pandas code style guide

pandas follows the PEP8 standard and uses Black and Flake8 to ensure a consistent code format throughout the project. We encourage you to use pre-commit to automatically run black, flake8, isort, and related code checks when you make a git commit.


We use a flake8 plugin, pandas-dev-flaker, to check our codebase for unwanted patterns. See its README for the up-to-date list of rules we enforce.


Failing tests

See for background.

Do not use pytest.xfail

Do not use this method. It has the same behavior as pytest.skip, namely it immediately stops the test and does not check if the test will fail. If this is the behavior you desire, use pytest.skip instead.

Using pytest.mark.xfail

Use this method if a test is known to fail but the manner in which it fails is not meant to be captured. It is common to use this method for a test that exhibits buggy behavior or a non-implemented feature. If the failing test has flaky behavior, use the argument strict=False. This will make it so pytest does not fail if the test happens to pass.

Prefer the decorator @pytest.mark.xfail and the argument pytest.param over usage within a test so that the test is appropriately marked during the collection phase of pytest. For xfailing a test that involves multiple parameters, a fixture, or a combination of these, it is only possible to xfail during the testing phase. To do so, use the request fixture:

import pytest

def test_xfail(request):
    mark = pytest.mark.xfail(raises=TypeError, reason="Indicate why here")

xfail is not to be used for tests involving failure due to invalid user arguments. For these tests, we need to verify the correct exception type and error message is being raised, using pytest.raises instead.


Reading from a url


from import urlopen

with urlopen("") as url:
    raw_text =