`ultralytics 8.2.68` new HUB GCP region latency tests (#14753)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com>pull/14754/head v8.2.68
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# Ultralytics YOLO 🚀, AGPL-3.0 license |
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import concurrent.futures |
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import statistics |
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import time |
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from typing import List, Optional, Tuple |
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import requests |
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class GCPRegions: |
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""" |
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A class for managing and analyzing Google Cloud Platform (GCP) regions. |
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This class provides functionality to initialize, categorize, and analyze GCP regions based on their |
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geographical location, tier classification, and network latency. |
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Attributes: |
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regions (Dict[str, Tuple[int, str, str]]): A dictionary of GCP regions with their tier, city, and country. |
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Methods: |
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tier1: Returns a list of tier 1 GCP regions. |
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tier2: Returns a list of tier 2 GCP regions. |
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lowest_latency: Determines the GCP region(s) with the lowest network latency. |
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Examples: |
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>>> from ultralytics.hub.google import GCPRegions |
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>>> regions = GCPRegions() |
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>>> lowest_latency_region = regions.lowest_latency(verbose=True, attempts=3) |
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>>> print(f"Lowest latency region: {lowest_latency_region[0][0]}") |
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""" |
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def __init__(self): |
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"""Initializes the GCPRegions class with predefined Google Cloud Platform regions and their details.""" |
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self.regions = { |
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"asia-east1": (1, "Taiwan", "China"), |
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"asia-east2": (2, "Hong Kong", "China"), |
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"asia-northeast1": (1, "Tokyo", "Japan"), |
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"asia-northeast2": (1, "Osaka", "Japan"), |
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"asia-northeast3": (2, "Seoul", "South Korea"), |
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"asia-south1": (2, "Mumbai", "India"), |
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"asia-south2": (2, "Delhi", "India"), |
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"asia-southeast1": (2, "Jurong West", "Singapore"), |
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"asia-southeast2": (2, "Jakarta", "Indonesia"), |
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"australia-southeast1": (2, "Sydney", "Australia"), |
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"australia-southeast2": (2, "Melbourne", "Australia"), |
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"europe-central2": (2, "Warsaw", "Poland"), |
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"europe-north1": (1, "Hamina", "Finland"), |
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"europe-southwest1": (1, "Madrid", "Spain"), |
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"europe-west1": (1, "St. Ghislain", "Belgium"), |
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"europe-west10": (2, "Berlin", "Germany"), |
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"europe-west12": (2, "Turin", "Italy"), |
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"europe-west2": (2, "London", "United Kingdom"), |
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"europe-west3": (2, "Frankfurt", "Germany"), |
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"europe-west4": (1, "Eemshaven", "Netherlands"), |
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"europe-west6": (2, "Zurich", "Switzerland"), |
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"europe-west8": (1, "Milan", "Italy"), |
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"europe-west9": (1, "Paris", "France"), |
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"me-central1": (2, "Doha", "Qatar"), |
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"me-west1": (1, "Tel Aviv", "Israel"), |
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"northamerica-northeast1": (2, "Montreal", "Canada"), |
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"northamerica-northeast2": (2, "Toronto", "Canada"), |
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"southamerica-east1": (2, "São Paulo", "Brazil"), |
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"southamerica-west1": (2, "Santiago", "Chile"), |
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"us-central1": (1, "Iowa", "United States"), |
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"us-east1": (1, "South Carolina", "United States"), |
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"us-east4": (1, "Northern Virginia", "United States"), |
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"us-east5": (1, "Columbus", "United States"), |
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"us-south1": (1, "Dallas", "United States"), |
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"us-west1": (1, "Oregon", "United States"), |
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"us-west2": (2, "Los Angeles", "United States"), |
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"us-west3": (2, "Salt Lake City", "United States"), |
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"us-west4": (2, "Las Vegas", "United States"), |
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} |
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def tier1(self) -> List[str]: |
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"""Returns a list of GCP regions classified as tier 1 based on predefined criteria.""" |
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return [region for region, info in self.regions.items() if info[0] == 1] |
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def tier2(self) -> List[str]: |
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"""Returns a list of GCP regions classified as tier 2 based on predefined criteria.""" |
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return [region for region, info in self.regions.items() if info[0] == 2] |
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@staticmethod |
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def _ping_region(region: str, attempts: int = 1) -> Tuple[str, float, float, float, float]: |
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"""Pings a specified GCP region and returns latency statistics: mean, min, max, and standard deviation.""" |
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url = f"https://{region}-docker.pkg.dev" |
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latencies = [] |
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for _ in range(attempts): |
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try: |
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start_time = time.time() |
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_ = requests.head(url, timeout=5) |
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latency = (time.time() - start_time) * 1000 # convert latency to milliseconds |
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if latency != float("inf"): |
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latencies.append(latency) |
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except requests.RequestException: |
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pass |
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if not latencies: |
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return region, float("inf"), float("inf"), float("inf"), float("inf") |
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std_dev = statistics.stdev(latencies) if len(latencies) > 1 else 0 |
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return region, statistics.mean(latencies), std_dev, min(latencies), max(latencies) |
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def lowest_latency( |
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self, |
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top: int = 1, |
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verbose: bool = False, |
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tier: Optional[int] = None, |
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attempts: int = 1, |
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) -> List[Tuple[str, float, float, float, float]]: |
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""" |
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Determines the GCP regions with the lowest latency based on ping tests. |
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Args: |
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top (int): Number of top regions to return. |
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verbose (bool): If True, prints detailed latency information for all tested regions. |
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tier (int | None): Filter regions by tier (1 or 2). If None, all regions are tested. |
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attempts (int): Number of ping attempts per region. |
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Returns: |
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(List[Tuple[str, float, float, float, float]]): List of tuples containing region information and |
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latency statistics. Each tuple contains (region, mean_latency, std_dev, min_latency, max_latency). |
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Examples: |
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>>> regions = GCPRegions() |
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>>> results = regions.lowest_latency(top=3, verbose=True, tier=1, attempts=2) |
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>>> print(results[0][0]) # Print the name of the lowest latency region |
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""" |
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if verbose: |
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print(f"Testing GCP regions for latency (with {attempts} {'retry' if attempts == 1 else 'attempts'})...") |
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regions_to_test = [k for k, v in self.regions.items() if v[0] == tier] if tier else list(self.regions.keys()) |
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with concurrent.futures.ThreadPoolExecutor(max_workers=50) as executor: |
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results = list(executor.map(lambda r: self._ping_region(r, attempts), regions_to_test)) |
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sorted_results = sorted(results, key=lambda x: x[1]) |
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if verbose: |
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print(f"{'Region':<20} {'Location':<35} {'Tier':<5} {'Latency (ms)'}") |
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for region, mean, std, min_, max_ in sorted_results: |
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tier, city, country = self.regions[region] |
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location = f"{city}, {country}" |
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if mean == float("inf"): |
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print(f"{region:<20} {location:<35} {tier:<5} {'Timeout'}") |
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else: |
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print(f"{region:<20} {location:<35} {tier:<5} {mean:.0f} ± {std:.0f} ({min_:.0f} - {max_:.0f})") |
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print(f"\nLowest latency region{'s' if top > 1 else ''}:") |
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for region, mean, std, min_, max_ in sorted_results[:top]: |
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tier, city, country = self.regions[region] |
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location = f"{city}, {country}" |
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print(f"{region} ({location}, {mean:.0f} ± {std:.0f} ms ({min_:.0f} - {max_:.0f}))") |
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return sorted_results[:top] |
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# Usage example |
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if __name__ == "__main__": |
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regions = GCPRegions() |
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top_3_latency_tier1 = regions.lowest_latency(top=3, verbose=True, tier=1, attempts=3) |
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