Run Python scripts with no hassle with IDLE
We use IDLE to test and run small scripts in Python when we don't want to open bigger IDEs such as Pycharm or Visual Studio (for example, …
Python IDLE
Python IDLE
Python IDLE
Overview
What is Python IDLE?
Python's IDLE is the integrated development environment (IDE) and learning platform for Python.
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What is Python IDLE?
Python's IDLE is the integrated development environment (IDE) and learning platform for Python.
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- No setup fee
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- Free Trial
- Free/Freemium Version
- Premium Consulting / Integration Services
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Product Details
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- Tech Details
What is Python IDLE?
Python's IDLE is the integrated development environment (IDE) and learning platform for Python.
Python IDLE Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
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Reviews and Ratings
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May 10, 2021
Run Python scripts with no hassle with IDLE
We use IDLE to test and run small scripts in Python when we don't want to open bigger IDEs such as Pycharm or Visual Studio (for example, calling simple internal scripts). We use it mainly in our own machines rather than running it on a server, so few users in the organization are using it.
- Simple to use.
- Fast
- Friendly interface (for someone who knows how to use it).
- It's a simple environment so for me there is no room for improvement. It does what it needs to do.
- Simple to use
- Built in with Python
January 29, 2021
Python IDLE - quick insights
We use Python IDLE for machine learning and AI projects at our organization. To perform analysis on health data and for decision making like whether a health center has to get an award or not based on their annual data reported, we perform some predictive analysis and make decisions.
- 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.
- Debugging could be more advanced.
- Can have more data science packages.
- Output features can be better.
- 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.
I have used Visual Studio Code as well but, I would prefer to use Python IDLE as it helps to debug easily and is user-friendly which ultimately helps to perform the tasks quickly.
January 05, 2021
Python IDLE--for basic stats analysis and model development
I think it depends on users. I prefer Python IDLE for machine learning
model development. It's widely used across science teams for ML
solutions in production as it's well integrated with most production
systems and AWS tools. Also, it is used as the default tool for machine
learning university internally.
- User friendly for basic stats analysis
- Well-developed packages for ML development
- Well integrated with production system
- More user-friendly tutorials
- Easier output format
- Quick intro guide to new features
- Positive on ML model in production
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.
December 31, 2020
Not for the advanced user
Python IDLE is used by some people as the IDE for python interpreter in a Windows environment. We don't use it department wide, as it has only basic functionalities in my opinion. Python IDLE is used mainly for writing simple scripts, which are used mainly for text processing and data cleanup purposes.
- GUI interface
- Has scope matching
- Debugging facilities can be integrated
- 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)
- Already comes along with the Python Interpreter in Windows, so no need to install any additional plug-ins. This is positive.
- Relatively intuitive with a flat learning curve. This is positive.
- Not too suitable for large program maintenance. This is negative.
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.
November 14, 2020
Review for Python IDLE
In the Python IDLE development environment, I am using it personally to carry out small developments or to migrate scripts made in shell to Python, to improve its performance and take advantage of the advantages of Python over sh / bash.
These scripts are for automating department, peer, or personal tasks.
I am using this IDE as it has an educational part that makes programming easier and allows you to debug.
- The best thing is the debug that incorporates.
- Friendly graphic environment.
- Provide keyword auto-fill.
- Color the command syntax automatically.
- Very configurable.
- Too minimalist GUI.
- It does not allow associating several code files to a development project.
- It does not have plugins.
- Little time is spent on small developments to automate routine tasks.
- Modernization of old scripts in a short time, also improving their performance.
- Any technician can understand the program code and adapt it to your needs in no time.
I have used other IDEs, such as jEdit, Geany, NetBeans, ...
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 is good to start programming in Python due to its great debugger, but once you are fluent and start developing projects it is necessary to jump to another, more complete IDE.
I am currently using jEdit and am very happy with it, even though it is not debugged.