JezK
Edit File: _add_docstring.py
"""A module for creating docstrings for sphinx ``data`` domains.""" import re import textwrap from ._generic_alias import NDArray _docstrings_list = [] def add_newdoc(name: str, value: str, doc: str) -> None: """Append ``_docstrings_list`` with a docstring for `name`. Parameters ---------- name : str The name of the object. value : str A string-representation of the object. doc : str The docstring of the object. """ _docstrings_list.append((name, value, doc)) def _parse_docstrings() -> str: """Convert all docstrings in ``_docstrings_list`` into a single sphinx-legible text block. """ type_list_ret = [] for name, value, doc in _docstrings_list: s = textwrap.dedent(doc).replace("\n", "\n ") # Replace sections by rubrics lines = s.split("\n") new_lines = [] indent = "" for line in lines: m = re.match(r'^(\s+)[-=]+\s*$', line) if m and new_lines: prev = textwrap.dedent(new_lines.pop()) if prev == "Examples": indent = "" new_lines.append(f'{m.group(1)}.. rubric:: {prev}') else: indent = 4 * " " new_lines.append(f'{m.group(1)}.. admonition:: {prev}') new_lines.append("") else: new_lines.append(f"{indent}{line}") s = "\n".join(new_lines) s_block = f""".. data:: {name}\n :value: {value}\n {s}""" type_list_ret.append(s_block) return "\n".join(type_list_ret) add_newdoc('ArrayLike', 'typing.Union[...]', """ A `~typing.Union` representing objects that can be coerced into an `~numpy.ndarray`. Among others this includes the likes of: * Scalars. * (Nested) sequences. * Objects implementing the `~class.__array__` protocol. .. versionadded:: 1.20 See Also -------- :term:`array_like`: Any scalar or sequence that can be interpreted as an ndarray. Examples -------- .. code-block:: python >>> import numpy as np >>> import numpy.typing as npt >>> def as_array(a: npt.ArrayLike) -> np.ndarray: ... return np.array(a) """) add_newdoc('DTypeLike', 'typing.Union[...]', """ A `~typing.Union` representing objects that can be coerced into a `~numpy.dtype`. Among others this includes the likes of: * :class:`type` objects. * Character codes or the names of :class:`type` objects. * Objects with the ``.dtype`` attribute. .. versionadded:: 1.20 See Also -------- :ref:`Specifying and constructing data types <arrays.dtypes.constructing>` A comprehensive overview of all objects that can be coerced into data types. Examples -------- .. code-block:: python >>> import numpy as np >>> import numpy.typing as npt >>> def as_dtype(d: npt.DTypeLike) -> np.dtype: ... return np.dtype(d) """) add_newdoc('NDArray', repr(NDArray), """ A :term:`generic <generic type>` version of `np.ndarray[Any, np.dtype[+ScalarType]] <numpy.ndarray>`. Can be used during runtime for typing arrays with a given dtype and unspecified shape. .. versionadded:: 1.21 Examples -------- .. code-block:: python >>> import numpy as np >>> import numpy.typing as npt >>> print(npt.NDArray) numpy.ndarray[typing.Any, numpy.dtype[+ScalarType]] >>> print(npt.NDArray[np.float64]) numpy.ndarray[typing.Any, numpy.dtype[numpy.float64]] >>> NDArrayInt = npt.NDArray[np.int_] >>> a: NDArrayInt = np.arange(10) >>> def func(a: npt.ArrayLike) -> npt.NDArray[Any]: ... return np.array(a) """) _docstrings = _parse_docstrings()