PUDL Archiver: Publishing New Data

Hey guys, let's dive into the latest from the PUDL Archiver! We've got some new archives to review and publish, and as always, we need to make sure everything is tip-top before we release it to the world. This post is all about summarizing the results from our recent archiving runs and detailing the steps we need to take to get these archives published.

So, first things first, you can check out all the job run logs and results over on GitHub. Just click this link: here. Give that a look to get the full picture of what's been going on.

Review and Publish Archives: The Nitty-Gritty

Alright team, here's the game plan for reviewing and publishing archives. For each of the archives we've processed, we need to check its status in the GitHub archiver run. Did the validation tests pass? If they did, awesome! Then, it's time for a manual review. We'll be looking over the archive to make sure everything makes sense. If, by chance, there are no changes detected since the last run, we can just delete the draft – easy peasy. However, if there are changes, we need to roll up our sleeves. We’ll manually review the archive following the guidelines in step 3 of the README.md. Once we're happy with it, we'll publish the new version. After publishing, we need to confirm that it went through successfully and add a little note about its status, like "v1 published" or "no changes detected, draft deleted". If anything seems a bit off or needs more attention, we'll create a follow-up sub-issue to tackle it.

Changed Archives: What's New?

Okay, so for the changed archives, these are the ones that have successfully run and are bringing new data to the table. This is where the bulk of our manual review will happen. We need to carefully review each archive prior to publication. This means going through the data, checking for any anomalies, and ensuring it aligns with our quality standards. Remember, publishing new data is a big deal, so we want to be absolutely sure it's accurate and reliable. Think of it like being a detective – we're looking for clues, ensuring consistency, and making sure everything checks out before we give it the green light. This meticulous process is what keeps our data trustworthy and useful for everyone relying on it. So, let's give these new datasets the attention they deserve!

Validation Failures: What Went Wrong?

Now, let's talk about the validation failures. Sometimes, things don't go as planned, and the validation tests might fail. When this happens, you'll see it in the GHA logs. We need to add these failed runs to our task list. To investigate, we'll download the run summary JSON. You can find this by going into the "Upload run summaries" tab of the GHA run for each dataset and following the link. Once we have the summary, we'll dive deep into why the validation failed. Sometimes, a validation failure is perfectly okay after a manual review. For example, if we see that the Q2 2024 data doubles the size of a file that only had Q1 data previously, but the new data looks exactly as expected, then we can go ahead and approve the archive. In such cases, we'll just leave a note in the task list explaining our decision. However, if the validation failure is more serious – like an incorrect file format or a dataset changing size by a whopping 200% unexpectedly – then that's a blocking issue. For these, we'll need to create a new issue specifically to resolve the problem. This ensures that we address these more critical failures systematically and don't let them slip through the cracks.

FERCEQR Failure Example:

We encountered a specific failure with ferceqr. The logs show an asyncio.TimeoutError originating from FercEQRArchiver.get_quarter_csv. There's also a RuntimeWarning noting that the coroutine was never awaited. This kind of error suggests a timing issue or perhaps a problem with how the asynchronous operation was handled. We'll need to investigate this further to understand the root cause and implement a fix. This might involve adjusting timeouts, ensuring async operations are properly awaited, or looking into the underlying data fetching process for get_quarter_csv. It's a good reminder that even seemingly small issues can point to deeper problems that need our attention.

Other Failures: Beyond Validation

Besides validation hiccups, we might encounter other failures. These could stem from various things, like unexpected changes in the underlying data sources, bugs in our code, or environmental issues. For any run that fails for these reasons, our process is to create an issue that clearly describes the failure. Then, we'll take the necessary steps to resolve it. This means identifying the problem, whether it's a code bug, a data pipeline issue, or something else, and then working on a solution. It's all about being proactive and ensuring the PUDL Archiver keeps humming along smoothly. Tackling these issues head-on is crucial for maintaining the integrity and reliability of the data we archive.

Unchanged Archives: Nothing New Here

Finally, we have the unchanged archives. These are the archives where our recent run detected no observed changes in the data. This is great news! It means the data is stable, and we don't need to do anything further for these specific archives. We can simply note that no changes were detected, and we can move on to the next task. It's always satisfying to see archives that are stable and don't require any intervention, allowing us to focus our energy on where it's needed most.

Other Issues to Keep an Eye On

Beyond the specific categories above, there might be other issues that crop up during the archiving process. These could be anything from minor bugs to process inefficiencies. We've got a placeholder here: [ ] issue. This is where we'll track any miscellaneous problems that need attention. If you encounter anything that doesn't fit neatly into the other categories, make sure to document it here so we can address it. Staying on top of all potential issues, big or small, is key to continuous improvement. Let's make sure we address these as they come up, keeping our archiving process as robust as possible!

That's the rundown, guys! Let's get these archives reviewed and published. Your diligence in this process is what makes the PUDL project a success. Keep up the great work!