kaggle-wandb-sync 0.1.0

A CLI tool to sync W&B offline runs from Kaggle Notebooks via GitHub Actions

kaggle-wandb-sync

A CLI tool to sync Weights & Biases offline runs from Kaggle Notebooks to W&B cloud — fully automated via GitHub Actions.

Why?

Kaggle Notebooks run in an isolated environment with internet access disabled for competition submissions. This means you can't push W&B metrics in real time. kaggle-wandb-sync solves this by:

1. Running your notebook with WANDB_MODE=offline (logs saved locally on Kaggle)
2. Downloading the output via kaggle kernels output
3. Syncing the offline runs to W&B cloud with wandb sync

Installation

pip install kaggle-wandb-sync

Prerequisites: Kaggle API credentials (~/.kaggle/kaggle.json) and a W&B API key.

Quick Start

All-in-one command

# Set your W&B API key
export WANDB_API_KEY=your_api_key

# Push notebook, wait for completion, download output, sync to W&B
kaggle-wandb-sync run my-notebook/

Step by step

kaggle-wandb-sync push   my-notebook/                      # push (with 409 protection)
kaggle-wandb-sync poll   yasunorim/my-notebook             # wait for COMPLETE
kaggle-wandb-sync output yasunorim/my-notebook             # download output
kaggle-wandb-sync sync   ./kaggle_output                   # wandb sync

Notebook Setup

Add these lines before importing wandb in your Kaggle Notebook:

import os
os.environ['WANDB_MODE'] = 'offline'   # must be set before import
os.environ['WANDB_PROJECT'] = 'my-project'

import wandb
wandb.init()
# ... your training code ...
wandb.log({"loss": 0.1, "accuracy": 0.95})
wandb.finish()

Important: Set WANDB_MODE=offline before import wandb, not after.

GitHub Actions Integration

Add this workflow to your Kaggle repo (.github/workflows/kaggle-wandb-sync.yml):

name: Kaggle W&B Sync

on:
  workflow_dispatch:
    inputs:
      notebook_dir:
        description: "Notebook directory (e.g. my-competition)"
        required: true
      kernel_id:
        description: "Kernel ID (e.g. username/my-competition-baseline)"
        required: true

jobs:
  sync:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - uses: actions/setup-python@v5
        with:
          python-version: "3.12"

      - name: Install kaggle-wandb-sync
        run: pip install kaggle-wandb-sync

      - name: Set up Kaggle credentials
        run: |
          mkdir -p ~/.kaggle
          echo '${{ secrets.KAGGLE_API_TOKEN }}' > ~/.kaggle/kaggle.json
          chmod 600 ~/.kaggle/kaggle.json

      - name: Run pipeline
        env:
          WANDB_API_KEY: ${{ secrets.WANDB_API_KEY }}
        run: |
          kaggle-wandb-sync run ${{ inputs.notebook_dir }} \
            --kernel-id ${{ inputs.kernel_id }}

Required secrets: KAGGLE_API_TOKEN (JSON content of ~/.kaggle/kaggle.json) and WANDB_API_KEY.

Commands

run — Full pipeline (recommended)

kaggle-wandb-sync run [DIRECTORY] [OPTIONS]

Option	Default	Description
--kernel-id, -k	from metadata	Kernel ID (username/slug)
--output-dir, -o	./kaggle_output	Directory for downloaded files
--poll-interval	30	Seconds between status checks
--max-attempts	60	Max poll attempts (30min total)
--skip-push	off	Skip push, re-run output+sync only
--skip-sync	off	Download output only, skip W&B sync

push — Push notebook

kaggle-wandb-sync push [DIRECTORY] [OPTIONS]

Waits for any currently running kernel to finish before pushing (prevents 409 Conflict errors).

poll — Wait for completion

kaggle-wandb-sync poll KERNEL_ID [--interval 30] [--max-attempts 60]

Exits with code 1 if the kernel finishes with ERROR or CANCEL.

output — Download output

kaggle-wandb-sync output KERNEL_ID [--output-dir ./kaggle_output]

sync — Sync to W&B

kaggle-wandb-sync sync [OUTPUT_DIR]

Finds all offline-run-* directories and runs wandb sync on each.

Known Issues

• Windows encoding: Prefix commands with PYTHONUTF8=1 if you see encoding errors on Windows.

License

MIT