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  • How to convert cURL commands to Python requests?

    Posted by Gerri Hiltraud on 12/10/2024 at 10:58 am

    Converting cURL commands to Python requests allows you to automate HTTP operations and integrate them into Python scripts. cURL is often used to test API endpoints or fetch data from a server, while Python’s requests library offers a flexible way to handle these tasks programmatically. The key is to translate cURL options (e.g., -X for method, -H for headers, -d for data) into their Python requests equivalents. You can use online tools like curlconverter.com or manually write the conversion.Here’s an example of converting a cURL command into Python:

    curl -X POST https://api.example.com/data \
    -H "Authorization: Bearer your_api_key" \
    -H "Content-Type: application/json" \
    -d '{"key": "value"}'
    

    Equivalent Python Code:

    import requests
    
    url = "https://api.example.com/data"
    headers = {
        "Authorization": "Bearer your_api_key",
        "Content-Type": "application/json"
    }
    data = {
        "key": "value"
    }
    response = requests.post(url, headers=headers, json=data)
    if response.status_code == 200:
        print("Success:", response.json())
    else:
        print("Error:", response.status_code, response.text)
    

    Python’s requests library provides a clean interface for HTTP methods like GET, POST, PUT, and DELETE. How do you handle complex cURL commands with multiple headers or authentication in Python?

    Audrey Tareq replied 1 week, 3 days ago 6 Members · 5 Replies
  • 5 Replies
  • Benno Livia

    Member
    12/10/2024 at 11:36 am

    To handle blocks, I implement proxy rotation and randomized delays between requests, reducing the likelihood of detection and blocking.

  • Rilla Anahita

    Member
    12/11/2024 at 8:04 am

    For dynamic content, I use Puppeteer’s waitForSelector method to ensure all results are loaded before extracting data. This avoids missing partial information.

  • Adil Linza

    Member
    12/11/2024 at 10:22 am

    Using a database like MySQL allows me to store and analyze price data over time, enabling detailed comparisons across different e-commerce platforms.

  • Uduak Pompeia

    Member
    12/12/2024 at 6:23 am

    When debugging complex requests, I log the entire request and response, including headers and payloads, to identify discrepancies between cURL and Python behavior.

  • Audrey Tareq

    Member
    12/12/2024 at 6:48 am

    For APIs requiring session management, I use requests.Session() to maintain cookies and headers across multiple requests efficiently.

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