pandas code style guide¶

Table of contents:

Patterns
- Using foo.__class__
String formatting
- Concatenated strings
  - Using f-strings
  - White spaces
- Representation function (aka ‘repr()’)
Imports (aim for absolute)
Miscellaneous
- Reading from a url

pandas follows the PEP8 standard and uses Black and Flake8 to ensure a consistent code format throughout the project. For details see the contributing guide to pandas.

Patterns ¶

Using foo.class¶

pandas uses ‘type(foo)’ instead ‘foo.__class__’ as it is making the code more readable. For example:

Good:

foo = "bar"
type(foo)

Bad:

foo = "bar"
foo.__class__

String formatting ¶

Concatenated strings ¶

Using f-strings ¶

pandas uses f-strings formatting instead of ‘%’ and ‘.format()’ string formatters.

The convention of using f-strings on a string that is concatenated over several lines, is to prefix only the lines containing values which need to be interpreted.

For example:

Good:

foo = "old_function"
bar = "new_function"

my_warning_message = (
    f"Warning, {foo} is deprecated, "
    "please use the new and way better "
    f"{bar}"
)

Bad:

foo = "old_function"
bar = "new_function"

my_warning_message = (
    f"Warning, {foo} is deprecated, "
    f"please use the new and way better "
    f"{bar}"
)

White spaces ¶

Only put white space at the end of the previous line, so there is no whitespace at the beginning of the concatenated string.

For example:

Good:

example_string = (
    "Some long concatenated string, "
    "with good placement of the "
    "whitespaces"
)

Bad:

example_string = (
    "Some long concatenated string,"
    " with bad placement of the"
    " whitespaces"
)

Representation function (aka ‘repr()’)¶

pandas uses ‘repr()’ instead of ‘%r’ and ‘!r’.

The use of ‘repr()’ will only happen when the value is not an obvious string.

For example:

Good:

value = str
f"Unknown received value, got: {repr(value)}"

Good:

value = str
f"Unknown received type, got: '{type(value).__name__}'"

In Python 3, absolute imports are recommended. Using absolute imports, doing something like import string will import the string module rather than string.py in the same directory. As much as possible, you should try to write out absolute imports that show the whole import chain from top-level pandas.

Explicit relative imports are also supported in Python 3 but it is not recommended to use them. Implicit relative imports should never be used and are removed in Python 3.

For example:

# preferred
import pandas.core.common as com

# not preferred
from .common import test_base

# wrong
from common import test_base

Miscellaneous ¶

Reading from a url ¶

Good:

from pandas.io.common import urlopen
with urlopen('http://www.google.com') as url:
    raw_text = url.read()

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