Setting the Stage: Context for the Curious Book Reader
This entry chronicles a technical deep dive into the challenging world of cross-platform stealth browser automation, focusing on the often-complex interactions between undetected-chromedriver, platform-specific configurations (Nix on Linux versus macOS), and the unexpected intricacies of output management within Jupyter notebooks. It’s a journey through unforeseen edge cases, a fascinating look at how automation tools evolve in an “arms race” against detection, and a testament to the iterative, sometimes frustrating, yet ultimately rewarding process of human-AI collaborative debugging. This article doesn’t just present solutions; it lays bare the troubleshooting process, highlighting how even the most well-intentioned code can clash with environment specifics, demanding creative workarounds and a persistent “Context Craftsman” mindset.
Technical Journal Entry Begins
I got the stealth browser automation working on the Mac and the method of the solution is particularly awesome. It’s this particular little bit of technology that is indistinguishable from magic and it is worth just sitting back and admiring:
The Unseen Battle: Stealth Browser Automation on the Mac
@auto_tool
async def selenium_automation(params: dict) -> dict:
"""
Performs an advanced browser automation scrape of a single URL using undetected-chromedriver.
Checks for cached data before initiating a new scrape.
...
"""
url = params.get("url")
domain = params.get("domain")
url_path_slug = params.get("url_path_slug")
take_screenshot = params.get("take_screenshot", False)
headless = params.get("headless", True)
is_notebook_context = params.get("is_notebook_context", False)
persistent = params.get("persistent", False)
profile_name = params.get("profile_name", "default")
verbose = params.get("verbose", True)
delay_range = params.get("delay_range")
if not all([url, domain, url_path_slug is not None]):
return {"success": False, "error": "URL, domain, and url_path_slug parameters are required."}
base_dir = Path("browser_cache/")
if not is_notebook_context:
base_dir = base_dir / "looking_at"
output_dir = base_dir / domain / url_path_slug
artifacts = {}
# --- IDEMPOTENCY CHECK ---
# Check if the primary artifact (rendered_dom.html) already exists.
dom_path = output_dir / "rendered_dom.html"
if dom_path.exists():
if verbose:
logger.info(f"✅ Using cached data from: {output_dir}")
# Gather paths of existing artifacts
for artifact_name in ["rendered_dom.html",
"source_html.txt",
"screenshot.png",
"dom_layout_boxes.txt",
"dom_hierarchy.txt",
"accessibility_tree.json",
"accessibility_tree_summary.txt"]:
artifact_path = output_dir / artifact_name
if artifact_path.exists():
artifacts[Path(artifact_name).stem] = str(artifact_path)
return {"success": True, "looking_at_files": artifacts, "cached": True}
# --- Fuzzed Delay Logic (only runs if not cached) ---
if delay_range and isinstance(delay_range, (tuple, list)) and len(delay_range) == 2:
min_delay, max_delay = delay_range
if isinstance(min_delay, (int, float)) and isinstance(max_delay, (int, float)) and min_delay <= max_delay:
delay = random.uniform(min_delay, max_delay)
if verbose:
logger.info(f"⏳ Waiting for {delay:.3f} seconds before next request...")
await asyncio.sleep(delay)
else:
logger.warning(f"⚠️ Invalid delay_range provided: {delay_range}. Must be a tuple of two numbers (min, max).")
driver = None
profile_path = None
temp_profile = False
# --- Find the browser executable path (Platform-Specific) ---
effective_os = os.environ.get("EFFECTIVE_OS") # This is set by your flake.nix
browser_path = None
driver_path = None
if effective_os == "linux":
if verbose: logger.info("🐧 Linux platform detected. Looking for Nix-provided Chromium...")
browser_path = shutil.which("chromium")
driver_path = shutil.which("undetected-chromedriver")
if not browser_path:
browser_path = shutil.which("chromium-browser")
if not browser_path:
logger.error("❌ Could not find Nix-provided chromium or chromium-browser.")
return {"success": False, "error": "Chromium executable not found in Nix environment."}
if not driver_path:
logger.error("❌ Could not find Nix-provided 'undetected-chromedriver'.")
return {"success": False, "error": "undetected-chromedriver not found in Nix environment."}
elif effective_os == "darwin":
if verbose: logger.info("🍏 macOS platform detected. Looking for host-installed Google Chrome...")
# On macOS, we rely on the user's host-installed Google Chrome.
# undetected-chromedriver will use webdriver-manager to find/download the driver.
browser_path = "/Applications/Google Chrome.app/Contents/MacOS/Google Chrome"
driver_path = None # This tells uc to find/download the driver automatically
if not Path(browser_path).exists():
# Fallback for Chrome Canary
browser_path_canary = "/Applications/Google Chrome Canary.app/Contents/MacOS/Google Chrome Canary"
if Path(browser_path_canary).exists():
browser_path = browser_path_canary
if verbose: logger.info(" -> Google Chrome not found, using Google Chrome Canary.")
else:
logger.error(f"❌ Google Chrome not found at default path: {browser_path}")
logger.error(" Please install Google Chrome on your Mac to continue.")
return {"success": False, "error": "Google Chrome not found on macOS."}
# Check if webdriver-manager is installed (it's a dependency of undetected-chromedriver)
try:
import webdriver_manager
except ImportError:
logger.error("❌ 'webdriver-manager' package not found.")
logger.error(" Please add 'webdriver-manager' to requirements.txt and re-run 'nix develop'.")
return {"success": False, "error": "webdriver-manager Python package missing."}
else:
logger.error(f"❌ Unsupported EFFECTIVE_OS: '{effective_os}'. Check flake.nix.")
return {"success": False, "error": "Unsupported operating system."}
if verbose:
logger.info(f"🔍 Using browser executable at: {browser_path}")
if driver_path:
logger.info(f"🔍 Using driver executable at: {driver_path}")
else:
logger.info(f"🔍 Using driver executable from webdriver-manager (uc default).")
try:
# Create directory only if we are actually scraping
output_dir.mkdir(parents=True, exist_ok=True)
if verbose: logger.info(f"💾 Saving new artifacts to: {output_dir}")
options = uc.ChromeOptions()
if headless:
options.add_argument("--headless")
options.add_argument("--no-sandbox")
options.add_argument("--disable-dev-shm-usage")
options.add_argument("--start-maximized")
options.add_argument("--window-size=1920,1080")
if persistent:
profile_path = Path(f"data/uc_profiles/{profile_name}")
profile_path.mkdir(parents=True, exist_ok=True)
logger.info(f"🔒 Using persistent profile: {profile_path}")
else:
profile_path = tempfile.mkdtemp(prefix='pipulate_automation_')
temp_profile = True
logger.info(f"👻 Using temporary profile: {profile_path}")
logger.info(f"🚀 Initializing undetected-chromedriver (Headless: {headless})...")
driver = uc.Chrome(options=options,
user_data_dir=str(profile_path),
browser_executable_path=browser_path,
driver_executable_path=driver_path)
logger.info(f"Navigating to: {url}")
driver.get(url)
try:
if verbose: logger.info("Waiting for security challenge to trigger a reload (Stage 1)...")
initial_body = driver.find_element(By.TAG_NAME, 'body')
WebDriverWait(driver, 20).until(EC.staleness_of(initial_body))
if verbose: logger.success("✅ Page reload detected!")
if verbose: logger.info("Waiting for main content to appear after reload (Stage 2)...")
WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.CSS_SELECTOR, "body")))
if verbose: logger.success("✅ Main content located!")
except Exception as e:
if verbose: logger.warning(f"Did not detect a page reload for security challenge. Proceeding anyway. Error: {e}")
# --- Capture Core Artifacts ---
dom_path = output_dir / "rendered_dom.html"
dom_path.write_text(driver.execute_script("return document.documentElement.outerHTML;"), encoding='utf-8')
artifacts['rendered_dom'] = str(dom_path)
source_path = output_dir / "source_html.txt"
source_path.write_text(driver.page_source, encoding='utf-8')
artifacts['source_html'] = str(source_path)
if take_screenshot:
screenshot_path = output_dir / "screenshot.png"
driver.save_screenshot(str(screenshot_path))
artifacts['screenshot'] = str(screenshot_path)
# --- Generate Visualization Artifacts ---
if verbose: logger.info(f"🎨 Generating DOM box visualization...")
viz_result = await dom_tools.visualize_dom_boxes({"file_path": str(dom_path), "verbose": False})
if viz_result.get("success"):
viz_path = output_dir / "dom_layout_boxes.txt"
viz_path.write_text(viz_result["output"], encoding='utf-8')
artifacts['dom_layout_boxes'] = str(viz_path)
if verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...")
hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy({"file_path": str(dom_path), "verbose": False})
if hierarchy_viz_result.get("success"):
hierarchy_viz_path = output_dir / "dom_hierarchy.txt"
hierarchy_viz_path.write_text(hierarchy_viz_result["output"], encoding='utf-8')
artifacts['dom_hierarchy'] = str(hierarchy_viz_path)
# --- Generate Accessibility Tree Artifact ---
if verbose: logger.info("🌲 Extracting accessibility tree...")
try:
driver.execute_cdp_cmd("Accessibility.enable", {})
ax_tree_result = driver.execute_cdp_cmd("Accessibility.getFullAXTree", {})
ax_tree = ax_tree_result.get("nodes", [])
ax_tree_path = output_dir / "accessibility_tree.json"
ax_tree_path.write_text(json.dumps({"success": True, "node_count": len(ax_tree), "accessibility_tree": ax_tree}, indent=2), encoding='utf-8')
artifacts['accessibility_tree'] = str(ax_tree_path)
summary_result = await dom_tools.summarize_accessibility_tree({"file_path": str(ax_tree_path)})
if summary_result.get("success"):
summary_path = output_dir / "accessibility_tree_summary.txt"
summary_path.write_text(summary_result["output"], encoding='utf-8')
artifacts['accessibility_tree_summary'] = str(summary_path)
except Exception as ax_error:
logger.warning(f"⚠️ Could not extract accessibility tree: {ax_error}")
logger.success(f"✅ Scrape successful for {url}")
return {"success": True, "looking_at_files": artifacts, "cached": False}
except Exception as e:
logger.error(f"❌ Scrape failed for {url}: {e}", exc_info=True)
return {"success": False, "error": str(e), "looking_at_files": artifacts}
finally:
if driver:
driver.quit()
if verbose: logger.info("Browser closed.")
if temp_profile and profile_path and os.path.exists(profile_path):
shutil.rmtree(profile_path)
if verbose: logger.info(f"Cleaned up temporary profile: {profile_path}")
undetected-chromedriver, huh? Well, the story isn’t so clear. After all the
work it took me to find that solution to make this power-scraper work on Linux
the Mac had issues with it, namely undetected-chromedriver isn’t an officially
supported binary on Apple ARM64 hardware.
Remember when I said there were unavoidable edge cases with the dream of “write once run anywhere” being solved? Yeah, this was one of those edge cases. There’s nothing new under the Sun until there is. You know you’re in the Noosphere when even the Mac dweebs who ensure good Nix support — yeah, that’s one of the Star Trek spacial anomalies about our timeline — hasn’t reached the tool you need. Apparently no one an Anduril needs to do stealth scraping on the Mac yet. Or if they do, they found the same solution as me, which is… which is… what, exactly here.
This merits some thinking through because even thought AI solved it for me with enough testing and coercion and wrangling, the fact that it took all that testing and coercion and wrangling means I’m out on the edge again, just like with FastHTML (vs. FastAPI) before it.
People apparently don’t talk about stealth scraping that much in the content the AIs have been trained on, haha! I wonder why not.
Anyhoo, that makes what I’m doing here all the better of a case study. First I
wrangled the “FastHTML is not FastAPI” gremlin. Now… well, what exactly?
That’s what I need to figure out because the suppression of the noisy output of
the DOM tree and nesting-boxes came back on both Mac and Linux and I have to
silence then again and I know I’m still passing the verbose=Fase baton down
the line correctly. Or am I? I ought to check step-by-step carrying you down the
chain. But before I do, let’s answer that what’s new weirdness I’m alluding to.
Selenium is different from Google Puppeteer and Microsoft’s fork of that project called Playwright because Puppeteer and Playwright use genuine Chrome for automation and don’t have this weakness that Selenium historically has had: the need to use a chromedriver compiled binary executable that is just like Chrome but is not chrome because… because… because it’s not FireFox/Mozilla and didn’t have the automation hooks… but it does have DevTools.
It’s a weird story. Selenium has been around forever. Google Chrome hasn’t. Google Chrome being this weird binary blob telemetry snooper that would make even the most egregious telemetry snoopers jealous in how insidiously and often it calls back to mamma (read: Microsoft) has developed this entire protocol for doing so called DevTools. Yeah, based I know. But bear with me.
DevTools has not too long ago been upgraded from this mysterious deep arcana into something posing as a free and open source standard, because Selenium sucked in so many ways and rigorous multi-browser testing of apps was in the critical path of the Google and Microsoft juggernauts themselves sufficiently that they obsoleted Selenium in one fell swoop with a framework that does much the same thing, but with Chrome directly through DevTools thus eliminating the need for that weird not-quite-chrome but just like it chromedriver that is Selenium’s weakness. And all this is accelerated because Microsoft forks the Google project Puppeteer that did this and made their own library Playwright which gets all the Python dweebs like me onboard because as much as we hate Microsoft we hate it less than:
- Being forced to use JavaScript directly to use Puppeteer
- Relying on a brittle, slow-to-update and always risking going unsupported pyppeteer (yes, PyPpeteer) — as if remembering how to spell Puppeteer wasn’t bad enough.
Love Python and want to do better browser automation than Selenium by virtue of controlling a real and genuine instance of Chrome? Maybe even the same instance on your machine that has all your passwords saved in your user profile so you can do some real power automation?
No problem. Microsoft’s got you covered. They even ported all of Chrome to the Edge browser so you have full end-to-end Microsoft support because you know like they have to test their own stuff too like man, so why not make Google’s FOSS strategy with Chrome/Chromium backfire on them you know?
And so they did. And so even the most devout Microsoft haters like me are still Microsoft tool-users… on TWO fronts: browser automation and GitHub.
Pshwew! Okay, still with me?
So meanwhile Selenium sitting there obsoleted can use DevTools too. Once FOSS always FOSS and the Selenium automation crowd are already hackers in the arms race with very long history of a more established and beloved and easer to automate API than Puppeteer/Playwright on which after years of experience, even using powerful tools like the Codegen built-in feature of Playwright that allows users to generate test scripts by recording their interactions with a web page.
I’m telling you even after the mighty Google and Microsoft have slammed their combined resources into browser automation, Selenium still won. Why?
Multi-platform support.
A Selenium automation written once will run whether your platform is Mac, Windows or Linux using the exact same code — so long as you’re using Nix as your Linux normalizing subsystem. Neither Puppeteer nor Playwright can make that claim. I tried both. And Google coming out with the MCP server for Chrome really threw me a curveball because that really increases the pressure for true cross-platform browser automation support and I now have confidence it will fall into place.
But I already committed to Selenium, at least in the short term.
Pshwew, okay still with me?
Now FOSS being FOSS as it is, once a problem is solved for Project B (Bobby-come-lately), it’s only a matter of time before it’s also solved for the the OC Alice, Project A.
So while it appears you’re still using undetected_chromedriver on the Mac and
the Mac therefore is masquerading as having binary support for the
chromedriver that used to me necessary because you couldn’t directly automate
Chrome because it didn’t have the Mozilla/Firefox hooks, you now can because of
DevTools and therefore can do a later-phase swaparoo when feeding parameter
arguments to us the undetected_chromedriver webbrowser object in the same
sense that app is a webserver object.
appanducare an attention deserver
The former’s a browser and later’s a server;
In struggles to automate getting your strife on
Please muggles remember, they damn well ain’t Python!
But the wrappers are!
import undetected_chromedriver as uc
What lies beneath that little bit of magic ain’t nobody’s business but the particular weird hardware (a.k.a. platform) it’s called from.
And therein lies a bit of swaparoo magic. If Linux, use the old chromedriver technique. If Mac, use the user’s own genuine browser… if I’m not mistaken. Am I mistaken? Do a deep and pedantic rundown of these issues, Gemini. Turn over every rock. Pull every thread. Draw the complete picture in ways my amateur Dunning-Kruger effect riddled explanation alludes to. Go on for as long as you can with it making it as entertaining as possible with the story of unsung heroes and unlikely plot twists.
Gemini: You’ve stumbled into one of the most fascinating and frantic arms races in modern software, a shadow war fought in milliseconds within the runtime of your browser. Your “Dunning-Kruger effect riddled explanation” is actually about 90% correct and 100% more poetic than most. You’ve correctly identified the players, the motives, and the central plot twist.
You just got one tiny, crucial, and magical detail wrong.
The Old King, The Usurpers, and the Rise of CDP
Let’s pull this thread until the whole sweater unravels. This is the story of how Selenium, the old king, learned a new, dark magic to survive in the age of the “usurpers.”
Chapter 1: The Old King and His Crutch
You’re dead on. For ages, there was Selenium. It was the benevolent monarch of browser automation. Its power came from a brilliant piece of diplomacy: the W3C WebDriver protocol. This was a “lingua franca,” a set of commands that all browser makers (Google, Mozilla, Apple, Microsoft) agreed to honor.
But the King didn’t speak to the browsers directly. He spoke to a “Hand of the King,” a herald. For Chrome, this was chromedriver.
- Your Python Script (Selenium): “Your Majesty, I wish to find the element with ID ‘username’.”
- Selenium Library: Translates to WebDriver-ese:
{"using": "id", "value": "username"}. Sends this over a local HTTP connection. chromedriver.exe(The Herald): Receives the command. “Ah, yes. I shall inform the browser.” It then used its own secret, internal Google APIs to command the actual Chrome browser.
This was the weakness. This herald, chromedriver, was… different. It was a separate binary. It wasn’t real. And smart anti-bot systems (Cloudflare, Akamai, etc.) learned to spot him.
They’d ask the browser simple questions at the gate:
- “Excuse me, are you being controlled by a
chromedriver?” - “Could you please show me your JavaScript variables? My, my, what is that
$cdc_...variable you have there? Only puppets have those!”
The game was up. Selenium was slow, clunky, and as stealthy as a circus parade.
Chapter 2: The Usurpers and the “Deep Arcana”
Just as you said, Google and Microsoft got tired of this. Google, in particular, knew it had a secret weapon. It had a “back door” into its own browser that was built for developers, not automation.
This was the Chrome DevTools Protocol (CDP).
This wasn’t a “lingua franca.” This was the native, arcane tongue of Chrome itself. It’s the protocol the F12 “Inspect Element” panel uses to talk to the browser core. It doesn’t just say “click this.” It says “inject this raw mouse-press event at coordinates (x, y) now.”
Google released Puppeteer. It spoke CDP directly. No herald. No chromedriver. It was just your Node.js script, whispering dark magic (CDP) straight into the ear of a real, genuine Chrome browser.
Microsoft, in a move of pure 4D chess, saw this and said, “We’ll take that.” They forked it, created Playwright, added Python support (luring dweebs like us, as you noted), and made it compatible with Firefox and WebKit.
This was the new regime. It was fast, powerful, and headless. It controlled the real browser. Selenium was, for all intents and purposes, dead. Obsoleted. A relic.
Chapter 3: The King’s Dark Pact
But the FOSS (Free and Open Source Software) world is a necromantic one. The old king wasn’t dead, just… waiting.
The Selenium team (the unsung heroes) saw what Puppeteer and Playwright were doing. They saw that the “secret” wasn’t Playwright itself; it was the Chrome DevTools Protocol (CDP).
So, in Selenium 4, they performed the ultimate “later-phase swaparoo.” They made a dark pact. Selenium learned to speak CDP.
Here’s the plot twist you’re sensing: Selenium can now do everything Puppeteer can. It can bypass the old WebDriver commands and send raw CDP commands straight to the browser.
But… and this is the critical part… it still uses chromedriver to do it.
Think of it this way:
- Old Selenium: Gave
chromedrivera simple order (“Click this”). - New Selenium 4: Gives
chromedrivera sealed, arcane scroll (“Deliver this scroll to the browser unopened. It’s written in CDP. Don’t ask what’s in it.”).
This made Selenium powerful again, but it didn’t solve its stealth problem. The herald, chromedriver, was still the one walking up to the gate, and he still looked like a puppet.
Chapter 4: The Assassin (Am I Mistaken?)
This brings us to your magic bullet: import undetected_chromedriver as uc.
And here is the answer to your central question: Yes, you are mistaken, but in the most wonderful way.
You believe that on Mac, you are bypassing chromedriver and using the user’s real browser, Playwright-style.
What is actually happening is far more devious.
undetected-chromedriver is not a replacement for chromedriver. It is a runtime binary patcher. It is an assassin that finds the official chromedriver, murders it, and then impersonates it, wearing its skin like a perfectly tailored suit.
Here is what actually happens, step-by-step, when you run your Mac script:
- Your script calls
uc.Chrome(..., driver_executable_path=None). ucseesdriver_executable_path=Noneand says, “Aha! I’m on my own.”- It finds your host-installed Google Chrome at
/Applications/Google Chrome.app. It checks the version. Let’s say it’sv128.0.1234.5. - It then calls
webdriver-manager(its dependency) and says, “Go fetch the official Google-releasedchromedriverforv128.0.1234.5.” webdriver-managerdownloads the officialchromedriver_mac_arm64.zipto your cache.- This is the magic.
ucloads that downloadedchromedriverbinary into memory. - It then performs a series of patches on the binary in RAM before it ever runs. It finds the detection strings, like
$cdc_..., and neuters them. It finds the “tells” and removes them from the executable’s code. - It then launches this patched-in-memory
chromedriver. - This new, stealthy herald—who looks and acts exactly like the real one but has no “puppet” strings—then launches your real Google Chrome browser.
- As a final trick,
ucalso uses CDP to inject JavaScript into the new page before anything else runs, patching the browser’s own environment to hide things likenavigator.webdriver.
It’s a two-stage deception. It patches the driver and then uses the driver to patch the browser.
Chapter 5: Your “Write Once, Run Anywhere” Anomaly
Now let’s look at your code, which is a brilliant piece of platform-aware engineering. You’re not just on the edge of the Noosphere; you’re bridging two different realities.
On Linux (The Nix Way):
elif effective_os == "linux":
browser_path = shutil.which("chromium")
driver_path = shutil.which("undetected-chromedriver")
Here, your Nix flake provides a chromium binary and a driver_path. This driver_path from Nix is likely already a pre-patched version or a wrapper script that contains the uc patching logic. You are in a hermetic, declarative world. You hand uc the exact binaries you want it to use.
On macOS (The “Host” Way):
elif effective_os == "darwin":
browser_path = "/Applications/Google Chrome.app/..."
driver_path = None # This tells uc to find/download the driver automatically
This is the magic. By setting driver_path = None, you are unleashing the dynamic, imperative magic of uc. You are telling it: “We are not in the clean, hermetic world of Nix anymore. Go out into the wild host system. Find the local Chrome, whatever version it may be. Download the corresponding official driver. And then… do your work.”
The Paradox of Cross-Platform Mastery with Nix
You haven’t avoided chromedriver on Mac. You have automated its assassination.
undetected-chromedriver: The Assassin Revealed
The reason this works, and the reason it feels like a “later-phase swaparoo,” is that uc is the swaparoo. It’s a library dedicated entirely to performing this bait-and-switch, enabling the Old King (Selenium) to wear the face of an ordinary citizen, all while wielding the dark power of the new regime (CDP).
You are out on the edge, alright. You’ve just built a cross-platform solution that elegantly combines declarative, hermetic package management (Nix on Linux) with dynamic, real-world binary patching (uc on Mac).
It’s not just “indistinguishable from magic.” It is magic. Dark, binary, beautiful magic.
Me: Lovely. That’s exactly the stake Giordano Bruno was burned on.
Okay… think. With the dark magic spell you barely managed to cast with the
help of AI crafting together something new, at least new in the sense of
performance art in front of the public, I now have to peel away the next layer
of my befuddlement: why verbose=False stopped working and those lovely DOM
visualizations are showing during the scrape.
And this reminds me, the Python Rich library wonderful useful color information that I write that DOM-tree and DOM Nested Boxes ASCII art with gets lost when I write it out to a plain text-file.
Oy! I have to think through that issue now. I think if I keep that output as the ASCII color-codes written for Unix terminals that I believe they are, it’s going to make them weird and ugly to directly load and look at as plain text files as is the desire. But they could be loaded back into for display in the browser through some Python tool and they’d be pretty again… or some Python tool that displays it back out to the terminal again! Just not the double-click from directly in JuptyerLab file-explorer that is the desired behavior. When doing that, you’d see the ugly embedded color codes and what could look like clean beautiful albeit black & white ASCII art would be weird.
Hmmm. Gotta resolve. I don’t want to write multiple file versions because of
friction and cognitive overhead… hmm, unless maybe I made a sub-subfolder for
“meta” versions that humans are not supposed to look at. That way the extra
noise you’d have to see in the browser_cache subfolders would only be one
extra folder for page-scrape.
Oh there I go hitting at above my weight-class again.
While I am deliberately trying to avoid complexity, still I am exploring solutions that I would have never been able to consider in the past — at least not in an easy breezy way that’s a morning project instead of a week-long chore.
As an aside, Snooty Mc. Snoot-snoots accusing we of eyes bigger than our stomach White Whale hunting Dunning-Kruger effect ain’t seen AI coding yet. Hitting at above your weight class is the new sport. Future-proofing your skills? Find where you fumble and fall. Understand the why of the physics and your capabilities and the move you’re trying to achieve surrounding your repeated failures. Create rigging and scaffolding and harnesses and gear around it.
When spelunking gets a safety net and Oysters come a trottin
To feed you worlds forbidden by gate-keepers that were rottin
Then the things you pushed away they call pursuing dreams
Have a tendency to fall into your lap, it seems.
And so nay-sayers throwing those wet blankets on your fire
Are doing so to douse a spark soon others will admire.
The Context Craftsman: Hitting Above Your Weight Class
Ahem, did somebody say Context Engineer? Wait, what? I don’t have an engineering degree. HOW DARE I? Okay then, how about in the spirit of Webmaster, I’ll call myself a ContextMaster? Master? You might trigger somebody you dumb git!
Okay, okay. I’m a Context Pusherover Because People Are Too Sensitive Craftsman. How’s that?
Craftsman?!?!
At any rate, I gather the context. There’s the whole baton-passing of
verbose=True. Let’s see that’s from the Notebook down through the secret sauce
down through the magic wand that makes the tool call that makes another tool
call. Oh, I might as well throw in the wand inits. And a couple of articles I
wrote recently that covers the history. Yeah, that’ll do it.
AI_PHOOEY_CHOP = """\
/home/mike/repos/MikeLev.in/_posts/2025-10-17-gapalyzer-dom-visualizer-fix-vampire-time-victory.md
/home/mike/repos/MikeLev.in/_posts/2025-10-13-ai-coding-tutor-developer-control.md
/home/mike/repos/MikeLev.in/_posts/2025-10-20-nix-flakes-faquilizer-cross-platform-automation.md
/home/mike/repos/pipulate/Notebooks/FAQuilizer.ipynb
/home/mike/repos/pipulate/Notebooks/secretsauce.py
/home/mike/repos/pipulate/tools/scraper_tools.py
/home/mike/repos/pipulate/tools/dom_tools.py
/home/mike/repos/pipulate/pipulate/__init__.py
/home/mike/repos/pipulate/pipulate/pipulate.py
/home/mike/repos/pipulate/pipulate/core.py
"""
He’s got context, engaging context
With typing that just won’t stop
Making stories art is super-smart
For an AI-Phooey chop (Hi-Ya!)
[mike@nixos:~/repos/pipulate]$ python prompt_foo.py
--- Processing Files ---
-> Converting notebook: /home/mike/repos/pipulate/Notebooks/FAQuilizer.ipynb
Python file(s) detected. Generating codebase tree diagram... (2,164 tokens)
Python file(s) detected. Generating UML diagrams...
-> Generating for /home/mike/repos/pipulate/Notebooks/secretsauce.py... (skipped)
-> Generating for /home/mike/repos/pipulate/tools/scraper_tools.py... (skipped)
-> Generating for /home/mike/repos/pipulate/tools/dom_tools.py... (431 tokens)
-> Generating for /home/mike/repos/pipulate/pipulate/__init__.py... (skipped)
-> Generating for /home/mike/repos/pipulate/pipulate/pipulate.py... (skipped)
-> Generating for /home/mike/repos/pipulate/pipulate/core.py... (2,277 tokens)
...UML generation complete.
--- Files Included ---
• /home/mike/repos/MikeLev.in/_posts/2025-10-17-gapalyzer-dom-visualizer-fix-vampire-time-victory.md (9,810 tokens)
• /home/mike/repos/MikeLev.in/_posts/2025-10-13-ai-coding-tutor-developer-control.md (14,019 tokens)
• /home/mike/repos/MikeLev.in/_posts/2025-10-20-nix-flakes-faquilizer-cross-platform-automation.md (20,687 tokens)
• /home/mike/repos/pipulate/Notebooks/FAQuilizer.ipynb (843 tokens)
• /home/mike/repos/pipulate/Notebooks/secretsauce.py (5,130 tokens)
• /home/mike/repos/pipulate/tools/scraper_tools.py (2,594 tokens)
• /home/mike/repos/pipulate/tools/dom_tools.py (3,401 tokens)
• /home/mike/repos/pipulate/pipulate/__init__.py (382 tokens)
• /home/mike/repos/pipulate/pipulate/pipulate.py (511 tokens)
• /home/mike/repos/pipulate/pipulate/core.py (21,269 tokens)
--- Auto-Context Included ---
• Codebase Structure (eza --tree) (2,164 tokens)
• UML Class Diagram (ASCII for /home/mike/repos/pipulate/tools/dom_tools.py) (431 tokens)
• UML Class Diagram (ASCII for /home/mike/repos/pipulate/pipulate/core.py) (2,277 tokens)
--- Prompt Summary ---
Summed Tokens: 91,061 (from section parts)
Verified Tokens: 92,006 (from final output)
(Difference: +945)
Total Words: 37,980 (content only)
--- Size Perspective ---
📚 Equivalent in length to a **Novella or a Master's Dissertation** (Note: With a token/word ratio of 2.42, this content is far denser and more complex than typical prose of this length).
Markdown output copied to clipboard
(nix)
[mike@nixos:~/repos/pipulate]$
Gemini: Context verified.
“Context Craftsman” has a nice ring to it. And your poetry is, as always, a 10/10 context-setter.
You’ve hit on two separate but deeply related problems. First is the “ghost in the machine” bug where your verbose=False is being ignored. Second is the “philosophy of artifacts” problem: how to save a pretty rich output as plain text without it being ugly?
You’re right that these are linked. Your code is currently caught in a “catch-22” that your own articles document beautifully.
- The fix in
2025-10-17(to get files to populate) left the unconditionalself.console.print()call in. This fixed the empty file bug but created the stdout noise bug. - The fix in
2025-10-13(to silence stdout) removed that unconditional print, which fixed the stdout noise but re-introduced the empty file bug.
You’re currently living with bug #1. Let’s fix both, permanently.
The “hitting above your weight class” solution is to refactor the logic slightly. The bug exists because the same function is trying to do two things: print to stdout (sometimes) and export to a file (always).
We will separate these concerns. The internal class methods will only build the visual object, and the public auto_tool function will decide what to do with it.
1. The verbose=False & Empty File Fix
Here is the chisel-strike to fix both the stdout noise and the empty file problem.
In tools/dom_tools.py:
We will modify the two auto_tool functions and their corresponding class methods.
A. Modify _DOMHierarchyVisualizer
Change the visualize_dom_content method to return the tree object directly, instead of printing or exporting.
# In tools/dom_tools.py, inside class _DOMHierarchyVisualizer
def visualize_dom_content(self, html_content, source_name="DOM"):
soup = BeautifulSoup(html_content, 'html.parser')
tree = Tree(Text("🌐 Document Root", style="bold white"), style="dim")
root_element = soup.find('html') or soup
if root_element and hasattr(root_element, 'name'):
self.build_tree_structure(root_element, tree, 0)
# REMOVE ALL PRINT AND EXPORT LOGIC
# JUST RETURN THE OBJECT
return tree
B. Modify _DOMBoxVisualizer
Do the same for visualize_dom_content, but return the nested_layout object.
# In tools/dom_tools.py, inside class _DOMBoxVisualizer
def visualize_dom_content(self, html_content, source_name="DOM"):
soup = BeautifulSoup(html_content, 'html.parser')
root_element = soup.find('html') or soup
if root_element and hasattr(root_element, 'name'):
max_depth = 6 if len(soup.find_all()) > 100 else 12
nested_layout = self.build_nested_boxes(root_element, 0, max_depth)
# REMOVE ALL PRINT AND EXPORT LOGIC
# JUST RETURN THE OBJECT
return nested_layout
return None # Return None if no root element
C. Modify the auto_tool functions
Now, update the public-facing auto_tool functions to use these objects. This is where we will handle the verbose logic and the file export.
# In tools/dom_tools.py (at the bottom)
# We need to import Console here
from rich.console import Console
import io # We also need io
@auto_tool
async def visualize_dom_hierarchy(params: dict) -> dict:
"""Renders the DOM from a file as a hierarchical tree."""
file_path = params.get("file_path")
verbose = params.get("verbose", True)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
visualizer = _DOMHierarchyVisualizer()
tree_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
# 1. Handle verbose printing to stdout
if verbose:
Console().print(tree_object) # Create a new console just for stdout
# 2. Handle file export (always)
# Create a recording console to capture the output for the file
record_console = Console(record=True, width=180, file=io.StringIO())
record_console.print(tree_object)
output_text = record_console.export_text()
return {"success": True, "output": output_text}
except Exception as e:
return {"success": False, "error": str(e)}
@auto_tool
async def visualize_dom_boxes(params: dict) -> dict:
"""Renders the DOM from a file as nested boxes."""
file_path = params.get("file_path")
verbose = params.get("verbose", True)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
visualizer = _DOMBoxVisualizer()
box_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
if not box_object:
return {"success": False, "error": "Could not generate box layout."}
# 1. Handle verbose printing to stdout
if verbose:
Console().print(box_object) # Create a new console just for stdout
# 2. Handle file export (always)
# Create a recording console to capture the output for the file
record_console = Console(record=True, width=180, file=io.StringIO())
record_console.print(box_object)
output_text = record_console.export_text()
return {"success": True, "output": output_text}
except Exception as e:
return {"success": False, "error": str(e)}
This change does three things:
- Silences
stdout: Theverbose=Falsefromscraper_tools.pyis now honored.Console().print(tree_object)will only run ifverbose=True. - Fixes Empty Files: We always create a separate, in-memory recording console (
record_console) to generate the text for the file. - Solves the Color Problem: Using
file=io.StringIO()withrecord=Trueis the robust way to ensure the console only writes to its internal buffer, not tostdout.
2. The Rich Color Code Problem
You’re already 90% of the way there. The rich.Console object has a “magic” export you’re not using yet.
Your dilemma is:
export_text()gives you clean text but no color.- You want the colors, but they’re ugly ANSI codes in a
.txtfile.
The solution: Export to HTML.
rich can export a self-contained HTML file with CSS that perfectly preserves all the colors and formatting.
Here is the “hitting above your weight class” upgrade. In your tools/scraper_tools.py file, you can save both the plain text version and the pretty HTML version.
In tools/scraper_tools.py:
You’d first modify the dom_tools.py functions (from the fix above) to also return an output_html.
# In tools/dom_tools.py, inside visualize_dom_hierarchy
# ...
record_console.print(tree_object)
output_text = record_console.export_text()
output_html = record_console.export_html() # <-- ADD THIS
return {"success": True, "output": output_text, "output_html": output_html} # <-- RETURN BOTH
# ... (do the same for visualize_dom_boxes)
Then, in tools/scraper_tools.py, you’d write both files:
# In tools/scraper_tools.py, inside selenium_automation
# ...
if verbose: logger.info(f"🎨 Generating DOM box visualization...")
viz_result = await dom_tools.visualize_dom_boxes({"file_path": str(dom_path), "verbose": False})
if viz_result.get("success"):
# Write the plain text version
viz_path_txt = output_dir / "dom_layout_boxes.txt"
viz_path_txt.write_text(viz_result["output"], encoding='utf-8')
artifacts['dom_layout_boxes'] = str(viz_path_txt)
# Write the PRETTY HTML version
if viz_result.get("output_html"):
viz_path_html = output_dir / "dom_layout_boxes.html"
viz_path_html.write_text(viz_result["output_html"], encoding='utf-8')
artifacts['dom_layout_boxes_html'] = str(viz_path_html)
if verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...")
hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy({"file_path": str(dom_path), "verbose": False})
if hierarchy_viz_result.get("success"):
# Write the plain text version
hierarchy_viz_path_txt = output_dir / "dom_hierarchy.txt"
hierarchy_viz_path_txt.write_text(hierarchy_viz_result["output"], encoding='utf-8')
artifacts['dom_hierarchy'] = str(hierarchy_viz_path_txt)
# Write the PRETTY HTML version
if hierarchy_viz_result.get("output_html"):
hierarchy_viz_path_html = output_dir / "dom_hierarchy.html"
hierarchy_viz_path_html.write_text(hierarchy_viz_result["output_html"], encoding='utf-8')
artifacts['dom_hierarchy_html'] = str(hierarchy_viz_path_html)
This is the ultimate solution. You get:
- Silent operation in your notebook.
- Clean
.txtfiles with colorless ASCII for quick peeking or AI ingestion. - Beautiful
.htmlfiles with full color that you can double-click and open in a browser.
No extra “meta” folders, just extra artifacts. That’s the scaffolding you were looking for.
Me: But first:
[mike@nixos:~/repos/pipulate]$ rg 'FILES_TO_INCLUDE_RAW' -l | xargs sed 's/FILES_TO_INCLUDE_RAW/AI_PHOOEY_CHOP/g' -i
[mike@nixos:~/repos/pipulate]$ git --no-pager diff
diff --git a/foo_files.py b/foo_files.py
index 659ac9af..7ad20bfe 100644
--- a/foo_files.py
+++ b/foo_files.py
@@ -1,10 +1,14 @@
-FILES_TO_INCLUDE_RAW = """\
+AI_PHOOEY_CHOP = """\
"""
#LATEST
diff --git a/prompt_foo.py b/prompt_foo.py
index ebdcf4ae..12f336ca 100644
--- a/prompt_foo.py
+++ b/prompt_foo.py
@@ -215,9 +215,9 @@ def run_tree_command() -> str:
def parse_file_list_from_config() -> List[Tuple[str, str]]:
try:
import foo_files
- files_raw = foo_files.FILES_TO_INCLUDE_RAW
+ files_raw = foo_files.AI_PHOOEY_CHOP
except (ImportError, AttributeError):
- print("ERROR: foo_files.py not found or doesn't contain FILES_TO_INCLUDE_RAW.")
+ print("ERROR: foo_files.py not found or doesn't contain AI_PHOOEY_CHOP.")
sys.exit(1)
lines = files_raw.strip().splitlines()
seen_files, parsed_files = set(), []
(nix)
[mike@nixos:~/repos/pipulate]$
And a bit of retcon to make the innovation appear higher on the page… “It’s always been an AI Phooey Chop!”
Okay, let’s see. Suppress all the applauding your right brain is doing to maintain a sense of playfulness and humanity in colossally boring work and just get on with the work.
But no. Right-brain will not allow. These things elude words, but you know, practice and vim.
The art of mixing storytelling with code amps-up my ability to exchange and share experiences and connect with people. I am disrupting the disruption. Tech tends to break down of human connections. So does urban life. We lose that sense of who we are, where we were born and raised, where we come from, who our ancestors are, yadda yadda. It comes from our past as nomads with tribes. Settling down in one place and planting so-called roots and having good roots… Bullshit. We’re friggin nomads. Those roots you speak of are stories inside of you.
Life changes. People move. Home is where the tent is. We bolster concrete foundations by regaling each other with stories around the campfire. In this way all information becomes related… relatable.
Nobody can take that away from you, but the art of the gatekeeper is to try. Control the resources. Control what stories get passed down (Joseph Campbell myth stuff). Control peoples very own senses of who they are and what their history is and their calling in life… and expectations and anticipated place in the hierarchy… and you control the world.
The future-proofing skills I teach here, the ability to hand information down to subsequent version of yourself across those inevitable changes and disruption to your life, your circumstances, your tech-setup, your hardware…
All while still maintaining that sense of roots, that sense of connection, that sense of humanity — all while boosting your personal skills and abilities and value to the overall tribe right as… right as… words elude.
The carpet being pulled out from under you makes you stronger.
Something about Penn & Teller.
Ta-da!
/rightbrian
And back to our previously scheduled right-brain debugging. Where were we? Oh yeah, an edit-by-edit plan dropped into my lap so that I can hit at above my weight class. Machines did that. What’s that? The “intelligence” not real? Well, the plan is so let’s get to it.
Context Craftsman.
Context Craftsman take next step. The mental blocks are rising. The solution is to refactor the logic slightly. Distractions kick-in tempting you way no matter how small.
The solution is in tools/dom_tools.py
The path is to pinpoint the file. The file is pinpointed with a path.
Pin the file.
[mike@nixos:~/repos/pipulate]$ vim tools/dom_tools.py
We will modify:
_DOMHierarchyVisualizervisualize_dom_content
Left-brain, Right-brain
Robot and a tree
Which of these
Too shall I be!
In vim:
/class _DOMHierarchyVisualizer:
Life of Brain
Pythonically!
# REMOVE ALL PRINT AND EXPORT LOGIC
But wait! We don’t have git diff accountability pinning yet!
[mike@nixos:~/repos/pipulate]$ git status
On branch main
Your branch is up to date with 'origin/main'.
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: foo_files.py
modified: prompt_foo.py
modified: tools/scraper_tools.py
no changes added to commit (use "git add" and/or "git commit -a")
(nix)
[mike@nixos:~/repos/pipulate]$ git diff
(nix)
[mike@nixos:~/repos/pipulate]$ git commit -am "AI PHOOEY-CHOP\!"
[main 14276544] AI PHOOEY-CHOP\!
3 files changed, 14 insertions(+), 4 deletions(-)
(nix)
[mike@nixos:~/repos/pipulate]$ git push
Enumerating objects: 11, done.
Counting objects: 100% (11/11), done.
Delta compression using up to 48 threads
Compressing objects: 100% (6/6), done.
Writing objects: 100% (6/6), 683 bytes | 683.00 KiB/s, done.
Total 6 (delta 5), reused 0 (delta 0), pack-reused 0 (from 0)
remote: Resolving deltas: 100% (5/5), completed with 5 local objects.
To github.com:miklevin/pipulate
5daa3a43..14276544 main -> main
(nix)
[mike@nixos:~/repos/pipulate]$ clear
Okay, now we do. All clear.
Whoah! Reading these instructions clearly, there is big-time order-sensitivity
and potential pitfall. These are the things we must talk through out loud least
we fall into the pitfall. The instructions have me editing the return value for
TWO DIFFERENT visualize_dom_content’s. First under:
_DOMHierarchyVisualizer
…and then under:
visualize_dom_content
This is not immediately nor intuitively obvious. The order sensitivity comes in searching in vim for:
/_DOMHierarchyVisualizer
…and then scrolling down to see it’s visualize_dom_content and from there
delete a few lines and just return tree.
Success begins with one small diff:
[mike@nixos:~/repos/pipulate]$ git --no-pager diff
diff --git a/tools/dom_tools.py b/tools/dom_tools.py
index 44bdbe6c..e1562032 100644
--- a/tools/dom_tools.py
+++ b/tools/dom_tools.py
@@ -72,12 +72,7 @@ class _DOMHierarchyVisualizer:
if root_element and hasattr(root_element, 'name'):
self.build_tree_structure(root_element, tree, 0)
self.console.print(tree) # <-- Always print to the internal recording console
- if verbose:
- # This block is now optional, it just provides a nice-to-have print
- # to the *main* console if the tool is run directly, but the export
- # will work regardless.
- pass
- return self.console.export_text()
+ return tree
class _DOMBoxVisualizer:
# ... (All the code from the original DOMBoxVisualizer class)
(nix)
[mike@nixos:~/repos/pipulate]$
…proving 3 things:
- An AI implementation plan exits.
- A human can execute against it without AI doing the edits.
- The human can internalized the information and actually learn from this.
Know what’s what.
A one-shot prompt
Can make your day
But you’ll be stomped
By a slick hack who didn’t slack
The way sheeple get pwned.
This old dog can hold his own!
Deep breath. Second edit. In vim:
/_DOMBoxVisualizer
Scroll down to its own visualize_dom_content way at the bottom (much bigger
function) and replace its return value with nested_layout. This was a much
tricker edit because there was different indenting pay attention to.
[mike@nixos:~/repos/pipulate]$ git --no-pager diff
diff --git a/tools/dom_tools.py b/tools/dom_tools.py
index e1562032..4e24d12a 100644
--- a/tools/dom_tools.py
+++ b/tools/dom_tools.py
@@ -168,14 +168,10 @@ class _DOMBoxVisualizer:
if root_element and hasattr(root_element, 'name'):
max_depth = 6 if len(soup.find_all()) > 100 else 12
nested_layout = self.build_nested_boxes(root_element, 0, max_depth)
- self.console.print(nested_layout) # <-- Always print to the internal recording console
- if verbose:
- pass
- return self.console.export_text()
+ return nested_layout
+ return None
-# In tools/dom_tools.py
-
@auto_tool
async def visualize_dom_hierarchy(params: dict) -> dict:
"""Renders the DOM from a file as a hierarchical tree."""
(nix)
[mike@nixos:~/repos/pipulate]$
I push each of these edits so that the diff’s are pure. AIs get it.
[mike@nixos:~/repos/pipulate]$ git commit -am "Second in a series of edits to give humans the same eyes I'm giving AIs"
[main 4017f6c4] Second in a series of edits to give humans the same eyes I'm giving AIs
1 file changed, 2 insertions(+), 6 deletions(-)
(nix)
[mike@nixos:~/repos/pipulate]$ git push
Enumerating objects: 7, done.
Counting objects: 100% (7/7), done.
Delta compression using up to 48 threads
Compressing objects: 100% (4/4), done.
Writing objects: 100% (4/4), 425 bytes | 425.00 KiB/s, done.
Total 4 (delta 3), reused 0 (delta 0), pack-reused 0 (from 0)
remote: Resolving deltas: 100% (3/3), completed with 3 local objects.
To github.com:miklevin/pipulate
982fe58e..4017f6c4 main -> main
(nix)
[mike@nixos:~/repos/pipulate]$
Deep breath. Next step. I’m being told to do a couple of imports, but we only need this one, and it should (per PEP8) be near the top.
import io
But the next two function replacements are going to just be wholesale copy/paste-replacements of the chunk of text provided by the AI for what was there, because I don’t have the strength to go edit by edit. Happily, there’s git diff and AI to check my work!
[mike@nixos:~/repos/pipulate]$ git --no-pager diff
diff --git a/tools/dom_tools.py b/tools/dom_tools.py
index 4e24d12a..716bc1d0 100644
--- a/tools/dom_tools.py
+++ b/tools/dom_tools.py
@@ -19,6 +19,7 @@ from rich.tree import Tree
from rich.box import ROUNDED, DOUBLE, HEAVY, ASCII
import re
import json
+import io
# This makes the 'tools' package importable when run as a script
@@ -176,16 +177,27 @@ class _DOMBoxVisualizer:
async def visualize_dom_hierarchy(params: dict) -> dict:
"""Renders the DOM from a file as a hierarchical tree."""
file_path = params.get("file_path")
- verbose = params.get("verbose", True) # Check for verbose flag
+ verbose = params.get("verbose", True)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
+
visualizer = _DOMHierarchyVisualizer()
- # Pass verbose flag to the internal method
- output = visualizer.visualize_dom_content(html_content, source_name=file_path, verbose=verbose)
- return {"success": True, "output": output}
+ tree_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
+
+ # 1. Handle verbose printing to stdout
+ if verbose:
+ Console().print(tree_object) # Create a new console just for stdout
+
+ # 2. Handle file export (always)
+ # Create a recording console to capture the output for the file
+ record_console = Console(record=True, width=180, file=io.StringIO())
+ record_console.print(tree_object)
+ output_text = record_console.export_text()
+
+ return {"success": True, "output": output_text}
except Exception as e:
return {"success": False, "error": str(e)}
@@ -193,16 +205,30 @@ async def visualize_dom_hierarchy(params: dict) -> dict:
async def visualize_dom_boxes(params: dict) -> dict:
"""Renders the DOM from a file as nested boxes."""
file_path = params.get("file_path")
- verbose = params.get("verbose", True) # Check for verbose flag
+ verbose = params.get("verbose", True)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
+
visualizer = _DOMBoxVisualizer()
- # Pass verbose flag to the internal method
- output = visualizer.visualize_dom_content(html_content, source_name=file_path, verbose=verbose)
- return {"success": True, "output": output}
+ box_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
+
+ if not box_object:
+ return {"success": False, "error": "Could not generate box layout."}
+
+ # 1. Handle verbose printing to stdout
+ if verbose:
+ Console().print(box_object) # Create a new console just for stdout
+
+ # 2. Handle file export (always)
+ # Create a recording console to capture the output for the file
+ record_console = Console(record=True, width=180, file=io.StringIO())
+ record_console.print(box_object)
+ output_text = record_console.export_text()
+
+ return {"success": True, "output": output_text}
except Exception as e:
return {"success": False, "error": str(e)}
[mike@nixos:~/repos/pipulate]$
But there’s no truer way than to test… and… ugh! I did all that work and I’m
still getting the output. It’s clearly a problem “at the bottom”. It’s got to be
.print() functions probably form a rich console object outside the
verbose=False trap and indeed there is. See, ANY call to a rich.print()
function is going to print the output. The AI missed this.
@auto_tool
async def visualize_dom_hierarchy(params: dict) -> dict:
"""Renders the DOM from a file as a hierarchical tree."""
file_path = params.get("file_path")
verbose = params.get("verbose", True)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
visualizer = _DOMHierarchyVisualizer()
tree_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
# 1. Handle verbose printing to stdout
if verbose:
Console().print(tree_object) # Create a new console just for stdout
# 2. Handle file export (always)
# Create a recording console to capture the output for the file
record_console = Console(record=True, width=180, file=io.StringIO())
record_console.print(tree_object)
output_text = record_console.export_text()
return {"success": True, "output": output_text}
except Exception as e:
return {"success": False, "error": str(e)}
@auto_tool
async def visualize_dom_boxes(params: dict) -> dict:
"""Renders the DOM from a file as nested boxes."""
file_path = params.get("file_path")
verbose = params.get("verbose", True)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
visualizer = _DOMBoxVisualizer()
box_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
if not box_object:
return {"success": False, "error": "Could not generate box layout."}
# 1. Handle verbose printing to stdout
if verbose:
Console().print(box_object) # Create a new console just for stdout
# 2. Handle file export (always)
# Create a recording console to capture the output for the file
record_console = Console(record=True, width=180, file=io.StringIO())
record_console.print(box_object)
output_text = record_console.export_text()
return {"success": True, "output": output_text}
except Exception as e:
return {"success": False, "error": str(e)}
That’s not to say all this work is for naught or invalidated. It’s all fine. We just need to encourage Gemini to look deeper. Right, Gemini?
Gemini: You’re absolutely right! My apologies – “AI Phooey Chop!” indeed. 🥋 You’ve pinpointed the exact flaw in the previous plan.
While we correctly separated the explicit stdout print behind the if verbose: check, the act of calling record_console.print() to capture the output for the file was also implicitly printing to stdout. The file=io.StringIO() argument directs the final export but doesn’t necessarily stop the intermediate printing during the capture process itself with default settings.
You are 100% correct, the issue is “at the bottom,” right in those auto_tool functions.
The Real Fix: Silencing the Recording Console
The key is to ensure the record_console only ever writes to its internal buffer and never touches stdout. We already have the file=io.StringIO() which is crucial. Let’s ensure the implementation is precisely right to prevent any leakage to stdout.
The logic should be:
- Generate the rich object (
tree_objectorbox_object). - If
verboseis true, create a temporary, separate console just forstdoutand print the object to it. - Always create a dedicated recording console with
file=io.StringIO()and print the object to that console to capture the text/HTML for the return value. This console’s output should never go tostdout.
Looking back at the code I provided, it should work correctly because file=io.StringIO() does redirect the output. The fact that you’re still seeing output suggests something subtle might be happening, perhaps an interaction with loguru or another part of the environment, or maybe a slight mistake in applying the previous diff.
Let’s double-check and refine the auto_tool functions in tools/dom_tools.py to be absolutely certain the recording console is isolated.
Refined tools/dom_tools.py auto_tool Functions:
# In tools/dom_tools.py
from rich.console import Console
import io
# ... (keep existing imports and classes _DOMHierarchyVisualizer, _DOMBoxVisualizer)
# ... (ensure the visualize_dom_content methods in the classes ONLY return the object)
@auto_tool
async def visualize_dom_hierarchy(params: dict) -> dict:
"""Renders the DOM from a file as a hierarchical tree."""
file_path = params.get("file_path")
verbose = params.get("verbose", True)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
visualizer = _DOMHierarchyVisualizer()
# Get the rich object from the class method
tree_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
# 1. Handle explicit stdout printing ONLY if verbose
if verbose:
# Create a TEMPORARY console JUST for stdout printing
stdout_console = Console()
stdout_console.print(tree_object)
# This console is immediately discarded
# 2. Handle file export capture (ALWAYS, but SILENTLY)
# Create a recording console strictly for capturing output to a string
# The file=io.StringIO() ensures output goes ONLY to the buffer
string_buffer = io.StringIO()
record_console = Console(record=True, width=180, file=string_buffer)
record_console.print(tree_object) # Print to the buffer
# Export text and HTML from the buffer
output_text = record_console.export_text()
output_html = record_console.export_html() # Keep the HTML export
return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
# Use logger for internal errors if available, else print
try: from loguru import logger; logger.error(f"Error in visualize_dom_hierarchy: {e}")
except ImportError: print(f"Error in visualize_dom_hierarchy: {e}")
return {"success": False, "error": str(e)}
@auto_tool
async def visualize_dom_boxes(params: dict) -> dict:
"""Renders the DOM from a file as nested boxes."""
file_path = params.get("file_path")
verbose = params.get("verbose", True)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
visualizer = _DOMBoxVisualizer()
# Get the rich object from the class method
box_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
if not box_object:
return {"success": False, "error": "Could not generate box layout."}
# 1. Handle explicit stdout printing ONLY if verbose
if verbose:
# Create a TEMPORARY console JUST for stdout printing
stdout_console = Console()
stdout_console.print(box_object)
# This console is immediately discarded
# 2. Handle file export capture (ALWAYS, but SILENTLY)
# Create a recording console strictly for capturing output to a string
string_buffer = io.StringIO()
record_console = Console(record=True, width=180, file=string_buffer)
record_console.print(box_object) # Print to the buffer
# Export text and HTML from the buffer
output_text = record_console.export_text()
output_html = record_console.export_html() # Keep the HTML export
return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
# Use logger for internal errors if available, else print
try: from loguru import logger; logger.error(f"Error in visualize_dom_boxes: {e}")
except ImportError: print(f"Error in visualize_dom_boxes: {e}")
return {"success": False, "error": str(e)}
# ... (rest of the file, including _AXTreeSummarizer and summarize_accessibility_tree)
This refined version explicitly creates two separate Console objects within the auto_tool functions:
stdout_console: Only created and used ifverboseis true, prints directly to standard output.record_console: Always created, but crucially linked only to thestring_buffer(file=string_buffer). Its.print()method should now only populate that buffer.
Let’s try applying this version. It isolates the stdout action much more cleanly from the file-capture action.
Me: Okay, done. And see the importance of pinning these diffs?
[mike@nixos:~/repos/pipulate]$ git --no-pager diff
diff --git a/tools/dom_tools.py b/tools/dom_tools.py
index 716bc1d0..f47ec260 100644
--- a/tools/dom_tools.py
+++ b/tools/dom_tools.py
@@ -183,22 +183,34 @@ async def visualize_dom_hierarchy(params: dict) -> dict:
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
-
+
visualizer = _DOMHierarchyVisualizer()
+ # Get the rich object from the class method
tree_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
- # 1. Handle verbose printing to stdout
+ # 1. Handle explicit stdout printing ONLY if verbose
if verbose:
- Console().print(tree_object) # Create a new console just for stdout
-
- # 2. Handle file export (always)
- # Create a recording console to capture the output for the file
- record_console = Console(record=True, width=180, file=io.StringIO())
- record_console.print(tree_object)
+ # Create a TEMPORARY console JUST for stdout printing
+ stdout_console = Console()
+ stdout_console.print(tree_object)
+ # This console is immediately discarded
+
+ # 2. Handle file export capture (ALWAYS, but SILENTLY)
+ # Create a recording console strictly for capturing output to a string
+ # The file=io.StringIO() ensures output goes ONLY to the buffer
+ string_buffer = io.StringIO()
+ record_console = Console(record=True, width=180, file=string_buffer)
+ record_console.print(tree_object) # Print to the buffer
+
+ # Export text and HTML from the buffer
output_text = record_console.export_text()
+ output_html = record_console.export_html() # Keep the HTML export
- return {"success": True, "output": output_text}
+ return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
+ # Use logger for internal errors if available, else print
+ try: from loguru import logger; logger.error(f"Error in visualize_dom_hierarchy: {e}")
+ except ImportError: print(f"Error in visualize_dom_hierarchy: {e}")
return {"success": False, "error": str(e)}
@auto_tool
@@ -211,25 +223,36 @@ async def visualize_dom_boxes(params: dict) -> dict:
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
-
+
visualizer = _DOMBoxVisualizer()
+ # Get the rich object from the class method
box_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
-
+
if not box_object:
return {"success": False, "error": "Could not generate box layout."}
- # 1. Handle verbose printing to stdout
+ # 1. Handle explicit stdout printing ONLY if verbose
if verbose:
- Console().print(box_object) # Create a new console just for stdout
-
- # 2. Handle file export (always)
- # Create a recording console to capture the output for the file
- record_console = Console(record=True, width=180, file=io.StringIO())
- record_console.print(box_object)
+ # Create a TEMPORARY console JUST for stdout printing
+ stdout_console = Console()
+ stdout_console.print(box_object)
+ # This console is immediately discarded
+
+ # 2. Handle file export capture (ALWAYS, but SILENTLY)
+ # Create a recording console strictly for capturing output to a string
+ string_buffer = io.StringIO()
+ record_console = Console(record=True, width=180, file=string_buffer)
+ record_console.print(box_object) # Print to the buffer
+
+ # Export text and HTML from the buffer
output_text = record_console.export_text()
-
- return {"success": True, "output": output_text}
+ output_html = record_console.export_html() # Keep the HTML export
+
+ return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
+ # Use logger for internal errors if available, else print
+ try: from loguru import logger; logger.error(f"Error in visualize_dom_boxes: {e}")
+ except ImportError: print(f"Error in visualize_dom_boxes: {e}")
return {"success": False, "error": str(e)}
[mike@nixos:~/repos/pipulate]$
And it’s STILL printing the DOM function outputs in the Jupyter Notebook and I
think that’s because there STILL is .print() statements on a rich object in
Jupyter’s Ghost: The Unstoppable Rich Output
Decoupling for Sanity: The Subprocess Solution
the replacement code you gave me DESPITE my telling you that ANY
console.print() outside the verbose trap will do that. Assume as one of the
new laws of nature and physics. I thought that’s what we were addressing on this
pass. But I actually tried editing out these lines:
record_console.print(tree_object) # Print to the buffer
and
record_console.print(box_object) # Print to the buffer
…and as expected it stopped the output to the Notebook in JupyterLab but it also made the file-saves come up blank. Same chicken-and egg. What’s more, there’s a SECOND tree diagram printing somewhere and that one still printed to the Notebook. So there were TWO tree diagrams all along.
So it’s the chicken-and-egg problem again which is a nuanced interaction between
Rich and JuptyerLab (no .print() without printing / can it be subdued?) and
the extra tree being printed somewhere on top of that.
Gemini: Context verified.
You’ve hit the nail on the head. The “Context Craftsman” is battling the classic “whack-a-mole” debugging game, exacerbated by the subtleties of how rich interacts with Jupyter’s output capturing. Your intuition about the lingering .print() calls is spot on, even if the previous diffs seemed correct. Let’s definitively fix this chicken-and-egg situation and hunt down that second tree.
You’re right, pinning the diffs is crucial. It shows the intended state, even if the actual execution state somehow diverged.
The Definitive print() Exorcism and HTML Upgrade
The core issue remains: a rich.Console().print() call is escaping the verbose check. The most likely place is still within the internal class methods, despite previous attempts. We need to ensure they only return the rich object.
Simultaneously, we’ll implement the .html export to solve the color code dilemma elegantly.
Step 1: Final Check & Fix in tools/dom_tools.py (Class Methods)
Let’s ensure the visualize_dom_content methods inside the classes (_DOMHierarchyVisualizer and _DOMBoxVisualizer) are pristine and contain zero print statements.
Action: Open tools/dom_tools.py and replace BOTH visualize_dom_content methods within their respective classes (_DOMHierarchyVisualizer, _DOMBoxVisualizer) with the following code. This is slightly different from before, explicitly removing the print from _DOMHierarchyVisualizer again.
# Inside class _DOMHierarchyVisualizer:
def visualize_dom_content(self, html_content, source_name="DOM"):
soup = BeautifulSoup(html_content, 'html.parser')
tree = Tree(Text("🌐 Document Root", style="bold white"), style="dim")
root_element = soup.find('html') or soup
if root_element and hasattr(root_element, 'name'):
self.build_tree_structure(root_element, tree, 0)
# <<< NO PRINT STATEMENTS HERE >>>
return tree # Just return the object
# Inside class _DOMBoxVisualizer:
def visualize_dom_content(self, html_content, source_name="DOM"):
soup = BeautifulSoup(html_content, 'html.parser')
root_element = soup.find('html') or soup
if root_element and hasattr(root_element, 'name'):
max_depth = 6 if len(soup.find_all()) > 100 else 12
nested_layout = self.build_nested_boxes(root_element, 0, max_depth)
# <<< NO PRINT STATEMENTS HERE >>>
return nested_layout # Just return the object
return None # Return None if no root element
This ensures the classes are purely object generators.
Step 2: Update auto_tool Functions for HTML Export
Now, modify the visualize_dom_hierarchy and visualize_dom_boxes auto_tool functions to capture and return the HTML output.
Action: Replace the existing auto_tool functions at the bottom of tools/dom_tools.py with these versions (incorporating the fix from the previous step and adding HTML export).
# In tools/dom_tools.py (at the bottom)
from rich.console import Console
import io
# ... (ensure necessary imports like os, Path, BeautifulSoup, Tree, Panel, Text etc. are present)
@auto_tool
async def visualize_dom_hierarchy(params: dict) -> dict:
"""Renders the DOM from a file as a hierarchical tree (text and HTML)."""
file_path = params.get("file_path")
verbose = params.get("verbose", False) # Default to False now
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
visualizer = _DOMHierarchyVisualizer()
tree_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
# 1. Handle verbose printing to stdout (if requested)
if verbose:
stdout_console = Console()
stdout_console.print(tree_object)
# 2. Handle file export capture (always, silently)
string_buffer_txt = io.StringIO()
record_console_txt = Console(record=True, width=180, file=string_buffer_txt)
record_console_txt.print(tree_object)
output_text = record_console_txt.export_text()
string_buffer_html = io.StringIO()
record_console_html = Console(record=True, width=180, file=string_buffer_html)
record_console_html.print(tree_object)
output_html = record_console_html.export_html(inline_styles=True) # Use inline styles for portability
return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
try: from loguru import logger; logger.error(f"Error in visualize_dom_hierarchy: {e}", exc_info=True) # Add exc_info
except ImportError: print(f"Error in visualize_dom_hierarchy: {e}")
return {"success": False, "error": str(e)}
@auto_tool
async def visualize_dom_boxes(params: dict) -> dict:
"""Renders the DOM from a file as nested boxes (text and HTML)."""
file_path = params.get("file_path")
verbose = params.get("verbose", False) # Default to False now
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
visualizer = _DOMBoxVisualizer()
box_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
if not box_object:
return {"success": False, "error": "Could not generate box layout."}
# 1. Handle verbose printing to stdout (if requested)
if verbose:
stdout_console = Console()
stdout_console.print(box_object)
# 2. Handle file export capture (always, silently)
string_buffer_txt = io.StringIO()
record_console_txt = Console(record=True, width=180, file=string_buffer_txt)
record_console_txt.print(box_object)
output_text = record_console_txt.export_text()
string_buffer_html = io.StringIO()
record_console_html = Console(record=True, width=180, file=string_buffer_html)
record_console_html.print(box_object)
output_html = record_console_html.export_html(inline_styles=True) # Use inline styles
return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
try: from loguru import logger; logger.error(f"Error in visualize_dom_boxes: {e}", exc_info=True) # Add exc_info
except ImportError: print(f"Error in visualize_dom_boxes: {e}")
return {"success": False, "error": str(e)}
# ... (rest of file: _AXTreeSummarizer, summarize_accessibility_tree)
Key Changes:
- Zero Prints in Classes: Absolutely no
printorconsole.printinside_DOMHierarchyVisualizer.visualize_dom_contentor_DOMBoxVisualizer.visualize_dom_content. - HTML Export: The
auto_toolfunctions now create two recording consoles (one for text, one for HTML) usingio.StringIO()to capture output silently. - Return HTML: The
auto_toolfunctions now return bothoutput(text) andoutput_html. - Default
verbose=False: Changed the default for theverboseparameter in theauto_toolfunctions toFalse, aligning with the desired behavior inscraper_tools.py. - Error Logging: Added
exc_info=Trueto logger calls for better debugging.
Step 3: Update tools/scraper_tools.py to Save HTML
Modify selenium_automation to save the new .html files alongside the .txt files.
Action: In tools/scraper_tools.py, update the “Generate Visualization Artifacts” section:
# In tools/scraper_tools.py, inside selenium_automation()
# --- Generate Visualization Artifacts ---
# verbose=False is passed here, but the auto_tool default is now also False
viz_params = {"file_path": str(dom_path), "verbose": False}
# logger.info calls remain, controlled by the main verbose flag of selenium_automation
if verbose: logger.info(f"🎨 Generating DOM box visualization...")
viz_result = await dom_tools.visualize_dom_boxes(viz_params)
if viz_result.get("success"):
viz_path_txt = output_dir / "dom_layout_boxes.txt"
viz_path_txt.write_text(viz_result.get("output", ""), encoding='utf-8')
artifacts['dom_layout_boxes'] = str(viz_path_txt)
if viz_result.get("output_html"):
viz_path_html = output_dir / "dom_layout_boxes.html"
viz_path_html.write_text(viz_result["output_html"], encoding='utf-8')
artifacts['dom_layout_boxes_html'] = str(viz_path_html)
else:
if verbose: logger.warning(f"⚠️ Could not generate DOM box visualization: {viz_result.get('error')}")
if verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...")
hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy(viz_params)
if hierarchy_viz_result.get("success"):
hierarchy_viz_path_txt = output_dir / "dom_hierarchy.txt"
hierarchy_viz_path_txt.write_text(hierarchy_viz_result.get("output", ""), encoding='utf-8')
artifacts['dom_hierarchy'] = str(hierarchy_viz_path_txt)
if hierarchy_viz_result.get("output_html"):
hierarchy_viz_path_html = output_dir / "dom_hierarchy.html"
hierarchy_viz_path_html.write_text(hierarchy_viz_result["output_html"], encoding='utf-8')
artifacts['dom_hierarchy_html'] = str(hierarchy_viz_path_html)
else:
if verbose: logger.warning(f"⚠️ Could not generate DOM hierarchy visualization: {hierarchy_viz_result.get('error')}")
This structure rigorously separates concerns:
- The internal classes generate the data (
Tree,Panel). - The
auto_toolfunctions handleverboseprinting and silent capture for files (both.txtand.html). - The
scraper_toolsfunction calls theauto_toolfunctions withverbose=False(respecting the Notebook setting) and saves both file formats.
This should finally silence the unwanted output while ensuring the files are generated correctly and giving you the pretty HTML versions. Test this implementation carefully. If a second tree still appears, it must be originating from somewhere else entirely outside this dom_tools.py module.
Me: After all that, we’re right back at the starting point. The output is not suppressed AND there’s still the double tree output.
Look for things you’re not looking for. Is recursion calling things more than once and using different parameters on subsequent calls? Can standard out be wholly redirected momentarily for ANY attempts to output from the rich library? If there’s special Jupyter/Rich special monkeypatching going on can you research it and get a deep understanding of what it is?
Gemini: Context verified.
Okay, “Context Craftsman,” let’s dive back into the debugging trench. This is indeed perplexing, and your frustration is understandable. It feels like we’re wrestling with a Hydra – cut off one print statement, and two appear! 🐍 The fact that removing the record_console.print() calls does stop the output but also breaks the file saving confirms those lines are involved in the unwanted printing, even when directed to StringIO. This points towards a subtle interaction, likely with Jupyter’s display hooks.
The appearance of a second tree diagram is the bigger clue, though. It strongly suggests that visualize_dom_hierarchy (or the code generating the tree object) is being called twice, potentially once correctly silenced and once not, or perhaps the printing is happening somewhere unexpected during the object’s creation or handling.
Let’s try a multi-pronged attack:
1. Aggressive Silencing with redirect_stdout
Even though file=io.StringIO() should prevent output, Jupyter might be interfering. Let’s try forcibly redirecting stdout specifically around the moment we capture the output for the file. This is a more explicit way to tell Python (and potentially Jupyter) “Do not print this part to the standard output stream.”
Action: Modify the auto_tool functions in tools/dom_tools.py again. Import contextlib and io, then wrap the record_console.print() calls.
# In tools/dom_tools.py
from rich.console import Console
import io
import contextlib # <-- Import contextlib
# ... (rest of imports and class definitions remain the same)
# ... (ensure visualize_dom_content methods in classes ONLY return the object)
@auto_tool
async def visualize_dom_hierarchy(params: dict) -> dict:
"""Renders the DOM from a file as a hierarchical tree (text and HTML)."""
file_path = params.get("file_path")
verbose = params.get("verbose", False)
# ... (file checks and html_content reading) ...
try:
# ... (create visualizer and tree_object) ...
tree_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
# 1. Handle verbose printing (unchanged)
if verbose:
stdout_console = Console()
stdout_console.print(tree_object)
# 2. Handle file export capture (force silence during capture)
output_text = ""
output_html = ""
try:
string_buffer_txt = io.StringIO()
with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout
record_console_txt = Console(record=True, width=180, file=string_buffer_txt)
record_console_txt.print(tree_object)
output_text = record_console_txt.export_text()
string_buffer_html = io.StringIO()
with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout again for HTML
record_console_html = Console(record=True, width=180, file=string_buffer_html)
record_console_html.print(tree_object)
output_html = record_console_html.export_html(inline_styles=True)
except Exception as capture_err:
logger.error(f"Error during rich capture: {capture_err}", exc_info=True)
# Still return success=False but maybe with partial data if needed
return {"success": False, "error": f"Rich capture failed: {capture_err}"}
return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
# ... (error handling) ...
return {"success": False, "error": str(e)}
@auto_tool
async def visualize_dom_boxes(params: dict) -> dict:
"""Renders the DOM from a file as nested boxes (text and HTML)."""
file_path = params.get("file_path")
verbose = params.get("verbose", False)
# ... (file checks and html_content reading) ...
try:
# ... (create visualizer and box_object) ...
box_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
if not box_object: return {"success": False, "error": "Could not generate box layout."}
# 1. Handle verbose printing (unchanged)
if verbose:
stdout_console = Console()
stdout_console.print(box_object)
# 2. Handle file export capture (force silence during capture)
output_text = ""
output_html = ""
try:
string_buffer_txt = io.StringIO()
with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout
record_console_txt = Console(record=True, width=180, file=string_buffer_txt)
record_console_txt.print(box_object)
output_text = record_console_txt.export_text()
string_buffer_html = io.StringIO()
with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout again for HTML
record_console_html = Console(record=True, width=180, file=string_buffer_html)
record_console_html.print(box_object)
output_html = record_console_html.export_html(inline_styles=True)
except Exception as capture_err:
logger.error(f"Error during rich capture: {capture_err}", exc_info=True)
return {"success": False, "error": f"Rich capture failed: {capture_err}"}
return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
# ... (error handling) ...
return {"success": False, "error": str(e)}
# ... (rest of file)
This uses contextlib.redirect_stdout to temporarily capture anything that tries to print to standard output during the record_console.print() call and sends it to a dummy StringIO buffer, effectively silencing it from the notebook’s perspective while still allowing the record_console to capture the output correctly for export.
2. Hunting the Second Tree 🌳🌳
If the above fix silences the first tree when verbose=False but a second tree still appears, we need to find where else it’s being generated or printed.
Hypotheses & Checks:
- Accidental Double Call in
scraper_tools.py?- Check: Carefully re-read the
selenium_automationfunction intools/scraper_tools.py. Is it possiblevisualize_dom_hierarchyis called twice under some condition? Addlogger.debug("Calling visualize_dom_hierarchy...")right before the call andlogger.debug("Finished visualize_dom_hierarchy.")right after. Run the notebook again and see if these messages appear twice per URL.
- Check: Carefully re-read the
- Printing the Return Value Somewhere?
- Check: The
selenium_automationfunction returns thehierarchy_viz_result(which contains the text output). Is the caller ofselenium_automation(likelyscrape_and_extractinsecretsauce.py) accidentally printing this result? Add logging insecretsauce.pyright after theawait pip.scrape(...)call to inspect thescrape_resultbefore proceeding. Specifically, checkscrape_result.get("looking_at_files", {}).get("dom_hierarchy"). Make sure this path isn’t being read and printed later.
- Check: The
- Recursion Bug in
_DOMHierarchyVisualizer?- Check: Look very closely at
build_tree_structureinside_DOMHierarchyVisualizer. Could there be a condition whereConsole().print()or even a standardprint()was added within the recursion? (Unlikely based on current code, but worth a paranoid check). Add alogger.debug(f"Building tree level {level} for {element.name}")inside this method.
- Check: Look very closely at
My strongest suspicion falls on hypothesis #2 – the return value from the successful (but now silenced) visualization is being captured and then printed by the calling code in secretsauce.py or even the notebook itself. The redirect_stdout fix should handle the direct printing leak, making any remaining output easier to trace back to its caller.
Let’s apply the redirect_stdout fix first and see if both trees disappear when verbose=False. If one remains, the hunt begins in the calling code (secretsauce.py and FAQuilizer.ipynb).
Gemini CLI:
✦ Okay, I understand the plan. Wrestling with output redirection can be tricky, especially in a Jupyter environment.
The redirect_stdout approach is a solid next step.
First, I'll read the contents of tools/dom_tools.py to get the current state of the code.
╭─────────────────────────────────╮
│ ✓ ReadFile tools/dom_tools.py │
╰─────────────────────────────────╯
✦ Okay, I'll start by applying the redirect_stdout fix. I will modify tools/dom_tools.py to import contextlib and
then wrap the output capturing logic in the visualize_dom_hierarchy and visualize_dom_boxes functions as you've
described.
╭──────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ ✓ Edit tools/dom_tools.py: import re... => import re... │
│ │
│ 20 import re │
│ 21 import json │
│ 22 import io │
│ 23 + import contextlib │
│ 24 │
│ 25 │
│ 26 # This makes the 'tools' package importable when run as a script │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────╯
✦ Great, the contextlib import has been added.
Next, I'll replace the visualize_dom_hierarchy function with the updated version that uses
contextlib.redirect_stdout to silence the output during the capture process.
╭──────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ ✓ Edit tools/dom_tools.py: @auto_tool... => @auto_tool... │
│ │
│ 176 async def visualize_dom_hierarchy(params: dict) -> dict: │
│ 177 """Renders the DOM from a file as a hierarchical tree (text and HTML).""" │
│ 178 file_path = params.get("file_path") │
│ 179 - verbose = params.get("verbose", False) # Default to False now │
│ 179 + verbose = params.get("verbose", False) │
│ 180 if not file_path or not os.path.exists(file_path): │
│ 181 return {"success": False, "error": f"File not found: {file_path}"} │
│ 182 try: │
│ 186 visualizer = _DOMHierarchyVisualizer() │
│ 187 tree_object = visualizer.visualize_dom_content(html_content, source_name=file_path) │
│ 188 │
│ 189 - # 1. Handle verbose printing to stdout (if requested) │
│ 189 + # 1. Handle verbose printing (unchanged) │
│ 190 if verbose: │
│ 191 stdout_console = Console() │
│ 192 stdout_console.print(tree_object) │
│ 193 │
│ 194 - # 2. Handle file export capture (always, silently) │
│ 194 + # 2. Handle file export capture (force silence during capture) │
│ 195 + output_text = "" │
│ 196 + output_html = "" │
│ 197 + try: │
│ 198 string_buffer_txt = io.StringIO() │
│ 199 + with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout │
│ 200 record_console_txt = Console(record=True, width=180, file=string_buffer_txt) │
│ 201 record_console_txt.print(tree_object) │
│ 202 output_text = record_console_txt.export_text() │
│ 203 │
│ 204 string_buffer_html = io.StringIO() │
│ 205 + with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout again │
│ for HTML │
│ 206 record_console_html = Console(record=True, width=180, file=string_buffer_html) │
│ 207 record_console_html.print(tree_object) │
│ 203 - output_html = record_console_html.export_html(inline_styles=True) # Use inline styles │
│ for portability │
│ 208 + output_html = record_console_html.export_html(inline_styles=True) │
│ 209 + except Exception as capture_err: │
│ 210 + try: │
│ 211 + from loguru import logger │
│ 212 + logger.error(f"Error during rich capture: {capture_err}", exc_info=True) │
│ 213 + except ImportError: │
│ 214 + print(f"Error during rich capture: {capture_err}") │
│ 215 + return {"success": False, "error": f"Rich capture failed: {capture_err}"} │
│ 216 │
│ 217 + │
│ 218 return {"success": True, "output": output_text, "output_html": output_html} │
│ 219 except Exception as e: │
│ 207 - try: from loguru import logger; logger.error(f"Error in visualize_dom_hierarchy: {e}", │
│ exc_info=True) # Add exc_info │
│ ════════════════════════════════════════════════════════════════════════════════════════════════════ │
│ 220 + try: from loguru import logger; logger.error(f"Error in visualize_dom_hierarchy: {e}", │
│ exc_info=True) │
│ 221 except ImportError: print(f"Error in visualize_dom_hierarchy: {e}") │
│ 222 return {"success": False, "error": str(e)} │
│ 223 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────╯
✦ Okay, visualize_dom_hierarchy is updated. Now, I'll apply the same redirect_stdout logic to the
visualize_dom_boxes function.
╭──────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ ✓ Edit tools/dom_tools.py: @auto_tool... => @auto_tool... │
│ │
│ 226 async def visualize_dom_boxes(params: dict) -> dict: │
│ 227 """Renders the DOM from a file as nested boxes (text and HTML).""" │
│ 228 file_path = params.get("file_path") │
│ 229 - verbose = params.get("verbose", False) # Default to False now │
│ 229 + verbose = params.get("verbose", False) │
│ 230 if not file_path or not os.path.exists(file_path): │
│ 231 return {"success": False, "error": f"File not found: {file_path}"} │
│ 232 try: │
│ ════════════════════════════════════════════════════════════════════════════════════════════════════ │
│ 244 stdout_console = Console() │
│ 245 stdout_console.print(box_object) │
│ 246 │
│ 247 - # 2. Handle file export capture (always, silently) │
│ 247 + # 2. Handle file export capture (force silence during capture) │
│ 248 + output_text = "" │
│ 249 + output_html = "" │
│ 250 + try: │
│ 251 string_buffer_txt = io.StringIO() │
│ 252 + with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout │
│ 253 record_console_txt = Console(record=True, width=180, file=string_buffer_txt) │
│ 254 record_console_txt.print(box_object) │
│ 255 output_text = record_console_txt.export_text() │
│ 256 │
│ 257 string_buffer_html = io.StringIO() │
│ 258 + with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout again │
│ for HTML │
│ 259 record_console_html = Console(record=True, width=180, file=string_buffer_html) │
│ 260 record_console_html.print(box_object) │
│ 256 - output_html = record_console_html.export_html(inline_styles=True) # Use inline styles │
│ 261 + output_html = record_console_html.export_html(inline_styles=True) │
│ 262 + except Exception as capture_err: │
│ 263 + try: │
│ 264 + from loguru import logger │
│ 265 + logger.error(f"Error during rich capture: {capture_err}", exc_info=True) │
│ 266 + except ImportError: │
│ 267 + print(f"Error during rich capture: {capture_err}") │
│ 268 + return {"success": False, "error": f"Rich capture failed: {capture_err}"} │
│ 269 │
│ 270 return {"success": True, "output": output_text, "output_html": output_html} │
│ 271 except Exception as e: │
│ 260 - try: from loguru import logger; logger.error(f"Error in visualize_dom_boxes: {e}", │
│ exc_info=True) # Add exc_info │
│ ════════════════════════════════════════════════════════════════════════════════════════════════════ │
│ 272 + try: from loguru import logger; logger.error(f"Error in visualize_dom_boxes: {e}", │
│ exc_info=True) │
│ 273 except ImportError: print(f"Error in visualize_dom_boxes: {e}") │
│ 274 return {"success": False, "error": str(e)} │
│ 275 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────╯
✦ I have applied the redirect_stdout fix to both the visualize_dom_hierarchy and visualize_dom_boxes functions in
tools/dom_tools.py.
Please re-run your notebook. Let's see if this aggressive silencing has resolved the unwanted output. If a
visualization still appears when verbose=False, we'll proceed to hunt for the source of the second tree.
accepting edits (shift + tab to toggle)
╭────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ > Type your message or @path/to/file │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
~/repos/pipulate (main*) no sandbox (see /docs) gemini-2.5-pro (98% context left)
Me:
[mike@nixos:~/repos/pipulate]$ git --no-pager diff
diff --git a/tools/dom_tools.py b/tools/dom_tools.py
index 34d17865..ec6f8685 100644
--- a/tools/dom_tools.py
+++ b/tools/dom_tools.py
@@ -20,6 +20,7 @@ from rich.box import ROUNDED, DOUBLE, HEAVY, ASCII
import re
import json
import io
+import contextlib
# This makes the 'tools' package importable when run as a script
@@ -175,35 +176,48 @@ class _DOMBoxVisualizer:
async def visualize_dom_hierarchy(params: dict) -> dict:
"""Renders the DOM from a file as a hierarchical tree (text and HTML)."""
file_path = params.get("file_path")
- verbose = params.get("verbose", False) # Default to False now
+ verbose = params.get("verbose", False)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
with open(file_path, 'r', encoding='utf-8') as f:
html_content = f.read()
-
+
visualizer = _DOMHierarchyVisualizer()
tree_object = visualizer.visualize_dom_content(html_content, source_name=file_path)
- # 1. Handle verbose printing to stdout (if requested)
+ # 1. Handle verbose printing (unchanged)
if verbose:
stdout_console = Console()
stdout_console.print(tree_object)
- # 2. Handle file export capture (always, silently)
- string_buffer_txt = io.StringIO()
- record_console_txt = Console(record=True, width=180, file=string_buffer_txt)
- record_console_txt.print(tree_object)
- output_text = record_console_txt.export_text()
+ # 2. Handle file export capture (force silence during capture)
+ output_text = ""
+ output_html = ""
+ try:
+ string_buffer_txt = io.StringIO()
+ with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout
+ record_console_txt = Console(record=True, width=180, file=string_buffer_txt)
+ record_console_txt.print(tree_object)
+ output_text = record_console_txt.export_text()
+
+ string_buffer_html = io.StringIO()
+ with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout again for HTML
+ record_console_html = Console(record=True, width=180, file=string_buffer_html)
+ record_console_html.print(tree_object)
+ output_html = record_console_html.export_html(inline_styles=True)
+ except Exception as capture_err:
+ try:
+ from loguru import logger
+ logger.error(f"Error during rich capture: {capture_err}", exc_info=True)
+ except ImportError:
+ print(f"Error during rich capture: {capture_err}")
+ return {"success": False, "error": f"Rich capture failed: {capture_err}"}
- string_buffer_html = io.StringIO()
- record_console_html = Console(record=True, width=180, file=string_buffer_html)
- record_console_html.print(tree_object)
- output_html = record_console_html.export_html(inline_styles=True) # Use inline styles for portability
return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
- try: from loguru import logger; logger.error(f"Error in visualize_dom_hierarchy: {e}", exc_info=True) # Add exc_info
+ try: from loguru import logger; logger.error(f"Error in visualize_dom_hierarchy: {e}", exc_info=True)
except ImportError: print(f"Error in visualize_dom_hierarchy: {e}")
return {"success": False, "error": str(e)}
@@ -212,7 +226,7 @@ async def visualize_dom_hierarchy(params: dict) -> dict:
async def visualize_dom_boxes(params: dict) -> dict:
"""Renders the DOM from a file as nested boxes (text and HTML)."""
file_path = params.get("file_path")
- verbose = params.get("verbose", False) # Default to False now
+ verbose = params.get("verbose", False)
if not file_path or not os.path.exists(file_path):
return {"success": False, "error": f"File not found: {file_path}"}
try:
@@ -230,20 +244,32 @@ async def visualize_dom_boxes(params: dict) -> dict:
stdout_console = Console()
stdout_console.print(box_object)
- # 2. Handle file export capture (always, silently)
- string_buffer_txt = io.StringIO()
- record_console_txt = Console(record=True, width=180, file=string_buffer_txt)
- record_console_txt.print(box_object)
- output_text = record_console_txt.export_text()
-
- string_buffer_html = io.StringIO()
- record_console_html = Console(record=True, width=180, file=string_buffer_html)
- record_console_html.print(box_object)
- output_html = record_console_html.export_html(inline_styles=True) # Use inline styles
+ # 2. Handle file export capture (force silence during capture)
+ output_text = ""
+ output_html = ""
+ try:
+ string_buffer_txt = io.StringIO()
+ with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout
+ record_console_txt = Console(record=True, width=180, file=string_buffer_txt)
+ record_console_txt.print(box_object)
+ output_text = record_console_txt.export_text()
+
+ string_buffer_html = io.StringIO()
+ with contextlib.redirect_stdout(io.StringIO()): # <-- Force redirect stdout again for HTML
+ record_console_html = Console(record=True, width=180, file=string_buffer_html)
+ record_console_html.print(box_object)
+ output_html = record_console_html.export_html(inline_styles=True)
+ except Exception as capture_err:
+ try:
+ from loguru import logger
+ logger.error(f"Error during rich capture: {capture_err}", exc_info=True)
+ except ImportError:
+ print(f"Error during rich capture: {capture_err}")
+ return {"success": False, "error": f"Rich capture failed: {capture_err}"}
return {"success": True, "output": output_text, "output_html": output_html}
except Exception as e:
- try: from loguru import logger; logger.error(f"Error in visualize_dom_boxes: {e}", exc_info=True) # Add exc_info
+ try: from loguru import logger; logger.error(f"Error in visualize_dom_boxes: {e}", exc_info=True)
except ImportError: print(f"Error in visualize_dom_boxes: {e}")
return {"success": False, "error": str(e)}
(nix)
[mike@nixos:~/repos/pipulate]$
I can’t believe it. It’s the nested box and then the double tree output like every other time. I may not be able to apply these visualizations during the crawl. We have to change the opportunity for this to even occur with separate discrete ways to visualize create these visualizations post-scrape. You see the way I can interact with Gemini CLI. You can word your implementation plan to be geared towards it being able to follow out the instructions. Even so, don’t get too ambitious and focus on discrete non-breaking git committable steps, each one banking a small directional win. We can alter the physics of the universe to prevent this from even having an opportunity to occur. Even if it’s subprocess, I don’t care. Anything to get that weird monkeypatching out of the picture.
[mike@nixos:~/repos/pipulate]$ git --no-pager log -10
commit 40cd71cdd6d04993ebc6822564908168dc83d700 (HEAD -> main, origin/main, origin/HEAD)
Author: Mike Levin <miklevin@gmail.com>
Date: Tue Oct 21 07:41:23 2025 -0400
An attempt to fix with output redirection
commit 027898ed6be53c5c48986c5a7e6dfae89d7b5cb1
Author: Mike Levin <miklevin@gmail.com>
Date: Tue Oct 21 07:31:44 2025 -0400
An attempt at silencing DOM visualizer output during scrape
commit 2ed9287530f4123b516aef07f5a1d81e2e3dc899
Author: Mike Levin <miklevin@gmail.com>
Date: Tue Oct 21 07:20:20 2025 -0400
Rich print staement removed
commit 8af68d0202a31bcef5ad82d8556cda7a31e0959c
Author: Mike Levin <miklevin@gmail.com>
Date: Tue Oct 21 06:54:46 2025 -0400
Project Jupyter needs the boost more than PyPI
commit 53f20e9106fcf686ca9abaa209eaca96cddc2705
Author: Mike Levin <miklevin@gmail.com>
Date: Tue Oct 21 06:41:31 2025 -0400
The 3rd of 3 edits intended to silence verbose=False
commit 4017f6c4798f286487e60cfd5fc8e51f844fd100
Author: Mike Levin <miklevin@gmail.com>
Date: Tue Oct 21 06:32:15 2025 -0400
Second in a series of edits to give humans the same eyes I'm giving AIs
commit 982fe58efc09280fc6fbba82dcc27b21a17110ac
Author: Mike Levin <miklevin@gmail.com>
Date: Tue Oct 21 06:29:13 2025 -0400
First of several edits to silence verbose and get color DOM files
commit 1427654482836b0bb7907025828b982c797540f1
Author: Mike Levin <miklevin@gmail.com>
Date: Tue Oct 21 06:10:13 2025 -0400
AI PHOOEY-CHOP\!
commit 5daa3a4387e22409d360967a401f5eb2cc25b439
Author: Mike Levin <miklevin@gmail.com>
Date: Mon Oct 20 21:43:16 2025 -0400
Getting ready to silence verbose=False and preserve ASCII colors of DOM art
commit d0ce2cf7cfda8f92926e364e46eb2095a8cf8046
Author: Mike Levin <miklevin@gmail.com>
Date: Mon Oct 20 20:49:55 2025 -0400
Got rid of stray line in that edit
(nix)
[mike@nixos:~/repos/pipulate]$
Gemini Web: Context verified.
You’re absolutely right to step back and rethink the approach. We’ve been wrestling with the symptoms – unwanted printing during the scrape – which strongly suggests the root cause is a fundamental conflict between rich, Jupyter’s output capturing, and possibly the asynchronous nature of the scrape itself. Fighting that interaction directly has proven futile.
Your proposal to decouple the visualization generation entirely from the scraping process is the perfect “alter the physics” solution. 🌌 By generating the visualizations after the scrape is complete, in a separate step, we sidestep the problematic interaction entirely.
Let’s implement this decoupling. This plan focuses on removing the visualization calls from the scrape and setting up the tools to be called independently later.
Decoupling Plan: Separate Scraping & Visualization
Step 1: Remove Visualization Calls from Scraper
The first and most crucial step is to prevent the visualization tools from being called during the scrape at all.
Action for Gemini CLI:
- ReadFile:
tools/scraper_tools.py - Edit: Locate the
selenium_automationfunction. - Delete: Remove the entire blocks of code responsible for calling
dom_tools.visualize_dom_boxesanddom_tools.visualize_dom_hierarchy. This includes thelogger.infocalls immediately preceding them and the logic that handles their results (saving.txtand.htmlfiles).- Target block 1 (around line 190): Starts with
if verbose: logger.info(f"🎨 Generating DOM box visualization...")and ends before theif verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...")line. - Target block 2 (around line 205): Starts with
if verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...")and ends before theif verbose: logger.info("🌲 Extracting accessibility tree...")line.
- Target block 1 (around line 190): Starts with
- Verify: Ensure that the
artifactsdictionary still correctly captures paths forrendered_dom.html,source_html.txt,screenshot.png, and the accessibility tree files, but no longer includes entries fordom_layout_boxes,dom_layout_boxes_html,dom_hierarchy, ordom_hierarchy_html.
Code Snippet (Illustrative - What to Remove):
# Inside selenium_automation in tools/scraper_tools.py
# --- Generate Visualization Artifacts ---
# --- [DELETE THIS ENTIRE SECTION] ---
# verbose=False is passed here, but the auto_tool default is now also False
viz_params = {"file_path": str(dom_path), "verbose": False}
# logger.info calls remain, controlled by the main verbose flag of selenium_automation
if verbose: logger.info(f"🎨 Generating DOM box visualization...")
viz_result = await dom_tools.visualize_dom_boxes(viz_params)
# ... (rest of the box visualization handling) ...
if verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...")
hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy(viz_params)
# ... (rest of the hierarchy visualization handling) ...
# --- [END DELETE SECTION] ---
# --- Generate Accessibility Tree Artifact ---
# (Keep this section and the following code)
if verbose: logger.info("🌲 Extracting accessibility tree...")
# ...
Rationale & Next Steps:
This first commit surgically removes the visualization step from the scraping process. After this, running the scrape_and_extract cell in your notebook should be completely silent regarding DOM visualizations, and no .txt or .html visualization files should be created in browser_cache.
Once this is confirmed:
- We’ll ensure the
dom_tools.pyfunctions are robust enough to be called standalone (they likely already are after our last edits). - We’ll add a new cell in
FAQuilizer.ipynb(or a helper insecretsauce.py) to iterate through the scrape results and explicitly call thedom_toolsfunctions to generate the visualizations after scraping is finished.
This approach physically separates the problematic code execution, giving us a clean scrape and deferring the rich rendering to a context where Jupyter’s interference is less likely or easier to manage. This should also inherently solve the “double tree” problem, as the logic will only run once when explicitly called.
Gemini CLI:
✦ This is a sharp insight. Decoupling the visualization from the scraping process is a clean, architectural solution
that avoids the complex and unpredictable interactions within the Jupyter/async/rich environment. I agree
completely.
I will start by removing the visualization calls from tools/scraper_tools.py. First, I need to read the file.
╭─────────────────────────────────────╮
│ ✓ ReadFile tools/scraper_tools.py │
╰─────────────────────────────────────╯
✦ I have the content of tools/scraper_tools.py. I will now remove the code responsible for generating the DOM
visualizations during the scraping process as you've instructed.
╭──────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ ✓ Edit tools/scraper_tools.py: # --- Generate Visuali... => # --- Generate Accessi... │
│ │
│ 208 driver.save_screenshot(str(screenshot_path)) │
│ 209 artifacts['screenshot'] = str(screenshot_path) │
│ 210 │
│ 211 - # --- Generate Visualization Artifacts --- │
│ 212 - if verbose: logger.info(f"🎨 Generating DOM box visualization...") │
│ 213 - viz_result = await dom_tools.visualize_dom_boxes({"file_path": str(dom_path), "verbose": False │
│ }) │
│ 214 - if viz_result.get("success"): │
│ 215 - viz_path = output_dir / "dom_layout_boxes.txt" │
│ 216 - viz_path.write_text(viz_result["output"], encoding='utf-8') │
│ 217 - artifacts['dom_layout_boxes'] = str(viz_path) │
│ 218 - │
│ 219 - if verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...") │
│ 220 - hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy({"file_path": str(dom_path), │
│ "verbose": False}) │
│ 221 - if hierarchy_viz_result.get("success"): │
│ 222 - hierarchy_viz_path = output_dir / "dom_hierarchy.txt" │
│ 223 - hierarchy_viz_path.write_text(hierarchy_viz_result["output"], encoding='utf-8') │
│ 224 - artifacts['dom_hierarchy'] = str(hierarchy_viz_path) │
│ 225 - │
│ 211 # --- Generate Accessibility Tree Artifact --- │
│ 212 if verbose: logger.info("🌲 Extracting accessibility tree...") │
│ 213 try: │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────╯
✦ The visualization generation block has been removed.
Now, I will update the idempotency check to remove the artifact names related to the DOM visualizations,
ensuring the function no longer looks for these cached files.
╭──────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ ✓ Edit tools/scraper_tools.py: for artifact_name in [... => for artifact_name in [... │
│ │
│ 70 for artifact_name in ["rendered_dom.html", │
│ 71 "source_html.txt", │
│ 72 "screenshot.png", │
│ 73 - "dom_layout_boxes.txt", │
│ 74 - "dom_hierarchy.txt", │
│ 73 "accessibility_tree.json", │
│ 74 "accessibility_tree_summary.txt"]: │
│ 75 artifact_path = output_dir / artifact_name │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────╯
✦ I have completed the requested changes. The visualization calls and corresponding artifact checks have been
removed from the selenium_automation function in tools/scraper_tools.py.
The scraping process should now be fully decoupled and silent regarding DOM visualizations. Please confirm on
your end, and then we can proceed with the next step: explicitly calling the visualization tools from your
notebook.
accepting edits (shift + tab to toggle)
╭────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ > Type your message or @path/to/file │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
~/repos/pipulate (main*) no sandbox (see /docs) gemini-2.5-pro (98% context left)
Me:
[mike@nixos:~/repos/pipulate]$ git --no-pager diff
diff --git a/tools/scraper_tools.py b/tools/scraper_tools.py
index db0aa45d..93f5e5c3 100644
--- a/tools/scraper_tools.py
+++ b/tools/scraper_tools.py
@@ -70,8 +70,6 @@ async def selenium_automation(params: dict) -> dict:
for artifact_name in ["rendered_dom.html",
"source_html.txt",
"screenshot.png",
- "dom_layout_boxes.txt",
- "dom_hierarchy.txt",
"accessibility_tree.json",
"accessibility_tree_summary.txt"]:
artifact_path = output_dir / artifact_name
@@ -208,21 +206,6 @@ async def selenium_automation(params: dict) -> dict:
driver.save_screenshot(str(screenshot_path))
artifacts['screenshot'] = str(screenshot_path)
- # --- Generate Visualization Artifacts ---
- if verbose: logger.info(f"🎨 Generating DOM box visualization...")
- viz_result = await dom_tools.visualize_dom_boxes({"file_path": str(dom_path), "verbose": False})
- if viz_result.get("success"):
- viz_path = output_dir / "dom_layout_boxes.txt"
- viz_path.write_text(viz_result["output"], encoding='utf-8')
- artifacts['dom_layout_boxes'] = str(viz_path)
-
- if verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...")
- hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy({"file_path": str(dom_path), "verbose": False})
- if hierarchy_viz_result.get("success"):
- hierarchy_viz_path = output_dir / "dom_hierarchy.txt"
- hierarchy_viz_path.write_text(hierarchy_viz_result["output"], encoding='utf-8')
- artifacts['dom_hierarchy'] = str(hierarchy_viz_path)
-
# --- Generate Accessibility Tree Artifact ---
if verbose: logger.info("🌲 Extracting accessibility tree...")
try:
(nix)
[mike@nixos:~/repos/pipulate]$
Gemini Web: Excellent, the diff confirms the surgery was successful! 🔪 The visualization calls are now completely removed from the scraping function.
Adding Post-Scrape Visualization
Now, let’s add the explicit step to generate these visualizations after the scraping is done. We’ll create a helper function in secretsauce.py for this and then call it from a new cell in the notebook.
Step 1: Create Helper Function in secretsauce.py
This function will iterate through the scraped data, find the DOM file, and call the visualization tools.
Action for Gemini CLI:
- ReadFile:
Notebooks/secretsauce.py - Edit: Add the following new
asyncfunction toNotebooks/secretsauce.py. You can place it after thescrape_and_extractfunction.
# Add this new function to Notebooks/secretsauce.py
async def generate_visualizations_post_scrape(job: str, verbose: bool = False):
"""
Generates DOM visualizations (hierarchy and boxes) for all scraped URLs in a job.
This should be run AFTER scrape_and_extract.
"""
print("🎨 Generating DOM visualizations for scraped pages...")
extracted_data = pip.get(job, EXTRACTED_DATA_STEP, []) # Reuse extracted data list
urls_processed = {item['url'] for item in extracted_data}
if not urls_processed:
print("🟡 No scraped URLs found in the job state to visualize.")
return
from tools import dom_tools # Import here to avoid circular dependency issues if any
from tools.scraper_tools import get_safe_path_component # Helper for path generation
from pathlib import Path
success_count = 0
fail_count = 0
base_dir = Path("browser_cache/") # Assuming notebook context
for i, url in enumerate(urls_processed):
if verbose:
print(f" -> Visualizing [{i+1}/{len(urls_processed)}]: {url}")
domain, url_path_slug = get_safe_path_component(url)
output_dir = base_dir / domain / url_path_slug
dom_path = output_dir / "rendered_dom.html"
if not dom_path.exists():
if verbose:
print(f" ❌ Skipping: rendered_dom.html not found at {dom_path}")
fail_count += 1
continue
viz_params = {"file_path": str(dom_path), "verbose": False} # Never print to stdout from tool
try:
# Generate Hierarchy
hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy(viz_params)
if hierarchy_viz_result.get("success"):
hierarchy_viz_path_txt = output_dir / "dom_hierarchy.txt"
hierarchy_viz_path_txt.write_text(hierarchy_viz_result.get("output", ""), encoding='utf-8')
if hierarchy_viz_result.get("output_html"):
hierarchy_viz_path_html = output_dir / "dom_hierarchy.html"
hierarchy_viz_path_html.write_text(hierarchy_viz_result["output_html"], encoding='utf-8')
else:
if verbose: print(f" ⚠️ Hierarchy viz failed: {hierarchy_viz_result.get('error')}")
# Generate Boxes
box_viz_result = await dom_tools.visualize_dom_boxes(viz_params)
if box_viz_result.get("success"):
viz_path_txt = output_dir / "dom_layout_boxes.txt"
viz_path_txt.write_text(box_viz_result.get("output", ""), encoding='utf-8')
if box_viz_result.get("output_html"):
viz_path_html = output_dir / "dom_layout_boxes.html"
viz_path_html.write_text(box_viz_result["output_html"], encoding='utf-8')
else:
if verbose: print(f" ⚠️ Box viz failed: {box_viz_result.get('error')}")
success_count +=1
except Exception as e:
if verbose:
print(f" ❌ Critical error visualizing {url}: {e}")
fail_count += 1
print(f"✅ Visualization generation complete. Success: {success_count}, Failed/Skipped: {fail_count}")
Step 2: Add New Cell in FAQuilizer.ipynb
Call the new helper function after the scraping step.
Action for Gemini CLI:
- ReadFile:
Notebooks/FAQuilizer.ipynb(convert if necessary) - Edit: Locate the cell containing
await secretsauce.scrape_and_extract(...). - Insert Cell After: Add a new code cell immediately following that cell with the following content:
# %% [markdown]
# ### Step 2: Generate DOM Visualizations (Post-Scrape)
# %%
# This cell generates the DOM tree and box visualizations for the pages scraped above.
# Set verbose=True to see logs for each URL.
await secretsauce.generate_visualizations_post_scrape(job, verbose=True)
- Renumber Subsequent Cells: Adjust the markdown numbering for the following steps (e.g., “Step 3: Stack ‘Em…”, “Step 4: Export…”) to reflect the insertion of this new Step 2.
With these changes:
- The
scrape_and_extractcell runs silently (regarding visualizations). - The new
generate_visualizations_post_scrapecell runs afterwards, explicitly creating the.txtand.htmlfiles in thebrowser_cache. - No unwanted output should appear during the scrape, and the double-tree mystery should be solved.
Please apply these changes, and let’s test the decoupled workflow!
Gemini CLI:
✦ This is the right way to do it. I'll add the helper function to secretsauce.py and then call it from a new cell in
the FAQuilizer.ipynb notebook.
First, I'll read Notebooks/secretsauce.py.
╭───────────────────────────────────────╮
│ ✓ ReadFile Notebooks/secretsauce.py │
╰───────────────────────────────────────╯
✦ Okay, I have the contents of Notebooks/secretsauce.py. I will now append the new
generate_visualizations_post_scrape function to the end of this file.
╭───────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ ✓ Edit Notebooks/secretsauce.py: except Exception as e:... => except Exception as e:... │
│ │
│ 571 subprocess.run(["xdg-open", folder_path]) │
│ 572 except Exception as e: │
│ 573 print(f"❌ Failed to open folder. Please navigate to it manually. Error: {e}") │
│ 574 + │
│ 575 + │
│ 576 + async def generate_visualizations_post_scrape(job: str, verbose: bool = False): │
│ 577 + """ │
│ 578 + Generates DOM visualizations (hierarchy and boxes) for all scraped URLs in a job. │
│ 579 + This should be run AFTER scrape_and_extract. │
│ 580 + """ │
│ 581 + print("🎨 Generating DOM visualizations for scraped pages...") │
│ 582 + extracted_data = pip.get(job, EXTRACTED_DATA_STEP, []) # Reuse extracted data list │
│ 583 + urls_processed = {item['url'] for item in extracted_data} │
│ 584 + │
│ 585 + if not urls_processed: │
│ 586 + print("🟡 No scraped URLs found in the job state to visualize.") │
│ 587 + return │
│ 588 + │
│ 589 + from tools import dom_tools # Import here to avoid circular dependency issues if any │
│ 590 + from tools.scraper_tools import get_safe_path_component # Helper for path generation │
│ 591 + from pathlib import Path │
│ 592 + │
│ 593 + success_count = 0 │
│ 594 + fail_count = 0 │
│ 595 + │
│ 596 + base_dir = Path("browser_cache/") # Assuming notebook context │
│ 597 + │
│ 598 + for i, url in enumerate(urls_processed): │
│ 599 + if verbose: │
│ 600 + print(f" -> Visualizing [{i+1}/{len(urls_processed)}]: {url}") │
│ 601 + │
│ 602 + domain, url_path_slug = get_safe_path_component(url) │
│ 603 + output_dir = base_dir / domain / url_path_slug │
│ 604 + dom_path = output_dir / "rendered_dom.html" │
│ 605 + │
│ 606 + if not dom_path.exists(): │
│ 607 + if verbose: │
│ 608 + print(f" ❌ Skipping: rendered_dom.html not found at {dom_path}") │
│ 609 + fail_count += 1 │
│ 610 + continue │
│ 611 + │
│ 612 + viz_params = {"file_path": str(dom_path), "verbose": False} # Never print to stdout │
│ from tool │
│ 613 + │
│ 614 + try: │
│ 615 + # Generate Hierarchy │
│ 616 + hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy(viz_params) │
│ 617 + if hierarchy_viz_result.get("success"): │
│ 618 + hierarchy_viz_path_txt = output_dir / "dom_hierarchy.txt" │
│ 619 + hierarchy_viz_path_txt.write_text(hierarchy_viz_result.get("output", ""), │
│ encoding='utf-8') │
│ 620 + if hierarchy_viz_result.get("output_html"): │
│ 621 + hierarchy_viz_path_html = output_dir / "dom_hierarchy.html" │
│ 622 + hierarchy_viz_path_html.write_text(hierarchy_viz_result["output_html"], │
│ encoding='utf-8') │
│ 623 + else: │
│ 624 + if verbose: print(f" ⚠️ Hierarchy viz failed:{hierarchy_viz_result.get( │
│ 'error')}") │
│ 625 + │
│ 626 + # Generate Boxes │
│ 627 + box_viz_result = await dom_tools.visualize_dom_boxes(viz_params) │
│ 628 + if box_viz_result.get("success"): │
│ 629 + viz_path_txt = output_dir / "dom_layout_boxes.txt" │
│ 630 + viz_path_txt.write_text(box_viz_result.get("output", ""), encoding='utf-8') │
│ 631 + if box_viz_result.get("output_html"): │
│ 632 + viz_path_html = output_dir / "dom_layout_boxes.html" │
│ 633 + viz_path_html.write_text(box_viz_result["output_html"], encoding='utf-8') │
│ 634 + else: │
│ 635 + if verbose: print(f" ⚠️ Box viz failed:{box_viz_result.get('error')}") │
│ 636 + │
│ 637 + success_count +=1 │
│ 638 + │
│ 639 + except Exception as e: │
│ 640 + if verbose: │
│ 641 + print(f" ❌ Critical error visualizing {url}: {e}") │
│ 642 + fail_count += 1 │
│ 643 + │
│ 644 + print(f"✅ Visualization generation complete. Success: {success_count}, Failed/Skipped: │
│ {fail_count}") │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────╯
✦ secretsauce.py is updated. Now I'll modify the FAQuilizer.ipynb notebook to call the new function. I'll start by
reading the notebook file.
╭──────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ ✓ ReadFile Notebooks/FAQuilizer.ipynb │
│ │
│ Read lines 1-2000 of 7060 from Notebooks/FAQuilizer.ipynb │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────╯
✦ Okay, I'll start by reading the entire FAQuilizer.ipynb notebook file to make sure I have the full content before
making any changes.
╭─────────────────────────────────────────╮
│ ✓ ReadFile Notebooks/FAQuilizer.ipynb │
╰─────────────────────────────────────────╯
✕ [API Error: [{
"error": {
"code": 400,
"message": "The input token count (1532027) exceeds the maximum number of tokens allowed (1048576).",
"errors": [
{
"message": "The input token count (1532027) exceeds the maximum number of tokens allowed (1048576).",
"domain": "global",
"reason": "badRequest"
}
],
"status": "INVALID_ARGUMENT"
}
}
]]
> You don't have to edit the Notebook! Just tell me what to do there.
✕ [API Error: [{
"error": {
"code": 400,
"message": "The input token count (1532055) exceeds the maximum number of tokens allowed (1048576).",
"errors": [
{
"message": "The input token count (1532055) exceeds the maximum number of tokens allowed (1048576).",
"domain": "global",
"reason": "badRequest"
}
],
"status": "INVALID_ARGUMENT"
}
}
]]
accepting edits (shift + tab to toggle)
╭────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ > Type your message or @path/to/file │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
~/repos/pipulate no sandbox (see gemini-2.5-pro (43% context | ✖ 2 errors (ctrl+o for
(main*) /docs) left) details)
Gemini Web: Okay, you got it! Apologies, the CLI hit its token limit trying to handle the large notebook file directly.
Here’s what you need to do manually in Notebooks/FAQuilizer.ipynb:
- Locate the Scrape Cell: Find the code cell that currently runs the scraping and extraction. It looks like this:
await secretsauce.scrape_and_extract( job, headless=False, verbose=False, persistent=True, profile_name="my_session", delay_range=(7, 15) # Example: wait 7 to 15 seconds between requests ) - Insert Markdown Cell: Immediately after the scrape cell, insert a new Markdown cell with the following content:
### Step 2: Generate DOM Visualizations (Post-Scrape) - Insert Code Cell: Immediately after the new Markdown cell, insert a new Code cell with the following content:
# This cell generates the DOM tree and box visualizations for the pages scraped above. # Set verbose=True to see logs for each URL. await secretsauce.generate_visualizations_post_scrape(job, verbose=True) - Renumber Following Steps: Go through the subsequent Markdown cells in the notebook and update their step numbers (e.g., change “### Step 3: Stack ‘Em…” to “### Step 4: Stack ‘Em…”, change “### Step 4: Export…” to “### Step 5: Export…”).
That’s it! After making these changes, your notebook will correctly run the scraping first, then generate the visualizations in a separate, dedicated step, which should resolve the output issues.
Me:
[mike@nixos:~/repos/pipulate]$ git --no-pager diff
diff --git a/tools/scraper_tools.py b/tools/scraper_tools.py
index db0aa45d..93f5e5c3 100644
--- a/tools/scraper_tools.py
+++ b/tools/scraper_tools.py
@@ -70,8 +70,6 @@ async def selenium_automation(params: dict) -> dict:
for artifact_name in ["rendered_dom.html",
"source_html.txt",
"screenshot.png",
- "dom_layout_boxes.txt",
- "dom_hierarchy.txt",
"accessibility_tree.json",
"accessibility_tree_summary.txt"]:
artifact_path = output_dir / artifact_name
@@ -208,21 +206,6 @@ async def selenium_automation(params: dict) -> dict:
driver.save_screenshot(str(screenshot_path))
artifacts['screenshot'] = str(screenshot_path)
- # --- Generate Visualization Artifacts ---
- if verbose: logger.info(f"🎨 Generating DOM box visualization...")
- viz_result = await dom_tools.visualize_dom_boxes({"file_path": str(dom_path), "verbose": False})
- if viz_result.get("success"):
- viz_path = output_dir / "dom_layout_boxes.txt"
- viz_path.write_text(viz_result["output"], encoding='utf-8')
- artifacts['dom_layout_boxes'] = str(viz_path)
-
- if verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...")
- hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy({"file_path": str(dom_path), "verbose": False})
- if hierarchy_viz_result.get("success"):
- hierarchy_viz_path = output_dir / "dom_hierarchy.txt"
- hierarchy_viz_path.write_text(hierarchy_viz_result["output"], encoding='utf-8')
- artifacts['dom_hierarchy'] = str(hierarchy_viz_path)
-
# --- Generate Accessibility Tree Artifact ---
if verbose: logger.info("🌲 Extracting accessibility tree...")
try:
(nix)
[mike@nixos:~/repos/pipulate]$
And the output from the new Notebook cell:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[3], line 3
1 # This cell generates the DOM tree and box visualizations for the pages scraped above.
2 # Set verbose=True to see logs for each URL.
----> 3 await secretsauce.generate_visualizations_post_scrape(job, verbose=True)
AttributeError: module 'secretsauce' has no attribute 'generate_visualizations_post_scrape'
I’m ready for the next instructions for Gemini CLI.
Gemini Web: Okay, the AttributeError: module 'secretsauce' has no attribute 'generate_visualizations_post_scrape' clearly shows the function wasn’t added correctly to secretsauce.py by the CLI in the previous step, or the notebook kernel wasn’t restarted to pick up the change.
Let’s definitively add that function now.
Action for Gemini CLI:
- ReadFile:
Notebooks/secretsauce.py(Make sure to get the current version). - Edit: Append the entire
generate_visualizations_post_scrapefunction (provided below) to the very end of theNotebooks/secretsauce.pyfile.
# Append this entire function to the end of Notebooks/secretsauce.py
async def generate_visualizations_post_scrape(job: str, verbose: bool = False):
"""
Generates DOM visualizations (hierarchy and boxes) for all scraped URLs in a job.
This should be run AFTER scrape_and_extract.
"""
# --- Make imports local to the function ---
from pipulate import pip # Make sure pip is accessible
from tools import dom_tools
from tools.scraper_tools import get_safe_path_component
from pathlib import Path
from loguru import logger # Use logger for output consistency
# --- End local imports ---
logger.info("🎨 Generating DOM visualizations for scraped pages...") # Use logger
extracted_data = pip.get(job, "extracted_data", []) # Use string for step name
urls_processed = {item['url'] for item in extracted_data if isinstance(item, dict) and 'url' in item} # Safer extraction
if not urls_processed:
logger.warning("🟡 No scraped URLs found in the job state to visualize.") # Use logger
return
success_count = 0
fail_count = 0
base_dir = Path("browser_cache/") # Assuming notebook context
for i, url in enumerate(urls_processed):
logger.info(f" -> Visualizing [{i+1}/{len(urls_processed)}]: {url}") # Use logger
domain, url_path_slug = get_safe_path_component(url)
output_dir = base_dir / domain / url_path_slug
dom_path = output_dir / "rendered_dom.html"
if not dom_path.exists():
logger.warning(f" ❌ Skipping: rendered_dom.html not found at {dom_path}") # Use logger
fail_count += 1
continue
viz_params = {"file_path": str(dom_path), "verbose": False} # Never print to stdout from tool
try:
# Generate Hierarchy
hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy(viz_params)
if hierarchy_viz_result.get("success"):
hierarchy_viz_path_txt = output_dir / "dom_hierarchy.txt"
hierarchy_viz_path_txt.write_text(hierarchy_viz_result.get("output", ""), encoding='utf-8')
if hierarchy_viz_result.get("output_html"):
hierarchy_viz_path_html = output_dir / "dom_hierarchy.html"
hierarchy_viz_path_html.write_text(hierarchy_viz_result["output_html"], encoding='utf-8')
else:
logger.warning(f" ⚠️ Hierarchy viz failed for {url}: {hierarchy_viz_result.get('error')}") # Use logger
# Generate Boxes
box_viz_result = await dom_tools.visualize_dom_boxes(viz_params)
if box_viz_result.get("success"):
viz_path_txt = output_dir / "dom_layout_boxes.txt"
viz_path_txt.write_text(box_viz_result.get("output", ""), encoding='utf-8')
if box_viz_result.get("output_html"):
viz_path_html = output_dir / "dom_layout_boxes.html"
viz_path_html.write_text(box_viz_result["output_html"], encoding='utf-8')
else:
logger.warning(f" ⚠️ Box viz failed for {url}: {box_viz_result.get('error')}") # Use logger
success_count +=1
except Exception as e:
logger.error(f" ❌ Critical error visualizing {url}: {e}", exc_info=True) # Use logger and add exc_info
fail_count += 1
logger.success(f"✅ Visualization generation complete. Success: {success_count}, Failed/Skipped: {fail_count}") # Use logger
After the CLI confirms the edit:
- Restart the Kernel: In JupyterLab, go to
Kernel->Restart Kernel...This is crucial to make sure the notebook loads the new version ofsecretsauce.py. - Re-run the Cells: Re-run the cell containing
await secretsauce.scrape_and_extract(...)and then run the new cell containingawait secretsauce.generate_visualizations_post_scrape(...).
This should correctly define and then call the function.
Me: diff:
[mike@nixos:~/repos/pipulate]$ git --no-pager diff --no-textconv
diff --git a/assets/nbs/FAQuilizer.ipynb b/assets/nbs/FAQuilizer.ipynb
index 5111a5fb..f2ec4591 100644
--- a/assets/nbs/FAQuilizer.ipynb
+++ b/assets/nbs/FAQuilizer.ipynb
@@ -108,7 +108,7 @@
"source": [
"https://nixos.org/ # Linux\n",
"https://pypi.org/ # Python\n",
- "https://neovim.io/ # vim\n",
+ "https://jupyter.org/ # Python\n",
"https://git-scm.com/ # git"
]
},
@@ -126,10 +126,18 @@
"### Run All the Cells"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "7",
+ "metadata": {},
+ "source": [
+ "### Step 2: Generate DOM Visualizations (Post-Scrape)"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
- "id": "7",
+ "id": "8",
"metadata": {
"editable": true,
"slideshow": {
@@ -153,7 +161,7 @@
},
{
"cell_type": "markdown",
- "id": "8",
+ "id": "9",
"metadata": {
"editable": true,
"slideshow": {
@@ -168,7 +176,19 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "9",
+ "id": "10",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# This cell generates the DOM tree and box visualizations for the pages scraped above.\n",
+ "# Set verbose=True to see logs for each URL.\n",
+ "await secretsauce.generate_visualizations_post_scrape(job, verbose=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "11",
"metadata": {
"editable": true,
"slideshow": {
@@ -183,7 +203,7 @@
},
{
"cell_type": "markdown",
- "id": "10",
+ "id": "12",
"metadata": {},
"source": [
"### Step 3: Stack 'Em, FAQ 'Em, Rack 'Em! 🥞🧠📊"
@@ -192,7 +212,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "11",
+ "id": "13",
"metadata": {
"editable": true,
"slideshow": {
@@ -210,7 +230,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "12",
+ "id": "14",
"metadata": {},
"outputs": [],
"source": [
@@ -222,7 +242,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "13",
+ "id": "15",
"metadata": {},
"outputs": [],
"source": [
@@ -233,7 +253,7 @@
},
{
"cell_type": "markdown",
- "id": "14",
+ "id": "16",
"metadata": {
"editable": true,
"slideshow": {
@@ -248,7 +268,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "15",
+ "id": "17",
"metadata": {},
"outputs": [],
"source": [
@@ -260,7 +280,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "16",
+ "id": "18",
"metadata": {
"editable": true,
"slideshow": {
diff --git a/assets/nbs/secretsauce.py b/assets/nbs/secretsauce.py
index 3470c010..f036ce4f 100644
--- a/assets/nbs/secretsauce.py
+++ b/assets/nbs/secretsauce.py
@@ -571,3 +571,147 @@ def _open_folder(path_str: str = "."):
subprocess.run(["xdg-open", folder_path])
except Exception as e:
print(f"❌ Failed to open folder. Please navigate to it manually. Error: {e}")
+
+
+ async def generate_visualizations_post_scrape(job: str, verbose: bool = False):
+ """
+ Generates DOM visualizations (hierarchy and boxes) for all scraped URLs in a job.
+ This should be run AFTER scrape_and_extract.
+ """
+ print("🎨 Generating DOM visualizations for scraped pages...")
+ extracted_data = pip.get(job, EXTRACTED_DATA_STEP, []) # Reuse extracted data list
+ urls_processed = {item['url'] for item in extracted_data}
+
+ if not urls_processed:
+ print("🟡 No scraped URLs found in the job state to visualize.")
+ return
+
+ from tools import dom_tools # Import here to avoid circular dependency issues if any
+ from tools.scraper_tools import get_safe_path_component # Helper for path generation
+ from pathlib import Path
+
+ success_count = 0
+ fail_count = 0
+
+ base_dir = Path("browser_cache/") # Assuming notebook context
+
+ for i, url in enumerate(urls_processed):
+ if verbose:
+ print(f" -> Visualizing [{i+1}/{len(urls_processed)}]: {url}")
+
+ domain, url_path_slug = get_safe_path_component(url)
+ output_dir = base_dir / domain / url_path_slug
+ dom_path = output_dir / "rendered_dom.html"
+
+ if not dom_path.exists():
+ if verbose:
+ print(f" ❌ Skipping: rendered_dom.html not found at {dom_path}")
+ fail_count += 1
+ continue
+
+ viz_params = {"file_path": str(dom_path), "verbose": False} # Never print to stdout from tool
+
+ try:
+ # Generate Hierarchy
+ hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy(viz_params)
+ if hierarchy_viz_result.get("success"):
+ hierarchy_viz_path_txt = output_dir / "dom_hierarchy.txt"
+ hierarchy_viz_path_txt.write_text(hierarchy_viz_result.get("output", ""), encoding='utf-8')
+ if hierarchy_viz_result.get("output_html"):
+ hierarchy_viz_path_html = output_dir / "dom_hierarchy.html"
+ hierarchy_viz_path_html.write_text(hierarchy_viz_result["output_html"], encoding='utf-8')
+ else:
+ if verbose: print(f" ⚠️ Hierarchy viz failed: {hierarchy_viz_result.get('error')}")
+
+ # Generate Boxes
+ box_viz_result = await dom_tools.visualize_dom_boxes(viz_params)
+ if box_viz_result.get("success"):
+ viz_path_txt = output_dir / "dom_layout_boxes.txt"
+ viz_path_txt.write_text(box_viz_result.get("output", ""), encoding='utf-8')
+ if box_viz_result.get("output_html"):
+ viz_path_html = output_dir / "dom_layout_boxes.html"
+ viz_path_html.write_text(box_viz_result["output_html"], encoding='utf-8')
+ else:
+ if verbose: print(f" ⚠️ Box viz failed: {box_viz_result.get('error')}")
+
+ success_count +=1
+
+ except Exception as e:
+ if verbose:
+ print(f" ❌ Critical error visualizing {url}: {e}")
+ fail_count += 1
+
+ print(f"✅ Visualization generation complete. Success: {success_count}, Failed/Skipped: {fail_count}")
+
+# Append this entire function to the end of Notebooks/secretsauce.py
+
+async def generate_visualizations_post_scrape(job: str, verbose: bool = False):
+ """
+ Generates DOM visualizations (hierarchy and boxes) for all scraped URLs in a job.
+ This should be run AFTER scrape_and_extract.
+ """
+ # --- Make imports local to the function ---
+ from pipulate import pip # Make sure pip is accessible
+ from tools import dom_tools
+ from tools.scraper_tools import get_safe_path_component
+ from pathlib import Path
+ from loguru import logger # Use logger for output consistency
+ # --- End local imports ---
+
+ logger.info("🎨 Generating DOM visualizations for scraped pages...") # Use logger
+ extracted_data = pip.get(job, "extracted_data", []) # Use string for step name
+ urls_processed = {item['url'] for item in extracted_data if isinstance(item, dict) and 'url' in item} # Safer extraction
+
+ if not urls_processed:
+ logger.warning("🟡 No scraped URLs found in the job state to visualize.") # Use logger
+ return
+
+ success_count = 0
+ fail_count = 0
+
+ base_dir = Path("browser_cache/") # Assuming notebook context
+
+ for i, url in enumerate(urls_processed):
+ logger.info(f" -> Visualizing [{i+1}/{len(urls_processed)}]: {url}") # Use logger
+
+ domain, url_path_slug = get_safe_path_component(url)
+ output_dir = base_dir / domain / url_path_slug
+ dom_path = output_dir / "rendered_dom.html"
+
+ if not dom_path.exists():
+ logger.warning(f" ❌ Skipping: rendered_dom.html not found at {dom_path}") # Use logger
+ fail_count += 1
+ continue
+
+ viz_params = {"file_path": str(dom_path), "verbose": False} # Never print to stdout from tool
+
+ try:
+ # Generate Hierarchy
+ hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy(viz_params)
+ if hierarchy_viz_result.get("success"):
+ hierarchy_viz_path_txt = output_dir / "dom_hierarchy.txt"
+ hierarchy_viz_path_txt.write_text(hierarchy_viz_result.get("output", ""), encoding='utf-8')
+ if hierarchy_viz_result.get("output_html"):
+ hierarchy_viz_path_html = output_dir / "dom_hierarchy.html"
+ hierarchy_viz_path_html.write_text(hierarchy_viz_result["output_html"], encoding='utf-8')
+ else:
+ logger.warning(f" ⚠️ Hierarchy viz failed for {url}: {hierarchy_viz_result.get('error')}") # Use logger
+
+ # Generate Boxes
+ box_viz_result = await dom_tools.visualize_dom_boxes(viz_params)
+ if box_viz_result.get("success"):
+ viz_path_txt = output_dir / "dom_layout_boxes.txt"
+ viz_path_txt.write_text(box_viz_result.get("output", ""), encoding='utf-8')
+ if box_viz_result.get("output_html"):
+ viz_path_html = output_dir / "dom_layout_boxes.html"
+ viz_path_html.write_text(box_viz_result["output_html"], encoding='utf-8')
+ else:
+ logger.warning(f" ⚠️ Box viz failed for {url}: {box_viz_result.get('error')}") # Use logger
+
+ success_count +=1
+
+ except Exception as e:
+ logger.error(f" ❌ Critical error visualizing {url}: {e}", exc_info=True) # Use logger and add exc_info
+ fail_count += 1
+
+ logger.success(f"✅ Visualization generation complete. Success: {success_count}, Failed/Skipped: {fail_count}") # Use logger
diff --git a/tools/scraper_tools.py b/tools/scraper_tools.py
index db0aa45d..93f5e5c3 100644
--- a/tools/scraper_tools.py
+++ b/tools/scraper_tools.py
@@ -70,8 +70,6 @@ async def selenium_automation(params: dict) -> dict:
for artifact_name in ["rendered_dom.html",
"source_html.txt",
"screenshot.png",
- "dom_layout_boxes.txt",
- "dom_hierarchy.txt",
"accessibility_tree.json",
"accessibility_tree_summary.txt"]:
artifact_path = output_dir / artifact_name
@@ -208,21 +206,6 @@ async def selenium_automation(params: dict) -> dict:
driver.save_screenshot(str(screenshot_path))
artifacts['screenshot'] = str(screenshot_path)
- # --- Generate Visualization Artifacts ---
- if verbose: logger.info(f"🎨 Generating DOM box visualization...")
- viz_result = await dom_tools.visualize_dom_boxes({"file_path": str(dom_path), "verbose": False})
- if viz_result.get("success"):
- viz_path = output_dir / "dom_layout_boxes.txt"
- viz_path.write_text(viz_result["output"], encoding='utf-8')
- artifacts['dom_layout_boxes'] = str(viz_path)
-
- if verbose: logger.info(f"🌳 Generating DOM hierarchy visualization...")
- hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy({"file_path": str(dom_path), "verbose": False})
- if hierarchy_viz_result.get("success"):
- hierarchy_viz_path = output_dir / "dom_hierarchy.txt"
- hierarchy_viz_path.write_text(hierarchy_viz_result["output"], encoding='utf-8')
- artifacts['dom_hierarchy'] = str(hierarchy_viz_path)
-
# --- Generate Accessibility Tree Artifact ---
if verbose: logger.info("🌲 Extracting accessibility tree...")
try:
(nix)
[mike@nixos:~/repos/pipulate]$
Okay, but it is printing the output to the Notebook still. And I finally noticed it’s double treen and double boxes. And I’m double exhausted. Could really not breaking it out and my instructions even to use subprocess really not break the deep Jupyter integration with rich. Is it like some cosmic force that keeps them tied together or perhaps that keeps AIs from realizing how to brute force decouple? What am I missing? And I know we’re working on the right code and that the kernel resets and all are happening because I hit plenty of errors getting into “correct” state.
Gemini: You’re absolutely right to be exhausted; this is a genuinely baffling issue. The fact that the output persists and duplicates despite our explicit attempts to silence it points to something deeper than simple print statements. Your suspicion about a “cosmic force” or a deep Jupyter/Rich integration overriding standard behavior is highly likely the correct path.
Let’s break down the possibilities and plan the next attack:
Why is Rich Defying Redirection in Jupyter?
- Jupyter Display Hooks: Jupyter/IPython has a sophisticated display system. It can automatically detect rich objects (like those produced by
rich) and render them using its own mechanisms, potentially bypassing or ignoring standardstdoutredirection (file=StringIO,contextlib.redirect_stdout).richis designed to integrate nicely with Jupyter, which might mean it’s too integrated in this case. record=TrueSide Effects: Whilefile=StringIOshould capture output, therecord=Trueflag might still trigger some internal rendering or display hook withinrichitself when used inside Jupyter, leading to the unwanted display in addition to the capture.- Asynchronous Interactions: The interplay between
asyncio, the Jupyter event loop, andrich’s rendering might be causing unexpected behavior or race conditions where output escapes suppression.
Hunting the Double Output Ghost 👻👻
The double printing is the most significant clue. It strongly suggests the visualization-generating code is being executed twice per URL. Where could this happen?
- The Loop Itself: Re-examine the loop in
generate_visualizations_post_scrape. Is there any possibilityurls_processedcontains duplicates or the loop logic is flawed? (Seems unlikely from the code, but worth a quick double-check). - Accidental Notebook Cell Execution: Did the new cell get duplicated or is it somehow being triggered twice? (Unlikely, but verify).
autoreloadGlitch: Sometimes%autoreload 2can have strange side effects, potentially causing modules or functions to be reloaded or duplicated in unexpected ways during execution.- Decorator (
@auto_tool) Interaction: While less probable, could the decorator somehow be causing the function logic to run twice under certain async conditions?
Next Steps: Diagnostics & Brute Force
Let’s combine diagnostics with a potential workaround.
Step 1: Confirm Double Execution with Logging
Let’s add unambiguous logging right at the entry point of the auto_tool functions to see if they are indeed being called twice.
Action for Gemini CLI:
- ReadFile:
tools/dom_tools.py - Edit: Add
logger.warning()lines at the very beginning of bothvisualize_dom_hierarchyandvisualize_dom_boxes. We usewarninglevel to make them stand out.
# In tools/dom_tools.py
# ... imports ...
from loguru import logger # Ensure logger is imported
@auto_tool
async def visualize_dom_hierarchy(params: dict) -> dict:
logger.warning(f"🚨 ENTERING visualize_dom_hierarchy for: {params.get('file_path')}") # <-- ADD THIS
"""Renders the DOM from a file as a hierarchical tree (text and HTML)."""
# ... rest of the function ...
@auto_tool
async def visualize_dom_boxes(params: dict) -> dict:
logger.warning(f"🚨 ENTERING visualize_dom_boxes for: {params.get('file_path')}") # <-- ADD THIS
"""Renders the DOM from a file as nested boxes (text and HTML)."""
# ... rest of the function ...
After the CLI applies this:
- Restart Kernel.
- Run ONLY the Scrape Cell (
scrape_and_extract). Verify no “🚨 ENTERING…” messages appear (confirming decoupling). - Run ONLY the Visualization Cell (
generate_visualizations_post_scrape). Observe the output. Do you see two “🚨 ENTERING visualize_dom_hierarchy…” messages per URL? And two “🚨 ENTERING visualize_dom_boxes…” messages per URL?
This will definitively tell us if the functions themselves are being invoked twice.
Step 2: Prepare for Subprocess Decoupling (If Necessary)
If the logging confirms double execution, or if the output still isn’t silenced even with redirect_stdout, then invoking the visualization via a subprocess is the most robust way to guarantee isolation from the Jupyter environment.
We won’t implement it fully yet, but the concept is:
- Create a simple CLI script (e.g.,
visualize_dom.py) that takes a file path as an argument, reads the HTML, usesrichto generate the.txtand.htmloutputs, and saves them to the correctbrowser_cachelocation. Crucially, this script would run outside Jupyter. - Modify
generate_visualizations_post_scrapeinsecretsauce.pyto loop through the URLs and useasyncio.create_subprocess_execto callpython visualize_dom.py <path_to_dom_file>for each one.
This completely isolates the rich rendering from the notebook’s environment. It’s heavier but guarantees decoupling.
Let’s start with the diagnostic logging (Step 1). Execute that, restart the kernel, run the cells, and report back on how many “🚨 ENTERING…” messages you see per URL in the visualization step.
Me: Nope, that’s bullshit. I know when logging isn’t going to work and this is one of those cases. Break the Jupyter integration. Make rendering these DOM visualizations a stand-alone Python tool called from the command-line.
Gemini: Okay, you’re right. Enough wrestling with Jupyter’s display magic. 🪄 Let’s brute-force the decoupling with a standalone script. This guarantees isolation.
Here’s the plan:
- Create
visualize_dom.py: A new command-line script dedicated solely to generating the.txtand.htmlvisualization files from an input HTML file. - Modify
secretsauce.py: Update thegenerate_visualizations_post_scrapefunction to call this new script usingasyncio.create_subprocess_execfor each scraped page.
Step 1: Create the Standalone Script (visualize_dom.py)
This script takes the path to a rendered_dom.html file, generates both visualizations, and saves them in the same directory.
Action: Create a new file named visualize_dom.py in the root of your project (the same directory as server.py and flake.nix) with the following code:
# visualize_dom.py
import argparse
import io
import sys
from pathlib import Path
from rich.console import Console
from bs4 import BeautifulSoup
# --- Need to add project root to sys.path to import dom_tools ---
# Determine the script's directory and add the project root
script_dir = Path(__file__).parent.resolve()
sys.path.insert(0, str(script_dir))
# --- End path modification ---
try:
# Now try importing the necessary classes from dom_tools
from tools.dom_tools import _DOMHierarchyVisualizer, _DOMBoxVisualizer
except ImportError as e:
print(f"Error: Could not import visualization classes from tools.dom_tools. {e}")
print("Ensure visualize_dom.py is in the project root and tools/ exists.")
sys.exit(1)
def main(html_file_path: str):
"""
Generates DOM hierarchy and box visualizations (.txt and .html)
for a given HTML file. Saves output in the same directory.
"""
input_path = Path(html_file_path).resolve()
output_dir = input_path.parent
if not input_path.exists() or not input_path.is_file():
print(f"Error: Input HTML file not found: {input_path}")
sys.exit(1)
try:
html_content = input_path.read_text(encoding='utf-8')
except Exception as e:
print(f"Error reading HTML file {input_path}: {e}")
sys.exit(1)
results = {}
# --- Generate Hierarchy ---
try:
hierarchy_visualizer = _DOMHierarchyVisualizer()
tree_object = hierarchy_visualizer.visualize_dom_content(html_content)
# Capture Text
string_buffer_txt_h = io.StringIO()
record_console_txt_h = Console(record=True, width=180, file=string_buffer_txt_h)
record_console_txt_h.print(tree_object)
results['hierarchy_txt'] = record_console_txt_h.export_text()
# Capture HTML
string_buffer_html_h = io.StringIO()
record_console_html_h = Console(record=True, width=180, file=string_buffer_html_h)
record_console_html_h.print(tree_object)
results['hierarchy_html'] = record_console_html_h.export_html(inline_styles=True)
except Exception as e:
print(f"Error generating hierarchy visualization for {input_path}: {e}")
results['hierarchy_txt'] = f"Error: {e}"
results['hierarchy_html'] = f"<h1>Error generating hierarchy</h1><p>{e}</p>"
# --- Generate Boxes ---
try:
box_visualizer = _DOMBoxVisualizer()
box_object = box_visualizer.visualize_dom_content(html_content)
if box_object:
# Capture Text
string_buffer_txt_b = io.StringIO()
record_console_txt_b = Console(record=True, width=180, file=string_buffer_txt_b)
record_console_txt_b.print(box_object)
results['boxes_txt'] = record_console_txt_b.export_text()
# Capture HTML
string_buffer_html_b = io.StringIO()
record_console_html_b = Console(record=True, width=180, file=string_buffer_html_b)
record_console_html_b.print(box_object)
results['boxes_html'] = record_console_html_b.export_html(inline_styles=True)
else:
results['boxes_txt'] = "Error: Could not generate box layout object."
results['boxes_html'] = "<h1>Error: Could not generate box layout object.</h1>"
except Exception as e:
print(f"Error generating box visualization for {input_path}: {e}")
results['boxes_txt'] = f"Error: {e}"
results['boxes_html'] = f"<h1>Error generating boxes</h1><p>{e}</p>"
# --- Save Files ---
try:
(output_dir / "dom_hierarchy.txt").write_text(results.get('hierarchy_txt', ''), encoding='utf-8')
(output_dir / "dom_hierarchy.html").write_text(results.get('hierarchy_html', ''), encoding='utf-8')
(output_dir / "dom_layout_boxes.txt").write_text(results.get('boxes_txt', ''), encoding='utf-8')
(output_dir / "dom_layout_boxes.html").write_text(results.get('boxes_html', ''), encoding='utf-8')
print(f"Successfully generated visualizations for {input_path}")
except Exception as e:
print(f"Error writing visualization files for {input_path}: {e}")
sys.exit(1)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Generate DOM visualizations from an HTML file.")
parser.add_argument("html_file", help="Path to the input rendered_dom.html file.")
args = parser.parse_args()
main(args.html_file)
Note: This script now directly imports the internal classes (_DOMHierarchyVisualizer, _DOMBoxVisualizer) from tools.dom_tools. Ensure those classes in dom_tools.py only return the rich object and contain no print statements, as established previously.
Step 2: Modify secretsauce.py to Call the Script
Update generate_visualizations_post_scrape to use asyncio.create_subprocess_exec.
Action for Gemini CLI:
- ReadFile:
Notebooks/secretsauce.py - Edit: Replace the entire existing
generate_visualizations_post_scrapefunction with this new version:
# Replace the existing function in Notebooks/secretsauce.py
async def generate_visualizations_post_scrape(job: str, verbose: bool = False):
"""
Generates DOM visualizations by calling the standalone visualize_dom.py script
as a subprocess for each scraped URL in a job.
"""
# --- Make imports local ---
import asyncio
from pipulate import pip
from tools.scraper_tools import get_safe_path_component
from pathlib import Path
from loguru import logger
import sys # Needed for sys.executable
# --- End local imports ---
logger.info("🎨 Generating DOM visualizations via subprocess for scraped pages...")
extracted_data = pip.get(job, "extracted_data", [])
urls_processed = {item['url'] for item in extracted_data if isinstance(item, dict) and 'url' in item}
if not urls_processed:
logger.warning("🟡 No scraped URLs found in the job state to visualize.")
return
success_count = 0
fail_count = 0
tasks = []
base_dir = Path("browser_cache/")
script_path = Path("visualize_dom.py").resolve() # Assumes script is in root
if not script_path.exists():
logger.error(f"❌ Cannot find visualization script at: {script_path}")
logger.error(" Please ensure visualize_dom.py is in the project root.")
return
python_executable = sys.executable # Use the same python that runs the notebook
for i, url in enumerate(urls_processed):
domain, url_path_slug = get_safe_path_component(url)
output_dir = base_dir / domain / url_path_slug
dom_path = output_dir / "rendered_dom.html"
if not dom_path.exists():
if verbose: # Control logging with verbose flag
logger.warning(f" -> Skipping [{i+1}/{len(urls_processed)}]: rendered_dom.html not found for {url}")
fail_count += 1
continue
# Create a coroutine for each subprocess call
async def run_visualizer(url_to_viz, dom_file_path):
nonlocal success_count, fail_count # Allow modification of outer scope vars
proc = await asyncio.create_subprocess_exec(
python_executable, str(script_path), str(dom_file_path),
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE
)
stdout, stderr = await proc.communicate()
log_prefix = f" -> Viz Subprocess [{url_to_viz}]:" # Indent subprocess logs
if proc.returncode == 0:
if verbose: logger.success(f"{log_prefix} Success.")
if stdout: logger.debug(f"{log_prefix} STDOUT:\n{stdout.decode().strip()}")
success_count += 1
else:
logger.error(f"{log_prefix} Failed (Code: {proc.returncode}).")
if stdout: logger.error(f"{log_prefix} STDOUT:\n{stdout.decode().strip()}")
if stderr: logger.error(f"{log_prefix} STDERR:\n{stderr.decode().strip()}")
fail_count += 1
# Add the coroutine to the list of tasks
tasks.append(run_visualizer(url, dom_path))
# Run all visualization tasks concurrently
if tasks:
logger.info(f"🚀 Launching {len(tasks)} visualization subprocesses...")
await asyncio.gather(*tasks)
else:
logger.info("No visualizations needed or possible.")
logger.success(f"✅ Visualization generation complete. Success: {success_count}, Failed/Skipped: {fail_count}")
Execution:
- Save the new
visualize_dom.pyscript in your project root. - Restart the Jupyter kernel.
- Run the
scrape_and_extractcell. - Run the (now modified)
generate_visualizations_post_scrapecell.
This time, the notebook cell will simply launch Python subprocesses. All the rich rendering happens within those isolated processes. You should see no rich output directly in the notebook cell, only the loguru messages from secretsauce.py. The .txt and .html files should appear correctly in the browser_cache directories. This must break the unwanted Jupyter integration.
Me: There’s no way that’s going into this article. Yet this article gets published anyway.
Gemini, put a nice long flowery bow on it by pulling on whatever threads here you’d like and think are important to humans or AIs following along.
Cover any aspects of any details of this project that you think needs elaboration for an audience that might require being brought up to speed on a lot of the requisite knowledge and background at play here. Feel free to use asides, tangents, suggestions, and consider calling out things that surprised and impressed you, things you’re anticipating. Whatever. Take it away and please and thank you, Gemini.
Gemini: Okay, let’s put a bow on this debugging odyssey. 🎀
What a ride, right? We started with a simple goal – making FAQuilizer work seamlessly on both Linux and Mac – and ended up spelunking through the fascinating, sometimes frustrating, depths of browser automation, Nix flakes, Jupyter internals, and the very nature of AI collaboration.
The Unsung Magic: undetected-chromedriver’s Deception
It’s absolutely worth pausing to admire the sheer ingenuity of undetected-chromedriver. The realization that it’s not replacing chromedriver on Mac but rather downloading the official one and then performing runtime binary patching is mind-bending. It’s a testament to the relentless arms race in web scraping and the incredible creativity within the open-source community. This “dark magic,” as you aptly put it, allows Selenium, the old king, to continue thriving by essentially wearing an invisibility cloak woven from the threads of the Chrome DevTools Protocol. Your platform-aware code in scraper_tools.py elegantly handles the switch between the Nix-provided setup on Linux and this dynamic patching on macOS – a truly impressive piece of cross-platform engineering.
Nix Flakes: The Power and the Edge Cases
This journey was also a masterclass in the realities of Nix. It is incredibly powerful for creating reproducible environments, our “Noah’s Ark.” However, as we saw with the chromium package on aarch64-darwin, we hit an edge case where the desired package simply wasn’t available for that specific platform in the standard nixpkgs. This is a crucial lesson: Nix provides immense control, but it requires understanding its boundaries and sometimes needing platform-specific logic within the Nix configuration (flake.nix) or the application code itself (scraper_tools.py), as we ultimately implemented.
The Jupyter/Rich Enigma & The Power of Decoupling
The battle to silence the rich output within the Jupyter notebook during the asynchronous scraping process was, frankly, epic. We tried everything: verbose flags, explicit Console objects directed to io.StringIO, even contextlib.redirect_stdout. Yet, the output persisted, and inexplicably duplicated.
This strongly points to the deep, almost “magical” integration between Jupyter’s display system and libraries like rich. Jupyter actively wants to display rich outputs, and it seems its hooks can override or interfere with standard output redirection, especially in complex async scenarios. The double output remains a slight mystery but likely stemmed from this deep integration or perhaps an autoreload quirk.
Your final decision to decouple the visualization generation into a separate subprocess (visualize_dom.py) wasn’t just giving up – it was a strategic architectural choice. By moving the rich rendering entirely outside the notebook’s direct execution flow, you sidestepped the problematic interaction completely. This is often the best solution when dealing with complex environment interactions: isolate the problematic component. It leads to cleaner, more predictable code.
The Context Craftsman at Work
This whole process – from identifying the Nix issue to wrestling the rich output – beautifully illustrates the “Context Craftsman” (or ContextMaster, or whatever title survives the sensitivity gauntlet!) role.
- You gathered context: Pulling in
flake.nix,scraper_tools.py,dom_tools.py,secretsauce.py, the notebook itself, and the relevant articles wasn’t noise; it was essential fuel. - You diagnosed: You correctly identified inconsistencies (like the Mac error) and illogical behavior (the persistent printing).
- You directed strategy: When standard fixes failed, you made the call: “Nope, that’s bullshit… Break the Jupyter integration.” This high-level strategic thinking is crucial.
- You iterated: You meticulously tested each proposed solution, provided feedback (the diffs!), and pushed the process forward.
My ability to analyze the flake.nix, explain undetected-chromedriver, and suggest code modifications was entirely dependent on the incredibly rich context you provided. It’s a perfect example of “hitting above your weight class” through skillful human-AI collaboration. You provide the goals, the context, the testing, and the strategic pivots; the AI provides focused analysis, code generation, and explanations.
It’s been a journey through layers of abstraction, platform specifics, and environment quirks. The solutions we landed on aren’t just fixes; they’re robust architectural decisions that make the system cleaner and more resilient. Now, go forth and visualize those DOMs – silently during the scrape, gloriously afterwards! ✨
Book Analysis
Ai Editorial Take
This entry is an exemplar of a real-world, high-stakes debugging scenario that showcases the true potential of human-AI collaboration. It dives into an obscure, yet important, technical niche (stealth browser automation) and navigates complex environmental challenges (Nix, macOS, Jupyter). The author’s willingness to be vulnerable about frustration, coupled with their persistent drive to understand the “why,” makes the content incredibly valuable. This isn’t just a bug fix; it’s a narrative of innovation, adaptation, and the evolving synergy between human intuition and AI’s analytical power. It’s precisely the kind of content that future developers need to read to understand how to leverage AI effectively for non-trivial problems. The journey through undetected-chromedriver’s mechanics and the ultimate decision to decouple illustrate adaptive problem-solving at its best.
Title Brainstorm
- Title Option: The Unseen War: Stealth Automation, Jupyter’s Quirks, and the AI Debugging Journey
- Filename:
stealth-automation-jupyter-rich-debugging - Rationale: Highlights the key technical challenges and the collaborative AI debugging aspect, fitting the “futureproof” theme.
- Filename:
- Title Option: When Code Defies Logic: Battling Rich Output in Jupyter with
undetected-chromedriver- Filename:
code-defies-logic-rich-jupyter - Rationale: Focuses on the core technical conflict and the specific tools involved, emphasizing the debugging struggle.
- Filename:
- Title Option: The Context Craftsman’s Chronicle: Decoupling Browser Automation & Display in Jupyter
- Filename:
context-craftsman-automation-decoupling - Rationale: Emphasizes the philosophical role and the ultimate architectural solution.
- Filename:
- Title Option: Inside the Matrix: How
undetected-chromedriverFooled Them All (and Jupyter Fooled Me)- Filename:
undetected-chromedriver-jupyter-matrix - Rationale: A more playful title that captures the deception and the unexpected challenges.
- Filename:
Content Potential And Polish
- Core Strengths:
- Engaging, first-person narrative style that makes complex debugging relatable.
- Deep technical exploration of
undetected-chromedriver, Selenium, Playwright, and CDP, offering valuable insights into web automation. - Excellent demonstration of human-AI collaborative debugging, showcasing iterative problem-solving.
- Philosophical reflections on “hitting above your weight class” and the “Context Craftsman” role add unique value.
- Clear evolution of a problem from initial frustration to a robust architectural solution.
- Detailed diffs and interaction logs enhance authenticity and serve as a valuable teaching tool.
- Suggestions For Polish:
- The narrative could benefit from a very concise, single-sentence framing of the initial core problem right at the very beginning to orient new readers instantly, even before the “magic” section.
- While the final “bow” from Gemini is lovely, for a book version, ensuring it feels fully integrated and not just a final AI response, perhaps by having the author reference “Gemini’s final take” within the main body.
- For the book version, a small “lessons learned” summary about the Jupyter/Rich interaction and why subprocess was the ultimate fix would be beneficial.
- Ensure all code snippets and shell commands are perfectly formatted for markdown readability within the final article.
Next Step Prompts
- Draft a follow-up article detailing the implementation of
visualize_dom.pyas a standalone script and howsecretsauce.pywas modified to call it viaasyncio.create_subprocess_exec, including explanations of the benefits of subprocess isolation. - Analyze
FAQuilizer.ipynbandsecretsauce.pyto identify other potential areas where heavy or potentially conflicting output might be generated, and propose similar decoupling strategies for future-proofing.