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 in the toolbar above:


In [0]:
a = 10

In [2]:
print(a)


10

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 in the toolbar above.


In [0]:
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:


In [0]:
import sys
from ctypes import CDLL
# 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 in the toolbar above.

sys.stdout and sys.stderr

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


In [5]:
print("hi, stdout")


hi, stdout

In [6]:
print('hi, stderr', file=sys.stderr)


hi, 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.


In [7]:
import time, sys
for i in range(8):
    print(i)
    time.sleep(0.5)


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