Skip to main content

A formatter for Python code.

Project description

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 code base 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

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 3.4.1+.

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]
            [--verify]
            [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 one of the
                        parent directories of the source file (or current
                        directory for stdin)
  --style-help          show style settings and exit
  --no-local-style      don't search for local style definition (.style.yapf)
  --verify              try to verify reformatted code for syntax errors

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).

It’s also possible to do the same on the command line with a dictionary. For example:

--style='{based_on_style: chromium, indent_width: 4}'

This will take the chromium base style and modify it to have four 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] secionf of a setup.cfg file in either the current directory or one of its parent directories.

  4. In the ~/.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.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.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

Knobs

ALIGN_CLOSING_BRACKET_WITH_VISUAL_INDENT

Align closing bracket with visual indentation.

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
COLUMN_LIMIT

The column limit (or max line-length)

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
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 reformattting 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.

JOIN_MULTIPLE_LINES

Join short lines into one line. E.g., single line if statements.

SPACE_BETWEEN_ENDING_COMMA_AND_CLOSING_BRACKET

Insert a space between the ending comma and closing bracket of a list, etc.

SPACES_BEFORE_COMMENT

The number of spaces required before a trailing comment.

SPLIT_BEFORE_BITWISE_OPERATOR

Set to True to prefer splitting before &, | or ^ rather than after.

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_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_BITWISE_OPERATOR

The penalty of splitting the line around the &, |, and ^ operators.

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.

(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 reason for this is many-fold. But in essence 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.

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!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

yapf-0.7.1.tar.gz (95.3 kB view details)

Uploaded Source

Built Distribution

yapf-0.7.1-py2.py3-none-any.whl (125.0 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file yapf-0.7.1.tar.gz.

File metadata

  • Download URL: yapf-0.7.1.tar.gz
  • Upload date:
  • Size: 95.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for yapf-0.7.1.tar.gz
Algorithm Hash digest
SHA256 efccf591945964b937fed3e638b507b271e2293d67df01b3cd139a72e07d02ef
MD5 30a9acf900144a32cc090fef088223fc
BLAKE2b-256 78d66dced73dcf71b93a67d421422a2edc7ee6eb874478942886fb53e5813918

See more details on using hashes here.

File details

Details for the file yapf-0.7.1-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for yapf-0.7.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 9620529ed8f24a2e06a2c11c4957861c9865c9dc3ff507f24dedbe9208092ef4
MD5 46c5b92ce108fb7e502a4fbf70e8c743
BLAKE2b-256 03ade83f1a5ea5d3aeaaa78bddf731ab5d45191c1695373534c3efb29f9c24f7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page