Appendix A — Companion Notebooks

Every chapter of this book has a companion Jupyter Notebook that replicates the chapter’s code and the narrative around it, so you can run, modify, and break the examples as you read. This appendix lists them all in one place.

A.1 How to Use the Notebooks

Download the notebook for the chapter you are reading (links below). Right-click and “Save link as…” if your browser displays the raw file instead of downloading it.
Launch Jupyter (jupyter lab or jupyter notebook) from the folder where you saved it. If you need help getting Jupyter running, see Missing Manual Chapter 16: Jupyter.
Install as you go. Each chapter introduces its own libraries (pip install lines appear in the first code cells). You do not need everything installed to start.
Supply your own credentials. Notebooks for the API chapters (Chapter 11 through Chapter 13) require your own API keys, set as environment variables — never pasted into cells.

The code cells ship unexecuted by design: running code, encountering errors, and debugging them is where the learning happens. Expect some cells to require your input (API keys, file paths, a chosen article or subreddit) before they run.

A.2 The Notebooks

Chapter	Notebook
1. Introduction to Web Data Science	ch-01-introduction.ipynb
2. Ethics, Law, and Responsible Data Collection	ch-02-ethics.ipynb
3. The Post-API Age	ch-03-post-api.ipynb
4. Data Formats: XML and JSON	ch-04-data-formats.ipynb
5. Web Architecture and Protocols	ch-05-protocols.ipynb
6. Parsing Static Web Pages	ch-06-static-pages.ipynb
7. Archived Web Pages and the Wayback Machine	ch-07-archives.ipynb
8. Dynamic Web Pages with Selenium	ch-08-dynamic-pages.ipynb
9. Extracting Data from PDFs	ch-09-pdfs.ipynb
10. Introduction to APIs: Wikipedia	ch-10-wikipedia.ipynb
11. Government Data APIs	ch-11-government.ipynb
12. Social and Media Platform APIs	ch-12-social.ipynb
13. AI and Language Model APIs	ch-13-ai-apis.ipynb
14. Automating Data Collection	ch-14-automation.ipynb
15. Research Design with Web Data	ch-15-research-design.ipynb

Chapter 3 is a conceptual chapter, so its notebook contains discussion and exercises rather than code — it is included for completeness (and for taking notes in).

A.3 How They Are Generated

The notebooks are generated directly from the chapter source files by tools/make_notebooks.py, which converts each chapter’s prose to Markdown cells and its code blocks to code cells. This keeps the notebooks in lockstep with the book: when a chapter changes, regenerating the notebooks (python tools/make_notebooks.py from the repository root) brings them back into sync. If you spot a discrepancy between a notebook and its chapter, trust the chapter — and please report it as an issue.

# Companion Notebooks {#sec-appendix-notebooks} Every chapter of this book has a companion Jupyter Notebook that replicates the chapter's code and the narrative around it, so you can run, modify, and break the examples as you read. This appendix lists them all in one place. ## How to Use the Notebooks 1. **Download** the notebook for the chapter you are reading (links below). Right-click and "Save link as…" if your browser displays the raw file instead of downloading it. 2. **Launch** Jupyter (`jupyter lab` or `jupyter notebook`) from the folder where you saved it. If you need help getting Jupyter running, see *Missing Manual* Chapter 16: Jupyter. 3. **Install as you go.** Each chapter introduces its own libraries (`pip install` lines appear in the first code cells). You do not need everything installed to start. 4. **Supply your own credentials.** Notebooks for the API chapters (@sec-government through @sec-ai-apis) require your own API keys, set as environment variables — never pasted into cells. The code cells ship unexecuted by design: running code, encountering errors, and debugging them is where the learning happens. Expect some cells to require your input (API keys, file paths, a chosen article or subreddit) before they run. ## The Notebooks | Chapter | Notebook | |---------|----------| | 1. Introduction to Web Data Science | [ch-01-introduction.ipynb](notebooks/ch-01-introduction.ipynb) | | 2. Ethics, Law, and Responsible Data Collection | [ch-02-ethics.ipynb](notebooks/ch-02-ethics.ipynb) | | 3. The Post-API Age | [ch-03-post-api.ipynb](notebooks/ch-03-post-api.ipynb) | | 4. Data Formats: XML and JSON | [ch-04-data-formats.ipynb](notebooks/ch-04-data-formats.ipynb) | | 5. Web Architecture and Protocols | [ch-05-protocols.ipynb](notebooks/ch-05-protocols.ipynb) | | 6. Parsing Static Web Pages | [ch-06-static-pages.ipynb](notebooks/ch-06-static-pages.ipynb) | | 7. Archived Web Pages and the Wayback Machine | [ch-07-archives.ipynb](notebooks/ch-07-archives.ipynb) | | 8. Dynamic Web Pages with Selenium | [ch-08-dynamic-pages.ipynb](notebooks/ch-08-dynamic-pages.ipynb) | | 9. Extracting Data from PDFs | [ch-09-pdfs.ipynb](notebooks/ch-09-pdfs.ipynb) | | 10. Introduction to APIs: Wikipedia | [ch-10-wikipedia.ipynb](notebooks/ch-10-wikipedia.ipynb) | | 11. Government Data APIs | [ch-11-government.ipynb](notebooks/ch-11-government.ipynb) | | 12. Social and Media Platform APIs | [ch-12-social.ipynb](notebooks/ch-12-social.ipynb) | | 13. AI and Language Model APIs | [ch-13-ai-apis.ipynb](notebooks/ch-13-ai-apis.ipynb) | | 14. Automating Data Collection | [ch-14-automation.ipynb](notebooks/ch-14-automation.ipynb) | | 15. Research Design with Web Data | [ch-15-research-design.ipynb](notebooks/ch-15-research-design.ipynb) | Chapter 3 is a conceptual chapter, so its notebook contains discussion and exercises rather than code — it is included for completeness (and for taking notes in). ## How They Are Generated The notebooks are generated directly from the chapter source files by `tools/make_notebooks.py`, which converts each chapter's prose to Markdown cells and its code blocks to code cells. This keeps the notebooks in lockstep with the book: when a chapter changes, regenerating the notebooks (`python tools/make_notebooks.py` from the repository root) brings them back into sync. If you spot a discrepancy between a notebook and its chapter, trust the chapter — and please report it as an [issue](https://github.com/cuinfoscience/Web-Data-Science-Book/issues).