Web Scraping & Bots · Lektion

URLs mit Requests verarbeiten

Lernen Sie, mit der Python-Bibliothek Requests GET- und POST-Anfragen zu senden, um Inhalte von Webseiten abzurufen.

URLs mit Requests verarbeiten ist eine kostenlose Web Scraping & Bots-Lektion auf CoddyKit. Dies ist Lektion 2 von 4. Du kannst die komplette Lektion unten kostenlos lesen – dann übst du sie direkt im Browser mit einem integrierten Code-Editor und einem KI-Tutor rund um die Uhr. Sie ist Teil des Web Scraping & Bots-Lernpfads, und dein Fortschritt wird über Web und CoddyKit-App synchronisiert. Der Web Scraping & Bots-Kurs umfasst insgesamt 4 Lektionen.

Teile dieser Lektion wurden noch nicht übersetzt und werden auf Englisch angezeigt.

Meet Python's Requests Library

Welcome to using Python for web interactions! In this lesson, we'll dive into the Requests library, your go-to tool for making HTTP requests.

Requests simplifies how your Python program talks to websites, acting like a web browser but without a graphical interface. It's essential for fetching web page content before you can extract data.

Setting Up Requests

Before we can use Requests, we need to install it. If you haven't already, open your terminal or command prompt and run the following command:

pip install requests

This command downloads and installs the library, making it available for your Python scripts. It's a one-time setup for your environment.

Your First GET Request

The most common type of request is GET. It's used to retrieve data from a specified resource, much like when your browser loads a webpage.

Let's make a simple GET request to fetch content from example.com. We'll then print the HTTP status code and a snippet of the page's text.

import requests

# Define the URL you want to fetch
url = "http://www.example.com"

# Send a GET request
response = requests.get(url)

# Print the status code and first 200 characters of the content
print(f"Status Code: {response.status_code}")
print(f"Content snippet:\n{response.text[:200]}")

Understanding the Response Object

When you make a request, the requests.get() function returns a Response object. This object holds all the information about the server's reply.

response.status_code: An integer indicating the HTTP status (e.g., 200 for OK, 404 for Not Found).
response.text: The content of the response, usually HTML, as a string.
response.url: The actual URL of the response.

Basic Error Checking

It's good practice to check if your request was successful. The response.raise_for_status() method is a simple way to do this.

If the HTTP status code indicates an error (e.g., 4xx or 5xx), this method will raise an HTTPError. Otherwise, it does nothing.

import requests

url = "http://www.example.com/nonexistent-page"

try:
    response = requests.get(url)
    response.raise_for_status() # Raises an HTTPError for bad responses (4xx or 5xx)
    print("Request successful!")
except requests.exceptions.HTTPError as err:
    print(f"HTTP Error occurred: {err}")
except requests.exceptions.ConnectionError as err:
    print(f"Connection Error occurred: {err}")
except Exception as err:
    print(f"An unexpected error occurred: {err}")

Adding Request Headers

Sometimes, websites check for specific HTTP headers to determine if a request is coming from a legitimate browser or a bot.

You can customize your request by passing a dictionary of headers. A common header to set is User-Agent to mimic a browser.

import requests

url = "http://httpbin.org/get" # A service that echoes your request

headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
    "Accept-Language": "en-US,en;q=0.9"
}

response = requests.get(url, headers=headers)

print("Your request headers sent to httpbin.org:")
# httpbin.org returns JSON, so we can use .json()
print(response.json()['headers']['User-Agent'])
print(response.json()['headers']['Accept-Language'])

Understanding POST Requests

While GET requests are for retrieving data, POST requests are used to send data to a server, typically for creating or updating a resource.

Think of submitting a form on a website – you're usually sending data via a POST request. The data is included in the request body, not in the URL.

Sending Data with POST

To send a POST request with data, you use requests.post() and pass your data as a dictionary to the data parameter.

Let's try sending some simple form data to httpbin.org/post, which will echo back the data it received.

import requests

url = "http://httpbin.org/post"

# Data to send in the POST request
payload = {
    "name": "Coddy",
    "city": "Kitland",
    "age": "5"
}

response = requests.post(url, data=payload)

print("Data received by httpbin.org:")
# The 'form' key in the JSON response contains the sent data
print(response.json()['form'])

GET vs. POST: Key Differences

It's crucial to understand when to use GET versus POST:

GET: Retrieves data, parameters are visible in the URL, requests can be bookmarked and cached. Best for non-sensitive data retrieval.
POST: Sends data to be processed, parameters are in the request body (not visible in URL), requests are not cached or bookmarked. Best for submitting forms, uploading files, or sensitive data.

Check Your Understanding

You've learned about GET and POST requests. Consider the following scenario:

You want to retrieve the current weather forecast for a specific city from a public API. Which HTTP request method is most appropriate?

Lesson Summary

Great job! You've taken a significant step in understanding how to interact with the web using Python's Requests library.

We installed the requests library.
We learned to send GET requests to fetch web content.
We explored the response object, checking status codes and content.
We briefly touched on handling request errors.
We customized requests with headers.
We learned to send data using POST requests.
Finally, we distinguished between GET and POST for different web interactions.

Next, we'll learn how to parse the HTML content you've fetched!

Häufig gestellte Fragen

Ist die Lektion „URLs mit Requests verarbeiten“ kostenlos?

Ja — der vollständige Text von „URLs mit Requests verarbeiten“ ist hier im Web kostenlos zu lesen. Um sie interaktiv zu üben (integrierter Code-Editor und 24/7 KI-Tutor) und den Rest des Web Scraping & Bots-Kurses freizuschalten, upgrade auf CoddyKit PRO. Der Web Scraping & Bots-Kurs umfasst insgesamt 4 Lektionen.

Was lerne ich in „URLs mit Requests verarbeiten“?

Lernen Sie, mit der Python-Bibliothek Requests GET- und POST-Anfragen zu senden, um Inhalte von Webseiten abzurufen. Du übst Web Scraping & Bots mit praktischem Code, den du direkt im Browser ausführst, und ein 24/7 KI-Tutor beantwortet deine Fragen während du die Lektion bearbeitest.

Brauche ich Erfahrung, um Web Scraping & Bots zu starten?

Keine Vorkenntnisse erforderlich. Web Scraping & Bots auf CoddyKit ist für Anfänger bis fortgeschrittene Lernende strukturiert, sodass du hier starten oder von Anfang an beginnen und in deinem eigenen Tempo voranschreiten kannst. Dies ist Lektion 2 von 4.

Wie lange dauert die Lektion „URLs mit Requests verarbeiten“?

Die meisten CoddyKit-Lektionen dauern etwa 5–10 Minuten. Jede ist kompakt und interaktiv, sodass du stetig Fortschritte machst und genau dort weitermachst, wo du aufgehört hast – im Web und in der App.

Kann ich in dieser Web Scraping & Bots-Lektion Code schreiben und ausführen?

Ja. Jede Web Scraping & Bots-Lektion enthält einen integrierten Code-Editor, sodass du echten Code direkt in deinem Browser schreibst und ausführst und sofort KI-Feedback erhältst — ohne lokale Einrichtung erforderlich.

Alle Lektionen in diesem Kurs

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