Indentation

Use 4 spaces per indentation level.

Continuation lines should align wrapped elements either vertically using Python’s implicit line joining inside parentheses, brackets and braces, or using a hanging indent 6. 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, it’s 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',
)

Tabs or Spaces?

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.

Maximum Line Length

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 Python’s 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 cannot use implicit continuation, so backslashes are acceptable:

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.

Should a Line Break Before or After a Binary Operator?

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 Knuth’s style is suggested.

Blank Lines

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.

Source File Encoding

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 z̯̯͡a̧͎̺l̡͓̫g̹̲o̡̼̘ 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 aren’t English).

Open source projects with a global audience are encouraged to adopt a similar policy.

Imports

• Imports should usually be on separate lines:

  # Correct:
  import os
  import sys
  

  # Wrong:
  import sys, os
  

  It’s okay to say this though:

  # Correct:
  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.

• Absolute imports are recommended, as they are usually more readable and tend to be better behaved (or at least give better error messages) if the import system is incorrectly configured (such as when a directory inside a package ends up on 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.

• 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 explicitly:

  import myclass
  import foo.bar.yourclass
  

  and use “myclass.MyClass” and “foo.bar.yourclass.YourClass”.

• Wildcard imports (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 isn’t known in advance).

  When republishing names this way, the guidelines below regarding public and internal interfaces still apply.

Module Level Dunder Names

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

Pet Peeves

Avoid extraneous whitespace in the following situations:

• Immediately inside parentheses, brackets or braces:

  # Correct:
  spam(ham[1], {eggs: 2})
  

  # Wrong:
  spam( ham[ 1 ], { eggs: 2 } )
  

• Between a trailing comma and a following close parenthesis:

  # Correct:
  foo = (0,)
  

  # Wrong:
  bar = (0, )
  

• Immediately before a comma, semicolon, or colon:

  # Correct:
  if x == 4: print x, y; x, y = y, x
  

  # Wrong:
  if x == 4 : print x , y ; x , y = y , x
  

• However, in a slice the colon acts like a binary operator, and should have equal amounts on either side (treating it as the operator with the lowest priority). In an extended slice, both colons must have the same amount of spacing applied. Exception: when a slice parameter is omitted, the space is omitted:

  # 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 : : upper]
  ham[ : upper]
  

• Immediately before the open parenthesis that starts the argument list of a function call:

  # Correct:
  spam(1)
  

  # Wrong:
  spam (1)
  

• Immediately before the open parenthesis that starts an indexing or slicing:

  # Correct:
  dct['key'] = lst[index]
  

  # Wrong:
  dct ['key'] = lst [index]
  

• More than one space around an assignment (or other) operator to align it with another:

  # Correct:
  x = 1
  y = 2
  long_variable = 3
  

  # Wrong:
  x             = 1
  y             = 2
  long_variable = 3
  

Other Recommendations

• Avoid trailing whitespace anywhere. Because it’s usually invisible, it can be confusing: e.g. a backslash followed by a space and a newline does not count as a line continuation marker. Some editors don’t preserve it and many projects (like CPython itself) have pre-commit hooks that reject it.
• 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).
• If operators with different priorities are used, consider adding whitespace around the operators with the lowest priority(ies). Use your own judgment; however, never use more than one space, and always have the same amount of whitespace on both sides of a binary operator:

  # 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)
  

• Function annotations should use the normal rules for colons and always have spaces around the -> 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: ...
  

• Don’t use spaces around the = 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): ...
  

• Compound statements (multiple statements on the same line) are generally discouraged:

  # 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()
  

• 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:

  # 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()
  

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.

• 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:

  """Return a foobang
  
  Optional plotz says to frobnicate the bizbaz first.
  """
  

• For one liner docstrings, please keep the closing """ on the same line:

  """Return an ex-parrot."""
  

Overriding Principle

Names that are visible to the user as public parts of the API should follow conventions that reflect usage rather than implementation.

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 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!)

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 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.

Prescriptive: Naming Conventions

from typing import TypeVar

VT_co = TypeVar('VT_co', covariant=True)
KT_contra = TypeVar('KT_contra', contravariant=True)

Public and Internal Interfaces

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 module’s API, such as os.path or a package’s __init__ module that exposes functionality from submodules.

Function Annotations

With the acceptance of PEP 484, the style rules for function annotations have changed.

• Function annotations should use PEP 484 syntax (There are some formatting recommendations for annotations in the previous section).
• The experimentation with annotation styles that was recommended previously in this PEP is no longer encouraged.
• However, outside the stdlib, experiments within the rules of PEP 484 are now encouraged. For example, marking up a large third party library or application with PEP 484 style type annotations, reviewing how easy it was to add those annotations, and observing whether their presence increases code understandability.
• The Python standard library should be conservative in adopting such annotations, but their use is allowed for new code and for big refactorings.
• For code that wants to make a different use of function annotations it is recommended to put a comment of the form:

  # 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.)

• Like linters, type checkers are optional, separate tools. Python interpreters by default should not issue any messages due to type checking and should not alter their behavior based on annotations.
• Users who don’t want to use type checkers are free to ignore them. However, it is expected that users of third party library packages may want to run type checkers over those packages. For this purpose PEP 484 recommends the use of stub files: .pyi files that are read by the type checker in preference of the corresponding .py files. Stub files can be distributed with a library, or separately (with the library author’s permission) through the typeshed repo 5.

Variable Annotations

PEP 526 introduced variable annotations. The style recommendations for them are similar to those on function annotations described above:

• Annotations for module level variables, class and instance variables, and local variables should have a single space after the colon.
• There should be no space before the colon.
• If an assignment has a right hand side, then the equality sign should have exactly one space on both sides:

  # 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
  

• Although the PEP 526 is accepted for Python 3.6, the variable annotation syntax is the preferred syntax for stub files on all versions of Python (see PEP 484 for details).

Footnotes

6

Hanging indentation is a type-setting style where all the lines in a paragraph are indented except the first line. In the context of Python, the term is used to describe a style where the opening parenthesis of a parenthesized statement is the last non-whitespace character of the line, with subsequent lines being indented until the closing parenthesis.