Updates

ETB-API/venv/lib/python3.12/site-packages/prometheus_client/multiprocess.py

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+from collections import defaultdict
+import glob
+import json
+import os
+import warnings
+
+from .metrics import Gauge
+from .metrics_core import Metric
+from .mmap_dict import MmapedDict
+from .samples import Sample
+from .utils import floatToGoString
+
+try:  # Python3
+    FileNotFoundError
+except NameError:  # Python >= 2.5
+    FileNotFoundError = IOError
+
+
+class MultiProcessCollector:
+    """Collector for files for multi-process mode."""
+
+    def __init__(self, registry, path=None):
+        if path is None:
+            # This deprecation warning can go away in a few releases when removing the compatibility
+            if 'prometheus_multiproc_dir' in os.environ and 'PROMETHEUS_MULTIPROC_DIR' not in os.environ:
+                os.environ['PROMETHEUS_MULTIPROC_DIR'] = os.environ['prometheus_multiproc_dir']
+                warnings.warn("prometheus_multiproc_dir variable has been deprecated in favor of the upper case naming PROMETHEUS_MULTIPROC_DIR", DeprecationWarning)
+            path = os.environ.get('PROMETHEUS_MULTIPROC_DIR')
+        if not path or not os.path.isdir(path):
+            raise ValueError('env PROMETHEUS_MULTIPROC_DIR is not set or not a directory')
+        self._path = path
+        if registry:
+            registry.register(self)
+
+    @staticmethod
+    def merge(files, accumulate=True):
+        """Merge metrics from given mmap files.
+
+        By default, histograms are accumulated, as per prometheus wire format.
+        But if writing the merged data back to mmap files, use
+        accumulate=False to avoid compound accumulation.
+        """
+        metrics = MultiProcessCollector._read_metrics(files)
+        return MultiProcessCollector._accumulate_metrics(metrics, accumulate)
+
+    @staticmethod
+    def _read_metrics(files):
+        metrics = {}
+        key_cache = {}
+
+        def _parse_key(key):
+            val = key_cache.get(key)
+            if not val:
+                metric_name, name, labels, help_text = json.loads(key)
+                labels_key = tuple(sorted(labels.items()))
+                val = key_cache[key] = (metric_name, name, labels, labels_key, help_text)
+            return val
+
+        for f in files:
+            parts = os.path.basename(f).split('_')
+            typ = parts[0]
+            try:
+                file_values = MmapedDict.read_all_values_from_file(f)
+            except FileNotFoundError:
+                if typ == 'gauge' and parts[1].startswith('live'):
+                    # Files for 'live*' gauges can be deleted between the glob of collect
+                    # and now (via a mark_process_dead call) so don't fail if
+                    # the file is missing
+                    continue
+                raise
+            for key, value, timestamp, _ in file_values:
+                metric_name, name, labels, labels_key, help_text = _parse_key(key)
+
+                metric = metrics.get(metric_name)
+                if metric is None:
+                    metric = Metric(metric_name, help_text, typ)
+                    metrics[metric_name] = metric
+
+                if typ == 'gauge':
+                    pid = parts[2][:-3]
+                    metric._multiprocess_mode = parts[1]
+                    metric.add_sample(name, labels_key + (('pid', pid),), value, timestamp)
+                else:
+                    # The duplicates and labels are fixed in the next for.
+                    metric.add_sample(name, labels_key, value)
+        return metrics
+
+    @staticmethod
+    def _accumulate_metrics(metrics, accumulate):
+        for metric in metrics.values():
+            samples = defaultdict(float)
+            sample_timestamps = defaultdict(float)
+            buckets = defaultdict(lambda: defaultdict(float))
+            samples_setdefault = samples.setdefault
+            for s in metric.samples:
+                name, labels, value, timestamp, exemplar, native_histogram_value = s
+                if metric.type == 'gauge':
+                    without_pid_key = (name, tuple(l for l in labels if l[0] != 'pid'))
+                    if metric._multiprocess_mode in ('min', 'livemin'):
+                        current = samples_setdefault(without_pid_key, value)
+                        if value < current:
+                            samples[without_pid_key] = value
+                    elif metric._multiprocess_mode in ('max', 'livemax'):
+                        current = samples_setdefault(without_pid_key, value)
+                        if value > current:
+                            samples[without_pid_key] = value
+                    elif metric._multiprocess_mode in ('sum', 'livesum'):
+                        samples[without_pid_key] += value
+                    elif metric._multiprocess_mode in ('mostrecent', 'livemostrecent'):
+                        current_timestamp = sample_timestamps[without_pid_key]
+                        timestamp = float(timestamp or 0)
+                        if current_timestamp < timestamp:
+                            samples[without_pid_key] = value
+                            sample_timestamps[without_pid_key] = timestamp
+                    else:  # all/liveall
+                        samples[(name, labels)] = value
+
+                elif metric.type == 'histogram':
+                    # A for loop with early exit is faster than a genexpr
+                    # or a listcomp that ends up building unnecessary things
+                    for l in labels:
+                        if l[0] == 'le':
+                            bucket_value = float(l[1])
+                            # _bucket
+                            without_le = tuple(l for l in labels if l[0] != 'le')
+                            buckets[without_le][bucket_value] += value
+                            break
+                    else:  # did not find the `le` key
+                        # _sum/_count
+                        samples[(name, labels)] += value
+                else:
+                    # Counter and Summary.
+                    samples[(name, labels)] += value
+
+            # Accumulate bucket values.
+            if metric.type == 'histogram':
+                for labels, values in buckets.items():
+                    acc = 0.0
+                    for bucket, value in sorted(values.items()):
+                        sample_key = (
+                            metric.name + '_bucket',
+                            labels + (('le', floatToGoString(bucket)),),
+                        )
+                        if accumulate:
+                            acc += value
+                            samples[sample_key] = acc
+                        else:
+                            samples[sample_key] = value
+                    if accumulate:
+                        samples[(metric.name + '_count', labels)] = acc
+
+            # Convert to correct sample format.
+            metric.samples = [Sample(name_, dict(labels), value) for (name_, labels), value in samples.items()]
+        return metrics.values()
+
+    def collect(self):
+        files = glob.glob(os.path.join(self._path, '*.db'))
+        return self.merge(files, accumulate=True)
+
+
+_LIVE_GAUGE_MULTIPROCESS_MODES = {m for m in Gauge._MULTIPROC_MODES if m.startswith('live')}
+
+
+def mark_process_dead(pid, path=None):
+    """Do bookkeeping for when one process dies in a multi-process setup."""
+    if path is None:
+        path = os.environ.get('PROMETHEUS_MULTIPROC_DIR', os.environ.get('prometheus_multiproc_dir'))
+    for mode in _LIVE_GAUGE_MULTIPROCESS_MODES:
+        for f in glob.glob(os.path.join(path, f'gauge_{mode}_{pid}.db')):
+            os.remove(f)