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import numpy as np |
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import pytest |
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from pandas import Series |
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from pandas.core.strings.accessor import StringMethods |
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_any_string_method = [ |
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("cat", (), {"sep": ","}), |
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("cat", (Series(list("zyx")),), {"sep": ",", "join": "left"}), |
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("center", (10,), {}), |
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("contains", ("a",), {}), |
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("count", ("a",), {}), |
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("decode", ("UTF-8",), {}), |
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("encode", ("UTF-8",), {}), |
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("endswith", ("a",), {}), |
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("endswith", ("a",), {"na": True}), |
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("endswith", ("a",), {"na": False}), |
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("extract", ("([a-z]*)",), {"expand": False}), |
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("extract", ("([a-z]*)",), {"expand": True}), |
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("extractall", ("([a-z]*)",), {}), |
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("find", ("a",), {}), |
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("findall", ("a",), {}), |
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("get", (0,), {}), |
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("index", ("",), {}), |
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("join", (",",), {}), |
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("ljust", (10,), {}), |
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("match", ("a",), {}), |
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("fullmatch", ("a",), {}), |
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("normalize", ("NFC",), {}), |
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("pad", (10,), {}), |
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("partition", (" ",), {"expand": False}), |
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("partition", (" ",), {"expand": True}), |
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("repeat", (3,), {}), |
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("replace", ("a", "z"), {}), |
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("rfind", ("a",), {}), |
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("rindex", ("",), {}), |
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("rjust", (10,), {}), |
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("rpartition", (" ",), {"expand": False}), |
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("rpartition", (" ",), {"expand": True}), |
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("slice", (0, 1), {}), |
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("slice_replace", (0, 1, "z"), {}), |
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("split", (" ",), {"expand": False}), |
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("split", (" ",), {"expand": True}), |
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("startswith", ("a",), {}), |
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("startswith", ("a",), {"na": True}), |
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("startswith", ("a",), {"na": False}), |
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("removeprefix", ("a",), {}), |
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("removesuffix", ("a",), {}), |
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("translate", ({97: 100},), {}), |
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("wrap", (2,), {}), |
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("zfill", (10,), {}), |
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] + list( |
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zip( |
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[ |
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"capitalize", |
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"cat", |
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"get_dummies", |
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"isalnum", |
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"isalpha", |
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"isdecimal", |
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"isdigit", |
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"islower", |
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"isnumeric", |
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"isspace", |
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"istitle", |
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"isupper", |
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"len", |
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"lower", |
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"lstrip", |
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"partition", |
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"rpartition", |
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"rsplit", |
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"rstrip", |
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"slice", |
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"slice_replace", |
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"split", |
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"strip", |
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"swapcase", |
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"title", |
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"upper", |
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"casefold", |
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], |
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[()] * 100, |
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[{}] * 100, |
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) |
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) |
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ids, _, _ = zip(*_any_string_method) |
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missing_methods = {f for f in dir(StringMethods) if not f.startswith("_")} - set(ids) |
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assert not missing_methods |
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@pytest.fixture(params=_any_string_method, ids=ids) |
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def any_string_method(request): |
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""" |
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Fixture for all public methods of `StringMethods` |
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This fixture returns a tuple of the method name and sample arguments |
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necessary to call the method. |
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Returns |
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------- |
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method_name : str |
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The name of the method in `StringMethods` |
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args : tuple |
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Sample values for the positional arguments |
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kwargs : dict |
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Sample values for the keyword arguments |
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Examples |
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-------- |
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>>> def test_something(any_string_method): |
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... s = Series(['a', 'b', np.nan, 'd']) |
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... |
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... method_name, args, kwargs = any_string_method |
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... method = getattr(s.str, method_name) |
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... # will not raise |
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... method(*args, **kwargs) |
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""" |
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return request.param |
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_any_allowed_skipna_inferred_dtype = [ |
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("string", ["a", np.nan, "c"]), |
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("bytes", [b"a", np.nan, b"c"]), |
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("empty", [np.nan, np.nan, np.nan]), |
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("empty", []), |
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("mixed-integer", ["a", np.nan, 2]), |
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] |
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ids, _ = zip(*_any_allowed_skipna_inferred_dtype) |
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@pytest.fixture(params=_any_allowed_skipna_inferred_dtype, ids=ids) |
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def any_allowed_skipna_inferred_dtype(request): |
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""" |
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Fixture for all (inferred) dtypes allowed in StringMethods.__init__ |
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The covered (inferred) types are: |
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* 'string' |
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* 'empty' |
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* 'bytes' |
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* 'mixed' |
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* 'mixed-integer' |
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Returns |
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------- |
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inferred_dtype : str |
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The string for the inferred dtype from _libs.lib.infer_dtype |
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values : np.ndarray |
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An array of object dtype that will be inferred to have |
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`inferred_dtype` |
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Examples |
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-------- |
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>>> from pandas._libs import lib |
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>>> |
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>>> def test_something(any_allowed_skipna_inferred_dtype): |
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... inferred_dtype, values = any_allowed_skipna_inferred_dtype |
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... # will pass |
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... assert lib.infer_dtype(values, skipna=True) == inferred_dtype |
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... |
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... # constructor for .str-accessor will also pass |
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... Series(values).str |
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""" |
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inferred_dtype, values = request.param |
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values = np.array(values, dtype=object) |
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return inferred_dtype, values |
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