Jupyter Notebook vs. Python IDLE

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Jupyter Notebook
Score 8.9 out of 10
N/A
Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A
Python IDLE
Score 8.8 out of 10
N/A
Python's IDLE is the integrated development environment (IDE) and learning platform for Python.N/A
Pricing
Jupyter NotebookPython IDLE
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Jupyter NotebookPython IDLE
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
More Pricing Information
Community Pulse
Jupyter NotebookPython IDLE
Considered Both Products
Jupyter Notebook
Chose Jupyter Notebook
Jupyter Notebook is very attractive platform for new developers to code and to learn programming and perform tasks as compared to other IDE. It has very well and easy visualization, interactive programming and sharing the live code and slideshow is very easy as compare to …
Chose Jupyter Notebook
It should have cleaner support for multi-environment setup and should also increase the amount of features. Moreover, more support should be present for other programming languages. It should also have the option to set a specific location that opens up whenever I run command …
Chose Jupyter Notebook
Jupyter is easier to handle and user friendly.

We have free access to it and its cell by cell executing feature is amazing.
Chose Jupyter Notebook
I selected Jupyter Notebook because this is better integrated with the existing production systems than optional tools (for example, R). It is also commonly used tool within the scientist community.
Python IDLE
Chose Python IDLE
It's easy to set up and run quick analysis in Python IDLE on my local machine. The output is direct and easy to read. But sometimes I prefer Jupyter Notebook when the datasets are large, since it would take too long to run on my local machine. It is easier to run Jupyter …
Top Pros
Top Cons
Features
Jupyter NotebookPython IDLE
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Jupyter Notebook
8.5
22 Ratings
Python IDLE
-
Ratings
Connect to Multiple Data Sources8.822 Ratings00 Ratings
Extend Existing Data Sources8.921 Ratings00 Ratings
Automatic Data Format Detection8.615 Ratings00 Ratings
MDM Integration7.516 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Jupyter Notebook
9.4
22 Ratings
Python IDLE
-
Ratings
Visualization9.422 Ratings00 Ratings
Interactive Data Analysis9.322 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Jupyter Notebook
8.8
22 Ratings
Python IDLE
-
Ratings
Interactive Data Cleaning and Enrichment9.121 Ratings00 Ratings
Data Transformations8.822 Ratings00 Ratings
Data Encryption8.415 Ratings00 Ratings
Built-in Processors8.815 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Jupyter Notebook
8.8
22 Ratings
Python IDLE
-
Ratings
Multiple Model Development Languages and Tools9.021 Ratings00 Ratings
Automated Machine Learning9.019 Ratings00 Ratings
Single platform for multiple model development9.122 Ratings00 Ratings
Self-Service Model Delivery8.321 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Jupyter Notebook
8.8
20 Ratings
Python IDLE
-
Ratings
Flexible Model Publishing Options8.820 Ratings00 Ratings
Security, Governance, and Cost Controls8.719 Ratings00 Ratings
User Ratings
Jupyter NotebookPython IDLE
Likelihood to Recommend
9.1
(23 ratings)
8.5
(5 ratings)
Usability
10.0
(1 ratings)
10.0
(1 ratings)
Support Rating
9.0
(1 ratings)
8.0
(1 ratings)
User Testimonials
Jupyter NotebookPython IDLE
Likelihood to Recommend
Open Source
I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
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Python Software Foundation
IDLE is a good option to run small scripts directly on the console, and that's it. It is a good exit when you don't want or need to open a proper IDE like Pycharm.
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Pros
Open Source
  • Simple and elegant code writing ability. Easier to understand the code that way.
  • The ability to see the output after each step.
  • The ability to use ton of library functions in Python.
  • Easy-user friendly interface.
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Python Software Foundation
  • Firstly, I would say Python IDLE interface is user friendly.
  • Easy to learn for the beginners.
  • Syntax highlighting is nice features.
  • Smart indent helps a lot.
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Cons
Open Source
  • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
  • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
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Python Software Foundation
  • More user-friendly tutorials
  • Easier output format
  • Quick intro guide to new features
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Usability
Open Source
Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
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Python Software Foundation
The IDE Python IDLE is a good place to start as it helps you become familiar with the way Python works and understand its syntax.
This IDE allows you to configure the environment, font, size, colors, .....
It also looks like any simple text editor for any operating system, I work with Windows or Linux interchangeably, and you don't have to learn to use the IDE before programming.
Once the IDE is executed you can start programming directly in it.
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Support Rating
Open Source
I haven't had a need to contact support. However, all required help is out there in public forums.
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Python Software Foundation
Python IDLE support is what the community can give you. As it is free software, it does not have support provided by the manufacturer or by third-parties.
In any case, for most of the problems that normal users can find, the solution, or alternatives, can be found quickly online.
As this IDE is made in Python, the support is the same group of Python developers.
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Alternatives Considered
Open Source
With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
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Python Software Foundation
Python IDLE is very easy to use compared to PyCharm. So for simple python scripting, Python IDLE is preferable to PyCharm, which has relatively steep learning curve. Compared to Python IDLE, PyCharm is more resource intensive, which may be worth it when comes to large projects, but PyChram does not provide any extra value for simple scripting.
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Return on Investment
Open Source
  • Positive impact: flexible implementation on any OS, for many common software languages
  • Positive impact: straightforward duplication for adaptation of workflows for other projects
  • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
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Python Software Foundation
  • In a short time, we were able to develop several ML models for various teams to make accurate decisions.
  • Beginners can easily understand and adapt to GUI.
  • We could automate several manual validation tasks and so could reduce human intervention.
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