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Python IDLE

Score8.9 out of 10

195 Reviews and Ratings

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What is Python IDLE?

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.

Categories & Use Cases

Reviews

What users are saying about Python IDLE.
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Python IDLE review

jordan alexis
Programmer in Information Technology at Techwalla (51-200 employees employees)

Use Cases and Deployment Scope

Our organization a data analytics firm, uses python IDLE for data analysis, machine learning, and data visualization tasks.python IDLE addresses several business problems for our organizationsuch as1-Rapid prototyping :python IDLE enables our team to quickly develop and test python scripts, which is essential for rapid prototyping and proof of concept development 2-Data Analysis and Visualization: python IDLE provides an interactive environment for data analysis and visualization, allowing our team to quickly explore and visualize data3-machine learning development:python IDLE supports the development of machine learning models using popular libraries like scikit learn and tensorflow.our use case for python IDLE involves1 Data analysis2 machine learning 3 Education and training

Pros

  • Data analysis
  • Machine learning development
  • Increased productivity

Cons

  • Code completion and intellisense
  • Debugging capabilities
  • Project management

Return on Investment

  • Increase development speed
  • Improve code quality
  • Limited scalability
  • Limited code analysis

Usability

Alternatives Considered

PyCharm

Other Software Used

PyCharm, VisualSEO Studio, Spyder

Run Python scripts with no hassle with IDLE

Incentivized
Gabriel KrahnView profile
Analista de Suporte de Sistemas in Information Technology at T-Systems do Brasil (10,001+ employees employees)

Pros

  • Simple to use.
  • Fast
  • Friendly interface (for someone who knows how to use it).

Cons

  • It's a simple environment so for me there is no room for improvement. It does what it needs to do.

Most Important Features

  • Simple to use
  • Built in with Python

Python IDLE--for basic stats analysis and model development

Incentivized
Yaxian Xie
BIE in Marketing at Amazon (10,001+ employees employees)

Pros

  • User friendly for basic stats analysis
  • Well-developed packages for ML development
  • Well integrated with production system

Cons

  • More user-friendly tutorials
  • Easier output format
  • Quick intro guide to new features

Return on Investment

  • Positive on ML model in production

Alternatives Considered

Jupyter Notebook

Other Software Used

Jupyter Notebook, RStudio, Amazon Redshift

Not for the advanced user

Incentivized
Mohammad Mahmud
Data Scientist in Engineering at Siemens Healthineers (1001-5000 employees employees)

Pros

  • GUI interface
  • Has scope matching
  • Debugging facilities can be integrated

Cons

  • 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)

Return on Investment

  • 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.

Alternatives Considered

PyCharm

Other Software Used

PyCharm, RStudio, JMP Statistical Discovery Software from SAS

Review for Python IDLE

Incentivized
José Javier Dominguez ReinaView profile
Jefe de Proyecto in Information Technology at Sadesi (201-500 employees employees)

Pros

  • The best thing is the debug that incorporates.
  • Friendly graphic environment.
  • Provide keyword auto-fill.
  • Color the command syntax automatically.
  • Very configurable.

Cons

  • Too minimalist GUI.
  • It does not allow associating several code files to a development project.
  • It does not have plugins.

Return on Investment

  • 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.

Usability

Other Software Used

NetBeans, Spyder, PyCharm