CodeOcean
replit
Open Science Framework
figshare
Watchist
Xpediter
Visual Studio Code
Sublime Web Inspector
Jupyter
Looker
Databricks
Google BigQuery
Presto DB
Rakam
Informatica
Concurrent
CodeOceanBased on our record, Jupyter seems to be a lot more popular than CodeOcean. While we know about 205 links to Jupyter, we've tracked only 3 mentions of CodeOcean. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I was an early hire at a computational reproducibility startup for scientists [0]; The platform was basically a web-based frontend wrapped around a Docker container hosted on AWS, and the idea was that you'd put your code and data on the platform and have it be online-executable indefinitely, and you wouldn't have to worry about package updates, functions breaking, etc., because it was containerized. The... - Source: Hacker News / 6 months ago
It looks like Magniv is targeting Python in general. This is similar to ClearML. What are the differentiating points to Magniv compared to similar products? It seems like the product also integrates with SCM systems. Are you using gitea and then containers to push code and data to execution like CodeOcean? https://github.com/allegroai/clearml https://codeocean.com/. - Source: Hacker News / about 2 years ago
Code ocean also exists for this purpose, though the number of compute hours is limited on free academic licenses. Source: over 2 years ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / 9 days ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / 19 days ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / 14 days ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 2 months ago
Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / 2 months ago
replit - Code, create, andlearn together. Use our free, collaborative, in-browser IDE to code in 50+ languages — without spending a second on setup.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Open Science Framework - Open Science Framework provides project management with collaborators, and project sharing with the public.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
figshare - Securely store and manage your research outputs in the cloud, or make them openly available and citable.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.