pandas code style guide

Patterns

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

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 serveral lines, is to prefix only the lines containing the value needs to be interpeted.

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

Putting the white space only at the end of the previous line, so there is no whitespace at the beggining 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 happend when the value is not an obvious string.

For example:

Good:

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

Good:

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

pandas docstring guide Pandas Maintenance