Skip to main content

SageWorks: A Python WorkBench for creating and deploying AWS SageMaker Models

Project description

Recent News

SageWorks is partnering with AWS® to accelerate your Machine Learning Pipelines development with our new Dashboard for ML Pipelines. Getting started with SageWorks is a snap and can be billed through AWS.

Welcome to SageWorks

The SageWorks framework makes AWS® both easier to use and more powerful. SageWorks handles all the details around updating and managing a complex set of AWS Services. With a simple-to-use Python API and a beautiful set of web interfaces, SageWorks makes creating AWS ML pipelines a snap. It also dramatically improves both the usability and visibility across the entire spectrum of services: Glue Job, Athena, Feature Store, Models, and Endpoints, SageWorks makes it easy to build production ready, AWS powered, machine learning pipelines.

sageworks_new_light

Full AWS ML OverView

  • Health Monitoring 🟢
  • Dynamic Updates
  • High Level Summary

Drill-Down Views

  • Incoming Data
  • Glue Jobs
  • DataSources
  • FeatureSets
  • Models
  • Endpoints

Private SaaS Architecture

Secure your Data, Empower your ML Pipelines

SageWorks is architected as a Private SaaS (also called BYOC: Bring Your Own Cloud). This hybrid architecture is the ultimate solution for businesses that prioritize data control and security. SageWorks deploys as an AWS Stack within your own cloud environment, ensuring compliance with stringent corporate and regulatory standards. It offers the flexibility to tailor solutions to your specific business needs through our comprehensive plugin support. By using SageWorks, you maintain absolute control over your data while benefiting from the power, security, and scalability of AWS cloud services. SageWorks Private SaaS Architecture

private_saas_compare

API Installation

  • pip install sageworks Installs SageWorks

  • sageworks Runs the SageWorks REPL/Initial Setup

For the full instructions for connecting your AWS Account see:

SageWorks Presentations

Even though SageWorks makes AWS easier, it's taking something very complex (the full set of AWS ML Pipelines/Services) and making it less complex. SageWorks has a depth and breadth of functionality so we've provided higher level conceptual documentation See: SageWorks Presentations

sageworks_api

SageWorks Documentation

The SageWorks documentation SageWorks Docs covers the Python API in depth and contains code examples. The documentation is fully searchable and fairly comprehensive.

The code examples are provided in the Github repo examples/ directory. For a full code listing of any example please visit our SageWorks Examples

Questions?

The SuperCowPowers team is happy to anser any questions you may have about AWS and SageWorks. Please contact us at sageworks@supercowpowers.com or chat us up on Discord

SageWorks Beta Program

Using SageWorks will minimize the time and manpower needed to incorporate AWS ML into your organization. If your company would like to be a SageWorks Beta Tester, contact us at sageworks@supercowpowers.com.

Using SageWorks with Additional Packages

pip install sageworks             # Installs SageWorks with Core Dependencies
pip install 'sageworks[ml-tools]' # + Shap and NetworkX
pip install 'sageworks[chem]'     # + RDKIT and Mordred (community)
pip install 'sageworks[ui]'       # + Plotly/Dash
pip install 'sageworks[dev]'      # + Pytest/flake8/black
pip install 'sageworks[all]'      # + All the things :)

*Note: Shells may interpret square brackets as globs, so the quotes are needed

Contributions

If you'd like to contribute to the SageWorks project, you're more than welcome. All contributions will fall under the existing project license. If you are interested in contributing or have questions please feel free to contact us at sageworks@supercowpowers.com.

® Amazon Web Services, AWS, the Powered by AWS logo, are trademarks of Amazon.com, Inc. or its affiliates

Project details


Release history Release notifications | RSS feed

This version

0.8.9

Download files

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

Source Distribution

sageworks-0.8.9.tar.gz (3.6 MB view details)

Uploaded Source

Built Distribution

sageworks-0.8.9-py2.py3-none-any.whl (344.4 kB view details)

Uploaded Python 2Python 3

File details

Details for the file sageworks-0.8.9.tar.gz.

File metadata

  • Download URL: sageworks-0.8.9.tar.gz
  • Upload date:
  • Size: 3.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.10.13

File hashes

Hashes for sageworks-0.8.9.tar.gz
Algorithm Hash digest
SHA256 91f9e561f7b0c049ae11dcd7184c11b2489ecfa71fb6bedac8f21662284848f2
MD5 3424371ba2c6d08e48eb6110d9ccccba
BLAKE2b-256 757519e990e92ea8d679a6fd89579129b9d43f17d30f666a2328fc70af34738d

See more details on using hashes here.

File details

Details for the file sageworks-0.8.9-py2.py3-none-any.whl.

File metadata

  • Download URL: sageworks-0.8.9-py2.py3-none-any.whl
  • Upload date:
  • Size: 344.4 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.10.13

File hashes

Hashes for sageworks-0.8.9-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 f361b6043f57facb41cf296cff14d40d9814c341baec6507d72d2b0cd85cb2ff
MD5 7308ef29240969fd7c67bf8ad9526019
BLAKE2b-256 f381898542ed5050469777697eeb42ceb693e1ec8b8b2a2120694e7310a63ada

See more details on using hashes here.

Supported by

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