IPython Documentation

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Coding guide

General coding conventions

In general, we’ll try to follow the standard Python style conventions as described in Python’s PEP 8 [PEP8], the official Python Style Guide.

Other general comments:

  • In a large file, top level classes and functions should be separated by 2 lines to make it easier to separate them visually.
  • Use 4 spaces for indentation, never use hard tabs.
  • Keep the ordering of methods the same in classes that have the same methods. This is particularly true for classes that implement similar interfaces and for interfaces that are similar.

Naming conventions

In terms of naming conventions, we’ll follow the guidelines of PEP 8 [PEP8]. Some of the existing code doesn’t honor this perfectly, but for all new IPython code (and much existing code is being refactored), we’ll use:

  • All lowercase module names.
  • CamelCase for class names.
  • lowercase_with_underscores for methods, functions, variables and attributes.

This may be confusing as some of the existing codebase uses a different convention (lowerCamelCase for methods and attributes). Slowly, we will move IPython over to the new convention, providing shadow names for backward compatibility in public interfaces.

There are, however, some important exceptions to these rules. In some cases, IPython code will interface with packages (Twisted, Wx, Qt) that use other conventions. At some level this makes it impossible to adhere to our own standards at all times. In particular, when subclassing classes that use other naming conventions, you must follow their naming conventions. To deal with cases like this, we propose the following policy:

  • If you are subclassing a class that uses different conventions, use its naming conventions throughout your subclass. Thus, if you are creating a Twisted Protocol class, used Twisted’s namingSchemeForMethodsAndAttributes.
  • All IPython’s official interfaces should use our conventions. In some cases this will mean that you need to provide shadow names (first implement fooBar and then foo_bar = fooBar). We want to avoid this at all costs, but it will probably be necessary at times. But, please use this sparingly!

Implementation-specific private methods will use _single_underscore_prefix. Names with a leading double underscore will only be used in special cases, as they makes subclassing difficult (such names are not easily seen by child classes).

Occasionally some run-in lowercase names are used, but mostly for very short names or where we are implementing methods very similar to existing ones in a base class (like runlines() where runsource() and runcode() had established precedent).

The old IPython codebase has a big mix of classes and modules prefixed with an explicit IP. In Python this is mostly unnecessary, redundant and frowned upon, as namespaces offer cleaner prefixing. The only case where this approach is justified is for classes which are expected to be imported into external namespaces and a very generic name (like Shell) is too likely to clash with something else. However, if a prefix seems absolutely necessary the more specific IPY or ipy are preferred.

[PEP8](1, 2) Python Enhancement Proposal 8. http://www.python.org/peps/pep-0008.html

Attribute declarations for objects

In general, objects should declare in their class all attributes the object is meant to hold throughout its life. While Python allows you to add an attribute to an instance at any point in time, this makes the code harder to read and requires methods to constantly use checks with hasattr() or try/except calls. By declaring all attributes of the object in the class header, there is a single place one can refer to for understanding the object’s data interface, where comments can explain the role of each variable and when possible, sensible deafaults can be assigned.


If an attribute is meant to contain a mutable object, it should be set to None in the class and its mutable value should be set in the object’s constructor. Since class attributes are shared by all instances, failure to do this can lead to difficult to track bugs. But you should still set it in the class declaration so the interface specification is complete and documdented in one place.

A simple example:

class foo:
    # X does..., sensible default given:
    x = 1
    # y does..., default will be set by constructor
    y = None
    # z starts as an empty list, must be set in constructor
    z = None

    def __init__(self, y):
        self.y = y
        self.z = []

New files

When starting a new file for IPython, you can use the following template as a starting point that has a few common things pre-written for you. The template is included in the documentation sources as docs/sources/development/template.py:

"""A one-line description.

A longer description that spans multiple lines.  Explain the purpose of the
file and provide a short list of the key classes/functions it contains.  This
is the docstring shown when some does 'import foo;foo?' in IPython, so it
should be reasonably useful and informative.
# Copyright (c) 2011, the IPython Development Team.
# Distributed under the terms of the Modified BSD License.
# The full license is in the file COPYING.txt, distributed with this software.

# Imports
from __future__ import print_function

# [remove this comment in production]
# List all imports, sorted within each section (stdlib/third-party/ipython).
# For 'import foo', use one import per line.  For 'from foo.bar import a, b, c'
# it's OK to import multiple items, use the parenthesized syntax 'from foo
# import (a, b, ...)' if the list needs multiple lines.

# Stdlib imports

# Third-party imports

# Our own imports

# [remove this comment in production]
# Use broad section headers like this one that make it easier to navigate the
# file, with descriptive titles.  For complex classes, simliar (but indented)
# headers are useful to organize the internal class structure.

# Globals and constants

# Local utilities

# Classes and functions