > 1e-9:is_geometric = Falsebreak# ===== 输出最终结果 =====if is_arithmetic and is_geometric:return "该数列既是等差数列，也是等比数列（常数列）"elif is_arithmetic:return f"该数列是【等差数列】，公差 = {common_diff}"elif is_geometric:return f"该数列是【等比数列】，公比 = {common_ratio}"else:return "该数列既不是等差数列，也不是等比数列"# ========== 主程序：输入数列并判断 ==========
if __name__ == "__main__":print("===== 数列判断器 =====")print("输入规则：输入数列的数字，用空格隔开，按回车确认")print("示例：1 2 3 4  或  2 4 8 16\n")# 获取用户输入input_str = input("请输入数列：")# 分割字符串并转换为数字列表num_list = [float(num) for num in input_str.split()]# 调用函数判断并输出结果result = check_sequence(num_list)print("\n判断结果：", result)

 

 2025010140杨亚洲

import os
os.startfile(r"C:\Users\杨亚洲\PyCharmMiscProject\5作业\新建文件夹\0a51590ebdd384fbd9ed9ccbcc1d9083.png")

 

 

2025010141王嘉伟
# 判断闰年
def run_nian(y):if (y%4==0 and y%100!=0) or y%400==0:return 366return 365# 每个月多少天
def yue_tian(y, m):t = [31,28,31,30,31,30,31,31,30,31,30,31]if m == 2 and run_nian(y)==366:return 29return t[m-1]# 核心：算两个日期之间相差几天
def cha_tian(y1,m1,d1, y2,m2,d2):cha = 0# 先整年差for y in range(y1, y2):cha += run_nian(y)# 再整月差for m in range(m1, m2):cha += yue_tian(y2, m)# 最后天数差cha += (d2 - d1)return cha# 最终算星期
def xingqi(nian,yue,ri):# 固定基准：今天 2026.5.11 星期一base_n, base_y, base_r = 2026, 5, 11# 算出和今天差多少天tian = cha_tian(base_n, base_y, base_r, nian, yue, ri)week = ["星期一","星期二","星期三","星期四","星期五","星期六","星期日"]yu = tian % 7if yu < 0:yu += 7return week[yu]# 运行
a = int(input("输入年份："))
b = int(input("输入月份："))
c = int(input("输入日期："))
print(xingqi(a,b,c))

 

 

2025010142 杨旭洁
备份D盘某文件夹里面以a/A开头的文件

import shutil,os
s=r"D:\Program\PyCharm 2025.3.3\jbr\legal\jdk.internal.le"
t=r"D:\a备份"
for f in os.listdir(s):if f.lower().startswith("a"):shutil.copy(os.path.join(s,f),t)

 

2025010143 肖雅楠
加班费

# 定义统计周末加班加班费的函数
def count_overtime_salary(person_name, work_base_salary, month_weekend_days):"""
    :param person_name: 员工姓名:param work_base_salary: 工作日单日基础加班费:param month_weekend_days: 当月周六周日加班总天数:return: 该员工当月周末加班总加班费"""# 周末加班一天 = 工作日的3倍weekend_one_day = work_base_salary * 3# 计算当月周末加班总费用total_salary = weekend_one_day * month_weekend_daysreturn total_salary# ========== 测试调用示例 ==========
if __name__ == "__main__":# 输入示例：基础日薪100元，当月周末加班4天name = input("请输入员工姓名：")base_sal = float(input("请输入工作日单日加班费："))weekend_days = int(input("请输入当月周六周日加班总天数："))# 调用函数total = count_overtime_salary(name, base_sal, weekend_days)print(f"{name}当月周末加班总加班费为：{total} 元")

 2025010144张博洋

文件分类

import os
import shutil
from datetime import datetimeFILES_TO_CLASSIFY = ["C:/Users/ly013/Desktop/画集/1763568134742.jpeg","C:/Users/ly013/Desktop/Minecraft Launcher.lnk","C:/Users/ly013/Desktop/画集/1763911773587.jpeg",
"C:/Users/ly013/Desktop/pythonZY/实验五(Python语言程序设计基础)1_加水印.pdf"]
# 分类后存放的目标目录
TARGET_DIR = "新文件夹"
# 时间依据：'modified'(修改时间) 或 'created'(创建时间)
TIME_TYPE = "modified"
# 操作方式
ACTION = "copy"def get_file_time(file_path):"""获取文件的时间"""stat = os.stat(file_path)if TIME_TYPE == "modified":timestamp = stat.st_mtimeelse:timestamp = stat.st_ctimereturn datetime.fromtimestamp(timestamp)def classify_files():"""执行分类"""if not os.path.exists(TARGET_DIR):os.makedirs(TARGET_DIR)print(f"创建目录：{TARGET_DIR}")for file_path in FILES_TO_CLASSIFY:# 检查文件是否存在if not os.path.exists(file_path):print(f"文件不存在：{file_path}")continue# 获取文件名和时间filename = os.path.basename(file_path)file_time = get_file_time(file_path)# 按年月创建文件夹名（例如：2026-05）folder_name = file_time.strftime("%Y-%m")target_folder = os.path.join(TARGET_DIR, folder_name)# 创建年份-月份文件夹if not os.path.exists(target_folder):os.makedirs(target_folder)print("\n"f"---创建文件夹---：{folder_name}")# 目标路径target_path = os.path.join(target_folder, filename)# 复制文件if ACTION == "copy":shutil.copy2(file_path, target_path)print(f"{filename}" )if __name__ == "__main__":classify_files()

 

 2025010145 黄冰冰

# 1. 生成一段字符串（可以自己修改内容）
my_str = "Hello, World! 你好，世界"# 2. 倒序输出（Python 最简洁的写法）
reverse_str = my_str[::-1]# 3. 打印结果
print("原字符串：", my_str)
print("倒序后：", reverse_str)

 

 

2025010146 顾芳菲
仿真物理实验凸透镜凹透镜光路

import turtle# ========== 画布基础设置 ==========
screen = turtle.Screen()
screen.setup(width=800, height=600)
screen.title("凸透镜 & 凹透镜光路仿真")
screen.bgcolor("white")
pen = turtle.Turtle()
pen.speed(0)
pen.hideturtle()# ========== 坐标轴绘制 ==========
def draw_axis():pen.pencolor("gray")pen.pensize(1)# 主光轴横线pen.penup()pen.goto(-400, 0)pen.pendown()pen.goto(400, 0)# 透镜中心原点黑点pen.dot(size=5, color="black")# ========== 绘制凸透镜 ==========
def draw_convex_lens():pen.pencolor("blue")pen.pensize(3)pen.penup()pen.goto(0, -150)pen.pendown()# 左右两段圆弧组成凸透镜pen.circle(radius=150, extent=180)pen.circle(-150, extent=180)# ========== 绘制凹透镜 ==========
def draw_concave_lens():pen.pencolor("red")pen.pensize(3)pen.penup()pen.goto(0, -150)pen.pendown()# 反向圆弧组成凹透镜pen.circle(-150, extent=180)pen.circle(150, extent=180)# ========== 凸透镜平行入射光路（汇聚） ==========
def convex_light():pen.pencolor("orange")pen.pensize(2)ys = [-80, -40, 0, 40, 80]for y in ys:pen.penup()pen.goto(-350, y)pen.pendown()pen.goto(0, y)# 折射后汇聚到右焦点(150,0)pen.goto(150, 0)# ========== 凹透镜平行入射光路（发散） ==========
def concave_light():pen.pencolor("green")pen.pensize(2)ys = [-80, -40, 0, 40, 80]for y in ys:pen.penup()pen.goto(-350, y)pen.pendown()pen.goto(0, y)# 折射发散pen.goto(350, y - 0.3 * y)# ========== 文字标注 ==========
def mark_text():pen.pencolor("black")pen.penup()pen.goto(-280, 120)pen.write("凸透镜汇聚光路", font=("宋体", 14))pen.goto(-280, -180)pen.write("凹透镜发散光路", font=("宋体", 14))# ========== 主程序运行 ==========
if __name__ == "__main__":draw_axis()# 上方凸透镜draw_convex_lens()convex_light()# 下移画笔，画下方凹透镜pen.penup()pen.goto(0, -300)draw_concave_lens()concave_light()mark_text()turtle.done()

 2025010147刘芝怡 倒计时

import time
import os# 清屏函数
def clear_screen():os.system("cls" if os.name == "nt" else "clear")# 用ASCII字符模拟数码管数字（0-9）
digit_segments = {'0': [" ██████ ","██    ██","██    ██","██    ██"," ██████ "],'1': ["    ██  ","   ███  ","    ██  ","    ██  ","  ██████"],'2': [" ██████ ","     ██ "," ██████ "," ██     "," ██████ "],'3': [" ██████ ","     ██ "," ██████ ","     ██ "," ██████ "],'4': ["██    ██","██    ██"," ██████ ","     ██ ","     ██ "],'5': [" ██████ "," ██     "," ██████ ","     ██ "," ██████ "],'6': [" ██████ "," ██     "," ██████ "," ██    ██"," ██████ "],'7': [" ██████ ","     ██ ","    ██  ","   ██   ","  ██    "],'8': [" ██████ ","██    ██"," ██████ ","██    ██"," ██████ "],'9': [" ██████ ","██    ██"," ██████ ","     ██ "," ██████ "]
}# 把时间字符串转成数码管样式
def format_time_display(time_str):# 把每个数字/符号按行拼接lines = ["", "", "", "", ""]for char in time_str:if char == ':':# 中间的冒号segment = ["   ", " ◆ ", "   ", " ◆ ", "   "]else:segment = digit_segments[char]for i in range(5):lines[i] += segment[i] + "  "return linesdef digital_timer(minutes=5, seconds=0):total_seconds = minutes * 60 + secondswhile total_seconds >= 0:clear_screen()# 格式化时间为 MM:SSmins = total_seconds // 60secs = total_seconds % 60time_str = f"{mins:02d}:{secs:02d}"# 打印标题print("          T I M E R          ")print()# 打印数码管样式的时间display_lines = format_time_display(time_str)for line in display_lines:print("        " + line)print()print("          BEEP READY         ")time.sleep(1)total_seconds -= 1clear_screen()print("          T I M E R          ")print()print("        ██████ ██████  ")print("        ██  ██ ██  ██  ")print("        ██████ ██████  ")print("        ██     ██      ")print("        ██     ██      ")print()print("          TIME'S UP!         ")# 设置倒计时
digital_timer(5, 0)

 

 

2025010148  岳嘉瑞 马鞍面

 

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D# 1. 生成 x, y 网格数据
x = np.linspace(-2, 2, 100)  # x 范围：-2 到 2
y = np.linspace(-2, 2, 100)  # y 范围：-2 到 2
X, Y = np.meshgrid(x, y)     # 生成二维网格# 2. 马鞍面方程：z = x² - y²
Z = X**2 - Y**2# 3. 创建3D画布
fig = plt.figure(figsize=(8, 6))
ax = fig.add_subplot(111, projection='3d')# 4. 绘制曲面
ax.plot_surface(X, Y, Z)# 5. 显示图像
plt.show()

 2025010149马相淼

# 定义字符串
name = "马相淼"# 截取左侧前两个字符
res = name[0:2]print(res)

　　

 

2025010150唐景泽

class Vector:
    
    def __init__(self, data):
        self.vec = list(data)

    
    def __add__(self, other):
        if len(self.vec) != len(other.vec):
            raise ValueError("两个向量维度必须相同")
        res = [a + b for a, b in zip(self.vec, other.vec)]
        return Vector(res)

    
    def __sub__(self, other):
        if len(self.vec) != len(other.vec):
            raise ValueError("两个向量维度必须相同")
        res = [a - b for a, b in zip(self.vec, other.vec)]
        return Vector(res)

   
    def dot(self, other):
        if len(self.vec) != len(other.vec):
            raise ValueError("两个向量维度必须相同")
        return sum(a * b for a, b in zip(self.vec, other.vec))

    
    def cross(self, other):
        if len(self.vec) != 3 or len(other.vec) != 3:
            raise ValueError("叉乘仅支持三维向量")
        x1, y1, z1 = self.vec
        x2, y2, z2 = other.vec
        x = y1 * z2 - z1 * y2
        y = z1 * x2 - x1 * z2
        z = x1 * y2 - y1 * x2
        return Vector([x, y, z])

    
    def __str__(self):
        return str(self.vec)



if __name__ == "__main__":
    v1 = Vector([1, 2, 3])
    v2 = Vector([4, 5, 6])

    print("向量 v1 =", v1)
    print("向量 v2 =", v2)

    # 加法
    v_add = v1 + v2
    print("v1 + v2 =", v_add)

    # 减法
    v_sub = v1 - v2
    print("v1 - v2 =", v_sub)

    # 点乘
    v_dot = v1.dot(v2)
    print("v1 · v2 (点乘) =", v_dot)

    # 叉乘
    v_cross = v1.cross(v2)
    print("v1 × v2 (叉乘) =", v_cross)

 

 2025010151侯益波

import requests
import pandas as pd
import mplfinance as mpf
import matplotlib.pyplot as plt
import time# ---------------------- 配置 ----------------------
STOCKS = {"贵州茅台": "sh600519","宁德时代": "sz300750","中国平安": "sh601318"
}
DAYS = 15  # 近半个月
# ---------------------------------------------------def get_k_data(code, days=15):"""新浪财经接口获取 K 线，自带重试、延时"""url = "https://quotes.sina.com/stock/api/json.php"params = {"symbol": code,"start": 0,"count": days,"type": "daily"}for i in range(3):  # 最多重试3次try:resp = requests.get(url, params=params, timeout=10)data = resp.json()df = pd.DataFrame(data, columns=["date", "open", "high", "low", "close", "volume", "turnover"])df["date"] = pd.to_datetime(df["date"])df = df.set_index("date")df = df.astype({"open": float,"high": float,"low": float,"close": float,"volume": float})return dfexcept Exception as e:print(f"重试 {i+1} 次失败：{e}")time.sleep(2)return None# 爬取
stock_dfs = {}
for name, code in STOCKS.items():print(f"正在爬取：{name}")df = get_k_data(code, DAYS)if df is not None:stock_dfs[name] = dfprint(f"✅ {name} 成功")time.sleep(1)  # 防封# 绘图
if stock_dfs:fig, axes = plt.subplots(3, 1, figsize=(14, 12), sharex=True)fig.suptitle("三支股票近半个月K线对比图", fontsize=18, fontweight="bold")colors = ["red", "blue", "green"]for i, (name, df) in enumerate(stock_dfs.items()):ax = axes[i]mpf.plot(df,type="candle",ax=ax,volume=False,style="yahoo",colorup="r",colordown="g",warn_too_much_data=1000)ax.set_title(name, fontsize=14, color=colors[i])ax.grid(alpha=0.3)plt.tight_layout()plt.subplots_adjust(top=0.93)plt.show()
else:print("所有股票均爬取失败，可能是网络问题或IP被临时限制，稍后再试。")

 

　　

 

 

 

2025010152刘金惺

import os
from PIL import Image# 你要转换的文件夹路径（自己改这里）
folder_path = "./"  # ./ 表示当前文件夹，也可以写成 "C:/图片/测试"# 遍历文件夹里所有文件
for filename in os.listdir(folder_path):# 只处理 .jpg 和 .jpeg 文件if filename.lower().endswith((".jpg", ".jpeg")):# 拼接完整路径jpg_path = os.path.join(folder_path, filename)# 生成新的 .png 文件名png_filename = os.path.splitext(filename)[0] + ".png"png_path = os.path.join(folder_path, png_filename)# 打开并保存为 PNG
        with Image.open(jpg_path) as img:img.save(png_path, "PNG")print("✅ 所有 .jpg 已转换为 .png！")

 

 

 

 

2025010153 范鹏展

光学实验

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation# 物理参数
wavelength = 589e-9  # 光波长 589nm (钠黄光)
d = 1.0e-3  # 双缝间距 (m)
D = 1.0  # 双缝到光屏距离 (m)
x = np.linspace(-0.02, 0.02, 2000)  # 光屏坐标范围# 创建画布
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 4))
line, = ax1.plot(x, np.zeros_like(x), "r")
im = ax2.imshow(np.zeros((200, len(x))), cmap="gray", aspect="auto", extent=[x.min(), x.max(), 0, 1])ax1.set_ylim(0, 4.2)
ax1.set_title("双缝干涉 光强动态变化")
ax1.set_ylabel("相对光强")
ax1.grid(alpha=0.3)ax2.set_title("动态干涉条纹")
ax2.set_xlabel("位置 x (m)")
ax2.set_yticks([])# 动画更新函数
def update(frame):# 模拟波长缓慢变化，观察条纹疏密改变lam = wavelength + frame * 10e-12phase = np.pi * d * x / (lam * D)inten = 4 * (np.cos(phase)) ** 2line.set_ydata(inten)im.set_data(np.tile(inten, (200, 1)))return line, im# 生成动画
ani = FuncAnimation(fig, update, frames=80, interval=80, blit=True
)plt.tight_layout()
plt.show()

 

 2025010154洪关瑞 

# 用来存放每个人的加班总次数
work = {}print("===== 签到加班录入系统 =====")
print("下班时间大于等于18点算加班\n")while True:name = input("请输入姓名（输入end结束）：")if name == "end":breaktime = int(input("输入下班时间（只输小时）："))# 判断是否加班if time >= 18:# 加班次数+1if name in work:work[name] = work[name] + 1else:work[name] = 1# 输出统计结果
print("\n======== 加班次数统计 ========")
for n, c in work.items():print(f"{n} 总共加班：{c} 次")

 

 2025010155王状

import cv2
import numpy as np
import matplotlib.pyplot as plt# ================== 1. 读取图片并转为灰度图 ==================
# 把这里换成你的图片路径（支持 jpg、png、jpeg）
img = cv2.imread(r"C:\Users\27019\Desktop/test.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  # 转为灰度图# ================== 2. 分成 8 个灰度等级（0~255） ==================
# 8级：0, 32, 64, 96, 128, 160, 192, 224
levels = 8
step = 256 // levels
gray_8level = (gray // step) * step  # 量化成8级灰度

# 统计每个灰度等级的像素数量
counts = [np.sum(gray_8level == val) for val in range(0, 256, step)]# ================== 3. 绘制 8 列灰度柱状图 ==================
plt.rcParams["font.sans-serif"] = ["SimHei"]  # 显示中文
plt.figure(figsize=(10, 5))x_labels = [f"等级{i}\n({i*32})" for i in range(8)]
plt.bar(x_labels, counts, color="gray", width=0.6)plt.title("图片8级灰度统计图（0~255）", fontsize=14)
plt.xlabel("灰度等级")
plt.ylabel("像素数量")
plt.grid(axis="y", linestyle="--", alpha=0.7)plt.show()

 

 

 

闫宸熙2025010157
import cv2
import time
from datetime import datetimedef campus_check_in_camera():"""
    校园打卡拍照程序功能：打开摄像头 → 实时显示时间 → 按 s 键拍照保存 → 按 q 键退出"""# 打开默认摄像头（0 是电脑自带摄像头，外接摄像头可能是 1）cap = cv2.VideoCapture(0)# 检查摄像头是否成功打开if not cap.isOpened():print("错误：无法打开摄像头！")returnprint("=== 校园打卡拍照工具 ===")print("按 s 键：拍照并保存")print("按 q 键：退出程序")print("="*30)while True:# 读取一帧画面ret, frame = cap.read()if not ret:print("读取画面失败")break# ========== 1. 获取当前系统时间 ==========now = datetime.now()time_str = now.strftime("%Y-%m-%d %H:%M:%S")  # 显示格式file_time_str = now.strftime("%Y%m%d_%H%M%S") # 文件名格式# ========== 2. 在画面上叠加时间 ==========# 字体、位置、颜色、大小font = cv2.FONT_HERSHEY_SIMPLEXcv2.putText(frame, time_str, (10, 50), font, 1.2,(0, 255, 255), 3, cv2.LINE_AA)  # 黄色字体# 显示画面窗口cv2.imshow('校园打卡拍照 - 按s保存，q退出', frame)# 键盘监听key = cv2.waitKey(1) & 0xFF# 按 s 键：拍照保存if key == ord('s'):# 文件名：打卡_年月日_时分秒.jpgfilename = f"打卡_{file_time_str}.jpg"cv2.imwrite(filename, frame)print(f"✅ 打卡成功！已保存：{filename}")# 按 q 键：退出if key == ord('q'):print("👋 程序已退出")break# 释放资源cap.release()cv2.destroyAllWindows()# 启动打卡程序
if __name__ == "__main__":campus_check_in_camera()

 

 

 

2025010158陈文洁

运费计算函数 重和长费用

def calculate_shipping_fee(weight, length): """计算运费：按重量和长度双重计费 :param weight: 包裹重量（kg）:param length: 包裹最长边长度（cm）:return: 总运费（元）"""# 1. 按重量计费if weight <= 1:weight_fee = 10else:weight_fee = 10 + (weight - 1) * 5 
# 2. 按长度计费（超过100cm加收）if length > 100:extra_length = length - 100 # 每超10cm加3元，不足10cm按10cm算length_fee = (extra_length // 10 + 1) * 3else:length_fee = 0 
# 3. 总运费total_fee = weight_fee + length_fee return total_fee# 测试if __name__ == "__main__":print("=== 运费计算器 ===")w = float(input("请输入包裹重量(kg)："))l = float(input("请输入包裹最长边长度(cm)："))fee = calculate_shipping_fee(w, l)print(f"包裹重量：{w}kg，长度：{l}cm") 
print(f"应支付运费：{fee}元")

2025010159成哲煜
def calc_3x3_window_sum(matrix):"""遍历4×4矩阵所有3×3窗口，计算每个9格窗口的总和:param matrix: 4行4列二维列表（16格）:return: 所有窗口坐标 + 对应9格总和"""result = []# 4×4矩阵，3×3窗口左上角行、列只能取 0、1for row in range(2):for col in range(2):total = 0# 遍历当前3×3窗口内9个格子for i in range(3):for j in range(3):val = matrix[row + i][col + j]total += valresult.append({"窗口左上角坐标": (row, col),"窗口9格总和": total})return result# 测试：4×4 16格示例数据
if __name__ == "__main__":# 4行4列（16格）grid_16 = [[1, 2, 3, 4],[5, 6, 7, 8],[9, 10, 11, 12],[13, 14, 15, 16]]res = calc_3x3_window_sum(grid_16)for item in res:print(item)

 

 

2025010160韩俊杰
将八个文件分配给40名学生

EXP_SOURCE_DIR = r"C:\Users\JioaeJ\Desktop\8份原始实验"
import os
import shutil# ===================== 路径配置 =====================
EXP_SOURCE_DIR = r"C:\Users\JioaeJ\Desktop\8份原始实验"
OUTPUT_BASE_DIR = r"C:\Users\JioaeJ\Desktop\学生实验分发结果"EXP_LIST = ["实验1-基础操作","实验2-数据处理","实验3-排序算法","实验4-批量复制","实验5-文件管理","实验6-自动汇总","实验7-学号匹配","实验8-最终提交"
]
# ===================================================def copy_oli_experiments():print("🔍 正在校验8份实验文件...")os.makedirs(OUTPUT_BASE_DIR, exist_ok=True)# 容错处理：找不到源文件夹也不崩溃if not os.path.exists(EXP_SOURCE_DIR):print(f"⚠️  提示：源文件夹不存在，仅演示分发流程")print(f"请之后把8份实验放入：{EXP_SOURCE_DIR}")else:exp_count = len([f for f in os.listdir(EXP_SOURCE_DIR) if os.path.isfile(os.path.join(EXP_SOURCE_DIR, f))])print(f"✅ 已找到 {exp_count} 份实验文件")def generate_student_list():students = []for num in range(1, 41):students.append({"学号": 2026000 + num, "姓名": f"学生{num}"})students.sort(key=lambda x: x["学号"])print(f"\n✅ 已生成并排序 {len(students)} 名学生\n")return studentsdef distribute_files(stu_list):print("===== 开始逐人分发8份实验 =====")for stu in stu_list:stu_id, stu_name = stu["学号"], stu["姓名"]stu_root = os.path.join(OUTPUT_BASE_DIR, f"{stu_id}_{stu_name}")os.makedirs(stu_root, exist_ok=True)# 为每个学生创建8个独立实验文件夹for exp_name in EXP_LIST:os.makedirs(os.path.join(stu_root, exp_name), exist_ok=True)print(f"✅ {stu_id} {stu_name} 8个实验目录全部创建完成")if __name__ == "__main__":copy_oli_experiments()student_data = generate_student_list()distribute_files(student_data)print("\n🎉 全部40名学生、8次实验流程执行完毕！")

 

 

2025010161朱星月

录入学生

students = []def add_student():"""录入新增学生"""try:sid = int(input("输入学号："))name = input("输入姓名：")age = int(input("输入年龄："))students.append([sid,name,age])print("✅ 新增学生完成")except:print("❌ 输入格式错误")# 调用
add_student()
print(students)

 2025010162 刘奕桐

 成绩转换表

import pandas as pdscore_map = {"A+": 95,"A": 90,"A-": 85,"B": 80,"B-": 75
}df = pd.read_excel("实验报告成绩表（等级）.xlsx")df["对应分数"] = df["等级"].map(score_map)df.to_excel("实验成绩分数表.xlsx", index=False)print("转换完成！已生成：实验成绩分数表.xlsx")
print("\n转换后表格预览：")
print(df)

 

 2025010163 刘志杰

统计参加会议次数最多的前五名

import pandas as pd
from collections import Counter
import re  # 引入正则表达式模块，用来处理多种标点# 读取Excel文件
file_name = '工作簿2.xlsx'# header=None 表示不读取第一行作为标题
df = pd.read_excel(file_name, header=None)print(df)
all_attendees = []# 遍历 B 列（第2列，索引为1）的数据
for names in df.iloc[:, 1]:if pd.notna(names):# 使用正则表达式 split(r'[，,]')# 遇到“中文逗号”或者“英文逗号”都进行拆分attendee_list = re.split(r'[，,]', str(names))# 去除名字周围可能存在的空格（比如 " 张三" -> "张三"）cleaned_list = [name.strip() for name in attendee_list if name.strip()]all_attendees.extend(cleaned_list)# 统计每个人的出席次数
attendance_count = Counter(all_attendees)#获取出席次数最多的前5名
top_5 = attendance_count.most_common(5)# 打印结果
print("出席次数最多的前5名同学是：")
print("-" * 30)
print(f"{'排名':<5}{'姓名':<10}{'出席次数'}")
print("-" * 30)for i, (name, count) in enumerate(top_5, 1):print(f"{i:<5}{name:<12}{count}")

 2025010164 李朋祖

import jieba
from wordcloud import WordCloud
import matplotlib.pyplot as plttext = """
Python 数据分析 人工智能 机器学习 深度学习 大数据
爬虫 算法 计算机视觉 自然语言处理 编程 代码
模型 训练 数据集 可视化 效率 科技 创新
"""
words = jieba.lcut(text)
processed_text = " ".join(words)# 生成词云
wc = WordCloud(background_color='white',font_path="simhei.ttf",width=1000,height=600
)
wc.generate(processed_text)
plt.imshow(wc)
plt.axis("off")
plt.show()

 

 

 2025010165 赵子月

按文件类型，分到不同文件夹

imfilenameport os
import shutilsource_dir = r"C:\Users\HUAWEI\Desktop\待分类文件"def sort_all_files():for filename in os.listdir(source_dir):file_path = os.path.join(source_dir, filename)if os.path.isdir(file_path):continuefile_suffix = os.path.splitext(filename)[1].lower()folder_name = file_suffix.lstrip(".") if file_suffix else "无后缀"target_folder = os.path.join(source_dir, folder_name)if not os.path.exists(target_folder):os.mkdir(target_folder)target_path = os.path.join(target_folder, filename)if os.path.exists(target_path):name, suf = os.path.splitext(filename)filename = f"{name}_copy{suf}"target_path = os.path.join(target_folder, filename)shutil.move(file_path, target_path)print(f"移动: {filename}")if __name__ == "__main__":sort_all_files()print("✅ 全部文件分类完成！")

 

 

 

 

2025010166蒋子凡

import random
import os# 配置
SIZE = 8
COLOR_CHAR = ["●", "■", "▲", "◆", "★"]
grid = []
score = 0# 生成棋盘
def init_board():board = []for y in range(SIZE):row = []for x in range(SIZE):row.append(random.randint(0, 4))board.append(row)# 清除开局自动三消while find_match(board):board = []for y in range(SIZE):row = [random.randint(0,4) for _ in range(SIZE)]board.append(row)return board# 打印棋盘
def show_board():os.system("cls")print(f"===== 消消乐 | 得分：{score} =====")print("  0 1 2 3 4 5 6 7")for i, line in enumerate(grid):print(i, end=" ")for num in line:print(COLOR_CHAR[num], end=" ")print()print("输入格式：x1 y1 x2 y2 交换两个相邻方块")print("输入q退出游戏")# 判断两点相邻
def near(p1, p2):x1,y1 = p1x2,y2 = p2dx = abs(x1-x2)dy = abs(y1-y2)return (dx == 1 and dy == 0) or (dx == 0 and dy == 1)# 交换格子
def swap(board, p1, p2):x1,y1 = p1x2,y2 = p2board[y1][x1], board[y2][x2] = board[y2][x2], board[y1][x1]# 查找所有消除坐标
def find_match(board):match = set()# 横向for y in range(SIZE):x = 0while x < SIZE - 2:c = board[y][x]if board[y][x+1]==c and board[y][x+2]==c:match.add((x,y))match.add((x+1,y))match.add((x+2,y))step = 3while x+step < SIZE and board[y][x+step]==c:match.add((x+step,y))step +=1x +=1# 纵向for x in range(SIZE):y = 0while y < SIZE - 2:c = board[y][x]if board[y+1][x]==c and board[y+2][x]==c:match.add((x,y))match.add((x,y+1))match.add((x,y+2))step =3while y+step < SIZE and board[y+step][x]==c:match.add((x,y+step))step +=1y +=1return list(match)# 消除+下落+补新方块
def eliminate(board):global scorematch_list = find_match(board)if not match_list:return Falsescore += len(match_list)*10# 标记为空for x,y in match_list:board[y][x] = -1# 下落填充for x in range(SIZE):stack = []for y in range(SIZE-1, -1, -1):if board[y][x] != -1:stack.append(board[y][x])# 从下往上填for y in range(SIZE-1, -1, -1):if stack:board[y][x] = stack.pop(0)else:board[y][x] = random.randint(0,4)return True# 循环消除连锁
def full_clear(board):while eliminate(board):pass# 主游戏逻辑
def game_loop():global gridgrid = init_board()while True:show_board()cmd = input("请输入指令：").strip()if cmd.lower() == "q":print("游戏结束，最终得分：", score)breaktry:x1,y1,x2,y2 = map(int, cmd.split())p1 = (x1,y1)p2 = (x2,y2)if not near(p1,p2):input("只能交换相邻方块！按回车继续")continue# 交换测试swap(grid, p1, p2)if not find_match(grid):swap(grid, p1, p2)input("交换后无法消除，自动复原，回车继续")else:full_clear(grid)except:input("输入错误！格式示例：0 0 0 1 ，回车继续")if __name__ == "__main__":game_loop()

　　

 

 2025010167杨书宇

停车场AI识别

import cv2
import hyperlpr3 as lpr3
import tkinter as tk
from tkinter import messagebox
import time# 计费参数
PER_HOUR_PRICE = 4  # 每小时4元
# 车辆存储字典：{车牌号:入场时间戳}
car_data = {}
# 初始化AI车牌识别
plate_ai = lpr3.LicensePlateCatcher(detect_level=lpr3.DETECT_LEVEL_HIGH)# 入场弹窗
def enter_pop(plate_num):root = tk.Tk()root.withdraw()win = tk.Toplevel()win.title("车辆入场")win.geometry("270x150")tk.Label(win, text=f"车牌：{plate_num}\n入场登记完成", font=("黑体",12)).pack(pady=40)tk.Button(win, text="关闭", command=win.destroy).pack()# 出场计费弹窗
def exit_pop(plate_num, hour, money):root = tk.Tk()root.withdraw()win = tk.Toplevel()win.title("停车收费")win.geometry("320x190")msg = f"车牌：{plate_num}\n停车时长：{hour:.2f}小时\n应付金额：{money:.2f}元"tk.Label(win, text=msg, font=("黑体",11)).pack(pady=35)def pay_finish():del car_data[plate_num]win.destroy()tk.Button(win, text="缴费完成离场", command=pay_finish).pack()# 打开摄像头
cap = cv2.VideoCapture(0)
print("启动摄像头，识别车牌自动入场，再次识别同一车牌自动计费，按q关闭")while True:ret, img = cap.read()if not ret:break# AI识别整张画面车牌result_list = plate_ai(img)for info in result_list:plate, score, _, pos = infox1,y1,x2,y2 = pos# 画框+标注车牌cv2.rectangle(img,(x1,y1),(x2,y2),(0,255,0),2)cv2.putText(img,f"{plate} {score:.2f}",(x1,y1-8),cv2.FONT_HERSHEY_SIMPLEX,0.7,(0,0,255),2)# 停车逻辑if plate not in car_data:car_data[plate] = time.time()enter_pop(plate)else:in_time = car_data[plate]stop_hours = (time.time() - in_time)/3600fee = round(stop_hours*PER_HOUR_PRICE,2)exit_pop(plate,stop_hours,fee)cv2.imshow("AI车牌识别停车场",img)if cv2.waitKey(1) & 0xFF == ord('q'):breakcap.release()
cv2.destroyAllWindows()

　　

2025010168 袁艺伦

# import pandas as pd
#
# # 模拟榜单数据
# data = [
#     {"排名": 1, "歌曲ID": 100001, "歌名": "歌曲A", "歌手": "歌手1", "时长(秒)": 215},
#     {"排名": 2, "歌曲ID": 100002, "歌名": "歌曲B", "歌手": "歌手2/歌手3", "时长(秒)": 242},
#     {"排名": 3, "歌曲ID": 100003, "歌名": "歌曲C", "歌手": "歌手4", "时长(秒)": 198},
#     {"排名": 4, "歌曲ID": 100004, "歌名": "歌曲D", "歌手": "歌手5/歌手6", "时长(秒)": 267},
#     {"排名": 5, "歌曲ID": 100005, "歌名": "歌曲E", "歌手": "歌手7", "时长(秒)": 229}
# ]
#
# df = pd.DataFrame(data)
# # 最简洁稳定的导出写法，不用嵌套ExcelWriter
# df.to_excel("网易云热歌榜.xlsx", index=False)
# print("✅ Excel文件导出成功！")
# print(df)
import requests
import pandas as pd
import time
from concurrent.futures import ThreadPoolExecutor# 榜单配置
RANK_LIST = {"热歌榜": 3778678,"新歌榜": 3779629,"飙升榜": 19723756,"原创榜": 28840835
}
SELECT_RANK = "热歌榜"
MAX_WORKERS = 2# 完整浏览器请求头，大幅降低被网易云拦截概率
HEADERS = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36","Referer": "https://music.163.com/","Origin": "https://music.163.com","Accept-Language": "zh-CN,zh;q=0.9","Accept": "application/json, text/plain, */*","sec-ch-ua": '"Chromium";v="124", "Google Chrome";v="124", "Not-A.Brand";v="99"',"sec-ch-ua-mobile": "?0","sec-ch-ua-platform": "Windows","sec-fetch-dest": "empty","sec-fetch-mode": "cors","sec-fetch-site": "same-origin"
}def get_rank_all_songs(playlist_id):api_url = f"http://music.163.com/api/playlist/detail?id={playlist_id}"try:time.sleep(0.3)  # 轻微延时防高频风控resp = requests.get(api_url, headers=HEADERS, timeout=12)res_data = resp.json()if res_data["code"] != 200:print(f"❌ 歌单{playlist_id}请求失败，错误码：{res_data['code']}")return None# 解析榜单歌曲数据playlist_info = res_data["result"]["playlist"]song_raw_list = playlist_info["tracks"]song_result = []for rank, song in enumerate(song_raw_list, start=1):song_id = song["id"]song_name = song["name"]# 拼接多位歌手名字singer_names = "/".join([artist["name"] for artist in song["ar"]])# 毫秒转秒duration = round(song["dt"] / 1000)song_result.append({"排名": rank,"歌曲ID": song_id,"歌名": song_name,"歌手": singer_names,"时长(秒)": duration})print(f"✅ 成功抓取{len(song_result)}首榜单歌曲")return song_resultexcept Exception as e:print(f"⚠️ 爬取出现异常：{e}")return Noneif __name__ == "__main__":target_id = RANK_LIST[SELECT_RANK]song_data = get_rank_all_songs(target_id)if song_data:df = pd.DataFrame(song_data)file_name = f"网易云_{SELECT_RANK}.xlsx"df.to_excel(file_name, index=False)print(f"\n🎉 全部完成！数据已导出文件：{file_name}")else:print("\n💡 未获取到榜单数据，接口被拦截/网络异常，可多运行1~2次重试")

 2025010169闵子怡+亮度调节

import cv2
import numpy as np
import osdef imread_chinese(path):"""支持中文路径的图片读取"""with open(path, "rb") as f:data = f.read()img_array = np.asarray(bytearray(data), dtype=np.uint8)img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)return imgdef imwrite_chinese(path, img):"""支持中文路径的图片保存"""ext = os.path.splitext(path)[1]success, encoded = cv2.imencode(ext, img)if success:with open(path, "wb") as f:f.write(encoded.tobytes())return Truereturn False# ========== 你的图片路径 ==========
image_path = r"C:\Users\Admin\Desktop\闵子怡.jpg"# 读取图片
img = imread_chinese(image_path)if img is None:print("❌ 图片读取失败！请检查：")print("   1. 文件是否在桌面上")print(f"   2. 路径是否正确: {image_path}")print("   3. 文件名是否是「闵子怡.jpg」")exit()print(f"✅ 读取成功！图片尺寸: {img.shape}")brightness = 0
window_name = "亮度调节 - 拖动滑动条"def update(x):global brightnessbrightness = x - 100img_bright = np.clip(img.astype(np.int16) + brightness, 0, 255).astype(np.uint8)display = img_bright.copy()cv2.putText(display, f"亮度: {brightness:+d}", (10, 40),cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)cv2.imshow(window_name, display)cv2.namedWindow(window_name)
cv2.createTrackbar("滑动条", window_name, 100, 200, update)
update(100)print("\n【操作说明】")
print("  🖱️ 拖动滑动条 → 实时调节亮度")
print("  💾 按空格键 → 保存图片")
print("  ❌ 按 ESC键 → 退出")while True:key = cv2.waitKey(1) & 0xFFif key == 27:  # ESCbreakelif key == ord(' '):  # 空格保存img_bright = np.clip(img.astype(np.int16) + brightness, 0, 255).astype(np.uint8)save_path = r"C:\Users\Admin\Desktop\闵子怡_bright.jpg"if imwrite_chinese(save_path, img_bright):print(f"✅ 已保存: {save_path} (亮度: {brightness:+d})")else:print("❌ 保存失败")cv2.destroyAllWindows()

 

 2025010170张家祺

 蔬菜店打折计算函数

from datetime import (datetime)def vegetable_discount(produce_str, buy_str, price):produce_date = datetime.strptime(produce_str, "%Y/%m/%d")buy_date = datetime.strptime(buy_str, "%Y/%m/%d")days = (buy_date - produce_date).daysif days <= 3:discount = 1.0elif days == 4:discount = 0.9elif days == 5:discount = 0.8else:discount = 0.7final_price = price * discountreturn days, discount, final_priceprint("蔬菜店折扣计算")
produce_date = input("请输入生产日期(格式：YYYY/MM/DD)：")
buy_date = input("请输入购买日期(格式：YYYY/MM/DD)：")
original_price = float(input("请输入蔬菜原价："))days, dis, final = vegetable_discount(produce_date, buy_date, original_price)print(f"蔬菜存放天数：{days} 天")
print(f"折扣比例：{dis}")
print(f"折后价格：{final:.2f} 元")

 

 

2025010171陈宣汝
# 导入课本datetime日期模块 + 窗口工具
from datetime import date
import tkinter as tk# 计算倒计时
def dao_ji():# 读取截止日期y = int(year.get())m = int(month.get())d = int(day.get())jiezhi = date(y, m, d)xianzai = date.today()# 算相差天数tian = (jiezhi - xianzai).daysres.config(text=f"距离任务结束还有：{tian} 天")# 创建简单窗口
win = tk.Tk()
win.title("简易倒计时")# 输入框
tk.Label(win,text="截止年份：").pack()
year = tk.Entry(win)
year.pack()tk.Label(win,text="截止月份：").pack()
month = tk.Entry(win)
month.pack()tk.Label(win,text="截止日期：").pack()
day = tk.Entry(win)
day.pack()# 按钮+结果
tk.Button(win,text="点击计算",command=dao_ji).pack(pady=10)
res = tk.Label(win,text="",font=("黑体",15))
res.pack()win.mainloop()

 

 

2025010172 张景悦
字符串截取函数
# 1. 自己定义一个截取子串的函数
def my_cut(s, start, end):result = ""for i in range(start, end):result += s[i]return result
# 2. 用这个函数截取三段字符串
if __name__ == "__main__":text = "Python安康学院编程"  # 原字符串
part1 = my_cut(text, 0, 3)part2 = my_cut(text, 3, 7)part3 = my_cut(text, 7, 11)
# 3. 输出三段结果print("第一段：", part1)print("第二段：", part2)print("第三段：", part3)

 

2025010173杨云飞

一个音频随机抽取一个片段

import wave
import randomdef random_wav_segment(input_path, output_path, duration=5):with wave.open(input_path, 'rb') as in_wav:# 获取音频参数（声道数、采样宽度、帧率等）params = in_wav.getparams()frame_rate = params.framerate  # 每秒帧数total_frames = params.nframes  # 总帧数total_duration = total_frames / frame_rate  # 总时长（秒）# 检查片段时长是否合理if duration >= total_duration:print("抽取时长超过音频总时长，直接保存完整音频")with wave.open(output_path, 'wb') as out_wav:out_wav.setparams(params)out_wav.writeframes(in_wav.readframes(total_frames))return# 计算片段的起始帧数和结束帧数start_frame = random.randint(0, int((total_duration - duration) * frame_rate))end_frame = start_frame + int(duration * frame_rate)# 定位到起始帧并读取片段in_wav.setpos(start_frame)segment_frames = in_wav.readframes(end_frame - start_frame)# 保存片段with wave.open(output_path, 'wb') as out_wav:out_wav.setparams(params)out_wav.writeframes(segment_frames)print(f"已随机抽取 {duration} 秒WAV片段，保存至：{output_path}")# 示例使用（仅支持WAV格式）
if __name__ == "__main__":random_wav_segment("input.wav", "output_segment.wav", duration=3)

 

2025010174 刘研
窗口登陆查询体测成绩
from tkinter import *
from tkinter import messagebox# 体测成绩数据库 我已经帮你建好
data = {"2025001":{"name":"张三","身高体重":80,"肺活量":76,"50米":82,"长跑":75,"立定跳远":79},"2025002":{"name":"李四","身高体重":60,"肺活量":55,"50米":59,"长跑":45,"立定跳远":65},"2025003":{"name":"你的名字","身高体重":88,"肺活量":90,"50米":85,"长跑":80,"立定跳远":92}
}# 判断合格函数
def judge(score):if score >= 60:return "合格"else:return "不合格"# 查询功能
def search():id = entry_id.get()name = entry_name.get()if id not in data:messagebox.showerror("错误","该学号不存在")returnif data[id]["name"] != name:messagebox.showerror("错误","姓名与学号不匹配")return# 取出所有成绩s1 = data[id]["身高体重"]s2 = data[id]["肺活量"]s3 = data[id]["50米"]s4 = data[id]["长跑"]s5 = data[id]["立定跳远"]res = f"""
====体测成绩查询结果====
身高体重：{s1}分  {judge(s1)}
肺活量：{s2}分  {judge(s2)}
50米跑：{s3}分  {judge(s3)}
耐力长跑：{s4}分  {judge(s4)}
立定跳远：{s5}分  {judge(s5)}"""messagebox.showinfo("查询成功",res)# 搭建窗口
root = Tk()
root.title("体测成绩查询系统")
root.geometry("400x300")# 组件布置
Label(root,text="学号",font=15).place(x=50,y=60)
Label(root,text="姓名",font=15).place(x=50,y=120)entry_id = Entry(root,width=30)
entry_id.place(x=120,y=65)entry_name = Entry(root,width=30)
entry_name.place(x=120,y=125)Button(root,text="点击查询成绩",command=search,bg="#4299ff",fg="white",width=15).place(x=140,y=180)root.mainloop()

 2025010175   孙兰妮

通讯录窗口

import tkinter as tk
from tkinter import simpledialog, messageboxclass AddressBook:def __init__(self, root):self.root = rootself.root.title("通讯录")self.root.geometry("500x400")self.contacts = {"张三": "13800000000", "李四": "13912345678"}  # 示例数据# 左侧列表框self.lb = tk.Listbox(root)self.lb.pack(side=tk.LEFT, padx=10, pady=10, fill=tk.BOTH, expand=True)self.lb.bind('<<ListboxSelect>>', self.show_info)# 右侧按钮frame = tk.Frame(root)frame.pack(side=tk.RIGHT, padx=10, pady=10)for text, cmd in [("添加", self.add), ("删除", self.delete), ("修改", self.modify), ("查找", self.search)]:tk.Button(frame, text=text, command=cmd, width=10).pack(pady=5)# 底部信息栏self.info = tk.Label(root, text="", anchor="w")self.info.pack(side=tk.BOTTOM, fill=tk.X, padx=10, pady=5)self.refresh()def refresh(self):"""刷新列表和底部计数"""self.lb.delete(0, tk.END)for name in sorted(self.contacts):self.lb.insert(tk.END, name)self.info.config(text=f"共 {len(self.contacts)} 人")def show_info(self, event):"""点击联系人显示电话"""sel = self.lb.curselection()if sel:name = self.lb.get(sel[0])self.info.config(text=f"{name} : {self.contacts[name]}")def add(self):name = simpledialog.askstring("添加", "姓名")if name and name not in self.contacts:phone = simpledialog.askstring("添加", "电话")if phone:self.contacts[name] = phoneself.refresh()elif name in self.contacts:messagebox.showerror("错误", "联系人已存在")def delete(self):sel = self.lb.curselection()if sel and messagebox.askyesno("确认", "删除？"):name = self.lb.get(sel[0])del self.contacts[name]self.refresh()def modify(self):sel = self.lb.curselection()if sel:name = self.lb.get(sel[0])new_phone = simpledialog.askstring("修改", f"新电话 for {name}")if new_phone:self.contacts[name] = new_phoneself.refresh()else:messagebox.showwarning("警告", "请先选择")def search(self):name = simpledialog.askstring("查找", "姓名")if name in self.contacts:messagebox.showinfo("结果", f"{name} : {self.contacts[name]}")# 高亮for i, n in enumerate(self.lb.get(0, tk.END)):if n == name:self.lb.selection_clear(0, tk.END)self.lb.selection_set(i)self.lb.see(i)self.show_info(None)breakelif name:messagebox.showerror("未找到", "无此联系人")if __name__ == "__main__":root = tk.Tk()AddressBook(root)root.mainloop()