Skip to main content

A papermill implementation to run notebooks inside dataproc serverless

Project description

Paperless

Made With Love ❤️ from :israel: :israel:

Paperless is a tool that extends the capabilities of Papermill by providing the ability to run Papermill via Google Cloud Dataproc Serverless.

ICON

Overview

Papermill is a powerful tool for parameterizing and executing Jupyter Notebooks. However, by default papermill dosn't support Jupyter Kernel Gateway - it was impossible to run spark notebook vs Google Cloud Dataproc Serverless environment with Papermill tool - this is where Paperless helps.

Paperless bridges the gap between Papermill and Google Cloud Dataproc Serverless interactive mode, allowing you to seamlessly integrate the two and harness the power of serverless execution for your Jupyter Notebooks.

Features

  • Serverless Execution: Run Papermill on Google Cloud Dataproc without managing the underlying infrastructure.

  • Scalability: Leverage the scalability of Google Cloud Dataproc for processing multiple Notebooks concurrently.

  • Cost-Effective: Pay only for the resources you consume during the execution, optimizing costs for your notebook parameterization tasks.

Pricing model is much more cost-effective considering other platofrms and technologies

https://cloud.google.com/dataproc-serverless/pricing resource: https://cloud.google.com/dataproc-serverless/pricing

Getting Started

Prerequisites

Before using Paperless, make sure you have the following:

  • A Google Cloud Platform (GCP) project
  • Access to Google Cloud Dataproc Enable the API
  • Papermill installed locally or in your environment

Step 1: Install Google Cloud SDK

To authenticate your application using Application Default Credentials (ADC) with gcloud - If you haven't already installed the Google Cloud SDK, you can download and install it from the Google Cloud SDK documentation.

Step 2: Authenticate with gcloud

Open a terminal and run the following command to authenticate your Google Cloud SDK with your Google Cloud Platform (GCP) account:

gcloud auth login

gcloud auth application-default login 

Step 3: Install Paperless

pip install paperless

Step 4: Create sessionTemplates For Paperless

Parameters and details can be found in GCP Docs.

 gcloud compute instance-templates create paperless-interactive --<extra params...>

You can change parameters as you need based on the jobs needs - check the docs for that.

Step 5: Test Executtion:

Paperless excepts && supports all list or arguments exists in original Papermill package - the minimum needed for testing:

 paperless <input_path> <output_path> ...

An extra parameter that is special for Paperless: --template_name Example:

 paperless ./resources/spark.ipynb ./resources/spark-out.ipynb --template_name paperless-interactive

You're all set, enjoy :)


Local development:

# Create a new directory for your project
git clone https://github.com/Plarium-Repo/paperless.git && cd paperless

# Create a virtual environment
python3 -m venv .venv

# Activate the virtual environment
# On Windows
.venv\Scripts\activate

# On macOS and Linux
source venv/bin/activate

# Install requirements
pip install -r requirements.txt

# Install the command line
python setup.py install 

# Execute example
paperless ./resources/spark.ipynb ./resources/spark-out.ipynb

MIT License

Contribution

Code Of Conduct

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

paperless-1.4.1.tar.gz (10.4 kB view details)

Uploaded Source

Built Distribution

paperless-1.4.1-py3-none-any.whl (10.7 kB view details)

Uploaded Python 3

File details

Details for the file paperless-1.4.1.tar.gz.

File metadata

  • Download URL: paperless-1.4.1.tar.gz
  • Upload date:
  • Size: 10.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.7

File hashes

Hashes for paperless-1.4.1.tar.gz
Algorithm Hash digest
SHA256 90a331049a09e8fcfe19efed45208da367c2b37ea28f3b278a959ced44af1df6
MD5 b68cd0ce3698ff6b409ef85c7cfc2cda
BLAKE2b-256 f00ac9c010fd5c51bb3fb904809d2922a85155057b5cbe8244281ecd7757be08

See more details on using hashes here.

File details

Details for the file paperless-1.4.1-py3-none-any.whl.

File metadata

  • Download URL: paperless-1.4.1-py3-none-any.whl
  • Upload date:
  • Size: 10.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.7

File hashes

Hashes for paperless-1.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 91d3763314382d3d24e8c9605ed0324e809438d85ab8064e84d0fd1c20292010
MD5 0fea88c531e45f34e59fbe88143d1115
BLAKE2b-256 01c0026d1a3c770c3c38e1ae726d82f329a5c92bb5ba1329ed1d994b9f395142

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page