A formatter for Python files

Overview

YAPF

PyPI version Build status Coverage status

Introduction

Most of the current formatters for Python --- e.g., autopep8, and pep8ify --- are made to remove lint errors from code. This has some obvious limitations. For instance, code that conforms to the PEP 8 guidelines may not be reformatted. But it doesn't mean that the code looks good.

YAPF takes a different approach. It's based off of 'clang-format', developed by Daniel Jasper. In essence, the algorithm takes the code and reformats it to the best formatting that conforms to the style guide, even if the original code didn't violate the style guide. The idea is also similar to the 'gofmt' tool for the Go programming language: end all holy wars about formatting - if the whole codebase of a project is simply piped through YAPF whenever modifications are made, the style remains consistent throughout the project and there's no point arguing about style in every code review.

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. It takes away some of the drudgery of maintaining your code.

Installation

To install YAPF from PyPI:

$ pip install yapf

(optional) If you are using Python 2.7 and want to enable multiprocessing:

$ pip install futures

YAPF is still considered in "alpha" 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.

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] ...

Python versions

YAPF supports Python 2.7 and 3.6.4+. (Note that some Python 3 features may fail to parse with Python versions before 3.6.4.)

YAPF requires the code it formats to be valid Python for the version YAPF itself runs under. Therefore, if you format Python 3 code with YAPF, run YAPF itself under Python 3 (and similarly for Python 2).

Usage

Options:

usage: yapf [-h] [-v] [-d | -i] [-r | -l START-END] [-e PATTERN]
            [--style STYLE] [--style-help] [--no-local-style] [-p]
            [-vv]
            [files [files ...]]

Formatter for Python code.

positional arguments:
  files

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         show version number and exit
  -d, --diff            print the diff for the fixed source
  -i, --in-place        make changes to files in place
  -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 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.
                        Requires concurrent.futures in Python 2.X
  -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)

In addition to exclude patterns provided on commandline, YAPF looks for additional patterns specified in a file named .yapfignore 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 ./.

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 [yapf] heading. For example:

[yapf]
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, yapf, and facebook (see _STYLE_NAME_TO_FACTORY in style.py).

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:

  1. Specified on the command line
  2. In the [style] section of a .style.yapf file in either the current directory or one of its parent directories.
  3. In the [yapf] section of a setup.cfg file in either the current directory or one of its parent directories.
  4. In the [style] section of a ~/.config/yapf/style file in your home directory.

If none of those files are found, the default style is used (PEP8).

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

>>> FormatCode("f ( a = 1, b = 2 )")
'f(a=1, b=2)\n'

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')
'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)])
'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 reformatter source.

>>> print(FormatCode("a==b", filename="foo.py", print_diff=True))
--- 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

>>> FormatFile("foo.py")
('a == b\n', 'utf-8')

The in_place argument saves the reformatted code back to the file:

>>> FormatFile("foo.py", in_place=True)
(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 file located in one of the
                        parent directories of the source file (or current
                        directory for stdin)
  --binary BINARY       location of binary to use for yapf

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_LINE_BEFORE_NESTED_CLASS_OR_DEF

Insert a blank line before a def or class immediately nested within another def or class. For example:

class Foo:
                   # <------ this blank line
    def method():
        pass
BLANK_LINE_BEFORE_MODULE_DOCSTRING
Insert a blank line before a module docstring.
BLANK_LINE_BEFORE_CLASS_DOCSTRING
Insert a blank line before a class-level docstring.
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_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 or INDENT_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 (ie: CONTINUATION_INDENT_WIDTH/INDENT_WIDTH tabs or CONTINUATION_INDENT_WIDTH spaces) for continuation alignment.
  • VALIGN-RIGHT: Vertically align continuation lines to multiple of INDENT_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.
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 than COLUMN_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_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.
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
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
SPACES_AROUND_POWER_OPERATOR
Set to True to prefer using spaces around **.
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_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 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). 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
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 }
SPLIT_ARGUMENTS_WHEN_COMMA_TERMINATED
Split before arguments if the argument list is terminated by a comma.
SPLIT_ALL_COMMA_SEPARATED_VALUES
If a comma separated list (dict, list, tuple, or function def) is on a line that is too long, split such that all elements are on a single 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 for b in this code:

abcdef(
    aReallyLongThing: int,
    b: [Int,
        Int])

With the new knob this is split as:

abcdef(
    aReallyLongThing: int,
    b: [Int, Int])
SPLIT_BEFORE_BITWISE_OPERATOR
Set to True to prefer splitting before &, | or ^ rather than after.
SPLIT_BEFORE_ARITHMETIC_OPERATOR
Set to True to prefer splitting before +, -, *, /, //, or @ rather than after.
SPLIT_BEFORE_CLOSING_BRACKET
Split before the closing bracket if a list or dict 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 the for:

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 before and or or 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 unwrapped 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 and or 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 UnwrappedLine object. It holds a list of FormatTokens, 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 UnwrappedLine object at a time.

An UnwrappedLine 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 UnwrappedLines 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!


YAPF is not an official Google product (experimental or otherwise), it is just code that happens to be owned by Google.
Owner
Google
Google ❤️ Open Source
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Calculator Python Package

Calculator Python Package This is a Calculator Package of Python. How To Install The Package? Install packagearinjoyn with pip (Package Installer Of P

Arinjoy_Programmer 1 Nov 21, 2021
An app to show the total number of lines of code written by an user.

Lines of code Have you ever wondered how many lines of code you wrote in github? This tool will calculate it for you! To calculate the total number of

B.Jothin kumar 10 Jan 26, 2022
CodeAnalysis - Static Code Analysis: a code comprehensive analysis platform

TCA, Tencent Cloud Code Analysis English | 简体中文 What is TCA Tencent Cloud Code A

Tencent 1.3k Jan 07, 2023
Collection of library stubs for Python, with static types

typeshed About Typeshed contains external type annotations for the Python standard library and Python builtins, as well as third party packages as con

Python 3.3k Jan 02, 2023
Unbearably fast O(1) runtime type-checking in pure Python.

Look for the bare necessities, the simple bare necessities. Forget about your worries and your strife. — The Jungle Book.

1.4k Dec 29, 2022
A static analysis tool for Python

pyanalyze Pyanalyze is a tool for programmatically detecting common mistakes in Python code, such as references to undefined variables and some catego

Quora 212 Jan 07, 2023
Guesslang detects the programming language of a given source code

Detect the programming language of a source code

Y. SOMDA 618 Dec 29, 2022
Python package to parse and generate C/C++ code as context aware preprocessor.

Devana Devana is a python tool that make it easy to parsing, format, transform and generate C++ (or C) code. This tool uses libclang to parse the code

5 Dec 28, 2022
Metrinome is an all-purpose tool for working with code complexity metrics.

Overview Metrinome is an all-purpose tool for working with code complexity metrics. It can be used as both a REPL and API, and includes: Converters to

26 Dec 26, 2022
🦔 PostHog is developer-friendly, open-source product analytics.

PostHog provides open-source product analytics, built for developers. Automate the collection of every event on your website or app, with no need to send data to 3rd parties. With just 1 click you ca

PostHog 10.3k Jan 01, 2023
Find dead Python code

Vulture - Find dead code Vulture finds unused code in Python programs. This is useful for cleaning up and finding errors in large code bases. If you r

Jendrik Seipp 2.4k Jan 03, 2023
A formatter for Python files

YAPF Introduction Most of the current formatters for Python --- e.g., autopep8, and pep8ify --- are made to remove lint errors from code. This has som

Google 13k Dec 31, 2022
Code audit tool for python.

Pylama Code audit tool for Python and JavaScript. Pylama wraps these tools: pycodestyle (formerly pep8) © 2012-2013, Florent Xicluna; pydocstyle (form

Kirill Klenov 966 Dec 29, 2022
Typing-toolbox for Python 3 _and_ 2.7 w.r.t. PEP 484.

Welcome to the pytypes project pytypes is a typing toolbox w.r.t. PEP 484 (PEP 526 on the road map, later also 544 if it gets accepted). Its main feat

Stefan Richthofer 188 Dec 29, 2022
A very minimalistic python module that lets you track the time your code snippets take to run.

Clock Keeper A very minimalistic python module that lets you track the time your code snippets take to run. This package is available on PyPI! Run the

Rajdeep Biswas 1 Jan 19, 2022
C/C++ Dependency Analyzer: a rewrite of John Lakos' dep_utils (adep/cdep/ldep) from

Version bêta d'un système pour suivre les prix des livres chez Books to Scrape, un revendeur de livres en ligne. En pratique, dans cette version bêta, le programme n'effectuera pas une véritable surv

Olzhas Rakhimov 125 Sep 21, 2022
Run-time type checker for Python

This library provides run-time type checking for functions defined with PEP 484 argument (and return) type annotations. Four principal ways to do type

Alex Grönholm 1.1k Dec 19, 2022
A static type analyzer for Python code

pytype - ? ✔ Pytype checks and infers types for your Python code - without requiring type annotations. Pytype can: Lint plain Python code, flagging c

Google 4k Dec 31, 2022
Performant type-checking for python.

Pyre is a performant type checker for Python compliant with PEP 484. Pyre can analyze codebases with millions of lines of code incrementally – providi

Facebook 6.2k Jan 07, 2023
A system for Python that generates static type annotations by collecting runtime types

MonkeyType MonkeyType collects runtime types of function arguments and return values, and can automatically generate stub files or even add draft type

Instagram 4.1k Jan 02, 2023