def __init__()

in eventdata/parameter_sources/weightedarray.py [0:0]

• 12 lines of code
• 4 McCabe index (conditional complexity)

    def __init__(self, json_file):
        with gzip.open(json_file, 'rt') as data_file:
            item_list = json.load(data_file)

        # 1. Calculate a histogram of all weights.
        h = self.histogram(item_list)

        # 2. Calculate the weight that represents the last percent based on the histogram ...
        bottom_percent_weight = self.weight_of_bottom_percent(h, percent=WeightedArray.CUTOFF_PERCENT)

        # 3. ... so we can partition the items into the bottom and top parts.
        #
        # This implementation results in a peak memory usage of one client between 200 and 300 MB.
        self._top_choices = self.create_items(item_list, min_weight=bottom_percent_weight)
        self._bottom_choices = self.create_items(item_list, max_weight=bottom_percent_weight)

        self._counter = 0
        # we increment before accessing the elements
        self._bottom_idx = -1
        self._top_idx = -1
        # Not calculating the length over and over on the hot code path gives us a little bit higher peak throughput
        self._bottom_len = len(self._bottom_choices)
        self._top_len = len(self._top_choices)