68 lines
2.4 KiB
Python
68 lines
2.4 KiB
Python
from locust import HttpUser, TaskSet, task, between, events
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import csv
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import random
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from collections import defaultdict
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import os
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class OSRMTasks(TaskSet):
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def on_start(self):
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random.seed(42)
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self.coordinates = []
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self.tracks = defaultdict(list)
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gps_traces_file_path = os.path.expanduser('~/gps_traces.csv')
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with open(gps_traces_file_path, 'r') as file:
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reader = csv.DictReader(file)
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for row in reader:
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coord = (float(row['Latitude']), float(row['Longitude']))
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self.coordinates.append(coord)
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self.tracks[row['TrackID']].append(coord)
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self.track_ids = list(self.tracks.keys())
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@task
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def get_route(self):
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start = random.choice(self.coordinates)
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end = random.choice(self.coordinates)
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start_coord = f"{start[1]:.6f},{start[0]:.6f}"
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end_coord = f"{end[1]:.6f},{end[0]:.6f}"
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self.client.get(f"/route/v1/driving/{start_coord};{end_coord}?overview=full&steps=true", name="route")
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@task
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def get_table(self):
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num_coords = random.randint(3, 50)
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selected_coords = random.sample(self.coordinates, num_coords)
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coords_str = ";".join([f"{coord[1]:.6f},{coord[0]:.6f}" for coord in selected_coords])
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self.client.get(f"/table/v1/driving/{coords_str}", name="table")
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@task
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def get_match(self):
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num_coords = random.randint(3, 50)
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track_id = random.choice(self.track_ids)
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track_coords = self.tracks[track_id][:num_coords]
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coords_str = ";".join([f"{coord[1]:.6f},{coord[0]:.6f}" for coord in track_coords])
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self.client.get(f"/match/v1/driving/{coords_str}?steps=true", name="match")
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@task
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def get_nearest(self):
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coord = random.choice(self.coordinates)
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coord_str = f"{coord[1]:.6f},{coord[0]:.6f}"
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self.client.get(f"/nearest/v1/driving/{coord_str}", name="nearest")
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@task
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def get_trip(self):
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num_coords = random.randint(2, 10)
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selected_coords = random.sample(self.coordinates, num_coords)
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coords_str = ";".join([f"{coord[1]:.6f},{coord[0]:.6f}" for coord in selected_coords])
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self.client.get(f"/trip/v1/driving/{coords_str}?steps=true", name="trip")
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class OSRMUser(HttpUser):
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tasks = [OSRMTasks]
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wait_time = between(0.01, 0.1)
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