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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

The Code Ocean Computational Workbench enhances usability, coding, data tool integration, and DevOps lifecycle processes by bridging technology gaps with a user-friendly, ready-to-use interface. It provides readily accessible tools like RStudio, Jupyter, Shiny, Terminal, and Git, while allowing users to select from a variety of popular programming languages. Users can access diverse data sizes and storage types, configure, and generate Docker environments with ease. Furthermore, it offers one-click access to AWS compute resources, streamlining workflows significantly. Through the app panel of the Code Ocean Computational Workbench, researchers can effortlessly share findings by creating and publishing user-friendly web analysis applications for teams of scientists, all without needing IT support, coding skills, or command-line proficiency. This platform allows for the creation and deployment of interactive analyses that operate seamlessly in standard web browsers. Collaboration and sharing of results are simplified, and resources can be reused and managed with minimal effort. By providing a straightforward application and repository, researchers can efficiently organize, publish, and safeguard project-based Compute Capsules, data assets, and their research outcomes, ultimately promoting a more collaborative and productive research environment. The versatility and ease of use of this workbench make it an invaluable tool for scientists looking to enhance their research capabilities.

Description

JupyterHub allows users to establish a multi-user environment that can spawn, manage, and proxy several instances of the individual Jupyter notebook server. Developed by Project Jupyter, JupyterHub is designed to cater to numerous users simultaneously. This platform can provide notebook servers for a variety of purposes, including educational environments for students, corporate data science teams, collaborative scientific research, or groups utilizing high-performance computing resources. It is important to note that JupyterHub does not officially support Windows operating systems. While it might be possible to run JupyterHub on Windows by utilizing compatible Spawners and Authenticators, the default configurations are not designed for this platform. Furthermore, any bugs reported on Windows will not be addressed, and the testing framework does not operate on Windows systems. Although minor patches to resolve basic Windows compatibility issues may be considered, they are rare. For users on Windows, it is advisable to run JupyterHub within a Docker container or a Linux virtual machine to ensure optimal performance and compatibility. This approach not only enhances functionality but also simplifies the installation process for Windows users.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Jupyter Notebook
Amazon EC2
Amazon S3
Amazon Web Services (AWS)
Azure Marketplace
Cleanlab
Coiled
DataOps.live
Docker
Git
GitHub
JetBrains DataSpell
JupyterLab
Kite
NeevCloud
OpenHexa
Terminal
Timbr.ai
Vast.ai
Wizata

Integrations

Jupyter Notebook
Amazon EC2
Amazon S3
Amazon Web Services (AWS)
Azure Marketplace
Cleanlab
Coiled
DataOps.live
Docker
Git
GitHub
JetBrains DataSpell
JupyterLab
Kite
NeevCloud
OpenHexa
Terminal
Timbr.ai
Vast.ai
Wizata

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Code Ocean

Country

United States

Website

codeocean.com/product/

Vendor Details

Company Name

JupyterHub

Founded

2014

Website

github.com/jupyterhub/jupyterhub

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Product Features

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