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Web Scraping & Bots · 课时

与 API 集成

将机器人连接到外部 API，以丰富数据、触发操作或与其他服务交互。

与 API 集成 是 CoddyKit 上的免费 Web Scraping & Bots 课时。 这是第 3 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Web Scraping & Bots 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Web Scraping & Bots 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

Bots & APIs: A Powerful Combo

You've learned to automate browser interactions and scrape web pages. But what if you need structured data, or to trigger actions on another service?

This is where APIs (Application Programming Interfaces) come in! APIs provide a direct, organized way for your bot to communicate with other software systems.

APIs vs. Web Scraping

While web scraping involves parsing HTML from web pages, APIs offer data in a more machine-readable format, typically JSON or XML.

  • Web Scraping: Best for public data on websites without APIs, or complex UI interactions.
  • API Integration: Ideal for structured data, performing actions (like creating a post), and when an API is explicitly provided.

Often, the most powerful bots combine both!

API Basics: Endpoints & Methods

APIs are accessed via endpoints, which are specific URLs. You interact with them using standard HTTP methods:

  • GET: To retrieve data (like reading a post).
  • POST: To send new data (like creating a post).
  • PUT/PATCH: To update existing data.
  • DELETE: To remove data.

For bots, GET and POST are the most common.

Making a Simple GET Request

Let's use Python's requests library to fetch some data from a public test API. We'll use jsonplaceholder.typicode.com which provides fake data.

Try running this example:

import requests

def main():
    api_url = "https://jsonplaceholder.typicode.com/todos/1"
    response = requests.get(api_url)
    
    print(f"Status Code: {response.status_code}")
    print(response.text)

if __name__ == "__main__":
    main()

Parsing JSON Responses

APIs commonly return data in JSON (JavaScript Object Notation) format. It's a lightweight, human-readable data interchange format.

The requests library can automatically parse JSON for you, turning it into a Python dictionary. Let's extract specific fields from our previous example.

import requests
import json

def main():
    api_url = "https://jsonplaceholder.typicode.com/todos/1"
    response = requests.get(api_url)
    
    if response.status_code == 200:
        todo_item = response.json() # Parse JSON into a Python dict
        print(f"User ID: {todo_item['userId']}")
        print(f"Title: {todo_item['title']}")
        print(f"Completed: {todo_item['completed']}")
    else:
        print("Failed to fetch data.")

if __name__ == "__main__":
    main()

API Authentication Concepts

Many APIs require authentication to ensure only authorized users or bots can access their data or services. Common methods include:

  • API Keys: A unique string sent with each request.
  • Tokens: Often generated after a login, valid for a certain period.
  • OAuth: A more complex standard for secure delegation of access.

For simple bots, API keys are often used.

Using API Keys in Requests

API keys are typically passed as a query parameter in the URL or as an HTTP header. requests makes this easy with the params argument.

This example shows how you would pass a key (using a fictional API for demonstration).

import requests

def main():
    # This is a placeholder for demonstration.
    # In a real scenario, use a valid API key.
    api_key = "YOUR_DUMMY_API_KEY_HERE"
    search_term = "bot automation"
    
    # Fictional API endpoint requiring a key
    api_url = "https://api.example.com/search"
    
    params = {
        "q": search_term,
        "apiKey": api_key # API key as a query parameter
    }
    
    response = requests.get(api_url, params=params)
    print(f"Request URL: {response.url}")
    print(f"Status Code: {response.status_code}")
    # In a real app, you'd process response.json()

if __name__ == "__main__":
    main()

Sending Data with POST Requests

If your bot needs to submit data, like creating a new entry or updating information, you'll use a POST request. The data payload is typically sent in the request body.

requests handles sending JSON data in the body automatically using the json parameter.

import requests
import json

def main():
    api_url = "https://jsonplaceholder.typicode.com/posts"
    
    new_post_data = {
        "title": "Bot-Generated Post",
        "body": "This is content created by our bot!",
        "userId": 1
    }
    
    # The 'json' parameter automatically sets Content-Type
    response = requests.post(api_url, json=new_post_data)
    
    print(f"Status Code: {response.status_code}")
    if response.status_code == 201: # 201 Created is common for successful POST
        print("Post created successfully!")
        print(response.json()) # API returns the created item
    else:
        print("Failed to create post.")
        print(response.text)

if __name__ == "__main__":
    main()

Robust Error Handling for APIs

API calls can fail due to network issues, incorrect requests, or server errors. Your bot should handle these gracefully.

  • Check response.status_code (e.g., 200 for OK, 404 for Not Found, 500 for Server Error).
  • Use response.raise_for_status() to automatically raise an HTTPError for bad responses.
  • Wrap calls in try-except blocks to catch network-related errors.
import requests

def main():
    # Intentional bad URL to show error handling
    api_url = "https://jsonplaceholder.typicode.com/nonexistent_endpoint"
    
    try:
        response = requests.get(api_url, timeout=5) # Set a timeout
        response.raise_for_status() # Raises HTTPError for 4xx/5xx responses
        print(f"Status Code: {response.status_code}")
        print("Successfully fetched data.")
    except requests.exceptions.HTTPError as err:
        print(f"HTTP Error occurred: {err}")
        print(f"Status Code: {response.status_code}")
    except requests.exceptions.ConnectionError as err:
        print(f"Connection Error occurred: {err}")
    except requests.exceptions.Timeout as err:
        print(f"Timeout Error occurred: {err}")
    except requests.exceptions.RequestException as err:
        print(f"An unexpected error occurred: {err}")

if __name__ == "__main__":
    main()

Quick Check: API Interaction

Which of the following are common ways bots interact with APIs?

Recap & Next Steps

Great job! You've learned how to integrate your bots with APIs:

  • APIs provide structured data and allow bots to trigger actions.
  • You use GET for fetching and POST for sending data.
  • Python's requests library simplifies API calls.
  • JSON is the common data format, easily parsed into Python dictionaries.
  • Authentication (like API keys) is crucial for many APIs.
  • Robust error handling is key for reliable bot operations.

Combining web scraping with API integration allows your bots to perform more complex and powerful workflows!

常见问题解答

「与 API 集成」课时是免费的吗？

是的 — 「与 API 集成」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Web Scraping & Bots 课程的其余内容，请升级到 CoddyKit PRO。 Web Scraping & Bots 课程共包含 4 节课。

「与 API 集成」这节课中我会学到什么？

将机器人连接到外部 API，以丰富数据、触发操作或与其他服务交互。 你通过在浏览器中直接运行的动手代码来练习 Web Scraping & Bots，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Web Scraping & Bots 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Web Scraping & Bots 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 3 节课，共 4 节。

「与 API 集成」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Web Scraping & Bots 课中编写并运行代码吗？

能。每节 Web Scraping & Bots 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

  1. 处理用户身份验证
  2. 模拟复杂用户流程
  3. 与 API 集成
  4. 管理会话与 Cookie
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