Skip to main content

Data aggregation pipeline for running real-time predictive models

Project description

Blurr

CircleCI Documentation Status Coverage Status PyPI version

Table of contents

What is Blurr?

Blurr transforms structured, streaming raw data into features for model training and prediction using a high-level expressive YAML-based language called the Blurr Transform Spec (BTS). The BTS merges the schema and computation model for data processing.

The BTS is a data transform definition for structured data. The BTS encapsulates the business logic of data transforms and Blurr orchestrates the execution of data transforms. Blurr is runner-agnostic, so BTSs can be run by event processors such as Spark, Spark Streaming or Flink.

Is Blurr for you?

Yes, if: you are well on your way on the ML 'curve of enlightenment', and are thinking about how to do online scoring

Curve

Playground

Launch playground

Tutorial and Docs

Coming up with features is difficult, time-consuming, requires expert knowledge. 'Applied machine learning' is basically feature engineering --- Andrew Ng

Read the docs

Streaming BTS Tutorial | Window BTS Tutorial

Preparing data for specific use cases using Blurr:

Contribute to Blurr

Welcome to the Blurr community! We are so glad that you share our passion for building MLOps!

Please create a new issue to begin a discussion. Alternatively, feel free to pick up an existing issue!

Please sign the Contributor License Agreement before raising a pull request.

Data Science 'Joel Test'

Inspired by the (old school) Joel Test to rate software teams, here's our version for data science teams. What's your score?

  1. Data pipelines are versioned and reproducible
  2. Pipelines (re)build in one step
  3. Deploying to production needs minimal engineering help
  4. Successful ML is a long game. You play it like it is
  5. Kaizen. Experimentation and iterations are a way of life

Roadmap

Blurr is currently in Developer Preview. Stay in touch!: Star this project or email hello@blurr.ai

  • Local transformations only
  • Support for custom functions and other python libraries in the BTS
  • Spark runner
  • S3 support for data sink
  • DynamoDB as an Intermediate Store
  • Features server

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

blurr-0.4.1.tar.gz (38.3 kB view details)

Uploaded Source

Built Distribution

blurr-0.4.1-py3-none-any.whl (52.9 kB view details)

Uploaded Python 3

File details

Details for the file blurr-0.4.1.tar.gz.

File metadata

  • Download URL: blurr-0.4.1.tar.gz
  • Upload date:
  • Size: 38.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for blurr-0.4.1.tar.gz
Algorithm Hash digest
SHA256 a685c257710bfa014942c83df9f939f93e138f6462a34fa8a0e3bfe115c653ae
MD5 cc904eeadbb712c0830eed24c59c59a5
BLAKE2b-256 8701ab3e479bb23b1dbfea441f0b425341a8dafcf6ed45f4f2f86eab666e21da

See more details on using hashes here.

File details

Details for the file blurr-0.4.1-py3-none-any.whl.

File metadata

File hashes

Hashes for blurr-0.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 865db7d29efcdd8b53358eb14861da1d75f19b18d51bf3356c0a76f2cab6c5ce
MD5 3e12007c8e8eb29f583840493b90d33f
BLAKE2b-256 9decffa763925c3f80ca218d68579d378971677f1b02000746dea9ed7d800127

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