My Jupyter (tmpnb) server and Thebe

%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from IPython.html.widgets import interact

def plot_sine(frequency=1.0, amplitude=1.0):
    plt.ylim(-1.0, 1.0);
    x = np.linspace(0, 10, 1000)
    plt.plot(x, amplitude*np.sin(x*frequency));

interact(plot_sine, frequency=(0.5, 10.0), amplitude=(0.0, 1.0));

Isn't that amazing?!?

I've recently installed an tmpnb sever on my digitalocean server, you can access it at nagasaki45.com:8000.

So, what's the big deal?
This configuration allow anyone to use python (or one of the other supported / installed kernels) on the web, using my server. You don't have to ask for permission; you can just go to the provided address and start to code without any local installation.

And it goes way beyond:

• You can open new terminal, 'git clone' your project, and demonstrate it to someone else. And you can do it on mobile devices too. Again, no installation required, everything is running on the server.
• You can use thebe to add code snippets as the one above to any static html page (your blog, as example). Even interactive widgets will run the computation back and fourth from the server to the web frontend for presentation.

So go ahead, write some code, let me execute it for you ;-)

# your python playground 

Edit 1.9.15:

My digitalocean VM has "only" 512MB of RAM. I decided to span tmpnb with 4 docker containers, 50MB RAM each, to keep the server load on minimum. Apparently, it possessed some issues as 50MB are probably not enough.

Right now the example above uses the same tmpnb server has the one in thebe example (here), namely https://oreillyorchard.com:8000/. It works much better now as there are no kernal failures when running the examples.

Edit 20.9.15:

I'm stopping the service on my server due to some number crunching tasks I'm running on it.