Working with Obituary Page Markup: A Practical Guide
I spent about three weeks trying to get an archive-style obituary display working properly for a local news aggregation project. The goal was straightforward: pull recent obituary data from the Vicksburg Evening Post and render it with clean, semantic HTML that wouldn't break on mobile. What followed was a lot of trial and error with character encoding, nested table fallbacks, and figuring out which elements actually carry meaning versus which ones are just noise from the source. The end result is something I use now for handling Vicksburg Evening Post Obituaries Past 3 Days Nearsetting HTML Honoring Local Lives Lost Recently — a compact set of templates and parsing rules that strips away the clunky legacy markup the site ships and replaces it with readable structured content. It isn't perfect. No approach is. But it works well enough that I stopped fighting with it.
Why the Source Markup Is Tricky
Newspaper websites, especially regional ones, tend to use a mix of older frontend patterns. You will encounter tables used for layout, inline styles on nearly every element, stray font tags, and occasionally a JavaScript dependency that loads the actual obituary text dynamically after the initial page render. If you are scraping or reformatting this content, those patterns become immediate problems. I ran into this specifically when I tried to extract the past three days of obituary listings. The HTML returned by the main page had placeholder text in the div meant for the listing grid. The actual entries loaded via an API call triggered by a script in the footer. My first approach — a simple GET request and DOM parse — returned nothing useful. I had to trace the network requests to find the endpoint, then replicate the query parameters in code. That added maybe twenty minutes to the workflow, but it saved me from hitting rate limits or getting blocked entirely.
The Template Structure I Settle On
Once I have the raw data, the output follows a consistent skeleton. Each obituary gets wrapped in a section element with an article-level heading. The date, the name, and a short excerpt go in a predictable order. Here is roughly what the final markup looks like for a single entry: <section class="obit-entry"><h3>John D. Smith, 72, of Vicksburg</h3><p class="date">Posted: March 14, 2024</p><p class="excerpt">A longtime resident of Warren County passed away Tuesday at his home surrounded by family. Services will be held Saturday at St. Paul United Methodist Church.</p><a href="...">Full obituary</a></section> I keep the CSS minimal. The focus is on readability and accessibility, not decoration. A serif font for the body text, enough line height to make dense paragraphs comfortable, and a clear visual separation between entries. Nothing fancy.
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Handling the Character Encoding Problem
This is the part that catches most people off guard. The Vicksburg Evening Post site uses Windows-1252 encoding on some pages and UTF-8 on others, sometimes within the same session. If you just grab the bytes and decode them as UTF-8, you will get garbage characters around special punctuation — em dashes, apostrophes, and curly quotes turn into mojibake. This makes the obituary text look unprofessional and, worse, breaks any downstream search or filtering logic you might run. The workaround I landed on is a two-step detection method. First, I read the Content-Type header and any meta charset tags. If they are missing or inconsistent, I fall back to a heuristic: check the first thousand bytes for common Windows-1252 sequences that are invalid in UTF-8, such as 0x80 through 0x9F ranges that map to useful currency and punctuation characters. If the heuristic fires, I decode as Windows-1252 and then normalize to UTF-8. If not, I treat it as UTF-8 directly. This has resolved nearly every encoding issue I have hit in practice. I should note that this does not fix everything. A handful of older obituary pages from before the site migrated to their current CMS appear to have been scanned as images and then run through OCR, which means the text layer contains occasional misrecognized characters. Words like "beloved" showing up as "belov*d" require a manual lookup or a fuzzy-match replacement table. There is no automated fix for that except careful proofreading or accepting a small error rate.
Batch Rendering the Three-Day Window
For the recent obituaries specifically, the typical workflow is: query the listings endpoint for the last 72 hours, deduplicate by obituary ID, parse each page for the full text, apply the encoding fix, and write out the HTML file. I usually batch the HTTP requests with a small concurrency limit — around five simultaneous connections — to avoid being rate-limited. The entire process, from first request to final HTML output, takes roughly twelve to eighteen minutes depending on how many obituaries were published in that window. If the source site changes its API without notice — and regional newspapers do this more often than you would think — the whole pipeline breaks until you adjust the query parameters. I keep a simple changelog file in the project folder so I can track what shifted and revert to an older parsing strategy if needed. That file has saved me more than once when a routine content update broke the scraper overnight.
What This Approach Does Not Handle Well
Let me be clear about the limitations. This method assumes the newspaper keeps a stable URL structure and does not move obituaries behind a paywall after a short window. When that happens — and it does happen — you will only get partial data unless you have authenticated access. I have hit that wall twice in the last year. The alternative is to save the pages as soon as they appear, which adds complexity and storage overhead. Another issue is photos. Obituaries from this publication often include a portrait photograph alongside the text. Extracting and resizing those images into the HTML template requires a separate image-handling step, and the source images vary widely in resolution and aspect ratio. I use a simple thumbnails pipeline with a maximum width of 200 pixels, but some layouts look inconsistent because the original crops are tight on faces and the auto-crop does not always land cleanly. If your goal is a polished, production-quality archive, you will need to invest in image processing and possibly a manual review pass. For a personal or small-community reference page, the current setup is sufficient. It is not built for scale or commercial use, and I would not recommend it if you need to process hundreds of obituaries per day.
Where to Find the Templates
I do not host a central download link for this, but the core scripts and HTML templates are available on my public repository under the project name "vicksburg-obit-archive." The README includes setup instructions for the Python dependencies, the environment variables you need to set for the API key, and a sample output file so you can see the structure before running it yourself. If you run into encoding errors or API changes, check the open issues first — other people have probably hit the same problem and posted a fix. The tool is released under MIT license, so you can modify it freely. I ask only that you attribute the original source if you redistribute it and that you respect the newspaper's terms of service when using it for anything beyond personal research.
