第一章 Python語言概述與生態體系

1.3 Python在工業界的應用場景

# 示例：使用FastAPI構建RESTful接口
from fastapi import FastAPI
from pydantic import BaseModelapp = FastAPI()class Item(BaseModel):name: strprice: float@app.post("/items/")
async def create_item(item: Item):return {"item_name": item.name, "adjusted_price": item.price*1.1}# 運行命令：uvicorn main:app --reload

1.4 Python版本選擇指南

• 性能對比測試

# 海象運算符示例（Python 3.8+）
if (n := len([1,2,3])) > 2:print(f"List length {n} is greater than 2")

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第三章 Python核心語法精解

3.2 數據結構進階操作

# 字典合并操作（Python 3.9+）
dict1 = {'a': 1, 'b': 2}
dict2 = {'b': 3, 'c': 4}
merged = dict1 | dict2  # {'a':1, 'b':3, 'c':4}# 列表推導式優化
matrix = [[1,2], [3,4], [5,6]]
flatten = [num for row in matrix for num in row]  # [1,2,3,4,5,6]

3.4 上下文管理器原理

# 自定義上下文管理器
class DatabaseConnection:def __init__(self, db_name):self.db_name = db_namedef __enter__(self):self.conn = sqlite3.connect(self.db_name)return self.conndef __exit__(self, exc_type, exc_val, exc_tb):self.conn.close()if exc_type:print(f"Error occurred: {exc_val}")# 使用示例
with DatabaseConnection("test.db") as conn:cursor = conn.cursor()cursor.execute("SELECT * FROM users")

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第六章 異常處理與調試技巧

6.2 調試器高級用法

# 使用pdb進行交互式調試
import pdbdef complex_calculation(a, b):result = 0for i in range(a):pdb.set_trace()  # 斷點設置result += (i * b) ** 2return result# 調試命令示例：
# n(ext), s(tep), c(ontinue), l(ist), p(rint)

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第十章 數據分析與可視化

10.1 Pandas數據處理實戰

import pandas as pd
import numpy as np# 創建時間序列數據
date_rng = pd.date_range(start='2023-01-01', end='2023-01-10', freq='D')
df = pd.DataFrame({'date': date_rng,'value': np.random.randn(len(date_rng)).cumsum()
})# 窗口計算
df['3_day_avg'] = df['value'].rolling(window=3).mean()# 數據透視表
pivot = pd.pivot_table(df, values='value',index=df['date'].dt.day,aggfunc=['mean', 'max'])

10.2 Matplotlib可視化進階

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3Dfig = plt.figure(figsize=(12,8))
ax = fig.add_subplot(111, projection='3d')x = np.random.standard_normal(100)
y = np.random.standard_normal(100)
z = np.sin(x**2 + y**2)ax.scatter(x, y, z, c=z, cmap='viridis')
ax.set_xlabel('X Axis')
ax.set_ylabel('Y Axis')
ax.set_zlabel('Z Value')
plt.title("3D Scatter Plot with Color Mapping")
plt