How to Initialize Sentry in All Notebooks Used in Jobs using __init__.py?

[jeremy98]

Hi Community,

I'm looking to initialize Sentry in all notebooks that are used across multiple jobs. My goal is to capture exceptions using Sentry whenever a job runs a notebook.

What’s the recommended approach for initializing Sentry packages in this context? Specifically:

• How should I structure the initialization code?

• Should I use a separate init notebook or a shared module?

• How can I ensure that Sentry is initialized automatically every time a notebook runs as part of a job?

Thanks in advance for your guidance!

[mark_ott]

To consistently initialize Sentry in all notebooks for reliable exception tracking, experts recommend using a shared initialization approach that minimizes duplication and ensures setup for every job execution. Here’s a structured approach:

Recommended Initialization Structure

• Shared Initialization Script or Module:
  Place Sentry's setup code in a dedicated Python module or script (e.g., sentry_init.py or sentry_shared.py). This can be imported at the beginning of each notebook to centralize configuration and prevent code duplication across multiple notebooks.

• Best Practice Example:

  python

  # sentry_init.py import sentry_sdk sentry_sdk.init( dsn="YOUR_SENTRY_DSN", traces_sample_rate=1.0, environment="production" )

  At the top of each notebook:

  python

  import sys sys.path.append('/path/to/shared/code') import sentry_init

Using an “Init” Notebook vs. Shared Module

• Separate Init Notebook:

  • Pros:
    Can be run once at the start of interactive sessions; may simplify setup for exploratory runs.

  • Cons:
    Not automatic for jobs that directly execute notebooks.

• Shared Module/Script:

  • Pros:
    Guarantees Sentry setup for every job or automated run if imported at the top of every notebook.
    Eases maintenance and scalability.

  • Recommended for job-based execution scenarios.

Automatic Initialization for Jobs

• Auto-Import in Each Notebook:
  Add the import for your Sentry initialization module at the very beginning of every notebook in job pipelines.

• Notebook Template:
  Use a starter template with Sentry initialization included for all new notebooks.

• Automated Preprocessing (Advanced):
  If your workflow programmatically executes notebooks (e.g., via Papermill, Jupyter nbconvert), use a notebook preprocessor or wrapper script to inject or ensure the init code runs first.

Key Points

• Centralize Sentry configuration in a single module or script.

• Import the module at the top of every notebook used in automated jobs.

• Don’t rely on manual initialization or on interactive “init” notebooks for jobs—prefer automated imports for consistency and reliability.

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References

• Sentry official docs: Python setup

• Best practices: Sentry in shared environments

• Python Sentry in job runners & automation pipelines

This method ensures you get comprehensive exception tracking across all notebooks and jobs with minimal maintenance required.