#1 most frequent
United States of America
69.7%138 installations of 198
What is Spyder?
Spyder is a free and open source scientific environment for Python. It combines advanced editing, analysis, debugging, and profiling, with data exploration, interactive execution, deep inspection, and visualization capabilities. Spyder is sponsored by open source supporters QuanSight, and NumFOCUS, as well as individual donors.
Categories & Use Cases
Product Demos
Who Buys & Uses Spyder
#2 most frequent
Canada
9.1%18 installations of 198
#3 most frequent
India
3.5%7 installations of 198
Best Oper source Python IDE
Use Cases and Deployment Scope
Spyder is one of our IDE that we're using for coding in python. Earlier I was using it for all kind of development in python but now I have restricted it's usage for writing single file code or writing scripts only. Apart from this it also provides limited data visualization for data structures and data frames too. It makes us easy to perform data related work too.
Pros
- 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
Cons
- Auto save functionality must be provided and files should be preserved on opening again
- I didn't find folder explorer option which makes it difficult work with projects with multiple files.
- Dark theme is good but light theme needs improvements
Return on Investment
- Not direct impact of business ROI but helped in improving coding process which leads to better and faster deployment
Usability
Alternatives Considered
Notepad++ and Microsoft Visual Studio Code
Other Software Used
Jupyter Notebook, MATLAB
Spyder - great for anybody using Python
Use Cases and Deployment Scope
Spyder is a Python IDE, and it is used by myself and my peers to write and run various Python scripts. Being a scientific organisation, this often means running scripts that will perform scientific functions for us. Of particular use to us is the built in plot feature within the GUI, meaning that as we run our scripts, useful plots are visible there and then.
Pros
- Python IDE
- No need to install python itself
- Plots
- Shows variables
- Can show other data files
Cons
- Remember GUI layout settings
- Allow plots to be viewed in their own window/made bigger
- Choose python version
Return on Investment
- Easy to analyse data
- Easy to be able to visualise data
- Easy to convert data from one domain to another.
Usability
This editor helped me learn Python
Use Cases and Deployment Scope
One of the big problems that I solved using the Spyder editor was mastering the basics of Python through which I understood how to practice programming, and I understood the way other languages work for use in other editors, as well as using the Python libraries that are inside Spyder when it was loaded.
Pros
- data analysis
- Speed in displaying output
- The large number of libraries
- Very easy user interface
Cons
- Colors in code format
- Add a broadcast to share the project with friends
- Contains more than one important language such as Python
Most Important Features
- the keyboard shortcuts
- flexible in dealing and very suitable for beginners
- it is open source and you can now download it and start using it
- Auto complete the words in the code
Return on Investment
- I found that there are errors in the output panel
- Shows unwanted results
Alternatives Considered
Microsoft Visual Studio Code
Other Software Used
Microsoft Visual Studio Code, PyCharm, Python IDLE
Spyder Review
Pros
- Well formatted comments in the code.
- It's Free and Open source to use any library in python
- Spyder is best suited for Python only with data analysis and reporting generation operations.
Cons
- Spyder can improve the data Analysis part, means how they show plotting's, charts and all
- Spyder can be improved when it comes with full set of the libraries that generally used in the Data Science
Most Important Features
- It's Free and open source.
- It is easy to use and handy tool with different types of themes.
- Well documented and commented code
- Attractive interface and UI
Return on Investment
- Not suitable for collaborative work.
- Difficult to setup its environment
- Suitable for Python only.
Alternatives Considered
Anaconda, Microsoft Visual Studio Code, Python IDLE and PyCharm
Other Software Used
PyCharm, Anaconda, Python IDLE, Jupyter Notebook
Spyder: a user friendly python programming platform
Pros
- Debugging of your existing code
- Generates figures very quickly as part of a figures tab which lets users understand results quickly
- Different layouts are available for the software which will give the users freedom to decide what layout works best for them
Cons
- The results tab needs to improved.
- The software requires a bit of a learning curve. Tutorials about how the software can be used should be added.
Most Important Features
- Strong debugging
- Quick figure generation
- Different layout types to meet user needs
Return on Investment
- It has helped me learn python quickly
- The ability to generate figures quickly and interact with them is helpful
Alternatives Considered
Jupyter Notebook and MATLAB
Other Software Used
MATLAB, Jupyter Notebook, AutoCAD