Preparation before the course starts

Collecting data through web scraping and APIs requires more than a web browser. For the practical parts of this course, you will work with Jupyter Notebooks and Python scripts.

Please complete the first two items before the first class. You do not need to install Python locally before the first class.

Required before the first class

1. Check your access to JupyterLab

Open JupyterLab at jupyterlab.uvt.nl and check that you can log in. We will use this environment for the Python Bootcamp and the introductory tutorials. No local Python distribution is needed for this initial preparation.

If you prefer to work locally, you may install Python from the official Python website and use JupyterLab or Visual Studio Code. A local installation is optional for the introductory work, but it may be useful for later tutorials that require browser automation.

2. Start the Python Bootcamp

The course does not depend on any pre-work in Python. Yet, if Python is entirely new to you, you may use:

• Python for Everybody
• Kaggle Learn: Python

These resources are not required, assessed, or assumed in later course materials.

Recommended before the first class

For advanced tutorials starting in week 2, you should prepare a local Python setup with Visual Studio Code and a Chromium-based browser. Please do this in advance, even if you initially plan to work in JupyterLab.

3. Install Python

Download Python from the official Python downloads page. Do not install Anaconda, Miniconda, or Conda. On Windows, use the standard graphical installer; on macOS, use the macOS installer provided on the Python website.

Check that Python is available after installation:

• Windows Command Prompt: open Command Prompt and run py --version.
• macOS Terminal: open Terminal and run python3 --version.

4. Install Visual Studio Code

Download and install Visual Studio Code. In VS Code, install these extensions:

• Python
• Jupyter

Open the folder containing the tutorial files in VS Code. The Python and Jupyter extensions will allow VS Code to run local Python files and notebooks.

5. Install packages for later tutorials

Create a short, easy-to-find folder for the course files, open a terminal in that folder, and run the following commands. These install the packages used by the tutorials currently included in the course.

Windows Command Prompt

py -m pip install --upgrade pip
py -m pip install jupyterlab requests beautifulsoup4 pandas selenium webdriver-manager python-dotenv openai

macOS Terminal

python3 -m pip install --upgrade pip
python3 -m pip install jupyterlab requests beautifulsoup4 pandas selenium webdriver-manager python-dotenv openai

The packages above cover the tutorials currently included in the course. Some tutorials may require additional packages or credentials; their own instructions will explain this.

6. Install a Chromium-based browser

Install Google Chrome or Chromium. Google Chrome is the simplest option for the current Selenium examples, which use webdriver-manager to obtain a compatible driver. You do not normally need to download ChromeDriver separately.

To test the local setup, open a new VS Code notebook or Python file and run the following code. This test is only needed when you prepare for the advanced web-scraping tutorial:

from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from webdriver_manager.chrome import ChromeDriverManager

driver = webdriver.Chrome(service=Service(ChromeDriverManager().install()))
driver.get("https://music-to-scrape.org/")
print(driver.title)
driver.quit()

If the browser does not start, first confirm that Chrome or Chromium is installed and that VS Code is using the Python installation where you installed Selenium. Also check that your internet connection allows the driver download. The Selenium documentation provides further troubleshooting information.

7. Set up AI tooling

In this course, we integrate Large Language Models (LLMs) and agentic coding into some activities.

• For feedback on your web-scraping projects, please use ScrAPI on Tilly. Follow the link and accept the invite.
• To integrate LLMs into your coding environment, install the tilburg.ai VS Code extension and generate an API key through Tilburg University’s API Platform. The relevant tutorials will explain when you need to use these tools.
• Do not enter private, confidential, or personally identifiable information into an AI tool.

8. Optional introduction to the command line

The command line can be useful when managing files and running longer data collections, but it is not required for accessing JupyterLab. To practice navigating folders and using terminal commands, work through the exercises at code-quest.hannesdatta.com.