Fix black linting

popmon/alerting/compute_tl_bounds.py

@@ -67,7 +67,7 @@ def traffic_light_summary(row, cols=None, prefix=""):
 
 
 def traffic_light(value, red_high, yellow_high, yellow_low=0, red_low=0):
-    """ Get corresponding traffic light given a value and traffic light bounds.
+    """Get corresponding traffic light given a value and traffic light bounds.
 
     :param float value: value to check
     :param float red_high: higher bound of red traffic light
@@ -337,8 +337,7 @@ def df_single_op_pull_bounds(
 
 
 class DynamicBounds(Pipeline):
-    """ Calculate dynamic traffic light bounds based on pull thresholds and dynamic mean and std.deviation.
-    """
+    """Calculate dynamic traffic light bounds based on pull thresholds and dynamic mean and std.deviation."""
 
     def __init__(
         self, read_key, rules, store_key="", suffix_mean="_mean", suffix_std="_std"
@@ -380,8 +379,7 @@ def transform(self, datastore):
 
 
 class StaticBounds(Pipeline):
-    """ Calculate static traffic light bounds based on pull thresholds and static mean and std.deviation.
-    """
+    """Calculate static traffic light bounds based on pull thresholds and static mean and std.deviation."""
 
     def __init__(
         self, read_key, rules, store_key="", suffix_mean="_mean", suffix_std="_std"

popmon/analysis/apply_func.py

@@ -187,7 +187,7 @@ def transform(self, datastore):
 def apply_func_array(
     feature, metrics, apply_to_df, assign_to_df, apply_funcs, same_key
 ):
-    """ Apply list of functions to dataframe
+    """Apply list of functions to dataframe
 
     Split off for parallellization reasons
 
@@ -231,7 +231,7 @@ def apply_func_array(
 
 
 def apply_func(feature, selected_metrics, df, arr):
-    """ Apply function to dataframe
+    """Apply function to dataframe
 
     :param str feature: feature currently looping over
     :param list selected_metrics: list of selected metrics to apply to

popmon/analysis/comparison/hist_comparer.py

@@ -135,8 +135,7 @@ def hist_compare(row, hist_name1="", hist_name2="", max_res_bound=7.0):
 
 
 class HistComparer(Pipeline):
-    """ Base pipeline to compare histogram to previous rolling histograms
-    """
+    """Base pipeline to compare histogram to previous rolling histograms"""
 
     def __init__(
         self,
@@ -192,8 +191,7 @@ def __init__(
 
 
 class RollingHistComparer(HistComparer):
-    """ Compare histogram to previous rolling histograms
-    """
+    """Compare histogram to previous rolling histograms"""
 
     def __init__(
         self,
@@ -238,8 +236,7 @@ def transform(self, datastore):
 
 
 class PreviousHistComparer(RollingHistComparer):
-    """ Compare histogram to previous histograms
-    """
+    """Compare histogram to previous histograms"""
 
     def __init__(
         self,
@@ -262,8 +259,7 @@ def __init__(
 
 
 class ExpandingHistComparer(HistComparer):
-    """ Compare histogram to previous expanding histograms
-    """
+    """Compare histogram to previous expanding histograms"""
 
     def __init__(
         self,
@@ -305,8 +301,7 @@ def transform(self, datastore):
 
 
 class ReferenceHistComparer(HistComparer):
-    """ Compare histogram to reference histograms
-    """
+    """Compare histogram to reference histograms"""
 
     def __init__(
         self,
@@ -349,8 +344,7 @@ def transform(self, datastore):
 
 
 class NormHistComparer(Pipeline):
-    """ Base pipeline to compare histogram to normalized histograms
-    """
+    """Base pipeline to compare histogram to normalized histograms"""
 
     def __init__(
         self,
@@ -396,8 +390,7 @@ def __init__(
 
 
 class RollingNormHistComparer(NormHistComparer):
-    """ Compare histogram to previous rolling normalized histograms
-    """
+    """Compare histogram to previous rolling normalized histograms"""
 
     def __init__(self, read_key, store_key, window, shift=1, hist_col="histogram"):
         """Initialize an instance of RollingNormHistComparer.
@@ -425,8 +418,7 @@ def transform(self, datastore):
 
 
 class ExpandingNormHistComparer(NormHistComparer):
-    """ Compare histogram to previous expanding normalized histograms
-    """
+    """Compare histogram to previous expanding normalized histograms"""
 
     def __init__(self, read_key, store_key, shift=1, hist_col="histogram"):
         """Initialize an instance of ExpandingNormHistComparer.
@@ -450,8 +442,7 @@ def transform(self, datastore):
 
 
 class ReferenceNormHistComparer(NormHistComparer):
-    """ Compare histogram to reference normalized histograms
-    """
+    """Compare histogram to reference normalized histograms"""
 
     def __init__(self, reference_key, assign_to_key, store_key, hist_col="histogram"):
         """Initialize an instance of ReferenceNormHistComparer.

popmon/analysis/functions.py

@@ -382,7 +382,7 @@ def expand_norm_hist_mean_cov(df, shift=1, *args, **kwargs):
 
 
 def normalized_hist_mean_cov(x, hist_name=""):
-    """ Mean normalized histogram and its covariance of list of input histograms
+    """Mean normalized histogram and its covariance of list of input histograms
 
     Usage: df['hists'].apply(normalized_hist_mean_cov) ; series.apply(normalized_hist_mean_cov)
 

popmon/analysis/hist_numpy.py

@@ -66,7 +66,7 @@ def prepare_2dgrid(hist):
 
 
 def set_2dgrid(hist, xkeys, ykeys):
-    """ Set 2d grid of first two dimenstions of input histogram
+    """Set 2d grid of first two dimenstions of input histogram
 
     Used as input by get_2dgrid(hist).
 
@@ -116,7 +116,7 @@ def set_2dgrid(hist, xkeys, ykeys):
 
 
 def get_2dgrid(hist, get_bin_labels=False):
-    """ Get filled x,y grid of first two dimensions of input histogram
+    """Get filled x,y grid of first two dimensions of input histogram
 
     :param hist: input histogrammar histogram
     :return: x,y grid of first two dimenstions of input histogram
@@ -141,7 +141,7 @@ def get_2dgrid(hist, get_bin_labels=False):
 
 
 def get_consistent_numpy_2dgrids(hc_list=[], get_bin_labels=False):
-    """ Get list of consistent x,y grids of first two dimensions of (sparse) input histograms
+    """Get list of consistent x,y grids of first two dimensions of (sparse) input histograms
 
     :param list hc_list: list of input histogrammar histograms
     :param bool get_bin_labels: if true, return x-keys and y-keys describing binnings of 2d-grid.
@@ -181,7 +181,7 @@ def get_consistent_numpy_2dgrids(hc_list=[], get_bin_labels=False):
 
 
 def get_consistent_numpy_1dhists(hc_list, get_bin_labels=False):
-    """ Get list of consistent numpy hists for list of sparse input histograms
+    """Get list of consistent numpy hists for list of sparse input histograms
 
     Note: a numpy histogram is a union of lists of bin_edges and number of entries
 
@@ -232,7 +232,7 @@ def get_consistent_numpy_1dhists(hc_list, get_bin_labels=False):
 
 
 def get_consistent_numpy_entries(hc_list, get_bin_labels=False):
-    """ Get list of consistent numpy bin_entries for list of 1d input histograms
+    """Get list of consistent numpy bin_entries for list of 1d input histograms
 
     :param list hist_list: list of input histogrammar histograms
     :return: list of consistent 1d numpy arrays with bin_entries for list of input histograms
@@ -439,7 +439,7 @@ def assert_similar_hists(hc_list, check_type=True, assert_type=used_hist_types):
 
 
 def check_same_hists(hc1, hc2):
-    """ Check if two hists are the same
+    """Check if two hists are the same
 
     :param hc1: input histogram container 1
     :param hc2: input histogram container 2

popmon/analysis/merge_statistics.py

@@ -24,8 +24,7 @@
 
 
 class MergeStatistics(Module):
-    """ Merging dictionaries of features containing dataframes with statistics as its values.
-    """
+    """Merging dictionaries of features containing dataframes with statistics as its values."""
 
     def __init__(self, read_keys, store_key):
         """Initialize an instance of MergeStatistics.

popmon/analysis/profiling/pull_calculator.py

@@ -34,7 +34,7 @@
 
 
 class PullCalculator(Pipeline):
-    """ Base module for pull calculation, based on mean and standard deviation calculation
+    """Base module for pull calculation, based on mean and standard deviation calculation
 
     Steps as performed by ApplyFunc modules:
 
@@ -103,8 +103,7 @@ def __init__(
 
 
 class RollingPullCalculator(PullCalculator):
-    """ Pull calculation based on rolling mean and standard deviations
-    """
+    """Pull calculation based on rolling mean and standard deviations"""
 
     def __init__(
         self,
@@ -158,8 +157,7 @@ def transform(self, datastore):
 
 
 class ExpandingPullCalculator(PullCalculator):
-    """ Pull calculation based on expanding mean and standard deviations
-    """
+    """Pull calculation based on expanding mean and standard deviations"""
 
     def __init__(
         self,
@@ -210,8 +208,7 @@ def transform(self, datastore):
 
 
 class ReferencePullCalculator(PullCalculator):
-    """ Pull calculation based on reference mean and standard deviations
-    """
+    """Pull calculation based on reference mean and standard deviations"""
 
     def __init__(
         self,
@@ -261,8 +258,7 @@ def transform(self, datastore):
 
 
 class RefMedianMadPullCalculator(PullCalculator):
-    """ Pull calculation based on reference median and mad
-    """
+    """Pull calculation based on reference median and mad"""
 
     def __init__(
         self,

popmon/base/module.py

@@ -22,19 +22,17 @@
 
 
 class Module:
-    """Base class used for modules in a pipeline.
-    """
+    """Base class used for modules in a pipeline."""
 
     def __init__(self):
-        """Module initialization
-        """
+        """Module initialization"""
         self.logger = logging.getLogger()
         self.features = []
         self.feature_begins_with = []
         self.ignore_features = []
 
     def set_logger(self, logger):
-        """ Set logger of module
+        """Set logger of module
 
         :param logger: input logger
         """

popmon/base/pipeline.py

@@ -24,8 +24,7 @@
 
 
 class Pipeline(Module):
-    """Base class used for to run modules in a pipeline.
-    """
+    """Base class used for to run modules in a pipeline."""
 
     def __init__(self, modules, logger=None):
         """Initialization of the pipeline

popmon/hist/filling/histogram_filler_base.py

@@ -486,11 +486,9 @@ def get_hist_bin(self, hist, features, quant, col, dt):
                     value=hist,
                 )
             else:
-                raise RuntimeError(
-                    "Do not know how to interpret bin specifications."
-                )
+                raise RuntimeError("Do not know how to interpret bin specifications.")
         else:
             # string and boolians are treated as categories
             hist = hg.Categorize(quantity=quant, value=hist)
 
-        return hist
+        return hist

popmon/hist/filling/make_histograms.py

@@ -47,7 +47,7 @@ def make_histograms(
     nbins_3d=10,
     max_nunique=500,
 ):
-    """ Create histograms from pandas or spark dataframe.
+    """Create histograms from pandas or spark dataframe.
 
     :param df: input pandas or spark dataframe to create histograms of.
     :param list features: columns to pick up from input data. (default is all features)

popmon/hist/filling/pandas_histogrammar.py

@@ -107,7 +107,7 @@ def assert_dataframe(self, df):
         return df
 
     def get_features(self, df):
-        """ Get columns of (pandas) dataframe
+        """Get columns of (pandas) dataframe
 
         :param df: input pandas dataframe
         """

popmon/hist/filling/spark_histogrammar.py

@@ -112,7 +112,7 @@ def assert_dataframe(self, df):
         return df
 
     def get_features(self, df):
-        """ Get columns of dataframe
+        """Get columns of dataframe
 
         :param df: input spark dataframe
         """

popmon/hist/histogram.py

@@ -59,7 +59,7 @@ def sum_entries(hist_data, default=True):
 
 
 def project_on_x(hist_data):
-    """ Project n-dim histogram onto x-axis
+    """Project n-dim histogram onto x-axis
 
     :param hist_data: input histogrammar histogram
     :return: on x-axis projected histogram (1d)
@@ -108,7 +108,7 @@ def project_on_x(hist_data):
 
 
 def sum_over_x(hist_data):
-    """ Integrate histogram over first dimension
+    """Integrate histogram over first dimension
 
     :param hist_data: input histogrammar histogram
     :return: integrated histogram
@@ -147,7 +147,7 @@ def sum_over_x(hist_data):
 
 
 def project_split2dhist_on_axis(splitdict, axis="x"):
-    """ Project a split 2d-histogram onto one axis
+    """Project a split 2d-histogram onto one axis
 
     Project a 2d hist that's been split with function split_hist_along_first_dimension
     onto x or y axis.
@@ -175,8 +175,7 @@ def project_split2dhist_on_axis(splitdict, axis="x"):
 
 
 class HistogramContainer:
-    """Wrapper class around histogrammar histograms with several utility functions.
-    """
+    """Wrapper class around histogrammar histograms with several utility functions."""
 
     def __init__(self, hist_obj):
         """Initialization
@@ -224,8 +223,7 @@ def _edit_name(self, axis_name, xname, yname, convert_time_index, short_keys):
         return axis_name
 
     def sparse_bin_centers_x(self):
-        """ Get x-axis bin centers of sparse histogram
-        """
+        """Get x-axis bin centers of sparse histogram"""
         keys = sorted(self.hist.bins.keys())
         if self.hist.minBin is None or self.hist.maxBin is None:
             # number of bins is set to 1.
@@ -239,8 +237,7 @@ def sparse_bin_centers_x(self):
         return centers, values
 
     def get_bin_centers(self):
-        """ Get bin centers or labels of histogram
-        """
+        """Get bin centers or labels of histogram"""
         if isinstance(self.hist, histogrammar.Bin):  # Bin
             centers, values = self.hist.bin_centers(), self.hist.values
         elif isinstance(self.hist, histogrammar.SparselyBin):
@@ -295,7 +292,7 @@ def split_hist_along_first_dimension(
         return hdict
 
     def _filter_empty_split_hists(self, centers, values):
-        """ Filter empty split histograms from input centers and values
+        """Filter empty split histograms from input centers and values
 
         :param list centers: input center values list
         :param list values: input values list