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PEP: 8
Title: Style Guide for Python Code
Version: $Revision$
Last-Modified: $Date$
Author: guido@python.org (Guido van Rossum),
barry@python.org (Barry Warsaw)
Status: Active
Type: Process
Created: 05-Jul-2001
Post-History: 05-Jul-2001
Introduction
This document gives coding conventions for the Python code comprising the
standard library in the main Python distribution. Please see the
companion informational PEP describing style guidelines for the C code in
the C implementation of Python[1].
This document was adapted from Guido's original Python Style Guide
essay[2], with some additions from Barry's style guide[5]. Where there's
conflict, Guido's style rules for the purposes of this PEP. This PEP may
still be incomplete (in fact, it may never be finished <wink>).
A Foolish Consistency is the Hobgoblin of Little Minds
One of Guido's key insights is that code is read much more often than it
is written. The guidelines provided here are intended to improve the
readability of code and make it consistent across the wide spectrum of
Python code. As PEP 20 [6] says, "Readability counts".
A style guide is about consistency. Consistency with this style guide is
important. Consistency within a project is more important. Consistency
within one module or function is most important.
But most importantly: know when to be inconsistent -- sometimes the style
guide just doesn't apply. When in doubt, use your best judgment. Look
at other examples and decide what looks best. And don't hesitate to ask!
Two good reasons to break a particular rule:
(1) When applying the rule would make the code less readable, even for
someone who is used to reading code that follows the rules.
(2) To be consistent with surrounding code that also breaks it (maybe for
historic reasons) -- although this is also an opportunity to clean up
someone else's mess (in true XP style).
Code lay-out
Indentation
Use 4 spaces per indentation level.
For really old code that you don't want to mess up, you can continue to
use 8-space tabs.
Tabs or Spaces?
Never mix tabs and spaces.
The most popular way of indenting Python is with spaces only. The
second-most popular way is with tabs only. Code indented with a mixture
of tabs and spaces should be converted to using spaces exclusively. When
invoking the Python command line interpreter with the -t option, it issues
warnings about code that illegally mixes tabs and spaces. When using -tt
these warnings become errors. These options are highly recommended!
For new projects, spaces-only are strongly recommended over tabs. Most
editors have features that make this easy to do.
Maximum Line Length
Limit all lines to a maximum of 79 characters.
There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to have
several windows side-by-side. The default wrapping on such devices
disrupts the visual structure of the code, making it more difficult to
understand. Therefore, please limit all lines to a maximum of 79
characters. For flowing long blocks of text (docstrings or comments),
limiting the length to 72 characters is recommended.
The preferred way of wrapping long lines is by using Python's implied line
continuation inside parentheses, brackets and braces. If necessary, you
can add an extra pair of parentheses around an expression, but sometimes
using a backslash looks better. Make sure to indent the continued line
appropriately. The preferred place to break around a binary operator is
*after* the operator, not before it. Some examples:
class Rectangle(Blob):
def __init__(self, width, height,
color='black', emphasis=None, highlight=0):
if width == 0 and height == 0 and \
color == 'red' and emphasis == 'strong' or \
highlight > 100:
raise ValueError("sorry, you lose")
if width == 0 and height == 0 and (color == 'red' or
emphasis is None):
raise ValueError("I don't think so -- values are %s, %s" %
(width, height))
Blob.__init__(self, width, height,
color, emphasis, highlight)
Blank Lines
Separate top-level function and class definitions with two blank lines.
Method definitions inside a class are separated by a single blank line.
Extra blank lines may be used (sparingly) to separate groups of related
functions. Blank lines may be omitted between a bunch of related
one-liners (e.g. a set of dummy implementations).
Use blank lines in functions, sparingly, to indicate logical sections.
Python accepts the control-L (i.e. ^L) form feed character as whitespace;
Many tools treat these characters as page separators, so you may use them
to separate pages of related sections of your file.
Encodings (PEP 263)
Code in the core Python distribution should aways use the ASCII or
Latin-1 encoding (a.k.a. ISO-8859-1). For Python 3.0 and beyond,
UTF-8 is preferred over Latin-1, see PEP 3120.
Files using ASCII should not have a coding cookie. Latin-1 (or
UTF-8) should only be used when a comment or docstring needs to
mention an author name that requires Latin-1; otherwise, using
\x, \u or \U escapes is the preferred way to include non-ASCII
data in string literals.
For Python 3.0 and beyond, the following policy is prescribed for
the standard library (see PEP 3131): All identifiers in the Python
standard library MUST use ASCII-only identifiers, and SHOULD use
English words wherever feasible (in many cases, abbreviations and
technical terms are used which aren't English). In addition,
string literals and comments must also be in ASCII. The only
exceptions are (a) test cases testing the non-ASCII features, and
(b) names of authors. Authors whose names are not based on the
latin alphabet MUST provide a latin transliteration of their
names.
Open source projects with a global audience are encouraged to
adopt a similar policy.
Imports
- Imports should usually be on separate lines, e.g.:
Yes: import os
import sys
No: import sys, os
it's okay to say this though:
from subprocess import Popen, PIPE
- Imports are always put at the top of the file, just after any module
comments and docstrings, and before module globals and constants.
Imports should be grouped in the following order:
1. standard library imports
2. related third party imports
3. local application/library specific imports
You should put a blank line between each group of imports.
Put any relevant __all__ specification after the imports.
- Relative imports for intra-package imports are highly discouraged.
Always use the absolute package path for all imports.
Even now that PEP 328 [7] is fully implemented in Python 2.5,
its style of explicit relative imports is actively discouraged;
absolute imports are more portable and usually more readable.
- When importing a class from a class-containing module, it's usually okay
to spell this
from myclass import MyClass
from foo.bar.yourclass import YourClass
If this spelling causes local name clashes, then spell them
import myclass
import foo.bar.yourclass
and use "myclass.MyClass" and "foo.bar.yourclass.YourClass"
Whitespace in Expressions and Statements
Pet Peeves
Avoid extraneous whitespace in the following situations:
- Immediately inside parentheses, brackets or braces.
Yes: spam(ham[1], {eggs: 2})
No: spam( ham[ 1 ], { eggs: 2 } )
- Immediately before a comma, semicolon, or colon:
Yes: if x == 4: print x, y; x, y = y, x
No: if x == 4 : print x , y ; x , y = y , x
- Immediately before the open parenthesis that starts the argument
list of a function call:
Yes: spam(1)
No: spam (1)
- Immediately before the open parenthesis that starts an indexing or
slicing:
Yes: dict['key'] = list[index]
No: dict ['key'] = list [index]
- More than one space around an assignment (or other) operator to
align it with another.
Yes:
x = 1
y = 2
long_variable = 3
No:
x = 1
y = 2
long_variable = 3
Other Recommendations
- Always surround these binary operators with a single space on
either side: assignment (=), augmented assignment (+=, -= etc.),
comparisons (==, <, >, !=, <>, <=, >=, in, not in, is, is not),
Booleans (and, or, not).
- Use spaces around arithmetic operators:
Yes:
i = i + 1
submitted += 1
x = x * 2 - 1
hypot2 = x * x + y * y
c = (a + b) * (a - b)
No:
i=i+1
submitted +=1
x = x*2 - 1
hypot2 = x*x + y*y
c = (a+b) * (a-b)
- Don't use spaces around the '=' sign when used to indicate a
keyword argument or a default parameter value.
Yes:
def complex(real, imag=0.0):
return magic(r=real, i=imag)
No:
def complex(real, imag = 0.0):
return magic(r = real, i = imag)
- Compound statements (multiple statements on the same line) are
generally discouraged.
Yes:
if foo == 'blah':
do_blah_thing()
do_one()
do_two()
do_three()
Rather not:
if foo == 'blah': do_blah_thing()
do_one(); do_two(); do_three()
- While sometimes it's okay to put an if/for/while with a small
body on the same line, never do this for multi-clause
statements. Also avoid folding such long lines!
Rather not:
if foo == 'blah': do_blah_thing()
for x in lst: total += x
while t < 10: t = delay()
Definitely not:
if foo == 'blah': do_blah_thing()
else: do_non_blah_thing()
try: something()
finally: cleanup()
do_one(); do_two(); do_three(long, argument,
list, like, this)
if foo == 'blah': one(); two(); three()
Comments
Comments that contradict the code are worse than no comments. Always make
a priority of keeping the comments up-to-date when the code changes!
Comments should be complete sentences. If a comment is a phrase or
sentence, its first word should be capitalized, unless it is an identifier
that begins with a lower case letter (never alter the case of
identifiers!).
If a comment is short, the period at the end can be omitted. Block
comments generally consist of one or more paragraphs built out of complete
sentences, and each sentence should end in a period.
You should use two spaces after a sentence-ending period.
When writing English, Strunk and White apply.
Python coders from non-English speaking countries: please write
your comments in English, unless you are 120% sure that the code
will never be read by people who don't speak your language.
Block Comments
Block comments generally apply to some (or all) code that follows them,
and are indented to the same level as that code. Each line of a block
comment starts with a # and a single space (unless it is indented text
inside the comment).
Paragraphs inside a block comment are separated by a line containing a
single #.
Inline Comments
Use inline comments sparingly.
An inline comment is a comment on the same line as a statement. Inline
comments should be separated by at least two spaces from the statement.
They should start with a # and a single space.
Inline comments are unnecessary and in fact distracting if they state
the obvious. Don't do this:
x = x + 1 # Increment x
But sometimes, this is useful:
x = x + 1 # Compensate for border
Documentation Strings
Conventions for writing good documentation strings (a.k.a. "docstrings")
are immortalized in PEP 257 [3].
- Write docstrings for all public modules, functions, classes, and
methods. Docstrings are not necessary for non-public methods, but you
should have a comment that describes what the method does. This comment
should appear after the "def" line.
- PEP 257 describes good docstring conventions. Note that most
importantly, the """ that ends a multiline docstring should be on a line
by itself, and preferably preceded by a blank line, e.g.:
"""Return a foobang
Optional plotz says to frobnicate the bizbaz first.
"""
- For one liner docstrings, it's okay to keep the closing """ on the same
line.
Version Bookkeeping
If you have to have Subversion, CVS, or RCS crud in your source file, do
it as follows.
__version__ = "$Revision$"
# $Source$
These lines should be included after the module's docstring, before any
other code, separated by a blank line above and below.
Naming Conventions
The naming conventions of Python's library are a bit of a mess, so we'll
never get this completely consistent -- nevertheless, here are the
currently recommended naming standards. New modules and packages
(including third party frameworks) should be written to these standards,
but where an existing library has a different style, internal consistency
is preferred.
Descriptive: Naming Styles
There are a lot of different naming styles. It helps to be able to
recognize what naming style is being used, independently from what they
are used for.
The following naming styles are commonly distinguished:
- b (single lowercase letter)
- B (single uppercase letter)
- lowercase
- lower_case_with_underscores
- UPPERCASE
- UPPER_CASE_WITH_UNDERSCORES
- CapitalizedWords (or CapWords, or CamelCase -- so named because
of the bumpy look of its letters[4]). This is also sometimes known as
StudlyCaps.
Note: When using abbreviations in CapWords, capitalize all the letters
of the abbreviation. Thus HTTPServerError is better than
HttpServerError.
- mixedCase (differs from CapitalizedWords by initial lowercase
character!)
- Capitalized_Words_With_Underscores (ugly!)
There's also the style of using a short unique prefix to group related
names together. This is not used much in Python, but it is mentioned for
completeness. For example, the os.stat() function returns a tuple whose
items traditionally have names like st_mode, st_size, st_mtime and so on.
(This is done to emphasize the correspondence with the fields of the
POSIX system call struct, which helps programmers familiar with that.)
The X11 library uses a leading X for all its public functions. In Python,
this style is generally deemed unnecessary because attribute and method
names are prefixed with an object, and function names are prefixed with a
module name.
In addition, the following special forms using leading or trailing
underscores are recognized (these can generally be combined with any case
convention):
- _single_leading_underscore: weak "internal use" indicator. E.g. "from M
import *" does not import objects whose name starts with an underscore.
- single_trailing_underscore_: used by convention to avoid conflicts with
Python keyword, e.g.
Tkinter.Toplevel(master, class_='ClassName')
- __double_leading_underscore: when naming a class attribute, invokes name
mangling (inside class FooBar, __boo becomes _FooBar__boo; see below).
- __double_leading_and_trailing_underscore__: "magic" objects or
attributes that live in user-controlled namespaces. E.g. __init__,
__import__ or __file__. Never invent such names; only use them
as documented.
Prescriptive: Naming Conventions
Names to Avoid
Never use the characters `l' (lowercase letter el), `O' (uppercase
letter oh), or `I' (uppercase letter eye) as single character variable
names.
In some fonts, these characters are indistinguishable from the numerals
one and zero. When tempted to use `l', use `L' instead.
Package and Module Names
Modules should have short, all-lowercase names. Underscores can be used
in the module name if it improves readability. Python packages should
also have short, all-lowercase names, although the use of underscores is
discouraged.
Since module names are mapped to file names, and some file systems are
case insensitive and truncate long names, it is important that module
names be chosen to be fairly short -- this won't be a problem on Unix,
but it may be a problem when the code is transported to older Mac or
Windows versions, or DOS.
When an extension module written in C or C++ has an accompanying Python
module that provides a higher level (e.g. more object oriented)
interface, the C/C++ module has a leading underscore (e.g. _socket).
Class Names
Almost without exception, class names use the CapWords convention.
Classes for internal use have a leading underscore in addition.
Exception Names
Because exceptions should be classes, the class naming convention
applies here. However, you should use the suffix "Error" on your
exception names (if the exception actually is an error).
Global Variable Names
(Let's hope that these variables are meant for use inside one module
only.) The conventions are about the same as those for functions.
Modules that are designed for use via "from M import *" should use the
__all__ mechanism to prevent exporting globals, or use the older
convention of prefixing such globals with an underscore (which you might
want to do to indicate these globals are "module non-public").
Function Names
Function names should be lowercase, with words separated by underscores
as necessary to improve readability.
mixedCase is allowed only in contexts where that's already the
prevailing style (e.g. threading.py), to retain backwards compatibility.
Function and method arguments
Always use 'self' for the first argument to instance methods.
Always use 'cls' for the first argument to class methods.
If a function argument's name clashes with a reserved keyword, it is
generally better to append a single trailing underscore rather than use
an abbreviation or spelling corruption. Thus "print_" is better than
"prnt". (Perhaps better is to avoid such clashes by using a synonym.)
Method Names and Instance Variables
Use the function naming rules: lowercase with words separated by
underscores as necessary to improve readability.
Use one leading underscore only for non-public methods and instance
variables.
To avoid name clashes with subclasses, use two leading underscores to
invoke Python's name mangling rules.
Python mangles these names with the class name: if class Foo has an
attribute named __a, it cannot be accessed by Foo.__a. (An insistent
user could still gain access by calling Foo._Foo__a.) Generally, double
leading underscores should be used only to avoid name conflicts with
attributes in classes designed to be subclassed.
Note: there is some controversy about the use of __names (see below).
Constants
Constants are usually declared on a module level and written in all
capital letters with underscores separating words. Examples include
MAX_OVERFLOW and TOTAL.
Designing for inheritance
Always decide whether a class's methods and instance variables
(collectively: "attributes") should be public or non-public. If in
doubt, choose non-public; it's easier to make it public later than to
make a public attribute non-public.
Public attributes are those that you expect unrelated clients of your
class to use, with your commitment to avoid backward incompatible
changes. Non-public attributes are those that are not intended to be
used by third parties; you make no guarantees that non-public attributes
won't change or even be removed.
We don't use the term "private" here, since no attribute is really
private in Python (without a generally unnecessary amount of work).
Another category of attributes are those that are part of the "subclass
API" (often called "protected" in other languages). Some classes are
designed to be inherited from, either to extend or modify aspects of the
class's behavior. When designing such a class, take care to make
explicit decisions about which attributes are public, which are part of
the subclass API, and which are truly only to be used by your base
class.
With this in mind, here are the Pythonic guidelines:
- Public attributes should have no leading underscores.
- If your public attribute name collides with a reserved keyword, append
a single trailing underscore to your attribute name. This is
preferable to an abbreviation or corrupted spelling. (However,
notwithstanding this rule, 'cls' is the preferred spelling for any
variable or argument which is known to be a class, especially the
first argument to a class method.)
Note 1: See the argument name recommendation above for class methods.
- For simple public data attributes, it is best to expose just the
attribute name, without complicated accessor/mutator methods. Keep in
mind that Python provides an easy path to future enhancement, should
you find that a simple data attribute needs to grow functional
behavior. In that case, use properties to hide functional
implementation behind simple data attribute access syntax.
Note 1: Properties only work on new-style classes.
Note 2: Try to keep the functional behavior side-effect free, although
side-effects such as caching are generally fine.
Note 3: Avoid using properties for computationally expensive
operations; the attribute notation makes the caller believe
that access is (relatively) cheap.
- If your class is intended to be subclassed, and you have attributes
that you do not want subclasses to use, consider naming them with
double leading underscores and no trailing underscores. This invokes
Python's name mangling algorithm, where the name of the class is
mangled into the attribute name. This helps avoid attribute name
collisions should subclasses inadvertently contain attributes with the
same name.
Note 1: Note that only the simple class name is used in the mangled
name, so if a subclass chooses both the same class name and attribute
name, you can still get name collisions.
Note 2: Name mangling can make certain uses, such as debugging and
__getattr__(), less convenient. However the name mangling algorithm
is well documented and easy to perform manually.
Note 3: Not everyone likes name mangling. Try to balance the
need to avoid accidental name clashes with potential use by
advanced callers.
Programming Recommendations
- Code should be written in a way that does not disadvantage other
implementations of Python (PyPy, Jython, IronPython, Pyrex, Psyco,
and such).
For example, do not rely on CPython's efficient implementation of
in-place string concatenation for statements in the form a+=b or a=a+b.
Those statements run more slowly in Jython. In performance sensitive
parts of the library, the ''.join() form should be used instead. This
will ensure that concatenation occurs in linear time across various
implementations.
- Comparisons to singletons like None should always be done with
'is' or 'is not', never the equality operators.
Also, beware of writing "if x" when you really mean "if x is not None"
-- e.g. when testing whether a variable or argument that defaults to
None was set to some other value. The other value might have a type
(such as a container) that could be false in a boolean context!
- Use class-based exceptions.
String exceptions in new code are forbidden, because this language
feature is being removed in Python 2.6.
Modules or packages should define their own domain-specific base
exception class, which should be subclassed from the built-in Exception
class. Always include a class docstring. E.g.:
class MessageError(Exception):
"""Base class for errors in the email package."""
Class naming conventions apply here, although you should add the suffix
"Error" to your exception classes, if the exception is an error.
Non-error exceptions need no special suffix.
- When raising an exception, use "raise ValueError('message')" instead of
the older form "raise ValueError, 'message'".
The paren-using form is preferred because when the exception arguments
are long or include string formatting, you don't need to use line
continuation characters thanks to the containing parentheses. The older
form will be removed in Python 3000.
- When catching exceptions, mention specific exceptions
whenever possible instead of using a bare 'except:' clause.
For example, use:
try:
import platform_specific_module
except ImportError:
platform_specific_module = None
A bare 'except:' clause will catch SystemExit and KeyboardInterrupt
exceptions, making it harder to interrupt a program with Control-C,
and can disguise other problems. If you want to catch all
exceptions that signal program errors, use 'except Exception:'.
A good rule of thumb is to limit use of bare 'except' clauses to two
cases:
1) If the exception handler will be printing out or logging
the traceback; at least the user will be aware that an
error has occurred.
2) If the code needs to do some cleanup work, but then lets
the exception propagate upwards with 'raise'.
'try...finally' is a better way to handle this case.
- Additionally, for all try/except clauses, limit the 'try' clause
to the absolute minimum amount of code necessary. Again, this
avoids masking bugs.
Yes:
try:
value = collection[key]
except KeyError:
return key_not_found(key)
else:
return handle_value(value)
No:
try:
# Too broad!
return handle_value(collection[key])
except KeyError:
# Will also catch KeyError raised by handle_value()
return key_not_found(key)
- Use string methods instead of the string module.
String methods are always much faster and share the same API with
unicode strings. Override this rule if backward compatibility with
Pythons older than 2.0 is required.
- Use ''.startswith() and ''.endswith() instead of string slicing to check
for prefixes or suffixes.
startswith() and endswith() are cleaner and less error prone. For
example:
Yes: if foo.startswith('bar'):
No: if foo[:3] == 'bar':
The exception is if your code must work with Python 1.5.2 (but let's
hope not!).
- Object type comparisons should always use isinstance() instead
of comparing types directly.
Yes: if isinstance(obj, int):
No: if type(obj) is type(1):
When checking if an object is a string, keep in mind that it might be a
unicode string too! In Python 2.3, str and unicode have a common base
class, basestring, so you can do:
if isinstance(obj, basestring):
In Python 2.2, the types module has the StringTypes type defined for
that purpose, e.g.:
from types import StringTypes
if isinstance(obj, StringTypes):
In Python 2.0 and 2.1, you should do:
from types import StringType, UnicodeType
if isinstance(obj, StringType) or \
isinstance(obj, UnicodeType) :
- For sequences, (strings, lists, tuples), use the fact that empty
sequences are false.
Yes: if not seq:
if seq:
No: if len(seq)
if not len(seq)
- Don't write string literals that rely on significant trailing
whitespace. Such trailing whitespace is visually indistinguishable and
some editors (or more recently, reindent.py) will trim them.
- Don't compare boolean values to True or False using ==
Yes: if greeting:
No: if greeting == True:
Worse: if greeting is True:
References
[1] PEP 7, Style Guide for C Code, van Rossum
[2] http://www.python.org/doc/essays/styleguide.html
[3] PEP 257, Docstring Conventions, Goodger, van Rossum
[4] http://www.wikipedia.com/wiki/CamelCase
[5] Barry's GNU Mailman style guide
http://barry.warsaw.us/software/STYLEGUIDE.txt
[6] PEP 20, The Zen of Python
[7] PEP 328, Imports: Multi-Line and Absolute/Relative
Copyright
This document has been placed in the public domain.
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