第三方库：requests 与数据处理

第 11 章 · requests 与 CSV 数据处理

本章目标：使用 requests 调用 REST API（如 https://api.example.com 教学端点）；处理超时、状态码与 JSON 响应；用标准库 csv 读写表格数据；完成 shop-demo 商品导入导出与简易报表；了解 pandas 为选修扩展。

学时建议：4～5 小时（含 1.5 小时跟练）

前置：ch10 虚拟环境与 pip；ch09 json。

11.1 安装与第一个请求

# 在 py-learn 或项目 .venv 中
pip install requests

import requests

resp = requests.get("https://api.example.com/health", timeout=5)
print(resp.status_code)
print(resp.text)

11.2 GET 与查询参数

url = "https://api.example.com/books"
params = {"page": 1, "limit": 10, "q": "python"}

resp = requests.get(url, params=params, timeout=10)
resp.raise_for_status()          # 4xx/5xx 抛 HTTPError

data = resp.json()
for item in data.get("items", []):
    print(item["title"], item.get("price"))

try:
    resp = requests.get(url, timeout=5)
    resp.raise_for_status()
except requests.Timeout:
    print("请求超时")
except requests.HTTPError as e:
    print("HTTP 错误", e.response.status_code)
except requests.RequestException as e:
    print("网络异常", e)

11.3 POST 与请求头

payload = {
    "user": "user-demo",
    "sku": "BK-001",
    "qty": 2,
}

headers = {
    "Content-Type": "application/json",
    "Accept": "application/json",
    # "Authorization": "Bearer <token>",  # 真实项目从环境变量读取
}

resp = requests.post(
    "https://api.example.com/cart/items",
    json=payload,
    headers=headers,
    timeout=10,
)

切勿在教程代码中硬编码真实密钥；练习可用虚构 token 或本地 mock 服务。

11.4 Session 与连接复用

session = requests.Session()
session.headers.update({"User-Agent": "shop-demo/1.0"})

r1 = session.get("https://api.example.com/books")
r2 = session.get("https://api.example.com/categories")

多次请求同一主机时 Session 更高效，并可保持 Cookie。

11.5 本地 Mock（无公网时）

若无法访问外网，可用本地 JSON 文件模拟：

from pathlib import Path
import json

def mock_get_books():
    path = Path("fixtures/books.json")
    return json.loads(path.read_text(encoding="utf-8"))

fixtures/books.json：

{
  "items": [
    {"sku": "BK-001", "title": "Python 基础", "price": 59.9},
    {"sku": "BK-002", "title": "Web 开发", "price": 79.0}
  ]
}

11.6 csv 模块读写

写入

import csv
from pathlib import Path

rows = [
    ["sku", "title", "price", "stock"],
    ["BK-001", "Python 基础", "59.9", "10"],
    ["BK-002", "Web 开发", "79.0", "5"],
]

path = Path("products.csv")
with open(path, "w", encoding="utf-8", newline="") as f:
    writer = csv.writer(f)
    writer.writerows(rows)