dios/requirements.txt

 numpy==1.19.1
-pandas==1.1.1
+pandas==1.2.4
 python-dateutil==2.8.1
-pytz==2020.1
+pytz==2021.1
 six==1.15.0

requirements.txt

 Click==7.1.2
 dtw==1.4.0
-hypothesis==6.8.3
+hypothesis==6.10.1
 matplotlib==3.4.1
 mlxtend==0.18.0
 numba==0.53.1
 numpy==1.20.2
 outlier-utils==0.0.3
-pandas==1.2.3
+pandas==1.2.4
 pyarrow==3.0.0
-pytest==6.2.2
+pytest==6.2.3
 pytest-lazy-fixture==0.6.3
 PyWavelets==1.1.1
-scikit-learn==0.24.1
-scipy==1.6.2
+scikit-learn==0.24.2
+scipy==1.6.3
 typing_extensions==3.7.4.3

saqc/core/history.py

@@ -255,7 +255,7 @@ class History:
             value_mask = value_mask.iloc[:, n:]
 
         # rename columns, to avoid ``pd.DataFrame.loc`` become confused
-        columns = pd.Index(range(n, len(value_hist.columns) + 1))
+        columns = pd.Index(range(n, n + len(value_hist.columns)))
         value_hist.columns = columns
         value_mask.columns = columns
 

saqc/core/register.py

@@ -11,7 +11,7 @@ import warnings
 from saqc.constants import *
 from saqc.core.lib import SaQCFunction
 from saqc.core.flags import initFlagsLike, Flags
-from saqc.lib.types import FuncReturnT
+
 
 # NOTE:
 # the global SaQC function store,
@@ -19,6 +19,7 @@ from saqc.lib.types import FuncReturnT
 FUNC_MAP: Dict[str, SaQCFunction] = {}
 
 MaskingStrT = Literal["all", "field", "none"]
+FuncReturnT = Tuple[dios.DictOfSeries, Flags]
 
 
 @dataclasses.dataclass
@@ -185,7 +186,7 @@ def _getMaskingThresh(masking, kwargs, fname):
         The kwargs that will be passed to the saqc-function, possibly contain ``to_mask``.
     fname : str
         The name of the saqc-function to be called later (not here), to use in meaningful
-         error messages
+        error messages
 
     Returns
     -------
@@ -212,7 +213,7 @@ def _getMaskingThresh(masking, kwargs, fname):
     if masking == "none" and thresh not in (False, np.inf):
         # TODO: fix warning reference to docu
         warnings.warn(
-            f"the saqc-function {fname!r} ignore masking and therefore does not evaluate the passed "
+            f"the saqc-function {fname!r} ignores masking and therefore does not evaluate the passed "
             f"'to_mask'-keyword. Please refer to the documentation: TODO"
         )
 
@@ -283,7 +284,7 @@ def _prepareFlags(flags: Flags, masking) -> Flags:
     if masking == "none":
         return flags.copy()
 
-    return initFlagsLike(flags, initial_value=UNTOUCHED)
+    return initFlagsLike(flags)
 
 
 def _restoreFlags(flags: Flags, old_state: CallState):
@@ -298,10 +299,17 @@ def _restoreFlags(flags: Flags, old_state: CallState):
 
     out = old_state.flags.copy()
     for c in columns:
-        # this implicitly squash the new flags history (RHS) to a single column, which than is appended to
-        # the old history (LHS). The new flags history possibly consist of multiple columns, one for each
-        # time a series or scalar was passed to the flags.
-        out[c] = flags[c]
+        # this implicitly squash the new flags history (RHS)
+        # to a single column, which than is appended to the
+        # old history (LHS). The new flags history possibly
+        # consists of multiple columns, one for each time a
+        # series or scalar was passed to the flags.
+        if len(flags.history[c].columns) > 1 or c not in out:
+            # We only want to assign a new column to our history
+            # if something changed on the RHS, or if a new variable
+            # appeared. Otherwise blow up our history with dummy
+            # columns
+            out[c] = flags[c]
 
     return out
 

sphinx-doc/how_to_doc_md/HowToDoc.md

@@ -26,94 +26,17 @@ The documents and the docstrings then are collected and rendered using [sphinx](
 - For one liner docstrings, please keep the closing `"""` on the same line. 
   [[PEP8](https://www.python.org/dev/peps/pep-0008/#documentation-strings)]
 
-### Numpy Style
+### Pandas Style
 
-We use NumPy-style docstrings. Like this:
-
-```python
-def diag(v, k=0):
-    """
-    Extract a diagonal or construct a diagonal array.
-
-    See the more detailed documentation for ``numpy.diagonal`` if you use this
-    function to extract a diagonal and wish to write to the resulting array;
-    whether it returns a copy or a view depends on what version of numpy you
-    are using.
-
-    Parameters
-    ----------
-    v : array_like
-        If `v` is a 2-D array, return a copy of its `k`-th diagonal.
-        If `v` is a 1-D array, return a 2-D array with `v` on the `k`-th
-        diagonal.
-    k : int, optional
-        Diagonal in question. The default is 0. Use `k>0` for diagonals
-        above the main diagonal, and `k<0` for diagonals below the main
-        diagonal.
-
-    Returns
-    -------
-    out : ndarray
-        The extracted diagonal or constructed diagonal array.
-
-    See Also
-    --------
-    diagonal : Return specified diagonals.
-    diagflat : Create a 2-D array with the flattened input as a diagonal.
-    trace : Sum along diagonals.
-    triu : Upper triangle of an array.
-    tril : Lower triangle of an array.
-
-    Examples
-    --------
-    >>> x = np.arange(9).reshape((3,3))
-    >>> x
-    array([[0, 1, 2],
-           [3, 4, 5],
-           [6, 7, 8]])
-    >>> np.diag(x)
-    array([0, 4, 8])
-    >>> np.diag(x, k=1)
-    array([1, 5])
-    >>> np.diag(x, k=-1)
-    array([3, 7])
-    >>> np.diag(np.diag(x))
-    array([[0, 0, 0],
-           [0, 4, 0],
-           [0, 0, 8]])
-    """
-```
+We use [Pandas-style](https://pandas.pydata.org/pandas-docs/stable/development/contributing_docstring.html) docstrings:
 
 
-For a description of the sections read the [numpydoc docstring guide](https://numpydoc.readthedocs.io/en/latest/format.html). 
-For a more descriptive, fully fledged example see [here](https://numpydoc.readthedocs.io/en/latest/example.html#example). Please use the official type hints, as defined in the [standard library module](https://docs.python.org/3/library/typing.html) `typing` wherever data type information is given.
-But mostly the following sections are sufficient:
-1. **Always give a *One-line summary***
-2. optionally use *Extended summary*
-2. **Always give the *Parameters* Section** with `typing` conform type descriptions
-3. **Always give the *Returns* Section** with `typing` conform type descriptions
-2. optionally use *See Also*
-2. optionally use *Notes*
-2. optionally use *Examples*
-3. every other Section is even more optional :P
-5. And **always check if the `-----` has the same length** as the word it underlines. Seriously, otherwise sphinx will mock, and its really no fun to find and correct these !.
-    ```
-    See Also
-    --------
-    ``` 
-    That's is ok, but following is **not**
-
-    ```
-    See Also
-    ---------
-            ^
-    ```
 
-## Flags, data, field, etc.
+## Flagger, data, field, etc.
 
 use this:
 ```py
-def foo(data, field, flags):
+def foo(data, field, flagger):
     """
     data : dios.DictOfSeries
 	A saqc-data object.
@@ -121,8 +44,8 @@ def foo(data, field, flags):
     field : str
 	A field denoting a column in data.
 
-    flags : saqc.Flags
-	A Flags object.
+    flagger : saqc.flagger.BaseFlagger
+	A saqc-flagger object.
     """
 ```
 

tests/funcs/test_generic_config_functions.py

@@ -264,11 +264,7 @@ def test_variableAssignments(data):
     assert set(result_flags.columns) == set(data.columns) | {"dummy1", "dummy2"}
 
 
-# TODO: why this must(!) fail ? - a comment would be helpful
-@pytest.mark.xfail(strict=True)
 def test_processMultiple(data_diff):
-    var1, var2, *_ = data_diff.columns
-
     config = f"""
     {F.VARNAME} ; {F.TEST}
     dummy       ; generic.process(func=var1 + 1)