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Jupyter VS Dask

Compare Jupyter VS Dask and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Jupyter logo Jupyter

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Dask logo Dask

Dask natively scales Python Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • Dask Landing page
    Landing page //
    2022-08-26

Jupyter videos

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What is Jupyter Notebook?

More videos:

  • Tutorial - Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough
  • Review - JupyterLab: The Next Generation Jupyter Web Interface

Dask videos

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DASK and Apache SparkGurpreet Singh Microsoft Corporation

More videos:

  • Review - VLOGTOBER : dask kitchen review ,groceries ,drinks
  • Review - Dask Futures: Introduction

Category Popularity

0-100% (relative to Jupyter and Dask)

Jupyter

Dask

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Workflows
0 0%
Workflows
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Databases
0 0%
Databases
100% 100

User comments

Share your experience with using Jupyter and Dask. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Jupyter and Dask

Jupyter Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Once you install nteract, you can open your notebook without having to launch the Jupyter Notebook or visit the Jupyter Lab. The nteract environment is similar to Jupyter Notebook but with more control and the possibility of extension via libraries like Papermill (notebook parameterization), Scrapbook (saving your notebook’s data and photos), and Bookstore (versioning).
Source: lakefs.io
7 best Colab alternatives in 2023
JupyterLab is the next-generation user interface for Project Jupyter. Like Colab, it's an interactive development environment for working with notebooks, code, and data. However, JupyterLab offers more flexibility as it can be self-hosted, enabling users to use their own hardware resources. It also supports extensions for integrating other services, making it a highly...
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Jupyter Notebook is a widely popular tool for data scientists to work on data science projects. This article reviews the top 12 alternatives to Jupyter Notebook that offer additional features and capabilities.
Source: noteable.io
15 data science tools to consider using in 2021
Jupyter Notebook's roots are in the programming language Python -- it originally was part of the IPython interactive toolkit open source project before being split off in 2014. The loose combination of Julia, Python and R gave Jupyter its name; along with supporting those three languages, Jupyter has modular kernels for dozens of others.
Source: searchbusinessanalytics.techtarget.com
Top 4 Python and Data Science IDEs for 2021 and Beyond
Yep — it’s the most popular IDE among data scientists. Jupyter Notebooks made interactivity a thing, and Jupyter Lab took the user experience to the next level. It’s a minimalistic IDE that does the essentials out of the box and provides options and hacks for more advanced use.
Source: towardsdatascience.com

Dask Reviews

Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
Dask: You can use Dask for Parallel computing via task scheduling. It can also process continuous data streams. Again, this is part of the "Blaze Ecosystem."
Source: www.xplenty.com

Social recommendations and mentions

Based on our record, Jupyter seems to be a lot more popular than Dask. While we know about 206 links to Jupyter, we've tracked only 16 mentions of Dask. 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.

Jupyter mentions (206)

  • Interactive Visualizations of Rate-Limiting Algorithms
    Interesting, I would have guessed you had used something jupyter-like: https://jupyter.org/ https://explorabl.es/all/. - Source: Hacker News / about 17 hours ago
  • scrape-yahoo-finance
    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 / 22 days ago
  • Let’s build AI-tools with the help of AI and Typescript!
    Jupyter Lab web-based interactive development environment. - Source: dev.to / about 1 month ago
  • Scrape Redfin Property Data
    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 / 28 days ago
  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    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
View more

Dask mentions (16)

  • Large Scale Hydrology: Geocomputational tools that you use
    We're using a lot of Python. In addition to these, gridMET, Dask, HoloViz, and kerchunk. Source: over 2 years ago
  • msgspec - a fast & friendly JSON/MessagePack library
    I wrote this for speeding up the RPC messaging in dask, but figured it might be useful for others as well. The source is available on github here: https://github.com/jcrist/msgspec. Source: over 2 years ago
  • What does it mean to scale your python powered pipeline?
    Dask: Distributed data frames, machine learning and more. - Source: dev.to / over 2 years ago
  • Data pipelines with Luigi
    To do that, we are efficiently using Dask, simply creating on-demand local (or remote) clusters on task run() method:. - Source: dev.to / over 2 years ago
  • How to load 85.6 GB of XML data into a dataframe
    I’m quite sure dask helps and has a pandas like api though will use disk and not just RAM. Source: over 2 years ago
View more

What are some alternatives?

When comparing Jupyter and Dask, you can also consider the following products

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.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

NumPy - NumPy is the fundamental package for scientific computing with Python

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