Python IDLE vs. Spyder

Scenarios where python IDLE is well suited 1-Quick scripting and prototyping 2-Education and training 3-small projects utilities 4-exploring python libraries and modules Scenarios where python is less appropriate 1 large scale projects 2 complex debugging and profiling 3 multi language development 4 Advanced code analysis and inspection

Spyder is an open-source Python IDE designed for the movement of data science work. Spyder comes with an Anaconda package manager distribution, so depending on your setup you may have installed it on your machine.

Spyder includes most of the "standard IDE" features you can expect, such as a strong syntax code editor, Python code rendering, and an integrated text browser.

Spyder is used when we want to develop a code that is useful and able to explore proper documentation of the code that has been written. We use Spyder to perform data-related operations like filtration, cleaning, and enhancing the data qualities. There some cases where it is less appropriate like working in an environment, creating dashboards of data visualizations and plots.

• 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.

Incentivized

• Provides wider screen to read and write code and flexibility to adjust size as per requirement.
• While running the code it provide the variable overview and memory overview
• Lightweight and easily available in Anaconda Navigator
• Multiple compilation options are available
• Works well for data analytics, Django, Flask and Fast API frameworks

Incentivized

• Too simplistic
• Could not find source revision management integration support
• Only basic debugging is available
• Does not have data-science-specific notebooks (but can be installed separately)

Incentivized

• Colors in code format
• Add a broadcast to share the project with friends
• Contains more than one important language such as Python

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.

Incentivized

It is fairly straightforward to use. Pretty much good to go as soon as you install it. The IDE itself is very user friendly, and it is only limited by whatever limitations Python has as a language. Great for those who want to run their scripts quickly or do some Python programming without fussing.

Incentivized

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.

Incentivized

Most of data scientists or data engineers are either using ec2 on the cloud or Atom or PyCharm locally. It is a bit hard to find people who are still using Spyder and have the sight of the IDE and can help you to answer your question.

Incentivized

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 Notebook on my cloud desktop

Incentivized

I think Spyder doesn't stack up as well as other IDEs due to its many limitations. But it is available for free and that is one advantage it has over its competitors

Incentivized

• 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.

Incentivized

• It has helped me learn python quickly
• The ability to generate figures quickly and interact with them is helpful

Incentivized