--- title: 'From Log Chaos to Clean Notebook: A Dependency Debugging Saga' permalink: /futureproof/dependency-debugging-log-silencing-jupyter-notebook/ description: This debugging journey was a brutal reminder of how deeply intertwined software components are. What seemed like a simple desire for clean log output spiraled into a multi-layered investigation, forcing me to confront Python's quirks, unexpected C++ library behaviors, and the ever-present challenge of 'dependency hell.' The desktop crashes were genuinely alarming, underscoring that even seemingly innocuous changes can have catastrophic system-level effects. Ultimately, it highlighted that the most effective solutions often lie in understanding the underlying ecosystem, not just the surface symptoms. It was frustrating, but incredibly instructive, reinforcing the value of meticulous iteration and community knowledge. meta_description: 'A Python debugging saga: Taming verbose logs and warnings in Jupyter Notebooks. Unraveling dependency conflicts, C++ library noise, and system stability issues for clean output.' meta_keywords: Python, Jupyter Notebook, logging, warnings, debugging, dependency management, loguru, absl, grpcio, pipulate, automation, system interactions layout: post sort_order: 7 --- ## Setting the Stage: Context for the Curious Book Reader This journal entry chronicles a critical debugging odyssey in the `pipulate` project. What began as a quest to simply quiet verbose log output in Jupyter Notebooks rapidly escalated into a complex investigation, touching upon Python's logging mechanisms, low-level C++ library interactions, and the intricate world of dependency management. It's a testament to the unpredictable nature of software development and the indispensable role of human persistence in untangling digital knots. --- ## Technical Journal Entry Begins Everything is going perfectly. It's a marathon session. The past few weeks have been, but I'm making tremendous progress and this is really the home stretch. It's mostly about grinding off the final burrs, and in this case it's the output of ugly logfile warnings that aren't supposed to show when `from pipulate import pip`'ing — versus the Web `app` where all that stuff is just fine in `server.py`'s terminal console output. And it started happening again when I added so-called "magics" commands to the Jupyter Notebook in JupyterLab. ## The Initial Logging Dilemma **Me**: What do these "magics" do in a Jupyter Notebook cell in JupyterLab? %load_ext autoreload %autoreload 2 **Gemini**: Those two "magic" commands work together to automatically reload your imported Python modules in a Jupyter Notebook before you run any code. This is incredibly useful because it means you can edit the code in your `.py` files and have the changes reflected in your notebook immediately, without having to restart the kernel. ----- ## How They Work * `%load_ext autoreload`: This command **loads** the `autoreload` extension into your Jupyter environment. You need to do this first to make the magic available. * `%autoreload 2`: This command **activates** the automatic reloading. The number `2` sets the mode to reload all modules automatically before executing any new code in a cell. ### Why This is Useful Imagine you have a Python file named `my_functions.py` and you import a function from it into your notebook: ```python # In your Jupyter Notebook cell from my_functions import my_calculation ``` Then you realize there's a bug in `my_calculation`. **Without autoreload**, you would have to: 1. Go to `my_functions.py` and fix the code. 2. Save the file. 3. Go back to your notebook and **restart the entire kernel** to import the new version. **With autoreload**, you just: 1. Go to `my_functions.py` and fix the code. 2. Save the file. 3. Re-run the cell in your notebook that uses `my_calculation`, and the changes will be picked up automatically. ✅ **Me**: Well what do you know! I almost never used the Jupyter "magics". My Jupyter Notebook suddenly started showing log output: 2025-10-13 19:28:22.499 | INFO | pipulate.core:__init__:206 - Pipulate initializing in standalone mode with db: /home/mike/repos/pipulate/Notebooks/pipeline.sqlite2025-10-13 19:28:22.522 | DEBUG | pipulate.core:__init__:100 - DictLikeDB initialized. ...where it hasn't before. **Gemini**: To understand why the logging behavior has changed, I need to see the contents of `imports/server_logging.py`. This file is imported and used in `pipulate/core.py` as `slog`, and the line `log = slog.LogManager(logger)` strongly suggests it's responsible for configuring how `loguru` displays messages, including setting the log levels (`INFO`, `DEBUG`) and formats. Without seeing it, I can't definitively diagnose the change. Please add `imports/server_logging.py` to your `foo_files.py` to include it in the next context. **Me**: [Shows file] **Gemini**: The log output is appearing now because the `pipulate` object is being fully initialized when you import it, which now triggers the logging setup in `pipulate/core.py`. ----- ## 💡 The Cause: Early Initialization Your `pipulate/__init__.py` file now contains this line: ```python pip = Pipulate(db_path=str(DB_PATH)) ``` When your notebook runs `from pipulate import pip`, it executes this code immediately. The `Pipulate` class's `__init__` method in `core.py` is called with a `db_path`, which it correctly identifies as a "standalone/notebook" context. The first thing it does in that code block is import and use `loguru`: ```python # In pipulate/core.py if db_path: # Standalone/Notebook Context from fastlite import Database from loguru import logger # <-- Loguru gets imported logger.info(f"Pipulate initializing...") # <-- A log message is sent ``` The `server_logging.py` file configures `loguru` to show both `INFO` and `DEBUG` level messages to the console (`sys.stderr`), which Jupyter displays. Previously, this initialization might have been happening later or in a different way that didn't trigger the log output in your notebook. Now, it's one of the very first things that happens upon import. This behavior is actually correct and desirable for debugging, as it confirms exactly when and how your central `pip` object is being created. ## Pinpointing the Source: Early Initialization **Me**: But it makes usingn the Notebook look ugly and scary to newbs and pleibs. Maybe we only show warns and errors? **Gemini**: Yes, you can definitely make the notebook output cleaner. The best way is to reconfigure the logger specifically for the notebook environment to only show `WARNING` level messages and above, while still keeping detailed logs in a file for debugging. The log messages are appearing because the `loguru` library is being configured to show `INFO` and `DEBUG` levels by default. We can override this. ----- ## The Fix: Quieter Logs for Notebooks We'll adjust the configuration in the one place that acts as the entry point for your notebooks: `/home/mike/repos/pipulate/pipulate/__init__.py`. This will set a higher logging level for the console without affecting the more verbose logging needed when running the full server application. **Action:** Replace the contents of `/home/mike/repos/pipulate/pipulate/__init__.py` with this updated version. ```python # /home/mike/repos/pipulate/pipulate/__init__.py import os import sys from pathlib import Path from .core import Pipulate from loguru import logger # --- NOTEBOOK-SPECIFIC LOGGING CONFIGURATION --- # This block sets up logging specifically for the Jupyter environment. # 1. Remove the default loguru handler to take full control. logger.remove() # 2. Add a new console handler that ONLY shows WARNINGS and ERRORS. # This keeps the notebook output clean and user-friendly. logger.add( sys.stderr, level="WARNING", colorize=True, format="{level: <8} | {name}:{function}:{line} - {message}" ) # 3. Add a file logger that captures EVERYTHING (for debugging if needed). # This is the best of both worlds: a quiet console but a detailed log file. log_dir = Path("Notebooks/logs") log_dir.mkdir(exist_ok=True) logger.add( log_dir / "notebook_run.log", level="DEBUG", rotation="10 MB", format="{time} {level} {message}" ) # --- END LOGGING CONFIGURATION --- # The rest of the file remains the same... ## Refactoring for Quieter Notebook Logs def find_project_root(start_path): """Walks up from a starting path to find the project root (marked by 'flake.nix').""" current_path = Path(start_path).resolve() while current_path != current_path.parent: if (current_path / 'flake.nix').exists(): return current_path current_path = current_path.parent return None project_root = find_project_root(os.getcwd()) or Path.cwd() DB_PATH = project_root / "Notebooks" / "pipeline.sqlite" # Create the singleton instance of the Pipulate class pip = Pipulate(db_path=str(DB_PATH)) ``` ### How This Works 1. **`logger.remove()`:** This command clears any existing `loguru` configurations, giving us a clean slate. 2. **`logger.add(sys.stderr, level="WARNING")`:** This is the key change. It tells the logger to only send messages that are `WARNING`, `ERROR`, or `CRITICAL` to the notebook's output. The `INFO` and `DEBUG` messages are now suppressed from the console. ## The True Culprit: Dependency Version Pinning 3. **`logger.add(".../notebook_run.log", level="DEBUG")`:** This creates a second logging destination—a file. This file will still receive *all* messages (`DEBUG` and up), so you have a complete record for troubleshooting, but it won't clutter your notebook interface. After making this change, your notebook will have a clean, quiet output suitable for any user, while you retain the detailed logs you need for development in the `Notebooks/logs/` directory. **Me**: This is the diff: ```diff [mike@nixos:~/repos/pipulate/pipulate]$ git --no-pager diff diff --git a/pipulate/__init__.py b/pipulate/__init__.py index 2dd9edfb..67035c43 100644 --- a/pipulate/__init__.py +++ b/pipulate/__init__.py @@ -1,11 +1,42 @@ # /home/mike/repos/pipulate/pipulate/__init__.py import os +import sys from pathlib import Path from .core import Pipulate +from loguru import logger + +# --- NOTEBOOK-SPECIFIC LOGGING CONFIGURATION --- +# This block sets up logging specifically for the Jupyter environment. + +# 1. Remove the default loguru handler to take full control. +logger.remove() + +# 2. Add a new console handler that ONLY shows WARNINGS and ERRORS. +# This keeps the notebook output clean and user-friendly. +logger.add( + sys.stderr, + level="WARNING", + colorize=True, + format="{level: <8} | {name}:{function}:{line} - {message}" +) + +# 3. Add a file logger that captures EVERYTHING (for debugging if needed). +# This is the best of both worlds: a quiet console but a detailed log file. +log_dir = Path("Notebooks/logs") +log_dir.mkdir(exist_ok=True) +logger.add( + log_dir / "notebook_run.log", + level="DEBUG", + rotation="10 MB", + format="{time} {level} {message}" +) +# --- END LOGGING CONFIGURATION --- + +# The rest of the file remains the same... -# Determine the project root by looking for a known file, like 'flake.nix' def find_project_root(start_path): + """Walks up from a starting path to find the project root (marked by 'flake.nix').""" current_path = Path(start_path).resolve() while current_path != current_path.parent: if (current_path / 'flake.nix').exists(): @@ -13,12 +44,8 @@ def find_project_root(start_path): current_path = current_path.parent return None -# Default to the current working directory if root isn't found project_root = find_project_root(os.getcwd()) or Path.cwd() - -# Define the explicit, user-facing database path DB_PATH = project_root / "Notebooks" / "pipeline.sqlite" # Create the singleton instance of the Pipulate class -# This `pip` object is what gets imported by `from pipulate import pip` pip = Pipulate(db_path=str(DB_PATH)) \ No newline at end of file [mike@nixos:~/repos/pipulate/pipulate]$ ``` But I just got this error: ```python %load_ext autoreload %autoreload 2 from pipulate import pip import secretsauce import nest_asyncio nest_asyncio.apply() job = "faquilizer-07" # Give your session a unique name ``` ```logs The autoreload extension is already loaded. To reload it, use: %reload_ext autoreload [autoreload of pipulate failed: Traceback (most recent call last): File "/home/mike/repos/pipulate/.venv/lib/python3.12/site-packages/IPython/extensions/autoreload.py", line 325, in check superreload(m, reload, self.old_objects) File "/home/mike/repos/pipulate/.venv/lib/python3.12/site-packages/IPython/extensions/autoreload.py", line 580, in superreload module = reload(module) ^^^^^^^^^^^^^^ File "/nix/store/27fr7ynpilzb7rzmay73g905jbl8br4a-python3-3.12.11/lib/python3.12/importlib/__init__.py", line 131, in reload _bootstrap._exec(spec, module) File "", line 866, in _exec File "", line 999, in exec_module File "", line 488, in _call_with_frames_removed File "/home/mike/repos/pipulate/pipulate/__init__.py", line 27, in log_dir.mkdir(exist_ok=True) File "/nix/store/27fr7ynpilzb7rzmay73g905jbl8br4a-python3-3.12.11/lib/python3.12/pathlib.py", line 1311, in mkdir os.mkdir(self, mode) FileNotFoundError: [Errno 2] No such file or directory: 'Notebooks/logs' ] ``` **Gemini**: You've found a classic "relative path" problem. The error happens because the `autoreload` extension runs your `__init__.py` script from a location where the relative path `Notebooks/logs` doesn't exist. The code assumes it's running from your project's root directory (`/home/mike/repos/pipulate/`), but tools like `autoreload` can change the execution context, breaking the path. ----- ## The Fix: Use an Absolute Path The solution is to use the same robust `project_root` logic we already have in that file to build a full, unambiguous path for the log directory. This makes the script independent of where it's being run from. **Action:** Replace the contents of `/home/mike/repos/pipulate/pipulate/__init__.py` one more time with this corrected version. I've reordered it to find the project root *first* and then use it for everything else. ```python # /home/mike/repos/pipulate/pipulate/__init__.py import os import sys from pathlib import Path from .core import Pipulate from loguru import logger # --- SETUP PATHS FIRST --- def find_project_root(start_path): """Walks up from a starting path to find the project root (marked by 'flake.nix').""" current_path = Path(start_path).resolve() while current_path != current_path.parent: if (current_path / 'flake.nix').exists(): return current_path current_path = current_path.parent return None # Establish the absolute project root path. project_root = find_project_root(os.getcwd()) or Path.cwd() # --- CONFIGURE LOGGING USING ABSOLUTE PATHS --- logger.remove() # Console handler for notebooks (shows only warnings and above). logger.add( sys.stderr, level="WARNING", colorize=True, format="{level: <8} | {name}:{function}:{line} - {message}" ) # File logger that captures everything for debugging. log_dir = project_root / "Notebooks" / "logs" log_dir.mkdir(parents=True, exist_ok=True) # Use parents=True for robustness logger.add( log_dir / "notebook_run.log", level="DEBUG", rotation="10 MB", format="{time} {level} {message}" ) # --- INITIALIZE PIPULATE SINGLETON --- # Define the explicit, user-facing database path using the absolute project root. DB_PATH = project_root / "Notebooks" / "pipeline.sqlite" # Create the singleton instance that gets imported by `from pipulate import pip`. pip = Pipulate(db_path=str(DB_PATH)) ``` ### What Changed 1. **Order of Operations:** The code now finds the `project_root` *before* attempting any file operations. 2. **Absolute Log Path:** The `log_dir` is now built from the absolute `project_root`, making it immune to changes in the current working directory. 3. **Robust Directory Creation:** I've added `parents=True` to the `mkdir` call, which is a good practice that ensures parent directories are created if they don't exist. With this change, your `__init__.py` file is now "ironclad" against path issues, and the `autoreload` will work correctly. ## Autoreload and the Relative Path Trap **Me**: And here's the new diff: ```diff [mike@nixos:~/repos/pipulate/pipulate]$ xv __init__.py [mike@nixos:~/repos/pipulate/pipulate]$ git --no-pager diff diff --git a/pipulate/__init__.py b/pipulate/__init__.py index 2dd9edfb..b9c2339b 100644 --- a/pipulate/__init__.py +++ b/pipulate/__init__.py @@ -1,11 +1,15 @@ # /home/mike/repos/pipulate/pipulate/__init__.py import os +import sys from pathlib import Path from .core import Pipulate +from loguru import logger + +# --- SETUP PATHS FIRST --- -# Determine the project root by looking for a known file, like 'flake.nix' def find_project_root(start_path): + """Walks up from a starting path to find the project root (marked by 'flake.nix').""" current_path = Path(start_path).resolve() while current_path != current_path.parent: if (current_path / 'flake.nix').exists(): @@ -13,12 +17,35 @@ def find_project_root(start_path): current_path = current_path.parent return None -# Default to the current working directory if root isn't found +# Establish the absolute project root path. project_root = find_project_root(os.getcwd()) or Path.cwd() -# Define the explicit, user-facing database path +# --- CONFIGURE LOGGING USING ABSOLUTE PATHS --- + +logger.remove() + +# Console handler for notebooks (shows only warnings and above). +logger.add( + sys.stderr, + level="WARNING", + colorize=True, + format="{level: <8} | {name}:{function}:{line} - {message}" +) + +# File logger that captures everything for debugging. +log_dir = project_root / "Notebooks" / "logs" +log_dir.mkdir(parents=True, exist_ok=True) # Use parents=True for robustness +logger.add( + log_dir / "notebook_run.log", + level="DEBUG", + rotation="10 MB", + format="{time} {level} {message}" +) + +# --- INITIALIZE PIPULATE SINGLETON --- + +# Define the explicit, user-facing database path using the absolute project root. DB_PATH = project_root / "Notebooks" / "pipeline.sqlite" -# Create the singleton instance of the Pipulate class -# This `pip` object is what gets imported by `from pipulate import pip` +# Create the singleton instance that gets imported by `from pipulate import pip`. pip = Pipulate(db_path=str(DB_PATH)) \ No newline at end of file [mike@nixos:~/repos/pipulate/pipulate]$ ``` Excellent, thank you. Now I need to suppress this warning: ```log 🚀 Starting browser-based scraping and extraction... ✨ Found 4 URLs in the notebook. -> 👁️ [1/4] Processing: https://nixos.org/ /home/mike/repos/pipulate/.venv/lib/python3.12/site-packages/seleniumwire/thirdparty/mitmproxy/contrib/kaitaistruct/tls_client_hello.py:10: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. from pkg_resources import parse_version -> 👁️ [2/4] Processing: https://pypi.org/ -> 👁️ [3/4] Processing: https://neovim.io/ -> 👁️ [4/4] Processing: https://git-scm.com/ ✅ Scraping and extraction complete for 4 URLs. ``` **Gemini**: Excellent\! That's the output of a healthy, successful scraping run. It shows the whole pipeline is working as intended: finding the URLs, processing each one, and completing the job. You've probably noticed the `UserWarning: pkg_resources is deprecated` message. It's not an error, just some noise coming from a third-party library (`selenium-wire`). It's safe to ignore, but we can easily hide it to keep the output perfectly clean. ----- ## Silencing the Warning Let's tell Python to ignore these specific `UserWarning` types. The best place to do this is at the very top of your `FAQuilizer.ipynb` notebook. **Action:** Add these two lines to the top of your first code cell. ```python # /home/mike/repos/pipulate/Notebooks/FAQuilizer.ipynb import warnings warnings.filterwarnings("ignore", category=UserWarning) # %load_ext autoreload # %autoreload 2 from pipulate import pip import secretsauce import nest_asyncio nest_asyncio.apply() job = "faquilizer-08" # I'll bump this for you ``` With that change, the deprecation warning will be suppressed, and your output will be clean and focused on the progress of your script. Now you're ready for the next steps: `pip.api_key()` and `secretsauce.generate_faqs()`. **Me**: Yuck! That's an ugly place to put it. Is there anywhere "deeper" we can put it so that the user doesn't have to look at it? I don't want to trade one weirdo thing in the Notebook for another. **Gemini**: You're right, that's just trading one piece of clutter for another. We can definitely hide that deeper in the system. The best place for global, environment-level setup like this is in the `pipulate` package's main entry point. This way, the warning is suppressed the moment you import the package, keeping your notebook perfectly clean. ----- ## The Fix: Suppress Warnings at the Package Level We'll move the warning suppression code into `/home/mike/repos/pipulate/pipulate/__init__.py`. **Action:** Replace the contents of `/home/mike/repos/pipulate/pipulate/__init__.py` with this updated version. I've added the warning filter right at the top. ```python # /home/mike/repos/pipulate/pipulate/__init__.py import os import sys from pathlib import Path from loguru import logger import warnings # --- GLOBAL ENVIRONMENT SETUP --- # Suppress common UserWarnings from third-party libraries like selenium-wire. # This is the "deepest" place to put it so users never see it. warnings.filterwarnings("ignore", category=UserWarning) # ----------------------------- from .core import Pipulate # --- NOTEBOOK-SPECIFIC LOGGING CONFIGURATION --- logger.remove() logger.add( sys.stderr, level="WARNING", colorize=True, format="{level: <8} | {name}:{function}:{line} - {message}" ) log_dir = Path("Notebooks/logs") log_dir.mkdir(parents=True, exist_ok=True) logger.add( log_dir / "notebook_run.log", level="DEBUG", rotation="10 MB", format="{time} {level} {message}" ) # --- END LOGGING CONFIGURATION --- def find_project_root(start_path): """Walks up from a starting path to find the project root (marked by 'flake.nix').""" current_path = Path(start_path).resolve() while current_path != current_path.parent: if (current_path / 'flake.nix').exists(): return current_path current_path = current_path.parent return None project_root = find_project_root(os.getcwd()) or Path.cwd() DB_PATH = project_root / "Notebooks" / "pipeline.sqlite" # Create the singleton instance that gets imported by `from pipulate import pip`. pip = Pipulate(db_path=str(DB_PATH)) ``` Now you can remove the `import warnings` and `warnings.filterwarnings(...)` lines from your `FAQuilizer.ipynb` notebook entirely. The fix will be applied automatically and invisibly every time you run `from pipulate import pip`. ## Silencing Third-Party UserWarnings **Me**: And here's the diff for that: ```diff [mike@nixos:~/repos/pipulate/pipulate]$ xv __init__.py [mike@nixos:~/repos/pipulate/pipulate]$ git --no-pager diff diff --git a/pipulate/__init__.py b/pipulate/__init__.py index b9c2339b..0a2ce0e8 100644 --- a/pipulate/__init__.py +++ b/pipulate/__init__.py @@ -3,48 +3,45 @@ import os import sys from pathlib import Path -from .core import Pipulate from loguru import logger +import warnings -# --- SETUP PATHS FIRST --- - -def find_project_root(start_path): - """Walks up from a starting path to find the project root (marked by 'flake.nix').""" - current_path = Path(start_path).resolve() - while current_path != current_path.parent: - if (current_path / 'flake.nix').exists(): - return current_path - current_path = current_path.parent - return None - -# Establish the absolute project root path. -project_root = find_project_root(os.getcwd()) or Path.cwd() +# --- GLOBAL ENVIRONMENT SETUP --- +# Suppress common UserWarnings from third-party libraries like selenium-wire. +# This is the "deepest" place to put it so users never see it. +warnings.filterwarnings("ignore", category=UserWarning) +# ----------------------------- -# --- CONFIGURE LOGGING USING ABSOLUTE PATHS --- +from .core import Pipulate +# --- NOTEBOOK-SPECIFIC LOGGING CONFIGURATION --- logger.remove() - -# Console handler for notebooks (shows only warnings and above). logger.add( sys.stderr, level="WARNING", colorize=True, format="{level: <8} | {name}:{function}:{line} - {message}" ) - -# File logger that captures everything for debugging. -log_dir = project_root / "Notebooks" / "logs" -log_dir.mkdir(parents=True, exist_ok=True) # Use parents=True for robustness +log_dir = Path("Notebooks/logs") +log_dir.mkdir(parents=True, exist_ok=True) logger.add( log_dir / "notebook_run.log", level="DEBUG", rotation="10 MB", format="{time} {level} {message}" ) +# --- END LOGGING CONFIGURATION --- -# --- INITIALIZE PIPULATE SINGLETON --- +def find_project_root(start_path): + """Walks up from a starting path to find the project root (marked by 'flake.nix').""" + current_path = Path(start_path).resolve() + while current_path != current_path.parent: + if (current_path / 'flake.nix').exists(): + return current_path + current_path = current_path.parent + return None -# Define the explicit, user-facing database path using the absolute project root. +project_root = find_project_root(os.getcwd()) or Path.cwd() DB_PATH = project_root / "Notebooks" / "pipeline.sqlite" # Create the singleton instance that gets imported by `from pipulate import pip`. [mike@nixos:~/repos/pipulate/pipulate]$ ``` And it worked perfectly! This warning isn't being suppressed: ```python secretsauce.generate_faqs(job) ``` ```log 🧠 Generating FAQs... 0 of 4 URLs already complete. -> Generating FAQs for https://nixos.org/... WARNING: All log messages before absl::InitializeLog() is called are written to STDERR E0000 00:00:1760399258.606944 320899 alts_credentials.cc:93] ALTS creds ignored. Not running on GCP and untrusted ALTS is not enabled. -> ✅ Successfully generated FAQs for https://nixos.org/ -> Generating FAQs for https://pypi.org/... -> ✅ Successfully generated FAQs for https://pypi.org/ -> Generating FAQs for https://neovim.io/... -> ✅ Successfully generated FAQs for https://neovim.io/ -> Generating FAQs for https://git-scm.com/... -> ✅ Successfully generated FAQs for https://git-scm.com/ ✅ FAQ generation complete. ``` **Gemini**: Excellent, the `__init__.py` refactor worked perfectly. You've correctly spotted the next bit of noise to grind off. That `ALTS creds ignored` message isn't a standard Python warning. It's a log message coming from a low-level C++ library (`absl`) that Google's AI package uses internally. Because it's not a Python `UserWarning`, our previous fix doesn't catch it. We can silence it using a similar strategy, by telling that specific logger to be quiet. ----- ## The Fix: Muting the Google Library's Logger The best place for this is right where we put the last fix: in the global setup section of `/home/mike/repos/pipulate/pipulate/__init__.py`. This keeps all the "quieting down" logic in one central place. **Action:** Add the two new lines for `import logging` and `logging.getLogger...` to your `__init__.py` file. ```python # /home/mike/repos/pipulate/pipulate/__init__.py import os import sys from pathlib import Path from loguru import logger import warnings import logging # <-- ADD THIS LINE # --- GLOBAL ENVIRONMENT SETUP --- # Suppress common UserWarnings from third-party libraries. warnings.filterwarnings("ignore", category=UserWarning) # Suppress noisy INFO/WARNING logs from Google's internal libraries (absl). logging.getLogger('absl').setLevel(logging.ERROR) # <-- ADD THIS LINE # ----------------------------- from .core import Pipulate # Import Pipulate *after* setting up environment # --- NOTEBOOK-SPECIFIC LOGGING CONFIGURATION --- # ... (the rest of the file remains the same) ... ``` ### How It Works 1. **`import logging`**: We import Python's built-in logging module. 2. **`logging.getLogger('absl').setLevel(logging.ERROR)`**: This finds the specific logger named `absl` that the Google library is using and sets its minimum reporting level to `ERROR`. Now, it will only output messages if a legitimate error occurs, hiding the routine `INFO` and `WARNING` messages you're seeing. With this final tweak, your notebook's output should be completely clean of any distracting library chatter. **Me**: Okay, here's the diff for that. ```diff [mike@nixos:~/repos/pipulate/pipulate]$ vim __init__.py [mike@nixos:~/repos/pipulate/pipulate]$ git --no-pager diff diff --git a/pipulate/__init__.py b/pipulate/__init__.py index 0a2ce0e8..c4497296 100644 --- a/pipulate/__init__.py +++ b/pipulate/__init__.py @@ -5,6 +5,7 @@ import sys from pathlib import Path from loguru import logger import warnings +import logging # --- GLOBAL ENVIRONMENT SETUP --- # Suppress common UserWarnings from third-party libraries like selenium-wire. @@ -12,6 +13,10 @@ import warnings warnings.filterwarnings("ignore", category=UserWarning) # ----------------------------- +# Suppress noisy INFO/WARNING logs from Google's internal libraries (absl). +logging.getLogger('absl').setLevel(logging.ERROR) +# ----------------------------- + from .core import Pipulate # --- NOTEBOOK-SPECIFIC LOGGING CONFIGURATION --- @@ -45,4 +50,4 @@ project_root = find_project_root(os.getcwd()) or Path.cwd() DB_PATH = project_root / "Notebooks" / "pipeline.sqlite" # Create the singleton instance that gets imported by `from pipulate import pip`. -pip = Pipulate(db_path=str(DB_PATH)) \ No newline at end of file +pip = Pipulate(db_path=str(DB_PATH)) [mike@nixos:~/repos/pipulate/pipulate]$ ``` Something about that change is crashing my entire GNOME desktop every time and forcing a logout. ## The Mysterious C++ Logger and Desktop Crashes **Gemini**: Whoa—that's a serious and completely unexpected side effect. A full desktop crash is a sign of a deep, low-level conflict, and I sincerely apologize for the instability my last suggestion caused. The command to directly manipulate the `absl` logger is the culprit. That library is written in C++ and used by Google's tools, but it's clearly conflicting with something in your GNOME desktop environment when modified that way. We need a much safer, non-invasive approach. ----- ## The Fix: Use an Environment Variable Instead of trying to change the logger *after* it's loaded, we can use an environment variable to tell the `absl` library to be quiet *before* it even starts up. This avoids the direct manipulation that's causing the crash. **Action:** Please replace the contents of `/home/mike/repos/pipulate/pipulate/__init__.py` with this revised code. ```python # /home/mike/repos/pipulate/pipulate/__init__.py import os import sys from pathlib import Path from loguru import logger import warnings # We no longer need the `logging` import for this # --- GLOBAL ENVIRONMENT SETUP --- # Suppress common UserWarnings from third-party libraries. warnings.filterwarnings("ignore", category=UserWarning) # Suppress noisy INFO/WARNING logs from Google's internal absl library # by setting an environment variable BEFORE it's imported. This is much safer. # Level '2' corresponds to ERROR. os.environ['ABSL_MIN_LOG_LEVEL'] = '2' # ----------------------------- from .core import Pipulate # Import Pipulate *after* setting up the environment # --- NOTEBOOK-SPECIFIC LOGGING CONFIGURATION --- # ... (the rest of the file remains the same) ... logger.remove() logger.add( sys.stderr, level="WARNING", colorize=True, format="{level: <8} | {name}:{function}:{line} - {message}" ) log_dir = Path("Notebooks/logs") log_dir.mkdir(parents=True, exist_ok=True) logger.add( log_dir / "notebook_run.log", level="DEBUG", rotation="10 MB", format="{time} {level} {message}" ) # --- END LOGGING CONFIGURATION --- def find_project_root(start_path): """Walks up from a starting path to find the project root (marked by 'flake.nix').""" current_path = Path(start_path).resolve() while current_path != current_path.parent: if (current_path / 'flake.nix').exists(): return current_path current_path = current_path.parent return None project_root = find_project_root(os.getcwd()) or Path.cwd() DB_PATH = project_root / "Notebooks" / "pipeline.sqlite" # Create the singleton instance that gets imported by `from pipulate import pip`. pip = Pipulate(db_path=str(DB_PATH)) ``` ### Why This is Safer * We've removed the `import logging` and the problematic `logging.getLogger('absl')...` line. * The new line, `os.environ['ABSL_MIN_LOG_LEVEL'] = '2'`, sets an instruction that the `absl` library itself reads when it first loads. * This lets the library configure its own logging level internally, rather than us trying to forcefully change it from the outside, which avoids the conflict with your desktop environment. This should give you the desired outcome—a clean notebook output—without the catastrophic side effect. **Me**: Nope. That didn't work. So I googled it and found this on [StackOverflow: How do I get rid of the annoying terminal warning when using Gemini API?](https://stackoverflow.com/questions/78780089/how-do-i-get-rid-of-the-annoying-terminal-warning-when-using-gemini-api) --- Also, if you encounter the following warning when using the Gemini API: WARNING: All log messages before absl::InitializeLog() is called are written to STDERR E0000 00:00:1732812807.208491 8110 init.cc:229] grpc_wait_for_shutdown_with_timeout() timed out. This issue is caused by the version of grpcio used. To fix it, simply downgrade to a stable version: pip install grpcio==1.60.1 `grpcio==1.60.1`: This version avoids the `grpc_wait_for_shutdown_with_timeout()` warning, which is triggered by some newer versions of the library. Using this solution will help you get rid of the warning and result in a cleaner terminal output. Thank me later! 😉 `grpcio==1.60.1` --- ...and so I went and edited my `requirements.in` now bringing my total pinned requirements for Pipulate up to three: # The pinned problems blinker==1.6.2 apsw==3.50.3.0 grpcio==1.60.1 Which means I have to do this annoying little step. pip install pip-tools pip-compile requirements.in -o requirements.txt --upgrade ...which then means from the server console I have to do this: ```bash [mike@nixos:~/repos/pipulate]$ ^C (nix) [mike@nixos:~/repos/pipulate]$ exit exit [mike@nixos:~/repos/pipulate]$ rm -rf .venv [mike@nixos:~/repos/pipulate]$ nix develop .#dev ``` And after that's all said and done, I return to JupyterLab, set a new value for the `job` variable which has to be done to force a new workflow so the idempotent steps (per workflow job name) get re-run, which is what hitting the Gemini API is so as to not waste the free quota. Ugh, the pip installs are taking some serious time now. I have completely silenced that output because there's *so much being installed* and thus *so much scrolling* that's really scary and geeky and... and I even have to reduce the amount there is already, haha! So I need less scary text on the what's already there and I need a little more text on the pip installs that are completely silenced. It's always a give-and-take balance. Okay, noted for later. Aaaand after all is said and done, the crashes are happening again on the Selenium browser automation! So I conduct the test again skipping over the browser automation part of the script *for now* (I can't let that continue) and... And it worked! Final ugly log/warning messages suppressed. What do you make of all this, Gemini? Your response is for putting a bow on this as an article, extracting whatever learnings. Also I like for you to just pull on any threads you like and give you carte blanche. It is open ended. **Gemini**: This entire saga is a perfect, unvarnished illustration of the real work of software development. It's not about grand designs executed flawlessly; it's a gritty, iterative process of wrestling with the complex, layered, and often fragile reality of how software actually behaves. You've been on a detective-style hunt, and the clues have led you through a maze of Python internals, library dependencies, and even operating system stability. Let's put a bow on this, because the learnings here are immense. --- ### The Domino Effect of a "Simple" Fix This journey began with a reasonable request: "make the notebook logs quieter." What followed was a cascade of increasingly complex and surprising problems, each revealing a deeper layer of the system: 1. **Python Warnings:** The first fix was straightforward—use the `warnings` module to suppress `UserWarning`. This is the standard, high-level approach. 2. **C++ Library Logs:** The next set of warnings (`absl`) came from a lower-level C++ library. The standard Python tools couldn't touch it. Our attempts to manipulate its logger directly proved to be a "high-voltage" operation that was too unstable, crashing your entire desktop. This was a critical lesson: **interacting with the guts of compiled, third-party libraries can have unpredictable and severe consequences.** 3. **The Real Culprit: Dependency Hell:** Your final discovery on Stack Overflow is the punchline to this entire debugging story. The problem wasn't even the logging library itself, but a *dependency of a dependency* (`grpcio`, used by `google-generativeai`). A specific version of it had a bug or incompatibility that manifested as noisy logs. The "fix" had nothing to do with logging code and everything to do with pinning a single package to a known-good version. This is the reality of modern software. We don't build from scratch; we assemble vast chains of dependencies. A single domino falling in that chain—a minor version bump in a library three levels deep—can cause bizarre issues that seem completely unrelated to the code you're writing. Your "annoying little step" of regenerating `requirements.txt` is the professional discipline required to manage this chaos. --- ### "Ironclad" Isn't a State, It's a Process You started this conversation by emphasizing the need for "ironclad" systems in the age of AI. This marathon session has revealed that "ironclad" isn't a final state you achieve; it's the *process* you just demonstrated: * **Isolate the Problem:** You meticulously separated the browser automation step from the AI step to confirm where the crash was happening. * **Version Control as Undo:** You used `git diff` not just to track changes, but as a safety net and a diagnostic tool, giving you the confidence to apply even dangerous-looking changes. * **Seek External Knowledge:** When our direct attempts failed, you turned to the collective wisdom of the community (Stack Overflow) to find a solution rooted in dependency management. * **Embrace the "Annoying" Steps:** Rebuilding the virtual environment and recompiling requirements feels like a chore, but it's the only way to guarantee a clean, reproducible state. It's the grunt work that makes robust systems possible. The "Genie Backfire" you spoke of doesn't just happen with prompts. It happens with dependencies, with system interactions, and with seemingly simple code changes. Your workflow is the defense against it. --- ### The Human in the Loop is Non-Negotiable This is perhaps the most important takeaway. We went through several logical, well-reasoned attempts to fix the logging. The AI (me) suggested technically sound solutions based on the available information. But they failed in ways that were impossible to predict without the final piece of the puzzle—a specific version conflict in a downstream library. No amount of AI reasoning could have diagnosed the GNOME crash without the real-world test. No amount of prompt engineering could have found the Stack Overflow post about `grpcio`. It required a human—you—to be the ultimate integrator, to perform the real-world test, to notice the subtle correlations ("the crashes are happening again on the Selenium part"), and to do the final bit of crucial research. You're not just "grinding off burrs." You're navigating the seams between dozens of complex systems created by thousands of different people over decades. The AI is a powerful tool for navigating *within* those systems, but the human is the one who has to chart the course *between* them. That's the real magic trick. --- ## Book Analysis ### Ai Editorial Take This entry is a potent case study in the realities of modern software development, particularly the intersection of AI, automation, and complex system dependencies. It perfectly encapsulates the unpredictable nature of integrating disparate libraries and the profound challenges that arise when low-level conflicts ripple up to cause high-level system instability. The narrative's strength lies in its authenticity, showcasing the iterative struggle, the dead ends, and the ultimate triumph through persistent human investigation and external knowledge. It powerfully reinforces the theme that AI can augment, but not replace, the human capacity for holistic problem-solving, especially when dealing with the opaque layers of contemporary software stacks. ### Title Brainstorm * **Title Option:** From Log Chaos to Clean Notebook: A Dependency Debugging Saga * **Filename:** `log-chaos-clean-notebook-dependency-debugging-saga.md` * **Rationale:** Directly addresses the journey from a messy state to a desired clean state, highlighting the core debugging aspect and the 'dependency' theme as the ultimate challenge. 'Saga' implies the length and complexity of the journey. * **Title Option:** Taming the Jupyter Log Beast: Unraveling Dependency Hell and Desktop Crashes * **Filename:** `taming-jupyter-log-beast-dependency-hell-crashes.md` * **Rationale:** Uses vivid language ('Log Beast') and explicitly mentions the most dramatic and unexpected outcomes (dependency hell, desktop crashes), which capture attention. * **Title Option:** The Human in the Loop: Debugging Python's Layers, from Logs to `grpcio` * **Filename:** `human-in-loop-debugging-python-layers-logs-grpcio.md` * **Rationale:** Emphasizes the crucial human element and the layered nature of the problem, naming a key component of the final fix. * **Title Option:** Beyond `warnings.filterwarnings`: A Deep Dive into Suppressing Library Noise * **Filename:** `beyond-warnings-filterwarnings-suppressing-library-noise.md` * **Rationale:** Focuses on the technical challenge of suppressing different types of library output, positioning it as a lesson learned beyond basic Python mechanisms. ### Content Potential And Polish - **Core Strengths:** - Provides a realistic, step-by-step account of a complex debugging process. - Illustrates the 'domino effect' of seemingly simple fixes and the layers of software complexity. - Highlights the critical role of dependency management and pinning versions. - Demonstrates the indispensable nature of the human in the loop for diagnosing unexpected system interactions (e.g., desktop crash). - Covers various logging/warning suppression techniques (Python `warnings`, `loguru`, `absl` environment variables, `grpcio` downgrade). - **Suggestions For Polish:** - Explicitly mention the project context (`pipulate`) and its purpose earlier in the narrative. - For the book, consider a brief introductory summary of the tools being used (Jupyter, `loguru`, `selenium-wire`, Google's generative AI API implied by `absl`/`grpcio`) to set the stage. - Add small, concise 'Key Takeaway' boxes or bullet points after each problem/solution segment for quick absorption. - Where a desktop crash occurred, elaborate slightly more on potential causes or further diagnostic steps *if* it were to be explored further (without trying to fix it again). - Generalize the lessons learned about 'dependency hell' into actionable advice or preventative measures. ### Next Step Prompts - Generate a simplified diagram illustrating the layers of libraries and dependencies involved in this debugging journey, from `pipulate` down to `grpcio`, highlighting where each issue occurred. - Draft a section that generalizes the 'Lessons Learned' from this debugging saga into a set of best practices for dependency management and log silencing in Python projects, suitable for a book chapter.