Running Code

First and foremost, the Jupyter Notebook is an interactive environment for writing and running code. The notebook is capable of running code in a wide range of languages. However, each notebook is associated with a single kernel. This notebook is associated with the IPython kernel, therefore runs Python code.

Code cells allow you to enter and run code

Run a code cell using Shift-Enter or pressing the <button class='btn btn-default btn-xs'><i class="icon-step-forward fa fa-play"></i></button> button in the toolbar above:

a = 10

print(a)

There are two other keyboard shortcuts for running code:

• Alt-Enter runs the current cell and inserts a new one below.
• Ctrl-Enter run the current cell and enters command mode.

Managing the Kernel

Code is run in a separate process called the Kernel. The Kernel can be interrupted or restarted. Try running the following cell and then hit the <button class='btn btn-default btn-xs'><i class='icon-stop fa fa-stop'></i></button> button in the toolbar above.

import time

time.sleep(10)

If the Kernel dies you will be prompted to restart it. Here we call the low-level system libc.time routine with the wrong argument via ctypes to segfault the Python interpreter:

import sys

# This will crash a Linux or Mac system
# equivalent calls can be made on Windows

# Uncomment these lines if you would like to see the segfault

# dll = 'dylib' if sys.platform == 'darwin' else 'so.6'
# libc = CDLL("libc.%s" % dll)
# libc.time(-1)  # BOOM!!

Cell menu

The "Cell" menu has a number of menu items for running code in different ways. These includes:

• Run and Select Below
• Run and Insert Below
• Run All
• Run All Above
• Run All Below

Restarting the kernels

The kernel maintains the state of a notebook's computations. You can reset this state by restarting the kernel. This is done by clicking on the <button class='btn btn-default btn-xs'><i class='fa fa-repeat icon-repeat'></i></button> in the toolbar above.

sys.stdout and sys.stderr

The stdout and stderr streams are displayed as text in the output area.

print("hi, stdout")

print("hi, stderr", file=sys.stderr)

Output is asynchronous

All output is displayed asynchronously as it is generated in the Kernel. If you execute the next cell, you will see the output one piece at a time, not all at the end.

import sys
import time

for i in range(8):
    print(i)
    time.sleep(0.5)

Large outputs

To better handle large outputs, the output area can be collapsed. Run the following cell and then single- or double- click on the active area to the left of the output:

for i in range(50):
    print(i)

Beyond a certain point, output will scroll automatically:

for i in range(500):
    print(2**i - 1)