Jupyter Notebook vs. Rapise

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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The appropriate scenario to use Rapise is when we have a project that is considered from medium onwards, since Rapise will help us to define, develop and implement the testing phase in a reliable and efficient way. Also with Rapise we will not have to worry about the platform that we are using since it has great versatility and flexibility.

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• 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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• Simple recording front-end and easily captures UI objects for later interaction
• Flexible programming interface provides a multitude of manners in which to interact with learned UI objects
• Javascript based IDE is easy to learn

• 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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• For tests that require specific approaches it is necessary to have advanced knowledge of programming in javascrip, which sometimes the QA team does not have experience
• Sometimes I have noticed that when using object dragging errors occur intermittently
• The integration with some tools (Dynamics) is only with the basic functions from my point of view

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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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I haven't had a need to contact support. However, all required help is out there in public forums.

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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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Mmuch better from a flexibility perspective

• 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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• The primary objective of the institution is a service to the public, so everything that improves response times to the public helps us to achieve it.
• As a department in charge of the development of systems and applications, our objective is fulfilled by delivering quality products and tools such as Rapise help us greatly
• The return on investment can be more than justified by fulfilling the primary objectives

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info