Python 实战项目精选（附源码）

以下是涵盖不同技术领域的5个完整项目源码，其他103个项目名称和源码获取方式见文末。所有项目按难度分级（⭐~⭐⭐⭐），适合从入门到进阶的开发者。

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1. 天气查询工具 ⭐

技术栈：API调用、JSON解析

import requests

def get_weather(city):
    API_KEY = "YOUR_API_KEY"  # 替换为openweathermap.org的API密钥
    url = f"http://api.openweathermap.org/data/2.5/weather?q={city}&appid={API_KEY}&units=metric"
    response = requests.get(url)
    data = response.json()
    if data["cod"] == 200:
        temp = data["main"]["temp"]
        desc = data["weather"][0]["description"]
        print(f"{city}天气: {desc}, 温度: {temp}℃")
    else:
        print("城市名称错误")

if __name__ == "__main__":
    get_weather(input("请输入城市名: "))

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2. 文件加密器 ⭐⭐

技术栈：对称加密、文件操作

from cryptography.fernet import Fernet

def generate_key():
    return Fernet.generate_key()

def encrypt_file(key, filename):
    fernet = Fernet(key)
    with open(filename, "rb") as file:
        data = file.read()
    encrypted = fernet.encrypt(data)
    with open(filename + ".enc", "wb") as file:
        file.write(encrypted)

def decrypt_file(key, filename):
    fernet = Fernet(key)
    with open(filename, "rb") as file:
        data = file.read()
    decrypted = fernet.decrypt(data)
    with open(filename[:-4], "wb") as file:  # 移除.enc后缀
        file.write(decrypted)

# 使用示例
key = generate_key()
encrypt_file(key, "test.txt")
decrypt_file(key, "test.txt.enc")

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3. 股票数据可视化 ⭐⭐

技术栈：Pandas、Matplotlib、yfinance

import yfinance as yf
import matplotlib.pyplot as plt

def plot_stock(ticker, start_date, end_date):
    data = yf.download(ticker, start=start_date, end=end_date)
    plt.figure(figsize=(10, 6))
    plt.plot(data['Close'], label='收盘价', color='blue')
    plt.title(f"{ticker} 股价走势")
    plt.xlabel("日期")
    plt.ylabel("价格(USD)")
    plt.legend()
    plt.grid(True)
    plt.savefig(f"{ticker}_chart.png")
    print("图表已保存")

if __name__ == "__main__":
    plot_stock("AAPL", "2023-01-01", "2023-12-31")

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4. 简易博客系统 ⭐⭐⭐

技术栈：Flask、SQLite、Jinja2

from flask import Flask, render_template, request, redirect
import sqlite3

app = Flask(__name__)

def init_db():
    conn = sqlite3.connect('blog.db')
    c = conn.cursor()
    c.execute('''CREATE TABLE IF NOT EXISTS posts
                 (id INTEGER PRIMARY KEY, title TEXT, content TEXT)''')
    conn.commit()
    conn.close()

@app.route('/')
def index():
    conn = sqlite3.connect('blog.db')
    c = conn.cursor()
    c.execute("SELECT * FROM posts")
    posts = c.fetchall()
    conn.close()
    return render_template('index.html', posts=posts)

@app.route('/add', methods=['POST'])
def add_post():
    title = request.form['title']
    content = request.form['content']
    conn = sqlite3.connect('blog.db')
    c = conn.cursor()
    c.execute("INSERT INTO posts (title, content) VALUES (?, ?)", (title, content))
    conn.commit()
    conn.close()
    return redirect('/')

if __name__ == '__main__':
    init_db()
    app.run(debug=True)

需配套templates/index.html模板文件

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5. 人脸识别门禁 ⭐⭐⭐

技术栈：OpenCV、face_recognition库

import face_recognition
import cv2
import numpy as np

def load_known_faces():
    known_encodings = []
    known_names = []
    # 加载已知人脸图片
    obama_image = face_recognition.load_image_file("obama.jpg")
    obama_encoding = face_recognition.face_encodings(obama_image)[0]
    known_encodings.append(obama_encoding)
    known_names.append("Barack Obama")
    return known_encodings, known_names

def realtime_face_check():
    known_encodings, known_names = load_known_faces()
    video_capture = cv2.VideoCapture(0)
    
    while True:
        ret, frame = video_capture.read()
        rgb_frame = frame[:, :, ::-1]
        face_locations = face_recognition.face_locations(rgb_frame)
        face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)
        
        for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
            matches = face_recognition.compare_faces(known_encodings, face_encoding)
            name = "Unknown"
            if True in matches:
                first_match_index = matches.index(True)
                name = known_names[first_match_index]
            
            cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
            cv2.putText(frame, name, (left+6, bottom-6), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255), 1)
        
        cv2.imshow('Face Recognition', frame)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    
    video_capture.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    realtime_face_check()

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108个项目完整列表

剩余项目包括：
1-10：基础应用

• 密码强度检测器
• 汇率转换器
• 文本词频统计
• 二维码生成器
• PDF合并工具

11-30：数据处理

• 电商销售分析仪表盘
• 社交媒体情感分析
• 疫情数据可视化
• 股票预测模型

31-50：Web开发

• 在线投票系统
• 电商购物车
• RESTful API服务
• 即时聊天应用

51-70：自动化

• 邮件自动回复机器人
• 网站健康监测器
• 文件自动归类系统

71-90：人工智能

• 手写数字识别
• 电影推荐系统
• 智能聊天机器人

91-108：游戏开发

• 贪吃蛇游戏
• 俄罗斯方块
• 2D平台跳跃游戏

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源码获取方式

所有108个项目的完整源码+数据集+详细文档可通过以下方式获取：

1. 访问 GitHub 仓库：
   github.com/python-projects-108
2. 在仓库搜索对应项目名称
3. 每个项目独立文件夹包含：
   • 完整.py源码文件
   • requirements.txt依赖列表
   • README.md操作指南
   • 测试数据集（如需要）

提示：运行项目前请先安装所需依赖：

pip install -r requirements.txt