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Multi-language interactive computing environments.
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What is Jupyter?

The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.
Jupyter is a tool in the Data Science Notebooks category of a tech stack.
Jupyter is an open source tool with 11.3K GitHub stars and 4.7K GitHub forks. Here’s a link to Jupyter's open source repository on GitHub

Who uses Jupyter?

291 companies reportedly use Jupyter in their tech stacks, including Delivery Hero, Hepsiburada, and Intuit.

1427 developers on StackShare have stated that they use Jupyter.

Jupyter Integrations

GitHub, Python, Dropbox, Scala, and TensorFlow are some of the popular tools that integrate with Jupyter. Here's a list of all 46 tools that integrate with Jupyter.
Pros of Jupyter
In-line code execution using blocks
In-line graphing support
Can be themed
Multiple kernel support
LaTex Support
Best web-browser IDE for Python
Export to python code
HTML export capability
Multi-user with Kubernetes
Decisions about Jupyter

Here are some stack decisions, common use cases and reviews by companies and developers who chose Jupyter in their tech stack.

Needs advice
Apache SparkApache Spark

My process is like this: I would get data once a month, either from Google BigQuery or as parquet files from Azure Blob Storage. I have a script that does some cleaning and then stores the result as partitioned parquet files because the following process cannot handle loading all data to memory.

The next process is making a heavy computation in a parallel fashion (per partition), and storing 3 intermediate versions as parquet files: two used for statistics, and the third will be filtered and create the final files.

I make a report based on the two files in Jupyter notebook and convert it to HTML.

  • Everything is done with vanilla python and Pandas.
  • sometimes I may get a different format of data
  • cloud service is Microsoft Azure.

What I'm considering is the following:

Get the data with Kafka or with native python, do the first processing, and store data in Druid, the second processing will be done with Apache Spark getting data from apache druid.

the intermediate states can be stored in druid too. and visualization would be with apache superset.

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Needs advice

I am learning Python coding and doing lots of hands on python problem. I like the feel of Jupyter notebook but I have concern will that slow my computer performance. Will PyCharm or Jupyter or Atom-IDE is good for python coding?

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Blog Posts

Jobs that mention Jupyter as a desired skillset

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Jupyter Alternatives & Comparisons

What are some alternatives to Jupyter?
Apache Zeppelin
A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.
PyCharm’s smart code editor provides first-class support for Python, JavaScript, CoffeeScript, TypeScript, CSS, popular template languages and more. Take advantage of language-aware code completion, error detection, and on-the-fly code fixes!
It provides a rich architecture for interactive computing with a powerful interactive shell, a kernel for Jupyter. It has a support for interactive data visualization and use of GUI toolkits. Flexible, embeddable interpreters to load into your own projects. Easy to use, high performance tools for parallel computing.
It is a powerful scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts.
A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
See all alternatives

Jupyter's Followers
1336 developers follow Jupyter to keep up with related blogs and decisions.