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The uncompromising Python code formatter
A tool that automatically formats Python code to conform to the PEP 8 style guide.
A tool (and pre-commit hook) to automatically upgrade syntax for newer versions of the language.
Simple Python style checker in one Python file
Quick Overview
YAPF (Yet Another Python Formatter) is a code formatter for Python developed by Google. It aims to produce consistently formatted Python code that adheres to style guidelines, with a focus on readability and minimal changes to the original code structure.
Pros
- Highly configurable, allowing users to customize formatting rules
- Supports multiple Python versions (2.7 and 3.6+)
- Can be integrated into various text editors and IDEs
- Preserves the semantic meaning of the code while reformatting
Cons
- May sometimes produce unexpected formatting results
- Can be slower than some other Python formatters
- Occasional conflicts with other linting tools
- Limited support for formatting comments
Code Examples
- Basic usage:
# Before formatting
def long_function_name(
var_one, var_two, var_three,
var_four):
print(var_one)
# After formatting with YAPF
def long_function_name(var_one, var_two, var_three, var_four):
print(var_one)
- Handling complex expressions:
# Before formatting
x = { 'a':37,'b':42,
'c':927}
# After formatting with YAPF
x = {'a': 37, 'b': 42, 'c': 927}
- Formatting function calls:
# Before formatting
result = some_function_that_takes_arguments(
'a', 'b', 'c',
'd', 'e', 'f',
)
# After formatting with YAPF
result = some_function_that_takes_arguments('a', 'b', 'c', 'd', 'e', 'f')
Getting Started
To use YAPF, first install it using pip:
pip install yapf
Then, you can format a Python file using the command line:
yapf -i your_file.py
For in-editor usage, many popular text editors and IDEs have YAPF integration available through plugins or extensions. Configure your editor to run YAPF on save or on-demand for seamless code formatting.
Competitor Comparisons
The uncompromising Python code formatter
Pros of Black
- Faster execution time, especially for large codebases
- Stricter formatting rules, leading to more consistent code across projects
- Wider adoption in the Python community, with integration in many popular tools
Cons of Black
- Less configurable, with fewer options for customization
- May produce less readable code in some cases due to its strict line length limit
- Can be more aggressive in reformatting, potentially causing larger diffs in version control
Code Comparison
Black formatting:
def long_function_name(
var_one: int, var_two: str, var_three: float, var_four: bool
) -> None:
print(f"{var_one} {var_two} {var_three} {var_four}")
YAPF formatting:
def long_function_name(var_one: int,
var_two: str,
var_three: float,
var_four: bool) -> None:
print(f"{var_one} {var_two} {var_three} {var_four}")
Both formatters aim to improve code readability, but they have different approaches. Black focuses on simplicity and consistency, while YAPF offers more flexibility in configuration. The choice between them often depends on project requirements and team preferences.
A tool that automatically formats Python code to conform to the PEP 8 style guide.
Pros of autopep8
- More configurable with a wide range of options
- Follows PEP 8 guidelines more strictly
- Can be used as a library in other Python projects
Cons of autopep8
- Slower performance on large codebases
- Less aggressive in reformatting, may require multiple passes
- Limited support for newer Python syntax features
Code Comparison
autopep8:
def example_function(arg1, arg2,arg3):
result = arg1+arg2+arg3
return result
After autopep8:
def example_function(arg1, arg2, arg3):
result = arg1 + arg2 + arg3
return result
YAPF:
def example_function(arg1, arg2,arg3):
result = arg1+arg2+arg3
return result
After YAPF:
def example_function(arg1, arg2, arg3):
result = arg1 + arg2 + arg3
return result
Both tools effectively format the code, but YAPF may be more aggressive in restructuring complex expressions and maintaining consistent style across different code structures. autopep8 focuses more on adhering to PEP 8 guidelines and offers more granular control over formatting options.
A tool (and pre-commit hook) to automatically upgrade syntax for newer versions of the language.
Pros of pyupgrade
- Focuses on upgrading Python syntax to newer versions
- Handles specific syntax upgrades like f-strings and set literals
- Lightweight and fast execution
Cons of pyupgrade
- Limited scope compared to YAPF's comprehensive formatting
- Doesn't address overall code style or formatting issues
- May require additional tools for complete code formatting
Code Comparison
pyupgrade:
# Before
x = '{}'.format(42)
# After
x = f'{42}'
YAPF:
# Before
x='{}'.format(42)
# After
x = '{}'.format(42)
Key Differences
- pyupgrade focuses on upgrading Python syntax to newer versions, while YAPF is a comprehensive code formatter
- YAPF aims to maintain consistent style across entire codebases, whereas pyupgrade targets specific syntax improvements
- pyupgrade is more specialized and lightweight, while YAPF offers broader formatting capabilities
Use Cases
- Use pyupgrade when specifically looking to modernize Python syntax
- Choose YAPF for comprehensive code formatting and style consistency
- Consider using both tools in combination for thorough code improvement
Simple Python style checker in one Python file
Pros of pycodestyle
- Lightweight and focused solely on style checking
- Widely adopted and integrated into many development workflows
- Highly configurable with numerous options for customization
Cons of pycodestyle
- Does not automatically format code; only reports issues
- Less comprehensive in scope compared to YAPF's formatting capabilities
- May require additional tools for complete code formatting
Code Comparison
pycodestyle (style checking):
def example_function(param1,param2):
return param1+param2
YAPF (automatic formatting):
def example_function(param1, param2):
return param1 + param2
pycodestyle would report style issues in the first example, while YAPF would automatically format the code to match the second example.
Summary
pycodestyle is a lightweight, widely-adopted style checker that focuses on identifying style issues in Python code. It's highly configurable but doesn't automatically format code. YAPF, on the other hand, is a more comprehensive tool that not only checks but also automatically formats Python code according to a set of predefined or custom style rules. While pycodestyle is excellent for style checking, YAPF provides a more complete solution for maintaining consistent code formatting across projects.
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YAPF
Introduction
YAPF is a Python formatter based on clang-format
(developed by Daniel Jasper). In essence, the algorithm takes the code and
calculates the best formatting that conforms to the configured style. It takes
away a lot of the drudgery of maintaining your code.
The ultimate goal is that the code YAPF produces is as good as the code that a programmer would write if they were following the style guide.
Note YAPF is not an official Google product (experimental or otherwise), it is just code that happens to be owned by Google.
Installation
To install YAPF from PyPI:
$ pip install yapf
YAPF is still considered in "beta" stage, and the released version may change often; therefore, the best way to keep up-to-date with the latest development is to clone this repository or install directly from github:
$ pip install git+https://github.com/google/yapf.git
Note that if you intend to use YAPF as a command-line tool rather than as a
library, installation is not necessary. YAPF supports being run as a directory
by the Python interpreter. If you cloned/unzipped YAPF into DIR
, it's
possible to run:
$ PYTHONPATH=DIR python DIR/yapf [options] ...
Using YAPF within your favorite editor
YAPF is supported by multiple editors via community extensions or plugins. See Editor Support for more info.
Required Python versions
YAPF supports Python 3.7+.
Usage
usage: yapf [-h] [-v] [-d | -i | -q] [-r | -l START-END] [-e PATTERN]
[--style STYLE] [--style-help] [--no-local-style] [-p] [-m] [-vv]
[files ...]
Formatter for Python code.
positional arguments:
files reads from stdin when no files are specified.
optional arguments:
-h, --help show this help message and exit
-v, --version show program's version number and exit
-d, --diff print the diff for the fixed source
-i, --in-place make changes to files in place
-q, --quiet output nothing and set return value
-r, --recursive run recursively over directories
-l START-END, --lines START-END
range of lines to reformat, one-based
-e PATTERN, --exclude PATTERN
patterns for files to exclude from formatting
--style STYLE specify formatting style: either a style name (for
example "pep8" or "google"), or the name of a file
with style settings. The default is pep8 unless a
.style.yapf or setup.cfg or pyproject.toml file
located in the same directory as the source or one of
its parent directories (for stdin, the current
directory is used).
--style-help show style settings and exit; this output can be saved
to .style.yapf to make your settings permanent
--no-local-style don't search for local style definition
-p, --parallel run YAPF in parallel when formatting multiple files.
-m, --print-modified print out file names of modified files
-vv, --verbose print out file names while processing
Return Codes
Normally YAPF returns zero on successful program termination and non-zero otherwise.
If --diff
is supplied, YAPF returns zero when no changes were necessary,
non-zero otherwise (including program error). You can use this in a CI workflow
to test that code has been YAPF-formatted.
Excluding files from formatting (.yapfignore or pyproject.toml)
In addition to exclude patterns provided on commandline, YAPF looks for
additional patterns specified in a file named .yapfignore
or pyproject.toml
located in the working directory from which YAPF is invoked.
.yapfignore
's syntax is similar to UNIX's filename pattern matching:
* matches everything
? matches any single character
[seq] matches any character in seq
[!seq] matches any character not in seq
Note that no entry should begin with ./
.
If you use pyproject.toml
, exclude patterns are specified by ignore_patterns
key
in [tool.yapfignore]
section. For example:
[tool.yapfignore]
ignore_patterns = [
"temp/**/*.py",
"temp2/*.py"
]
Formatting style
The formatting style used by YAPF is configurable and there are many "knobs"
that can be used to tune how YAPF does formatting. See the style.py
module
for the full list.
To control the style, run YAPF with the --style
argument. It accepts one of
the predefined styles (e.g., pep8
or google
), a path to a configuration
file that specifies the desired style, or a dictionary of key/value pairs.
The config file is a simple listing of (case-insensitive) key = value
pairs
with a [style]
heading. For example:
[style]
based_on_style = pep8
spaces_before_comment = 4
split_before_logical_operator = true
The based_on_style
setting determines which of the predefined styles this
custom style is based on (think of it like subclassing). Four
styles are predefined:
pep8
(default)google
(based off of the Google Python Style Guide)yapf
(for use with Google open source projects)facebook
See _STYLE_NAME_TO_FACTORY
in style.py
for details.
It's also possible to do the same on the command line with a dictionary. For example:
--style='{based_on_style: pep8, indent_width: 2}'
This will take the pep8
base style and modify it to have two space
indentations.
YAPF will search for the formatting style in the following manner:
- Specified on the command line
- In the
[style]
section of a.style.yapf
file in either the current directory or one of its parent directories. - In the
[yapf]
section of asetup.cfg
file in either the current directory or one of its parent directories. - In the
[tool.yapf]
section of apyproject.toml
file in either the current directory or one of its parent directories. - In the
[style]
section of a~/.config/yapf/style
file in your home directory.
If none of those files are found, the default style PEP8 is used.
Example
An example of the type of formatting that YAPF can do, it will take this ugly code:
x = { 'a':37,'b':42,
'c':927}
y = 'hello ''world'
z = 'hello '+'world'
a = 'hello {}'.format('world')
class foo ( object ):
def f (self ):
return 37*-+2
def g(self, x,y=42):
return y
def f ( a ) :
return 37+-+a[42-x : y**3]
and reformat it into:
x = {'a': 37, 'b': 42, 'c': 927}
y = 'hello ' 'world'
z = 'hello ' + 'world'
a = 'hello {}'.format('world')
class foo(object):
def f(self):
return 37 * -+2
def g(self, x, y=42):
return y
def f(a):
return 37 + -+a[42 - x:y**3]
Example as a module
The two main APIs for calling YAPF are FormatCode
and FormatFile
, these
share several arguments which are described below:
>>> from yapf.yapflib.yapf_api import FormatCode # reformat a string of code
>>> formatted_code, changed = FormatCode("f ( a = 1, b = 2 )")
>>> formatted_code
'f(a=1, b=2)\n'
>>> changed
True
A style_config
argument: Either a style name or a path to a file that
contains formatting style settings. If None is specified, use the default style
as set in style.DEFAULT_STYLE_FACTORY
.
>>> FormatCode("def g():\n return True", style_config='pep8')[0]
'def g():\n return True\n'
A lines
argument: A list of tuples of lines (ints), [start, end], that we
want to format. The lines are 1-based indexed. It can be used by third-party
code (e.g., IDEs) when reformatting a snippet of code rather than a whole file.
>>> FormatCode("def g( ):\n a=1\n b = 2\n return a==b", lines=[(1, 1), (2, 3)])[0]
'def g():\n a = 1\n b = 2\n return a==b\n'
A print_diff
(bool): Instead of returning the reformatted source, return a
diff that turns the formatted source into reformatted source.
>>> print(FormatCode("a==b", filename="foo.py", print_diff=True)[0])
--- foo.py (original)
+++ foo.py (reformatted)
@@ -1 +1 @@
-a==b
+a == b
Note: the filename
argument for FormatCode
is what is inserted into the
diff, the default is <unknown>
.
FormatFile
returns reformatted code from the passed file along with its encoding:
>>> from yapf.yapflib.yapf_api import FormatFile # reformat a file
>>> print(open("foo.py").read()) # contents of file
a==b
>>> reformatted_code, encoding, changed = FormatFile("foo.py")
>>> formatted_code
'a == b\n'
>>> encoding
'utf-8'
>>> changed
True
The in_place
argument saves the reformatted code back to the file:
>>> FormatFile("foo.py", in_place=True)[:2]
(None, 'utf-8')
>>> print(open("foo.py").read()) # contents of file (now fixed)
a == b
Formatting diffs
Options:
usage: yapf-diff [-h] [-i] [-p NUM] [--regex PATTERN] [--iregex PATTERN][-v]
[--style STYLE] [--binary BINARY]
This script reads input from a unified diff and reformats all the changed
lines. This is useful to reformat all the lines touched by a specific patch.
Example usage for git/svn users:
git diff -U0 --no-color --relative HEAD^ | yapf-diff -i
svn diff --diff-cmd=diff -x-U0 | yapf-diff -p0 -i
It should be noted that the filename contained in the diff is used
unmodified to determine the source file to update. Users calling this script
directly should be careful to ensure that the path in the diff is correct
relative to the current working directory.
optional arguments:
-h, --help show this help message and exit
-i, --in-place apply edits to files instead of displaying a diff
-p NUM, --prefix NUM strip the smallest prefix containing P slashes
--regex PATTERN custom pattern selecting file paths to reformat
(case sensitive, overrides -iregex)
--iregex PATTERN custom pattern selecting file paths to reformat
(case insensitive, overridden by -regex)
-v, --verbose be more verbose, ineffective without -i
--style STYLE specify formatting style: either a style name (for
example "pep8" or "google"), or the name of a file
with style settings. The default is pep8 unless a
.style.yapf or setup.cfg or pyproject.toml file
located in the same directory as the source or one of
its parent directories (for stdin, the current
directory is used).
--binary BINARY location of binary to use for YAPF
Python features not yet supported
- Python 3.12 â PEP 695 â Type Parameter Syntax â YAPF #1170
- Python 3.12 â PEP 701 â Syntactic formalization of f-strings â YAPF #1136
Knobs
ALIGN_CLOSING_BRACKET_WITH_VISUAL_INDENT
Align closing bracket with visual indentation.
ALLOW_MULTILINE_LAMBDAS
Allow lambdas to be formatted on more than one line.
ALLOW_MULTILINE_DICTIONARY_KEYS
Allow dictionary keys to exist on multiple lines. For example:
x = {
('this is the first element of a tuple',
'this is the second element of a tuple'):
value,
}
ALLOW_SPLIT_BEFORE_DEFAULT_OR_NAMED_ASSIGNS
Allow splitting before a default / named assignment in an argument list.
ALLOW_SPLIT_BEFORE_DICT_VALUE
Allow splits before the dictionary value.
ARITHMETIC_PRECEDENCE_INDICATION
Let spacing indicate operator precedence. For example:
a = 1 * 2 + 3 / 4
b = 1 / 2 - 3 * 4
c = (1 + 2) * (3 - 4)
d = (1 - 2) / (3 + 4)
e = 1 * 2 - 3
f = 1 + 2 + 3 + 4
will be formatted as follows to indicate precedence:
a = 1*2 + 3/4
b = 1/2 - 3*4
c = (1+2) * (3-4)
d = (1-2) / (3+4)
e = 1*2 - 3
f = 1 + 2 + 3 + 4
BLANK_LINES_AROUND_TOP_LEVEL_DEFINITION
Sets the number of desired blank lines surrounding top-level function and class definitions. For example:
class Foo:
pass
# <------ having two blank lines here
# <------ is the default setting
class Bar:
pass
BLANK_LINE_BEFORE_CLASS_DOCSTRING
Insert a blank line before a class-level docstring.
BLANK_LINE_BEFORE_MODULE_DOCSTRING
Insert a blank line before a module docstring.
BLANK_LINE_BEFORE_NESTED_CLASS_OR_DEF
Insert a blank line before a
def
orclass
immediately nested within anotherdef
orclass
. For example:
class Foo:
# <------ this blank line
def method():
pass
BLANK_LINES_BETWEEN_TOP_LEVEL_IMPORTS_AND_VARIABLES
Sets the number of desired blank lines between top-level imports and variable definitions. Useful for compatibility with tools like isort.
COALESCE_BRACKETS
Do not split consecutive brackets. Only relevant when
DEDENT_CLOSING_BRACKETS
orINDENT_CLOSING_BRACKETS
is set. For example:
call_func_that_takes_a_dict(
{
'key1': 'value1',
'key2': 'value2',
}
)
would reformat to:
call_func_that_takes_a_dict({
'key1': 'value1',
'key2': 'value2',
})
COLUMN_LIMIT
The column limit (or max line-length)
CONTINUATION_ALIGN_STYLE
The style for continuation alignment. Possible values are:
SPACE
: Use spaces for continuation alignment. This is default behavior.FIXED
: Use fixed number (CONTINUATION_INDENT_WIDTH
) of columns (i.e.CONTINUATION_INDENT_WIDTH
/INDENT_WIDTH
tabs orCONTINUATION_INDENT_WIDTH
spaces) for continuation alignment.VALIGN-RIGHT
: Vertically align continuation lines to multiple ofINDENT_WIDTH
columns. Slightly right (one tab or a few spaces) if cannot vertically align continuation lines with indent characters.
CONTINUATION_INDENT_WIDTH
Indent width used for line continuations.
DEDENT_CLOSING_BRACKETS
Put closing brackets on a separate line, dedented, if the bracketed expression can't fit in a single line. Applies to all kinds of brackets, including function definitions and calls. For example:
config = {
'key1': 'value1',
'key2': 'value2',
} # <--- this bracket is dedented and on a separate line
time_series = self.remote_client.query_entity_counters(
entity='dev3246.region1',
key='dns.query_latency_tcp',
transform=Transformation.AVERAGE(window=timedelta(seconds=60)),
start_ts=now()-timedelta(days=3),
end_ts=now(),
) # <--- this bracket is dedented and on a separate line
DISABLE_ENDING_COMMA_HEURISTIC
Disable the heuristic which places each list element on a separate line if the list is comma-terminated.
Note: The behavior of this flag changed in v0.40.3. Before, if this flag was true, we would split lists that contained a trailing comma or a comment. Now, we have a separate flag,
DISABLE_SPLIT_LIST_WITH_COMMENT
, that controls splitting when a list contains a comment. To get the old behavior, set both flags to true. More information in CHANGELOG.md.
DISABLE_SPLIT_LIST_WITH_COMMENT
Don't put every element on a new line within a list that contains interstitial comments.
Without this flag (default):
[ a, b, # c ]
With this flag:
[ a, b, # c ]
This mirrors the behavior of clang-format and is useful for forming "logical groups" of elements in a list. It also works in function declarations.
EACH_DICT_ENTRY_ON_SEPARATE_LINE
Place each dictionary entry onto its own line.
FORCE_MULTILINE_DICT
Respect
EACH_DICT_ENTRY_ON_SEPARATE_LINE
even if the line is shorter thanCOLUMN_LIMIT
.
I18N_COMMENT
The regex for an internationalization comment. The presence of this comment stops reformatting of that line, because the comments are required to be next to the string they translate.
I18N_FUNCTION_CALL
The internationalization function call names. The presence of this function stops reformatting on that line, because the string it has cannot be moved away from the i18n comment.
INDENT_BLANK_LINES
Set to
True
to prefer indented blank lines rather than empty
INDENT_CLOSING_BRACKETS
Put closing brackets on a separate line, indented, if the bracketed expression can't fit in a single line. Applies to all kinds of brackets, including function definitions and calls. For example:
config = {
'key1': 'value1',
'key2': 'value2',
} # <--- this bracket is indented and on a separate line
time_series = self.remote_client.query_entity_counters(
entity='dev3246.region1',
key='dns.query_latency_tcp',
transform=Transformation.AVERAGE(window=timedelta(seconds=60)),
start_ts=now()-timedelta(days=3),
end_ts=now(),
) # <--- this bracket is indented and on a separate line
INDENT_DICTIONARY_VALUE
Indent the dictionary value if it cannot fit on the same line as the dictionary key. For example:
config = {
'key1':
'value1',
'key2': value1 +
value2,
}
INDENT_WIDTH
The number of columns to use for indentation.
JOIN_MULTIPLE_LINES
Join short lines into one line. E.g., single line
if
statements.
NO_SPACES_AROUND_SELECTED_BINARY_OPERATORS
Do not include spaces around selected binary operators. For example:
1 + 2 * 3 - 4 / 5
will be formatted as follows when configured with
*
,/
:
1 + 2*3 - 4/5
SPACE_BETWEEN_ENDING_COMMA_AND_CLOSING_BRACKET
Insert a space between the ending comma and closing bracket of a list, etc.
SPACE_INSIDE_BRACKETS
Use spaces inside brackets, braces, and parentheses. For example:
method_call( 1 )
my_dict[ 3 ][ 1 ][ get_index( *args, **kwargs ) ]
my_set = { 1, 2, 3 }
SPACES_AROUND_DEFAULT_OR_NAMED_ASSIGN
Set to
True
to prefer spaces around the assignment operator for default or keyword arguments.
SPACES_AROUND_DICT_DELIMITERS
Adds a space after the opening '{' and before the ending '}' dict delimiters.
{1: 2}
will be formatted as:
{ 1: 2 }
SPACES_AROUND_LIST_DELIMITERS
Adds a space after the opening '[' and before the ending ']' list delimiters.
[1, 2]
will be formatted as:
[ 1, 2 ]
SPACES_AROUND_POWER_OPERATOR
Set to
True
to prefer using spaces around**
.
SPACES_AROUND_SUBSCRIPT_COLON
Use spaces around the subscript / slice operator. For example:
my_list[1 : 10 : 2]
SPACES_AROUND_TUPLE_DELIMITERS
Adds a space after the opening '(' and before the ending ')' tuple delimiters.
(1, 2, 3)
will be formatted as:
( 1, 2, 3 )
SPACES_BEFORE_COMMENT
The number of spaces required before a trailing comment. This can be a single value (representing the number of spaces before each trailing comment) or list of values (representing alignment column values; trailing comments within a block will be aligned to the first column value that is greater than the maximum line length within the block).
Note: Lists of values may need to be quoted in some contexts (eg. shells or editor config files).
For example, with
spaces_before_comment=5
:
1 + 1 # Adding values
will be formatted as:
1 + 1 # Adding values <-- 5 spaces between the end of the statement and comment
with
spaces_before_comment="15, 20"
:
1 + 1 # Adding values
two + two # More adding
longer_statement # This is a longer statement
short # This is a shorter statement
a_very_long_statement_that_extends_beyond_the_final_column # Comment
short # This is a shorter statement
will be formatted as:
1 + 1 # Adding values <-- end of line comments in block aligned to col 15
two + two # More adding
longer_statement # This is a longer statement <-- end of line comments in block aligned to col 20
short # This is a shorter statement
a_very_long_statement_that_extends_beyond_the_final_column # Comment <-- the end of line comments are aligned based on the line length
short # This is a shorter statement
SPLIT_ALL_COMMA_SEPARATED_VALUES
If a comma separated list (
dict
,list
,tuple
, or functiondef
) is on a line that is too long, split such that each element is on a separate line.
SPLIT_ALL_TOP_LEVEL_COMMA_SEPARATED_VALUES
Variation on
SPLIT_ALL_COMMA_SEPARATED_VALUES
in which, if a subexpression with a comma fits in its starting line, then the subexpression is not split. This avoids splits like the one forb
in this code:
abcdef(
aReallyLongThing: int,
b: [Int,
Int])
with the new knob this is split as:
abcdef(
aReallyLongThing: int,
b: [Int, Int])
SPLIT_ARGUMENTS_WHEN_COMMA_TERMINATED
Split before arguments if the argument list is terminated by a comma.
SPLIT_BEFORE_ARITHMETIC_OPERATOR
Set to
True
to prefer splitting before+
,-
,*
,/
,//
, or@
rather than after.
SPLIT_BEFORE_BITWISE_OPERATOR
Set to
True
to prefer splitting before&
,|
or^
rather than after.
SPLIT_BEFORE_CLOSING_BRACKET
Split before the closing bracket if a
list
ordict
literal doesn't fit on a single line.
SPLIT_BEFORE_DICT_SET_GENERATOR
Split before a dictionary or set generator (
comp_for
). For example, note the split before thefor
:
foo = {
variable: 'Hello world, have a nice day!'
for variable in bar if variable != 42
}
SPLIT_BEFORE_DOT
Split before the
.
if we need to split a longer expression:
foo = ('This is a really long string: {}, {}, {}, {}'.format(a, b, c, d))
would reformat to something like:
foo = ('This is a really long string: {}, {}, {}, {}'
.format(a, b, c, d))
SPLIT_BEFORE_EXPRESSION_AFTER_OPENING_PAREN
Split after the opening paren which surrounds an expression if it doesn't fit on a single line.
SPLIT_BEFORE_FIRST_ARGUMENT
If an argument / parameter list is going to be split, then split before the first argument.
SPLIT_BEFORE_LOGICAL_OPERATOR
Set to
True
to prefer splitting beforeand
oror
rather than after.
SPLIT_BEFORE_NAMED_ASSIGNS
Split named assignments onto individual lines.
SPLIT_COMPLEX_COMPREHENSION
For list comprehensions and generator expressions with multiple clauses (e.g multiple
for
calls,if
filter expressions) and which need to be reflowed, split each clause onto its own line. For example:
result = [
a_var + b_var for a_var in xrange(1000) for b_var in xrange(1000)
if a_var % b_var]
would reformat to something like:
result = [
a_var + b_var
for a_var in xrange(1000)
for b_var in xrange(1000)
if a_var % b_var]
SPLIT_PENALTY_AFTER_OPENING_BRACKET
The penalty for splitting right after the opening bracket.
SPLIT_PENALTY_AFTER_UNARY_OPERATOR
The penalty for splitting the line after a unary operator.
SPLIT_PENALTY_ARITHMETIC_OPERATOR
The penalty of splitting the line around the
+
,-
,*
,/
,//
,%
, and@
operators.
SPLIT_PENALTY_BEFORE_IF_EXPR
The penalty for splitting right before an
if
expression.
SPLIT_PENALTY_BITWISE_OPERATOR
The penalty of splitting the line around the
&
,|
, and^
operators.
SPLIT_PENALTY_COMPREHENSION
The penalty for splitting a list comprehension or generator expression.
SPLIT_PENALTY_EXCESS_CHARACTER
The penalty for characters over the column limit.
SPLIT_PENALTY_FOR_ADDED_LINE_SPLIT
The penalty incurred by adding a line split to the logical line. The more line splits added the higher the penalty.
SPLIT_PENALTY_IMPORT_NAMES
The penalty of splitting a list of
import as
names. For example:
from a_very_long_or_indented_module_name_yada_yad import (long_argument_1,
long_argument_2,
long_argument_3)
would reformat to something like:
from a_very_long_or_indented_module_name_yada_yad import (
long_argument_1, long_argument_2, long_argument_3)
SPLIT_PENALTY_LOGICAL_OPERATOR
The penalty of splitting the line around the
and
andor
operators.
USE_TABS
Use the Tab character for indentation.
(Potentially) Frequently Asked Questions
Why does YAPF destroy my awesome formatting?
YAPF tries very hard to get the formatting correct. But for some code, it won't be as good as hand-formatting. In particular, large data literals may become horribly disfigured under YAPF.
The reasons for this are manyfold. In short, YAPF is simply a tool to help with development. It will format things to coincide with the style guide, but that may not equate with readability.
What can be done to alleviate this situation is to indicate regions YAPF should ignore when reformatting something:
# yapf: disable
FOO = {
# ... some very large, complex data literal.
}
BAR = [
# ... another large data literal.
]
# yapf: enable
You can also disable formatting for a single literal like this:
BAZ = {
(1, 2, 3, 4),
(5, 6, 7, 8),
(9, 10, 11, 12),
} # yapf: disable
To preserve the nice dedented closing brackets, use the
dedent_closing_brackets
in your style. Note that in this case all
brackets, including function definitions and calls, are going to use
that style. This provides consistency across the formatted codebase.
Why Not Improve Existing Tools?
We wanted to use clang-format's reformatting algorithm. It's very powerful and designed to come up with the best formatting possible. Existing tools were created with different goals in mind, and would require extensive modifications to convert to using clang-format's algorithm.
Can I Use YAPF In My Program?
Please do! YAPF was designed to be used as a library as well as a command line tool. This means that a tool or IDE plugin is free to use YAPF.
I still get non-PEP8 compliant code! Why?
YAPF tries very hard to be fully PEP 8 compliant. However, it is paramount to not risk altering the semantics of your code. Thus, YAPF tries to be as safe as possible and does not change the token stream (e.g., by adding parentheses). All these cases however, can be easily fixed manually. For instance,
from my_package import my_function_1, my_function_2, my_function_3, my_function_4, my_function_5
FOO = my_variable_1 + my_variable_2 + my_variable_3 + my_variable_4 + my_variable_5 + my_variable_6 + my_variable_7 + my_variable_8
won't be split, but you can easily get it right by just adding parentheses:
from my_package import (my_function_1, my_function_2, my_function_3,
my_function_4, my_function_5)
FOO = (my_variable_1 + my_variable_2 + my_variable_3 + my_variable_4 +
my_variable_5 + my_variable_6 + my_variable_7 + my_variable_8)
Gory Details
Algorithm Design
The main data structure in YAPF is the LogicalLine
object. It holds a list
of FormatToken
\s, that we would want to place on a single line if there
were no column limit. An exception being a comment in the middle of an
expression statement will force the line to be formatted on more than one line.
The formatter works on one LogicalLine
object at a time.
An LogicalLine
typically won't affect the formatting of lines before or
after it. There is a part of the algorithm that may join two or more
LogicalLine
\s into one line. For instance, an if-then statement with a
short body can be placed on a single line:
if a == 42: continue
YAPF's formatting algorithm creates a weighted tree that acts as the solution space for the algorithm. Each node in the tree represents the result of a formatting decision --- i.e., whether to split or not to split before a token. Each formatting decision has a cost associated with it. Therefore, the cost is realized on the edge between two nodes. (In reality, the weighted tree doesn't have separate edge objects, so the cost resides on the nodes themselves.)
For example, take the following Python code snippet. For the sake of this example, assume that line (1) violates the column limit restriction and needs to be reformatted.
def xxxxxxxxxxx(aaaaaaaaaaaa, bbbbbbbbb, cccccccc, dddddddd, eeeeee): # 1
pass # 2
For line (1), the algorithm will build a tree where each node (a
FormattingDecisionState
object) is the state of the line at that token given
the decision to split before the token or not. Note: the FormatDecisionState
objects are copied by value so each node in the graph is unique and a change in
one doesn't affect other nodes.
Heuristics are used to determine the costs of splitting or not splitting. Because a node holds the state of the tree up to a token's insertion, it can easily determine if a splitting decision will violate one of the style requirements. For instance, the heuristic is able to apply an extra penalty to the edge when not splitting between the previous token and the one being added.
There are some instances where we will never want to split the line, because
doing so will always be detrimental (i.e., it will require a backslash-newline,
which is very rarely desirable). For line (1), we will never want to split the
first three tokens: def
, xxxxxxxxxxx
, and (
. Nor will we want to
split between the )
and the :
at the end. These regions are said to be
"unbreakable." This is reflected in the tree by there not being a "split"
decision (left hand branch) within the unbreakable region.
Now that we have the tree, we determine what the "best" formatting is by finding the path through the tree with the lowest cost.
And that's it!
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