mathoudebine / mathoudebine/turing-smart-screen-python
The ability to "Auto split text if outside the frame" Option.
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Description
Is your feature request related to a problem? If so, please describe the problem.
Sometimes the text go outside of the frame aka the screen, Depdning on how long it is, And it's not cool to make the font size smaller just to fit it lol
Describe the feature / solution to your problem you'd like
The ability to "Auto split text if outside the frame" Option. Where if the text goes outside the frame, The last word that has the letters that went out of the frame get's split and shown in the middle under the text, Something like this:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
| | = the screen frame
| This is ftk 789 doing some nice feature request as exp | laining how to do this
And should be like this:
| | = the screen frame
| This is ftk doing some nice feature request as |
"space " explaining how to do this
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Describe alternatives you've considered / and or tested
Tried to manually split the text but don't work. made the font size smaller but that's a downside.
Screenshots / photos & mockups of the Turing screen
Before the feautre:

After the feature:

Environment:
Windows 10
Python 3.X
Additional context
Thank you for an amazing project!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No file, test, or entry point is named. Start by locating the text-rendering code that constrains content to the display frame and review how manual line splitting works. Done means text that exceeds the frame is automatically split at an appropriate word boundary and remains readable without reducing the font size.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- frontend
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100