Archive the Internet

As the Internet continues to grow and age, we are seeing more and more of a phenomenon called “link rot”. Link rot is the all-too-familiar experience of returning to a bookmark or link only to find that it's no longer maintained, been taken down, or even changed to something else. What can we do about this?

Sites like archive.org were created to combat this exact problem. That site exists for the sole purpose of maintaining snapshots of the Internet over time so that you can always find old copies of a web page from years back.

The problem, of course, is that you never know if the site you actually need will be archived because they only archive sites that are explicitly submitted by users. For popular sites, this won't be a problem. But what about an obscure blog post or research article you read 4 years ago that you now want to reference? If you didn't remember to archive it at the time, you're out of luck.

Other sites like Pinboard offer an automatic archiving feature for all of your bookmarks. Pinboard is a great, well-run, and honest service that I use and recommend. For a fee, Pinboard will regularly download a copy of your bookmarks to save them from link rot.

The solution to this problem is actually quite easy, technically speaking. I've been itching for a new project, so I thought this would be a good problem to tackle.

The system I wanted to create has basically 3 components: input, retrieval, and presentation. The input component relates to how I specify which web pages I want to archive. Retrieval involves actually downloading those pages in such a manner that they can be accurately duplicated. Presentation deals with viewing the archive when needed.

All three of these components need to work with a common data source. In the interest of simplicity and to avoid reinventing the wheel, the obvious choice is to use some kind of plain-text format to represent which web pages I want to archive. This ensures that I can leverage standard UNIX command line utilities such as wget and awk.

I first considered GNU's recutils, a plain-text database format that supports inserting and selecting records into “recfiles”. The format is brain dead simple and easy to understand, and since I'm not going to be carrying around millions of entries (like SQL databases are made for), the performance factor is not really a concern for me.

The only drawback to recutils is support, or lack thereof. The presentation component of this system will need to involve a webserver of some kind and recfiles are not a natively supported database format in any language I am aware of. Integrating recfile support into a webserver would involve either parsing the files using regular expressions (hacky and non-portable) or writing a recfile driver myself (a lot of work and I'm lazy). Instead, I decided to use a tab-delimited CSV file.

My tab-delimited CSV database has a very simple format: it's a single file where each line in the file has two fields separated by a tab character. The first field is the web page title or description, and the second field is the URL. For example

Personal website of Greg Anders	https://gpanders.com
                               ^ literal tab character (\t)

Why a tab? Traditionally, CSV files use commas to separate field values (hence the C in CSV); however, page titles and descriptions can contain basically any printable character imaginable, including commas, semicolons, pipes, and slashes. But they don't contain raw tab characters, so there will never be any ambiguity. This format is easy to read, easy to manually update (if I want), works perfectly with traditional UNIX tools, and is widely supported (many languages come with native CSV support with no 3rd party dependencies).

To populate the database, I import my bookmarks from Pinboard and convert them into the tab-delimited CSV format:

$ curl -s "https://api.pinboard.in/v1/posts/all?auth_token=$PINBOARD_API_KEY&format=json" | jq -r '.[] | "\(.description)\t\(.href)"' > links.csv

Then, I use awk to parse the URLs from the CSV file and wget to download the web pages:

$ awk -F'\t' '{print $2}' links.csv | while read -r url; do
>   wget -ENHkpc --wait=1 --random-wait --user-agent="" -e robots=off "$url"
> done

To build the wget command I referred to a few different examples across the web. The flags given will download all of the resources on the given page and adjust their paths accordingly so that the web page can be viewed offline. The --wait and --random-wait flags tell wget to wait between 0.5 and 1.5 seconds between each download request which reduces the load on the servers a bit.

For the presentation component, I wrote an ultra-simple Go web server that simply serves up the web archive and provides a dynamic index of archived pages from the database. The entire program is fewer than 100 lines and you can find it here.

By setting up a cron job on my Raspberry Pi, I can now completely automate the creation and maintenance of an offline web archive (using Borg for regular backups!). Bookmarks are automatically imported from Pinboard into a CSV file which is read by standard UNIX tools awk and wget to download a web archive, which is viewable at any time from a webserver.

This solution is extremely stable as it uses technologies and tools that have been around for decades. By leveraging the UNIX philosophy of using simple, composable tools with flexible interfaces, the system is highly modular and configurable (I can easily modify or replace the web interface without having to do anything to the other components, and vice versa). And since I'm backing up the whole archive to Borg, I can maintain a weekly snapshot of all of my bookmarks in perpetuity at the cost of very little storage space.

This whole thing took me a little over 6 hours to create. Most of that time was spent deciding on a database format and building the Go webserver (like I said, it's extremely simple but I am also a total Go newbie, so it was a great learning experience). Future improvements involve tweaking up the web interface to make it a bit more aesthetically appealing and adding some functional improvements such as a search feature.