Downloading SmugMug Captions with Python and Jupyter

This blog post started out as an experimental rendering of a Jupyter notebook. I wanted to see how difficult it would be to convert a notebook to a WordPress.com blog post. Even though Jupyter exports notebooks in HTML and Markdown they do not display well “out of the box.” No doubt one could craft CSS that would help but the entire point of Jupyter exports is to cut down on pointless format thrashing.

This post is a teaser. If you want to get to the source notebook follow this link to my GitHub repositories.

If you only want to read the notebook use this nbviewer link.

Why am I doing this?

My photo captions have evolved into a form of milliblogging. Milliposts (milliblog posts) are terse and tiny; many are single sentences or paragraphs. Taken one-at-a-time milliposts seldom impress but when gathered in hundreds or thousands accidental epics emerge. So, to prevent “epic loss” I want a simple way of downloading and archiving my captions off-line.

If you don’t control it you cannot trust it!

When I started blogging I knew that you could not depend on blogging websites to archive and preserve your documents. We had already seen cases of websites mangling content, shutting down without warning, and even worse, censoring bloggers. It was a classic case of, “If you don’t control it you cannot trust it.” I resolved to keep complete off-line version controlled copies of my blog posts.

Maintaining off-line copies was made easier by WordPress.com‘s excellent blog export utility. A simple button push downloads a large XML file that has all your blog posts with embedded references to images and other inclusions. XML is not my preferred archive format. I am a huge fan of LaTeX and Markdown: two text formats that are directly supported in Jupyter Notebooks. I wrote a little system that parses the WordPress XML file and generates LaTeX and Markdown files. Yet, despite milliblogging long before blogging, I don’t have a similar system for downloading and archiving SmugMug metadata. This Jupyter notebook addresses this omission and shows how you can use Python and the SmugMug API to extract gallery and image metadata and store it in version controlled local directories as CSV files.