diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index d995cc8..60b8387 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -53,7 +53,7 @@ jobs: # Use always() to always run this step to publish test results when there are test failures if: ${{ always() }} - name: Upload coverage to Codecov - uses: codecov/codecov-action@v1 + uses: codecov/codecov-action@v3 with: token: ${{ secrets.CODECOV_TOKEN }} fail_ci_if_error: true diff --git a/.github/workflows/pre-commit.yml b/.github/workflows/pre-commit.yml index bf8aeaa..5f27942 100644 --- a/.github/workflows/pre-commit.yml +++ b/.github/workflows/pre-commit.yml @@ -11,6 +11,6 @@ jobs: group: ${{ github.ref }}-pre-commit cancel-in-progress: ${{github.event_name == 'pull_request'}} steps: - - uses: actions/checkout@v2 - - uses: actions/setup-python@v2 - - uses: pre-commit/action@v2.0.0 + - uses: actions/checkout@v3 + - uses: actions/setup-python@v3 + - uses: pre-commit/action@v3.0.0 diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 91467ce..4000fbd 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,16 +1,16 @@ repos: - repo: https://github.com/pycqa/isort - rev: 5.10.1 + rev: 5.12.0 hooks: - id: isort args: ["--profile", "black", "--filter-files"] name: isort - repo: https://github.com/psf/black - rev: 22.3.0 + rev: 22.10.0 hooks: - id: black exclude: ^staircase/test_data* - - repo: https://gitlab.com/pycqa/flake8 - rev: 4.0.1 + - repo: https://github.com/pycqa/flake8 + rev: 5.0.4 hooks: - - id: flake8 \ No newline at end of file + - id: flake8 diff --git a/LICENSE b/LICENSE index 64f4445..e5f9f6b 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2020-2021 Riley Clement +Copyright (c) 2020-2023 Riley Clement Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/docs/getting_started/overview.rst b/docs/getting_started/overview.rst index 6c64df6..b8e4981 100644 --- a/docs/getting_started/overview.rst +++ b/docs/getting_started/overview.rst @@ -21,7 +21,7 @@ License This project is licensed under the MIT License:: - Copyright © 2020-2021 + Copyright © 2020-2023 Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software diff --git a/docs/release_notes/changelog.rst b/docs/release_notes/changelog.rst index 07c5986..b0c36cf 100644 --- a/docs/release_notes/changelog.rst +++ b/docs/release_notes/changelog.rst @@ -6,6 +6,15 @@ Changelog ========= +**v2.5.1 2023-04-25** + +- compatible with Pandas 2.0 +- added type hints (#GH36) +- `mypy` added to development environment + +Contributors: @PabloRuizCuevas + + **v2.5.0 2022-10-19** - dropped support for Python 3.6 diff --git a/poetry.lock b/poetry.lock index b968d5e..b7d8706 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,18 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Strongly aligned with pandas." readme = "README.md" authors = ["Riley Clement "] @@ -34,13 +34,19 @@ classifiers=[ 'Programming Language :: Python :: 3.8', 'Programming Language :: Python :: 3.9', 'Programming Language :: Python :: 3.10', + 'Programming Language :: Python :: 3.11', 'Topic :: Scientific/Engineering', ] +[tool.poetry.urls] +"Bug Tracker" = "https://github.com/staircase-dev/staircase/issues" + + [tool.poetry.dependencies] python = "^3.7" matplotlib = ">=2" pytz = "*" +typing-extensions = "^4.4.0" [[tool.poetry.dependencies.pandas]] python = ">=3.7,<3.10" @@ -48,7 +54,7 @@ version = "^1" [[tool.poetry.dependencies.pandas]] python = "^3.10" -version = "^1.3.4" +version = ">=1.3.4,<3" [[tool.poetry.dependencies.numpy]] python = ">=3.7,<3.10" @@ -59,8 +65,6 @@ python = "^3.10" version = "^1.21.2" - - [tool.poetry.dev-dependencies] ipykernel = "^6" pytest = "^6" @@ -70,18 +74,37 @@ nbsphinx = ">=0.8.5" sphinx-autobuild = "*" seaborn = ">=0.8.0" notebook = ">= 6.0" -isort = ">=5.8" -black = {version = "*", python = "^3.6.2"} -flake8 = ">=3.9" -pre-commit = {version = ">=2.13", python = "^3.6.1"} +isort = ">=5.8,<5.12" +black = ">=22.10" +flake8 = ">=5" +pre-commit = ">=2.20" tox=">=3.15" - +mypy = "^0.982" [tool.poetry.extras] codecov = ["codecov"] -[tool.poetry.urls] -"Bug Tracker" = "https://github.com/staircase-dev/staircase/issues" +[tool.black] +line-length=88 + +[tool.mypy] +# disallow_untyped_defs='true' +# disallow_incomplete_defs='true' +# no_implicit_optional='true' +exclude = [ + '^docs/.', + '^core/ops.', + 'docstrings\\.pyi$', + '^tests/.', + '^staircase/plotting.', +] + +[[tool.mypy.overrides]] +module=[ + 'matplotlib.*', + 'pandas.*', +] +ignore_missing_imports='true' [tool.isort] # make it compatible with black diff --git a/staircase/constants.py b/staircase/constants.py index 3b36d96..ee611d0 100644 --- a/staircase/constants.py +++ b/staircase/constants.py @@ -1,19 +1,22 @@ +from __future__ import annotations + + class NegInf: def __init__(self): pass - def __lt__(self, other): + def __lt__(self, other) -> bool: assert not isinstance(other, NegInf) return True - def __gt__(self, other): + def __gt__(self, other) -> bool: assert not isinstance(other, (Inf, NegInf)) return False - def __neg__(self): + def __neg__(self) -> Inf: return inf - def __str__(self): + def __str__(self) -> str: return "-inf" @@ -21,18 +24,18 @@ class Inf: def __init__(self): pass - def __gt__(self, other): + def __gt__(self, other) -> bool: assert not isinstance(other, Inf) return True - def __lt__(self, other): + def __lt__(self, other) -> bool: assert not isinstance(other, (Inf, NegInf)) return False - def __neg__(self): + def __neg__(self) -> NegInf: return neginf - def __str__(self): + def __str__(self) -> str: return "inf" diff --git a/staircase/core/arrays/accessor.py b/staircase/core/arrays/accessor.py index 53d80a9..9749236 100644 --- a/staircase/core/arrays/accessor.py +++ b/staircase/core/arrays/accessor.py @@ -17,7 +17,7 @@ def __init__(self, pandas_obj): self._obj = pandas_obj @Appender(docstrings.make_docstring("accessor", "corr"), join="\n", indents=1) - def corr(self, where=(-inf, inf)): + def corr(self, where=(-inf, inf)) -> pd.DataFrame: return pd.DataFrame( self._obj.values.corr(where), index=self._obj.index, @@ -25,7 +25,7 @@ def corr(self, where=(-inf, inf)): ) @Appender(docstrings.make_docstring("accessor", "cov"), join="\n", indents=1) - def cov(self, where=(-inf, inf)): + def cov(self, where=(-inf, inf)) -> pd.DataFrame: return pd.DataFrame( self._obj.values.cov(where), index=self._obj.index, diff --git a/staircase/core/arrays/extension.py b/staircase/core/arrays/extension.py index 68ee88b..d1d7bcb 100644 --- a/staircase/core/arrays/extension.py +++ b/staircase/core/arrays/extension.py @@ -1,5 +1,8 @@ +from __future__ import annotations + import numbers from collections.abc import Iterable +from typing import Any, Callable, Type import matplotlib.pyplot as plt import numpy as np @@ -27,22 +30,22 @@ class StairsDtype(ExtensionDtype): na_value = pd.NA @classmethod - def construct_from_string(cls, string): + def construct_from_string(cls, string: str) -> StairsDtype: if string == cls.name: return cls() else: raise TypeError("Cannot construct a '{}' from '{}'".format(cls, string)) @classmethod - def construct_array_type(cls): + def construct_array_type(cls) -> Type[StairsArray]: return StairsArray -def _isna(value): +def _isna(value: pd.Series) -> pd.Series: return pd.isna(value) -def _make_logical(func): +def _make_logical(func: Callable) -> Callable: def logical_func(x, axis=0): return np.where( np.logical_or.reduce(np.isnan(x), axis=axis), @@ -75,13 +78,13 @@ def __init__(self, data): raise TypeError("'data' should be array of Stairs objects.") @property - def dtype(self): + def dtype(self) -> type: return self._dtype - def __len__(self): + def __len__(self) -> int: return len(self.data) - def __getitem__(self, idx): + def __getitem__(self, idx: int) -> Any: if isinstance(idx, numbers.Integral): return self.data[idx] elif isinstance(idx, (Iterable, slice)): @@ -185,7 +188,7 @@ def agg(self, func): )._remove_redundant_step_points() @Appender(docstrings.make_docstring("array", "sample"), join="\n", indents=1) - def sample(self, x): + def sample(self, x) -> pd.Series: array = pd.Series(self.data) return array.apply(Stairs.sample, x=x, include_index=True) @@ -234,7 +237,7 @@ def negate(self): __neg__ = negate -def _make_binary_func(func_str): +def _make_binary_func(func_str: str) -> Callable: stairs_func = getattr(Stairs, func_str) docstring = docstrings.make_binop_docstring(funcstr) @@ -285,7 +288,9 @@ def func(self, other): setattr(StairsArray, f"__{magic}__", func) -def _make_corr_cov_func(docstring, stairs_method, assume_ones_diagonal): +def _make_corr_cov_func( + docstring: str, stairs_method: Callable, assume_ones_diagonal: int +) -> Callable: @Appender(docstring, join="\n", indents=1) def func(self, where=(-inf, inf)): size = len(self.data) diff --git a/staircase/core/layering.py b/staircase/core/layering.py index 800304d..3220bc1 100644 --- a/staircase/core/layering.py +++ b/staircase/core/layering.py @@ -1,5 +1,8 @@ +from __future__ import annotations + import datetime import warnings +from typing import Any import numpy as np import pandas as pd @@ -23,7 +26,7 @@ def _check_args_dtypes(*vectors): is_numeric_dtype, ] - def _check_approved_dtype(vec): + def _check_approved_dtype(vec: pd.Series): approved = any(map(lambda func: func(vec), approved_dtypes_checks)) if not approved: warnings.warn( @@ -59,7 +62,7 @@ def _check_approved_type(arg, approved_types): _check_approved_type(end, tuple(base_approved_types + [NegInf])) -def _convert_to_series(vec): +def _convert_to_series(vec: Any) -> pd.Series: if not isinstance(vec, pd.Series): if vec is None or (isinstance(vec, (tuple, list)) and not len(vec)): vec = pd.Series(vec, dtype="float64") diff --git a/staircase/core/sampling.py b/staircase/core/sampling.py index 1be5706..e0eaa3b 100644 --- a/staircase/core/sampling.py +++ b/staircase/core/sampling.py @@ -1,7 +1,10 @@ +from __future__ import annotations + import numpy as np import pandas as pd from pandas.api.types import is_list_like +from staircase.core.stairs import Stairs from staircase.docstrings import examples from staircase.util import _is_datetime_like from staircase.util._decorators import Appender @@ -9,7 +12,9 @@ # capable of single or vector @Appender(examples.sample_example, join="\n", indents=1) -def sample(self, x, include_index=False): +def sample( + self: Stairs, x: int | float | np.array | pd.Series, include_index=False +) -> pd.Series: """ Evaluates the value of the step function at one, or more, points. @@ -42,7 +47,7 @@ def sample(self, x, include_index=False): @Appender(examples.limit_example, join="\n", indents=1) -def limit(self, x, side, include_index=False): +def limit(self: Stairs, x, side, include_index=False) -> pd.Series: """ Evaluates the limit of the step function as it approaches one, or more, points. diff --git a/staircase/core/slicing.py b/staircase/core/slicing.py index 04fa3c5..f2eee8a 100644 --- a/staircase/core/slicing.py +++ b/staircase/core/slicing.py @@ -1,6 +1,11 @@ +from __future__ import annotations + +from typing import Callable + import numpy as np import pandas as pd from pandas.api.types import is_list_like +from typing_extensions import Literal import staircase as sc from staircase.core.ops.masking import clip @@ -10,22 +15,22 @@ class StairsSlicer: - def __init__(self, stairs, interval_index): + def __init__(self, stairs: sc.Stairs, interval_index): self._stairs = stairs self._interval_index = interval_index - self._slices = None + self._slices: pd.Series | None = None - def _create_slices(self): + def _create_slices(self) -> None: slices = self._interval_index.map(lambda i: clip(self._stairs, i.left, i.right)) self._slices = pd.Series(slices, index=self._interval_index) - def _ensure_slices(self): + def _ensure_slices(self) -> StairsSlicer: if self._slices is None: self._create_slices() return self @Appender(docstrings.agg_docstring, join="\n", indents=1) - def agg(self, funcs): + def agg(self, funcs) -> pd.DataFrame: if isinstance(funcs, str): funcs = [funcs] self._ensure_slices() @@ -35,12 +40,12 @@ def agg(self, funcs): return df @Appender(docstrings.apply_docstring, join="\n", indents=1) - def apply(self, func, *args, **kwargs): + def apply(self, func: Callable, *args, **kwargs) -> pd.Series: self._ensure_slices() return self._slices.apply(func, args=args, **kwargs) @Appender(docstrings._docstrings["max"], join="\n", indents=1) - def max(self): + def max(self) -> float: result = self._max() if self._stairs._closed == "left" and self._interval_index.closed in ( "right", @@ -55,7 +60,7 @@ def max(self): return result @Appender(docstrings._docstrings["min"], join="\n", indents=1) - def min(self): + def min(self) -> float: result = self._min() if self._stairs._closed == "left" and self._interval_index.closed in ( "right", @@ -72,13 +77,13 @@ def min(self): @Appender(docstrings.hist_docstring, join="\n", indents=1) def hist(self, *args, **kwargs): self._ensure_slices() - zero = ( # hack to get 0 or pd.Timedelta(0) + zero = ( self._stairs._data.index[0] - self._stairs._data.index[0] - ) + ) # hack to get 0 or pd.Timedelta(0) return self._slices.apply(sc.Stairs.hist, *args, **kwargs).fillna(zero) @Appender(docstrings.resample_docstring, join="\n", indents=1) - def resample(self, func): + def resample(self, func: str): if not self._interval_index.is_non_overlapping_monotonic: raise ValueError( "Slices must be monotonic increasing (ascending order) and not overlapping" @@ -96,7 +101,7 @@ def resample(self, func): ) -def make_slice_method(method_name): +def make_slice_method(method_name: str) -> Callable: func = _get_stairs_method(method_name) docstring = docstrings._docstrings.get(method_name, "") @@ -114,7 +119,9 @@ def method(self): setattr(StairsSlicer, method_name, method) -def slice(self, cuts, closed="left"): +def slice( + self: sc.Stairs, cuts, closed: Literal["left", "right", "both", "neither"] = "left" +) -> StairsSlicer: """ Slice the step function into pieces. @@ -123,6 +130,7 @@ def slice(self, cuts, closed="left"): Parameters ---------- + self : Stairs : class cuts : sequence, :class:`pandas.IntervalIndex`, :class:`pandas.PeriodIndex`. Used to slice the step function. If *cuts* is a sequence then it should comprised of monotonically increasing values from the step function domain. diff --git a/staircase/core/stairs.py b/staircase/core/stairs.py index d4f26b6..c6c19be 100644 --- a/staircase/core/stairs.py +++ b/staircase/core/stairs.py @@ -6,8 +6,10 @@ staircase is a MIT licensed library, written in pure-Python, for modelling step functions. See :ref:`Getting Started ` for more information. """ +from __future__ import annotations import warnings +from typing import Any, Callable import numpy as np import pandas as pd @@ -17,6 +19,7 @@ is_numeric_dtype, is_timedelta64_dtype, ) +from typing_extensions import Literal from staircase import docstrings from staircase.constants import inf @@ -28,7 +31,7 @@ from staircase.util._decorators import Appender -def _make_deltas_from_vals(init_val, vals): +def _make_deltas_from_vals(init_val, vals: pd.DataFrame) -> pd.Series: if not np.isnan(vals).any(): result = pd.Series(np.diff((np.append([init_val], vals.values)))) else: @@ -42,7 +45,7 @@ def _make_deltas_from_vals(init_val, vals): return result -def _make_vals_from_deltas(init_val, deltas): +def _make_vals_from_deltas(init_val: float, deltas: pd.DataFrame): base = 0 if np.isnan(init_val) else init_val return deltas.cumsum() + base @@ -54,12 +57,12 @@ class Stairs: @Appender(docstrings.Stairs_docstring, join="\n", indents=2) def __init__( self, - frame=None, - start=None, + frame: pd.DataFrame | None = None, + start: int | None = None, end=None, value=None, initial_value=0, - closed="left", + closed: Literal["left", "right"] = "left", ): assert frame is None or isinstance(frame, pd.DataFrame) self._data = None @@ -78,7 +81,12 @@ def _clear_cache(self): self._integral_and_mean = None @classmethod - def _new(cls, initial_value, data, closed="left"): + def _new( + cls, + initial_value: float, + data: pd.DataFrame, + closed: Literal["left", "right"] = "left", + ) -> Stairs: new_instance = cls(closed=closed) new_instance.initial_value = initial_value new_instance._data = data @@ -87,7 +95,12 @@ def _new(cls, initial_value, data, closed="left"): return new_instance @classmethod - def from_values(cls, initial_value, values=None, closed="left"): + def from_values( + cls, + initial_value: float = 0, + values: pd.Series | None = None, + closed: Literal["left", "right"] = "left", + ) -> Stairs: """ Construct :class:`Stairs` from :class:`pandas.Series`. @@ -132,10 +145,10 @@ def from_values(cls, initial_value, values=None, closed="left"): new_instance._valid_values = True return new_instance - def _has_na(self): + def _has_na(self) -> bool | np.array: return np.isnan(self._data.values).any() or np.isnan(self.initial_value) - def _create_values(self): + def _create_values(self) -> Stairs: assert self._valid_deltas self._data["value"] = _make_vals_from_deltas( self.initial_value, self._data["delta"] @@ -143,7 +156,7 @@ def _create_values(self): self._valid_values = True return self - def _create_deltas(self): + def _create_deltas(self) -> Stairs: assert self._valid_values self._data["delta"] = _make_deltas_from_vals( self.initial_value, self._data["value"] @@ -151,14 +164,14 @@ def _create_deltas(self): self._valid_deltas = True return self - def _get_deltas(self): + def _get_deltas(self) -> pd.Series: if self._data is None: return pd.Series(dtype="float64") if not self._valid_deltas: self._create_deltas() return self._data["delta"] - def _get_values(self): + def _get_values(self) -> pd.Series: if self._data is None: return pd.Series(dtype="float64") if not self._valid_values: @@ -308,7 +321,7 @@ def hist(self, bins="unit", closed="left", stat="sum"): """ return self.dist.hist(bins=bins, closed=closed, stat=stat) - def quantiles(self, q): + def quantiles(self, q: int): """ Returns an array of q-quantiles. @@ -348,7 +361,7 @@ def quantiles(self, q): return self.dist.quantiles(q) @Appender(stats.docstrings.simple_max_example, join="\n", indents=2) - def max(self): + def max(self) -> float: """ The maximum of the step function. @@ -364,7 +377,7 @@ def max(self): return stats.max(self) @Appender(stats.docstrings.simple_min_example, join="\n", indents=2) - def min(self): + def min(self) -> float: """ The minimum of the step function. @@ -382,7 +395,7 @@ def min(self): plot = CachedAccessor("plot", PlotAccessor) @property - def step_changes(self): + def step_changes(self) -> pd.Series: """ A pandas Series of key, value pairs of indicating where step changes occur in the step function, and the change in value @@ -447,7 +460,7 @@ def step_values(self): return self._get_values().copy() @property - def step_points(self): + def step_points(self) -> np.array: """ A numpy arrauy of domain values indicating where step changes occur in the step function. @@ -477,7 +490,7 @@ def step_points(self): @Appender(docstrings.examples.number_of_steps_example, join="\n", indents=2) @property - def number_of_steps(self): + def number_of_steps(self) -> int: """ Calculates the number of step changes @@ -493,17 +506,17 @@ def number_of_steps(self): """ return len(self.step_points) - def _remove_redundant_step_points(self): + def _remove_redundant_step_points(self) -> Stairs: # preferred over values method - def remove_via_deltas(): + def remove_via_deltas() -> None: remove_index = ( self._data["delta"].isna() & self._data["delta"].isna().shift() ) | (self._data["delta"] == 0) self._data = self._data.loc[~remove_index] # do we just make deltas and then run above method? - def remove_via_values(): + def remove_via_values() -> None: remove_index = ( self._data["value"].isna() & self._data["value"].isna().shift() ) | (self._data["value"] == self._data["value"].shift()) @@ -526,7 +539,7 @@ def remove_via_values(): return self - def copy(self): + def copy(self) -> Stairs: """ Returns a deep copy of this Stairs instance @@ -541,7 +554,7 @@ def copy(self): ) return new_instance - def __bool__(self): + def __bool__(self) -> bool: """ Return True if and only if step function has a value of 1 everywhere. @@ -554,7 +567,12 @@ def __bool__(self): return False @Appender(docstrings.examples.describe_example, join="\n", indents=2) - def describe(self, where=(-inf, inf), percentiles=(25, 50, 75)): + def describe( + self, + where: tuple[float | int, float | int] + | list[float | int, float | int] = (-inf, inf), + percentiles: list[float | int] | tuple[float | int] = (25, 50, 75), + ) -> pd.Series: """ Generate descriptive statistics for the step function values over a specified domain. @@ -591,7 +609,7 @@ def describe(self, where=(-inf, inf), percentiles=(25, 50, 75)): ) @Appender(docstrings.examples.shift_example, join="\n", indents=2) - def shift(self, delta): + def shift(self, delta: pd.Series | int | float) -> Stairs: """ Returns a stairs instance corresponding to a horizontal translation by delta @@ -621,7 +639,7 @@ def shift(self, delta): ) @Appender(docstrings.examples.diff_example, join="\n", indents=2) - def diff(self, delta): + def diff(self, delta: int | float | pd.Timedelta) -> Stairs: """ Returns a stairs instance corresponding to the difference between the step function corresponding to *self* and the same step-function translated by delta. @@ -643,7 +661,11 @@ def diff(self, delta): return self - self.shift(delta) @Appender(docstrings.examples.rolling_mean_example, join="\n", indents=2) - def rolling_mean(self, window=(0, 0), where=(-inf, inf)): + def rolling_mean( + self, + window: tuple[int | int] = (0, 0), + where: tuple[float | float] = (-inf, inf), + ) -> pd.Series: """ Returns coordinates defining rolling mean @@ -699,7 +721,7 @@ def rolling_mean(self, window=(0, 0), where=(-inf, inf)): s = s.loc[s.index <= upper - right_delta] return s - def to_frame(self): + def to_frame(self) -> pd.DataFrame: """ Returns a pandas.DataFrame with columns 'start', 'end' and 'value' @@ -739,7 +761,7 @@ def to_frame(self): values = np.append(self.initial_value, self._data["value"].values) return pd.DataFrame({"start": starts, "end": ends, "value": values}) - def pipe(self, func, *args, **kwargs): + def pipe(self, func: Callable, *args, **kwargs) -> Any: """ Applies func and returns the result. @@ -761,13 +783,13 @@ def pipe(self, func, *args, **kwargs): """ return func(self, *args, **kwargs) - def __str__(self): + def __str__(self) -> str: """ Return str(self) """ return f"" - def __repr__(self): + def __repr__(self) -> str: """ Return string representation of Stairs """ @@ -777,7 +799,7 @@ def __call__(self, *args, **kwargs): return self.sample(*args, **kwargs) -def _add_operations(): +def _add_operations() -> None: from staircase.core import layering, ops, sampling, slicing ops.add_operations(Stairs) diff --git a/staircase/test_data.py b/staircase/test_data.py index 7ab171c..c6b9599 100644 --- a/staircase/test_data.py +++ b/staircase/test_data.py @@ -1,8 +1,17 @@ +from __future__ import annotations + +from typing import Optional + import numpy as np import pandas as pd -def make_test_data(dates=True, positive_only=True, groups=(), seed=None): +def make_test_data( + dates: bool = True, + positive_only: bool = True, + groups: tuple[Optional[str]] | list[Optional[str]] = (), + seed: int | None = None, +) -> pd.DataFrame: """ Creates interval data for use with staircase. @@ -77,7 +86,9 @@ def _get_random_functions(seed=None): return rng.integers, rng.random -def _make_test_data(dates=True, positive_only=True, seed=None): +def _make_test_data( + dates: bool = True, positive_only: bool = True, seed: str | bool | None = None +) -> pd.DataFrame: random_integers, random_floats = _get_random_functions(seed) diff --git a/tox.ini b/tox.ini index a89c868..2c2fa1e 100644 --- a/tox.ini +++ b/tox.ini @@ -1,6 +1,6 @@ [tox] isolated_build=true -envlist = py{36,37,38,39}-numpy{114,115,116,117,118,119,120,121}-pandas{024,025,10,11,12,13} +envlist = py{36,37,38,39,310,311}-numpy{114,115,116,117,118,119,120,121}-pandas{024,025,10,11,12,13} skipdist = true [testenv]