81–90 of 95 posts
I would be wonderful if we could re-use the notebook interface for other language - Octave, Julia, R, Ruby. (Would also be nice if building ipython on OS X was easier!)
I was lucky enough to find IPython early on when I started with Python. I'm constantly amazed with its feature set. Some cool things I found useful: The "run" command for running python scripts: * -t to print timing information * -p to print profiling info from profiler module * -d run the script under pdb interactively (with -b to set line breakpoints) * -n to set __name__ All of these things can be done fairly easi…
IPython notebook is actually one of the most interesting developments not just in the python world, but in computing generally. It's the first step towards the fully graphical shell on the internet that many of us have been looking for, whether or not we realize it. Being able to weave together text|markdown, tabular data (in almost any format you want) and images ( whether from matplotlib, raw captures, or synthetic…
IPython notebook is actually one of the most interesting developments not just in the python world, but in computing generally. It's the first step towards the fully graphical shell on the internet that many of us have been looking for, whether or not we realize it. Being able to weave together text|markdown, tabular data (in almost any format you want) and images ( whether from matplotlib, raw captures, or synthetic…
Most of my programming these days is actually done in IPython notebook. Having an instant feedback is invaluable. I put my code in plain old .py files only once it needs to be imported. I'm even wondering: if there was a way for notebooks to import each other, would I still bother with modules?
1. In ipython_notebook_config.py, set the following:
# Save .py for each notebook for import elsewhere
c.NotebookManager.save_script = True
2. Restart your notebook server. 3. Save any notebooks you'd like to import under module friendly names. (They wind up in the same dir as the ipynb files.) 4. In your interactive notebook, import your_other_notebook.
This works well when all your notebooks are in the same folder, which is the default. I haven't given much thought to how you might create packages this way, but perhaps with a few code changes you could?
IPython notebook is actually one of the most interesting developments not just in the python world, but in computing generally. It's the first step towards the fully graphical shell on the internet that many of us have been looking for, whether or not we realize it. Being able to weave together text|markdown, tabular data (in almost any format you want) and images ( whether from matplotlib, raw captures, or synthetic…
To be fair, this graphical shell functionality has been part of Mathematica for at least the past 7-8 years. In fact, I would argue that within Mathematica, one can work with a much larger number of formats and data sources.
I would be wonderful if we could re-use the notebook interface for other language - Octave, Julia, R, Ruby. (Would also be nice if building ipython on OS X was easier!)
The related features in Org-mode are known as Org-babel, uniting disparate languages under the single umbrella of Org-mode. The support for language evaluation in Org-mode is slightly more cumbersome than that offered in IPython, but also arguably more flexible and powerful. Plus you get to edit your notebook in a powerful editor with best outliner ever, plus all of Org-mode's many other features (I'm a Vim person but I give credit where credit is due).
Org-babel is a rich and deep niche of Org-mode, and one of the areas under the most constant development. You can read some docs on it here, but it can be hard to wrap your head around all of it until you actually use it:
http://orgmode.org/manual/Working-With-Source-Code.html#Work...
Why does IPython get all the love? I tried it out back in the day, but it was not very impressive. bpython is much better, but doesn't seem to get as much attention.
Earlier quoted context omitted.
It sorely needs some better tutorials, demos. The official docs are dry and dwell on technical matters rather than giving you some sense of the potential. There isn't much else out there - especially if you aren't doing scientific or statistical work. I'm sure the iPython Notebook could be useful in my day to day Python/Django usage but I haven't figured out how yet.
In addition to the other links in this thread, Fernando's PyCon.ca keynote's has a great introduction to the power of IPython and how it's revolutionizing the scientific (and soon the general developer) communities. https://www.youtube.com/watch?v=F4rFuIb1Ie4