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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.
This document and PEP 257 (Docstring Conventions) were adapted from Guidos original Python Style Guide essay, with some additions from Barrys style guide [2].
This style guide evolves over time as additional conventions are identified and past conventions are rendered obsolete by changes in the language itself.
Many projects have their own coding style guidelines. In the event of any conflicts, such project-specific guides take precedence for that project.
One of Guidos 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 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 the most important.
However, know when to be inconsistent sometimes style guide recommendations just arent applicable. When in doubt, use your best judgment. Look at other examples and decide what looks best. And dont hesitate to ask!
In particular: do not break backwards compatibility just to comply with this PEP!
Some other good reasons to ignore a particular guideline:
Use 4 spaces per indentation level.
Continuation lines should align wrapped elements either vertically using Pythons implicit line joining inside parentheses, brackets and braces, or using a hanging indent [1]. When using a hanging indent the following should be considered; there should be no arguments on the first line and further indentation should be used to clearly distinguish itself as a continuation line:
# Correct:
# Aligned with opening delimiter.
foo = long_function_name(var_one, var_two,
var_three, var_four)
# Add 4 spaces (an extra level of indentation) to distinguish arguments from the rest.
def long_function_name(
var_one, var_two, var_three,
var_four):
print(var_one)
# Hanging indents should add a level.
foo = long_function_name(
var_one, var_two,
var_three, var_four)
# Wrong:
# Arguments on first line forbidden when not using vertical alignment.
foo = long_function_name(var_one, var_two,
var_three, var_four)
# Further indentation required as indentation is not distinguishable.
def long_function_name(
var_one, var_two, var_three,
var_four):
print(var_one)
The 4-space rule is optional for continuation lines.
Optional:
# Hanging indents *may* be indented to other than 4 spaces.
foo = long_function_name(
var_one, var_two,
var_three, var_four)
When the conditional part of an if-statement is long enough to require
that it be written across multiple lines, its worth noting that the
combination of a two character keyword (i.e. if), plus a single space,
plus an opening parenthesis creates a natural 4-space indent for the
subsequent lines of the multiline conditional. This can produce a visual
conflict with the indented suite of code nested inside the if-statement,
which would also naturally be indented to 4 spaces. This PEP takes no
explicit position on how (or whether) to further visually distinguish such
conditional lines from the nested suite inside the if-statement.
Acceptable options in this situation include, but are not limited to:
# No extra indentation.
if (this_is_one_thing and
that_is_another_thing):
do_something()
# Add a comment, which will provide some distinction in editors
# supporting syntax highlighting.
if (this_is_one_thing and
that_is_another_thing):
# Since both conditions are true, we can frobnicate.
do_something()
# Add some extra indentation on the conditional continuation line.
if (this_is_one_thing
and that_is_another_thing):
do_something()
(Also see the discussion of whether to break before or after binary operators below.)
The closing brace/bracket/parenthesis on multiline constructs may either line up under the first non-whitespace character of the last line of list, as in:
my_list = [
1, 2, 3,
4, 5, 6,
]
result = some_function_that_takes_arguments(
'a', 'b', 'c',
'd', 'e', 'f',
)
or it may be lined up under the first character of the line that starts the multiline construct, as in:
my_list = [
1, 2, 3,
4, 5, 6,
]
result = some_function_that_takes_arguments(
'a', 'b', 'c',
'd', 'e', 'f',
)
Spaces are the preferred indentation method.
Tabs should be used solely to remain consistent with code that is already indented with tabs.
Python disallows mixing tabs and spaces for indentation.
Limit all lines to a maximum of 79 characters.
For flowing long blocks of text with fewer structural restrictions (docstrings or comments), the line length should be limited to 72 characters.
Limiting the required editor window width makes it possible to have several files open side by side, and works well when using code review tools that present the two versions in adjacent columns.
The default wrapping in most tools disrupts the visual structure of the code, making it more difficult to understand. The limits are chosen to avoid wrapping in editors with the window width set to 80, even if the tool places a marker glyph in the final column when wrapping lines. Some web based tools may not offer dynamic line wrapping at all.
Some teams strongly prefer a longer line length. For code maintained exclusively or primarily by a team that can reach agreement on this issue, it is okay to increase the line length limit up to 99 characters, provided that comments and docstrings are still wrapped at 72 characters.
The Python standard library is conservative and requires limiting lines to 79 characters (and docstrings/comments to 72).
The preferred way of wrapping long lines is by using Pythons implied line continuation inside parentheses, brackets and braces. Long lines can be broken over multiple lines by wrapping expressions in parentheses. These should be used in preference to using a backslash for line continuation.
Backslashes may still be appropriate at times. For example, long,
multiple with-statements could not use implicit continuation
before Python 3.10, so backslashes were acceptable for that case:
with open('/path/to/some/file/you/want/to/read') as file_1, \
open('/path/to/some/file/being/written', 'w') as file_2:
file_2.write(file_1.read())
(See the previous discussion on multiline if-statements for further
thoughts on the indentation of such multiline with-statements.)
Another such case is with assert statements.
Make sure to indent the continued line appropriately.
For decades the recommended style was to break after binary operators. But this can hurt readability in two ways: the operators tend to get scattered across different columns on the screen, and each operator is moved away from its operand and onto the previous line. Here, the eye has to do extra work to tell which items are added and which are subtracted:
# Wrong:
# operators sit far away from their operands
income = (gross_wages +
taxable_interest +
(dividends - qualified_dividends) -
ira_deduction -
student_loan_interest)
To solve this readability problem, mathematicians and their publishers follow the opposite convention. Donald Knuth explains the traditional rule in his Computers and Typesetting series: Although formulas within a paragraph always break after binary operations and relations, displayed formulas always break before binary operations [3].
Following the tradition from mathematics usually results in more readable code:
# Correct:
# easy to match operators with operands
income = (gross_wages
+ taxable_interest
+ (dividends - qualified_dividends)
- ira_deduction
- student_loan_interest)
In Python code, it is permissible to break before or after a binary operator, as long as the convention is consistent locally. For new code Knuths style is suggested.
Surround top-level function and class definitions with two blank lines.
Method definitions inside a class are surrounded 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. Note, some editors and web-based code viewers may not recognize control-L as a form feed and will show another glyph in its place.
Code in the core Python distribution should always use UTF-8, and should not have an encoding declaration.
In the standard library, non-UTF-8 encodings should be used only for test purposes. Use non-ASCII characters sparingly, preferably only to denote places and human names. If using non-ASCII characters as data, avoid noisy Unicode characters like zalgo and byte order marks.
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 arent English).
Open source projects with a global audience are encouraged to adopt a similar policy.
# Correct:
import os
import sys
# Wrong:
import sys, os
Its okay to say this though:
# Correct:
from subprocess import Popen, PIPE
Imports should be grouped in the following order:
You should put a blank line between each group of imports.
sys.path):import mypkg.sibling
from mypkg import sibling
from mypkg.sibling import example
However, explicit relative imports are an acceptable alternative to absolute imports, especially when dealing with complex package layouts where using absolute imports would be unnecessarily verbose:
from . import sibling
from .sibling import example
Standard library code should avoid complex package layouts and always use absolute imports.
from myclass import MyClass
from foo.bar.yourclass import YourClass
If this spelling causes local name clashes, then spell them explicitly:
import myclass
import foo.bar.yourclass
and use myclass.MyClass and foo.bar.yourclass.YourClass.
from <module> import *) should be avoided, as
they make it unclear which names are present in the namespace,
confusing both readers and many automated tools. There is one
defensible use case for a wildcard import, which is to republish an
internal interface as part of a public API (for example, overwriting
a pure Python implementation of an interface with the definitions
from an optional accelerator module and exactly which definitions
will be overwritten isnt known in advance).When republishing names this way, the guidelines below regarding public and internal interfaces still apply.
Module level dunders (i.e. names with two leading and two trailing
underscores) such as __all__, __author__, __version__,
etc. should be placed after the module docstring but before any import
statements except from __future__ imports. Python mandates that
future-imports must appear in the module before any other code except
docstrings:
"""This is the example module.
This module does stuff.
"""
from __future__ import barry_as_FLUFL
__all__ = ['a', 'b', 'c']
__version__ = '0.1'
__author__ = 'Cardinal Biggles'
import os
import sys
In Python, single-quoted strings and double-quoted strings are the same. This PEP does not make a recommendation for this. Pick a rule and stick to it. When a string contains single or double quote characters, however, use the other one to avoid backslashes in the string. It improves readability.
For triple-quoted strings, always use double quote characters to be consistent with the docstring convention in PEP 257.
Avoid extraneous whitespace in the following situations:
# Correct:
spam(ham[1], {eggs: 2})
# Wrong:
spam( ham[ 1 ], { eggs: 2 } )
# Correct:
foo = (0,)
# Wrong:
bar = (0, )
# Correct:
if x == 4: print(x, y); x, y = y, x
# Wrong:
if x == 4 : print(x , y) ; x , y = y , x
# Correct:
ham[1:9], ham[1:9:3], ham[:9:3], ham[1::3], ham[1:9:]
ham[lower:upper], ham[lower:upper:], ham[lower::step]
ham[lower+offset : upper+offset]
ham[: upper_fn(x) : step_fn(x)], ham[:: step_fn(x)]
ham[lower + offset : upper + offset]
# Wrong:
ham[lower + offset:upper + offset]
ham[1: 9], ham[1 :9], ham[1:9 :3]
ham[lower : : step]
ham[ : upper]
# Correct:
spam(1)
# Wrong:
spam (1)
# Correct:
dct['key'] = lst[index]
# Wrong:
dct ['key'] = lst [index]
# Correct:
x = 1
y = 2
long_variable = 3
# Wrong:
x = 1
y = 2
long_variable = 3
=), augmented assignment (+=, -=
etc.), comparisons (==, <, >, !=, <=, >=, in,
not in, is, is not), Booleans (and, or, not).# Correct:
i = i + 1
submitted += 1
x = x*2 - 1
hypot2 = x*x + y*y
c = (a+b) * (a-b)
# Wrong:
i=i+1
submitted +=1
x = x * 2 - 1
hypot2 = x * x + y * y
c = (a + b) * (a - b)
-> arrow if present. (See
Function Annotations below for more about function annotations.):# Correct:
def munge(input: AnyStr): ...
def munge() -> PosInt: ...
# Wrong:
def munge(input:AnyStr): ...
def munge()->PosInt: ...
= sign when used to indicate a
keyword argument, or when used to indicate a default value for an
unannotated function parameter:# Correct:
def complex(real, imag=0.0):
return magic(r=real, i=imag)
# Wrong:
def complex(real, imag = 0.0):
return magic(r = real, i = imag)
When combining an argument annotation with a default value, however, do use
spaces around the = sign:
# Correct:
def munge(sep: AnyStr = None): ...
def munge(input: AnyStr, sep: AnyStr = None, limit=1000): ...
# Wrong:
def munge(input: AnyStr=None): ...
def munge(input: AnyStr, limit = 1000): ...
# Correct:
if foo == 'blah':
do_blah_thing()
do_one()
do_two()
do_three()
Rather not:
# Wrong:
if foo == 'blah': do_blah_thing()
do_one(); do_two(); do_three()
Rather not:
# Wrong:
if foo == 'blah': do_blah_thing()
for x in lst: total += x
while t < 10: t = delay()
Definitely not:
# Wrong:
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()
Trailing commas are usually optional, except they are mandatory when making a tuple of one element. For clarity, it is recommended to surround the latter in (technically redundant) parentheses:
# Correct:
FILES = ('setup.cfg',)
# Wrong:
FILES = 'setup.cfg',
When trailing commas are redundant, they are often helpful when a version control system is used, when a list of values, arguments or imported items is expected to be extended over time. The pattern is to put each value (etc.) on a line by itself, always adding a trailing comma, and add the close parenthesis/bracket/brace on the next line. However it does not make sense to have a trailing comma on the same line as the closing delimiter (except in the above case of singleton tuples):
# Correct:
FILES = [
'setup.cfg',
'tox.ini',
]
initialize(FILES,
error=True,
)
# Wrong:
FILES = ['setup.cfg', 'tox.ini',]
initialize(FILES, error=True,)
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. The first word should be capitalized, unless it is an identifier that begins with a lower case letter (never alter the case of identifiers!).
Block comments generally consist of one or more paragraphs built out of complete sentences, with each sentence ending in a period.
You should use one or two spaces after a sentence-ending period in multi-sentence comments, except after the final sentence.
Ensure that your comments are clear and easily understandable to other speakers of the language you are writing in.
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 dont speak your language.
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 #.
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. Dont do this:
x = x + 1 # Increment x
But sometimes, this is useful:
x = x + 1 # Compensate for border
Conventions for writing good documentation strings (a.k.a. docstrings) are immortalized in PEP 257.
def line.""" that ends a multiline docstring should be
on a line by itself:"""Return a foobang
Optional plotz says to frobnicate the bizbaz first.
"""
""" on
the same line:"""Return an ex-parrot."""
The naming conventions of Pythons library are a bit of a mess, so well 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.
Names that are visible to the user as public parts of the API should follow conventions that reflect usage rather than implementation.
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)lowercaselower_case_with_underscoresUPPERCASEUPPER_CASE_WITH_UNDERSCORESCapitalizedWords (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 acronyms in CapWords, capitalize all the letters of the acronym. Thus HTTPServerError is better than HttpServerError.
mixedCase (differs from CapitalizedWords by initial lowercase
character!)Capitalized_Words_With_Underscores (ugly!)Theres 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 names start
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.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.
Identifiers used in the standard library must be ASCII compatible as described in the policy section of PEP 3131.
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.
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 should normally use the CapWords convention.
The naming convention for functions may be used instead in cases where the interface is documented and used primarily as a callable.
Note that there is a separate convention for builtin names: most builtin names are single words (or two words run together), with the CapWords convention used only for exception names and builtin constants.
Names of type variables introduced in PEP 484 should normally use CapWords
preferring short names: T, AnyStr, Num. It is recommended to add
suffixes _co or _contra to the variables used to declare covariant
or contravariant behavior correspondingly:
from typing import TypeVar
VT_co = TypeVar('VT_co', covariant=True)
KT_contra = TypeVar('KT_contra', contravariant=True)
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).
(Lets 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 should be lowercase, with words separated by underscores as necessary to improve readability.
Variable names follow the same convention as function names.
mixedCase is allowed only in contexts where thats already the prevailing style (e.g. threading.py), to retain backwards compatibility.
Always use self for the first argument to instance methods.
Always use cls for the first argument to class methods.
If a function arguments 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 class_ is better
than clss. (Perhaps better is to avoid such clashes by using a
synonym.)
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 Pythons 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 are usually defined on a module level and written in all
capital letters with underscores separating words. Examples include
MAX_OVERFLOW and TOTAL.
Always decide whether a classs methods and instance variables (collectively: attributes) should be public or non-public. If in doubt, choose non-public; its 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 backwards 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 wont change or even be removed.
We dont 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 classs 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:
Note 1: See the argument name recommendation above for class methods.
Note 1: Try to keep the functional behavior side-effect free, although side-effects such as caching are generally fine.
Note 2: Avoid using properties for computationally expensive operations; the attribute notation makes the caller believe that access is (relatively) cheap.
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.
Any backwards compatibility guarantees apply only to public interfaces. Accordingly, it is important that users be able to clearly distinguish between public and internal interfaces.
Documented interfaces are considered public, unless the documentation explicitly declares them to be provisional or internal interfaces exempt from the usual backwards compatibility guarantees. All undocumented interfaces should be assumed to be internal.
To better support introspection, modules should explicitly declare the
names in their public API using the __all__ attribute. Setting
__all__ to an empty list indicates that the module has no public API.
Even with __all__ set appropriately, internal interfaces (packages,
modules, classes, functions, attributes or other names) should still be
prefixed with a single leading underscore.
An interface is also considered internal if any containing namespace (package, module or class) is considered internal.
Imported names should always be considered an implementation detail.
Other modules must not rely on indirect access to such imported names
unless they are an explicitly documented part of the containing modules
API, such as os.path or a packages __init__ module that exposes
functionality from submodules.
For example, do not rely on CPythons efficient implementation of
in-place string concatenation for statements in the form a += b
or a = a + b. This optimization is fragile even in CPython (it
only works for some types) and isnt present at all in implementations
that dont use refcounting. 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.
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!
is not operator rather than not ... is. While both
expressions are functionally identical, the former is more readable
and preferred:# Correct:
if foo is not None:
# Wrong:
if not foo is None:
__eq__, __ne__,
__lt__, __le__, __gt__, __ge__) rather than relying
on other code to only exercise a particular comparison.To minimize the effort involved, the functools.total_ordering()
decorator provides a tool to generate missing comparison methods.
PEP 207 indicates that reflexivity rules are assumed by Python.
Thus, the interpreter may swap y > x with x < y, y >= x
with x <= y, and may swap the arguments of x == y and x !=
y. The sort() and min() operations are guaranteed to use
the < operator and the max() function uses the >
operator. However, it is best to implement all six operations so
that confusion doesnt arise in other contexts.
# Correct:
def f(x): return 2*x
# Wrong:
f = lambda x: 2*x
The first form means that the name of the resulting function object is specifically f instead of the generic <lambda>. This is more useful for tracebacks and string representations in general. The use of the assignment statement eliminates the sole benefit a lambda expression can offer over an explicit def statement (i.e. that it can be embedded inside a larger expression)
Exception rather than BaseException.
Direct inheritance from BaseException is reserved for exceptions
where catching them is almost always the wrong thing to do.Design exception hierarchies based on the distinctions that code catching the exceptions is likely to need, rather than the locations where the exceptions are raised. Aim to answer the question What went wrong? programmatically, rather than only stating that A problem occurred (see PEP 3151 for an example of this lesson being learned for the builtin exception hierarchy)
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 that are used for non-local flow control or other forms of signaling need no special suffix.
raise X from Y
should be used to indicate explicit replacement without losing the
original traceback.When deliberately replacing an inner exception (using raise X from
None), ensure that relevant details are transferred to the new
exception (such as preserving the attribute name when converting
KeyError to AttributeError, or embedding the text of the original
exception in the new exception message).
except: clause: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: (bare except is equivalent to except
BaseException:).
A good rule of thumb is to limit use of bare except clauses to two cases:
raise. try...finally
can be a better way to handle this case.errno
values.try clause
to the absolute minimum amount of code necessary. Again, this
avoids masking bugs:# Correct:
try:
value = collection[key]
except KeyError:
return key_not_found(key)
else:
return handle_value(value)
# Wrong:
try:
# Too broad!
return handle_value(collection[key])
except KeyError:
# Will also catch KeyError raised by handle_value()
return key_not_found(key)
with statement to ensure it is cleaned up promptly and reliably
after use. A try/finally statement is also acceptable.# Correct:
with conn.begin_transaction():
do_stuff_in_transaction(conn)
# Wrong:
with conn:
do_stuff_in_transaction(conn)
The latter example doesnt provide any information to indicate that
the __enter__ and __exit__ methods are doing something other
than closing the connection after a transaction. Being explicit is
important in this case.
return
None, and an explicit return statement should be present at the
end of the function (if reachable):# Correct:
def foo(x):
if x >= 0:
return math.sqrt(x)
else:
return None
def bar(x):
if x < 0:
return None
return math.sqrt(x)
# Wrong:
def foo(x):
if x >= 0:
return math.sqrt(x)
def bar(x):
if x < 0:
return
return math.sqrt(x)
''.startswith() and ''.endswith() instead of string
slicing to check for prefixes or suffixes.startswith() and endswith() are cleaner and less error prone:
# Correct:
if foo.startswith('bar'):
# Wrong:
if foo[:3] == 'bar':
# Correct:
if isinstance(obj, int):
# Wrong:
if type(obj) is type(1):
# Correct:
if not seq:
if seq:
# Wrong:
if len(seq):
if not len(seq):
==:# Correct:
if greeting:
# Wrong:
if greeting == True:
Worse:
# Wrong:
if greeting is True:
return/break/continue
within the finally suite of a try...finally, where the flow control
statement would jump outside the finally suite, is discouraged. This
is because such statements will implicitly cancel any active exception
that is propagating through the finally suite:# Wrong:
def foo():
try:
1 / 0
finally:
return 42
With the acceptance of PEP 484, the style rules for function annotations have changed.
# type: ignore
near the top of the file; this tells type checkers to ignore all annotations. (More fine-grained ways of disabling complaints from type checkers can be found in PEP 484.)
PEP 526 introduced variable annotations. The style recommendations for them are similar to those on function annotations described above:
# Correct:
code: int
class Point:
coords: Tuple[int, int]
label: str = '<unknown>'
# Wrong:
code:int # No space after colon
code : int # Space before colon
class Test:
result: int=0 # No spaces around equality sign
Footnotes
This document has been placed in the public domain.
Source: https://github.com/python/peps/blob/main/peps/pep-0008.rst
Last modified: 2025-04-04 00:19:04 UTC
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