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What exactly is wrong with it? I use Jupyter daily and find no other Python environment more productive, be it scripts or IPython or IDEs. Granted, I work in scientific computing and use Python for data wrangling and stats. I find immense value in interactivity and iteration speed.
You should never use notebooks - period. My TL;DR: • Confusing for beginners • Encourage bad practices • Poor editor
Most comments here express disbelief and disappointment in Jupyter from the software engineering point of view. What exactly is wrong with it? I use Jupyter daily and find no other Python environment more productive, be it scripts or IPython or IDEs. Granted, I work in scientific computing and use Python for data wrangling and stats. I find immense value in interactivity and iteration speed.
I understand why they became popular, but as a software engineer considering how they work, I am just full of disappointment. we're going to spend the next ten years re-inventing every single software engineering best practice for jupyter's weirdo environment.
This is definitely one of my concerns too. Ad hoc code inside these notebooks is almost completely unmanageable from any reasonable software maintenance perspective, and refactoring code out of them is prohibitively difficult as well. I really want something to emerge that combines the best of both worlds of an IDE and notebook development, but there isn't anything close currently.
Most comments here express disbelief and disappointment in Jupyter from the software engineering point of view. What exactly is wrong with it? I use Jupyter daily and find no other Python environment more productive, be it scripts or IPython or IDEs. Granted, I work in scientific computing and use Python for data wrangling and stats. I find immense value in interactivity and iteration speed.
It isn't that you aren't getting good results and doing good work. It is that there are many practices that were hammered out in software development that were completely tossed out the window. 4GL comes to mind as a comparison. Makes great demos. Is not likely to lead to good engineering.
Earlier quoted context omitted.
This is definitely one of my concerns too. Ad hoc code inside these notebooks is almost completely unmanageable from any reasonable software maintenance perspective, and refactoring code out of them is prohibitively difficult as well. I really want something to emerge that combines the best of both worlds of an IDE and notebook development, but there isn't anything close currently.
What? What are you using Jupyter notebooks for where you want maintenance? They should be records of data analysis/ procedures, not code that runs in production or something.
"jupyter is the new bash" As much as I love Jupyter this is a bridge too far even for me. There's nothing about Jupyter that makes sense for non-interactive scripting. Although, I suppose it would help you do block chain calculations... which would also be a terrible idea.
Inline documentation and charting (which for data tasks is a honking huge deal). It's literate programming with an actual use-case. Very into this idea.
Most comments here express disbelief and disappointment in Jupyter from the software engineering point of view. What exactly is wrong with it? I use Jupyter daily and find no other Python environment more productive, be it scripts or IPython or IDEs. Granted, I work in scientific computing and use Python for data wrangling and stats. I find immense value in interactivity and iteration speed.
How do you find it compares to Spyder?
If I need a file browser or I want to quickly view two notebooks side-by-side, Jupyter Lab is still more convenient than Spyder. Although it doesn't support all the features of the notebook, and you end up installing additional extensions managed through yarn and webpack (jeez).
Most comments here express disbelief and disappointment in Jupyter from the software engineering point of view. What exactly is wrong with it? I use Jupyter daily and find no other Python environment more productive, be it scripts or IPython or IDEs. Granted, I work in scientific computing and use Python for data wrangling and stats. I find immense value in interactivity and iteration speed.
My hunch is the same disdain you probably have towards scientists using excel is how many software engineers feel about your using jupyter. It isn't that you aren't getting good results and doing good work. It is that there are many practices that were hammered out in software development that were completely tossed out the window. 4GL comes to mind as a comparison. Makes great demos. Is not likely to lead to good en…
1. Interactive computation and plotting, run data through a pipeline.
2. Quick prototyping and testing. Once a function/class is ready, it goes into a module, together with some unit tests.
Nothing beats Jupyter for that second use case, 90% of the bugs are squashed through interaction and inspection in the notebook cells, not through unit tests.
Earlier quoted context omitted.
What? What are you using Jupyter notebooks for where you want maintenance? They should be records of data analysis/ procedures, not code that runs in production or something.
exactly. I use it for quick data exploration and experimentation but it remains at that level.