Python's IDLE is the integrated development environment (IDE) and learning platform for Python, presented as a basic and simple IDE appropriate for learners in educational settings.
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SQL Server Management Studio (SSMS)
Score 8.4 out of 10
N/A
SQL Server Management Studio (SSMS) is an integrated environment for managing any SQL infrastructure, from SQL Server to Azure SQL Database.
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
The tool is excellent for managing virtually all aspects of SQL Server - multiple servers, databases, hundreds of tables and procedures, dozens of SQL Agent jobs. We have not encountered any situations where it is not appropriate.
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.
It's very user friendly. If you know T-SQL then you can use this. Really even if you don't it's not that hard to figure out. You can create things visually as well.
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.
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