Merge branch 'warnings' into 'develop'

remove logging output in favor of warnings

See merge request !316

saqc/core/core.py

@@ -2,11 +2,10 @@
 # -*- coding: utf-8 -*-
 from __future__ import annotations
 
-import logging
 import inspect
+import warnings
 import copy as stdcopy
 from typing import Any, Callable, Tuple, Union, Optional
-from typing_extensions import Literal
 
 import pandas as pd
 import numpy as np
@@ -310,8 +309,7 @@ def _warnForUnusedKwargs(func, keywords, translator: Translator):
 
     Notes
     -----
-    A single warning via the logging module is thrown, if any number of
-    missing kws are detected, naming each missing kw.
+    A single warning is thrown, if any number of missing kws are detected, naming each missing kw.
     """
     sig_kws = inspect.signature(func).parameters
 
@@ -328,4 +326,4 @@ def _warnForUnusedKwargs(func, keywords, translator: Translator):
 
     if missing:
         missing = ", ".join(missing)
-        logging.warning(f"Unused argument(s): {missing}")
+        warnings.warn(f"Unused argument(s): {missing}")

saqc/funcs/changepoints.py

@@ -2,8 +2,6 @@
 # -*- coding: utf-8 -*-
 from __future__ import annotations
 
-import logging
-
 import pandas as pd
 import numpy as np
 import numba
@@ -18,8 +16,6 @@ from saqc.lib.tools import customRoller
 from saqc.core import flagging, Flags
 from saqc.lib.types import FreqString
 
-logger = logging.getLogger("SaQC")
-
 
 @flagging(masking="field", module="changepoints")
 def flagChangePoints(

saqc/funcs/resampling.py

@@ -3,7 +3,6 @@
 
 from typing import Callable, Tuple, Optional, Union
 from typing_extensions import Literal
-import logging
 import numpy as np
 import pandas as pd
 from dios import DictOfSeries
@@ -17,8 +16,6 @@ from saqc.funcs.interpolation import interpolateIndex, _SUPPORTED_METHODS
 import saqc.funcs.tools as tools
 
 
-logger = logging.getLogger("SaQC")
-
 METHOD2ARGS = {
     "inverse_fshift": ("backward", pd.Timedelta),
     "inverse_bshift": ("forward", pd.Timedelta),

saqc/lib/tools.py

 #! /usr/bin/env python
 # -*- coding: utf-8 -*-
 
-import logging
 import re
 import datetime
 import itertools
+import warnings
 from typing import Sequence, Union, Any, Iterator, Callable
 
 import numpy as np
@@ -23,9 +23,6 @@ from saqc.lib.types import T
 from saqc.lib.rolling import customRoller
 
 
-logger = logging.getLogger("SaQC")
-
-
 def assertScalar(name, value, optional=False):
     if (not np.isscalar(value)) and (value is not None) and (optional is True):
         raise ValueError(f"'{name}' needs to be a scalar or 'None'")
@@ -446,9 +443,9 @@ def evalFreqStr(freq, check, index):
         if freq is None:
             freq, freqs = estimateFrequency(index)
         if freq is None:
-            logging.warning("Sampling rate could not be estimated.")
+            warnings.warn("Sampling rate could not be estimated.")
         if len(freqs) > 1:
-            logging.warning(
+            warnings.warn(
                 f"Sampling rate seems to be not uniform!." f"Detected: {freqs}"
             )
 
@@ -456,7 +453,7 @@ def evalFreqStr(freq, check, index):
             f_passed_seconds = pd.Timedelta(f_passed).total_seconds()
             freq_seconds = pd.Timedelta(freq).total_seconds()
             if f_passed_seconds != freq_seconds:
-                logging.warning(
+                warnings.warn(
                     f"Sampling rate estimate ({freq}) missmatches passed frequency ({f_passed})."
                 )
         elif check == "auto":

saqc/lib/ts_operators.py

@@ -4,9 +4,10 @@
 """
 The module gathers all kinds of timeseries tranformations.
 """
-import logging
 import re
+import warnings
 from typing import Union
+
 import pandas as pd
 import numpy as np
 import numba as nb
@@ -15,8 +16,6 @@ from scipy.stats import iqr, median_abs_deviation
 from scipy.signal import filtfilt, butter
 import numpy.polynomial.polynomial as poly
 
-logger = logging.getLogger("SaQC")
-
 
 def identity(ts):
     # identity function
@@ -249,7 +248,7 @@ def interpolateNANs(
                 try:
                     return x.interpolate(method=wrap_method, order=int(wrap_order))
                 except (NotImplementedError, ValueError):
-                    logger.warning(
+                    warnings.warn(
                         f"Interpolation with method {method} is not supported at order "
                         f"{wrap_order}. and will be performed at order {wrap_order-1}"
                     )

tests/core/test_core.py

 #! /usr/bin/env python
 # -*- coding: utf-8 -*-
 
-import logging
 import pytest
 import numpy as np
 import pandas as pd
@@ -13,10 +12,6 @@ from saqc import SaQC, flagging
 
 from tests.common import initData, flagAll
 
-# no logging output needed here
-# -> can this be configured on the test runner level?
-logging.disable(logging.CRITICAL)
-
 
 OPTIONAL = [False, True]
 

tests/fuzzy/test_masking.py

 #! /usr/bin/env python
 # -*- coding: utf-8 -*-
 
-import logging
-
 import pandas as pd
 
 from hypothesis import given, settings
@@ -13,9 +11,6 @@ from saqc.core.register import _maskData, _unmaskData, CallState
 from tests.fuzzy.lib import dataFieldFlags, MAX_EXAMPLES
 
 
-logging.disable(logging.CRITICAL)
-
-
 @settings(max_examples=MAX_EXAMPLES, deadline=None)
 @given(data_field_flags=dataFieldFlags())
 def test_maskingMasksData(data_field_flags):