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This is the API documentation for the gdtest_stress_all_docstr library.
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## Classes

Main classes provided by the package


DataHolder(name: str)

A container for holding computation results.

Parameters
----------
name : str
    The name of the data holder.

Examples
--------
>>> dh = DataHolder("results")
>>> dh.get_data()
{}


## Functions

Utility functions


mega_function(data: list, mode: str = 'default', threshold: float = 0.5) -> dict

Perform a mega computation combining all docstring features.

Applies a configurable analysis pipeline to the input data,
returning detailed results. Uses :py:func:`other_func` for
element-wise transformations and :py:class:`DataHolder` for
result storage.

.. versionadded:: 3.0

.. note:: This replaces the old API.

Parameters
----------
data : list
    A list of numeric values to process. Must contain at
    least one element.
mode : str, optional
    The processing mode. One of ``"default"`` or ``"strict"``.
    Defaults to ``"default"``.
threshold : float, optional
    The minimum threshold for filtering values. Values below
    this threshold are excluded. Defaults to ``0.5``.

Returns
-------
dict
    A dictionary with the following keys:

    - ``"result"`` — the computed aggregate value (float).
    - ``"filtered"`` — data points above threshold (list).
    - ``"mode"`` — the mode that was used (str).
    - ``"count"`` — number of points processed (int).

Raises
------
ValueError
    If ``data`` is empty or ``mode`` is not recognized.

Notes
-----
The ``"default"`` mode applies a simple mean calculation:

.. math::

    R = \frac{1}{n} \sum_{i=1}^{n} f(x_i)

where :math:`f` is the :py:func:`other_func` transformation.

The ``"strict"`` mode additionally filters values below the
``threshold`` before computing the mean. This can significantly
reduce the number of data points in the output.

The time complexity is ``O(n)`` for both modes. Memory usage
is proportional to the size of the input data.

Warnings
--------
Input is modified in-place when ``mode="strict"`` is used.
Make a copy of the data before calling if you need to preserve
the original values.

See Also
--------
other_func : Element-wise transformation used internally.
DataHolder : Class for storing computation results.

References
----------
.. [1] Smith et al. (2020). "Advanced Data Processing
   Techniques." Journal of Computation, 15(3), 42-58.

Examples
--------
Basic usage with default mode:

>>> result = mega_function([1.0, 2.0, 3.0])
>>> result["mode"]
'default'
>>> result["count"]
3

Using strict mode with a threshold:

>>> result = mega_function([0.1, 0.6, 0.9], mode="strict", threshold=0.5)
>>> result["filtered"]
[0.6, 0.9]

The transformation uses :py:func:`other_func` internally:

>>> result = mega_function([4.0])
>>> result["result"]
2.0

other_func(x: float) -> float

Apply a square-root transformation to a single value.

Parameters
----------
x : float
    A numeric value to transform.

Returns
-------
float
    The square root of the absolute value of ``x``.

See Also
--------
mega_function : Main function that uses this transformation.

Examples
--------
>>> other_func(4.0)
2.0

>>> other_func(0.0)
0.0