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How to use requests_csv method in locust

Best Python code snippet using locust

data_serializer.py

Source:data_serializer.py

1import sys2import pickle3import pandas as pd4sys.path.append("../..")5from src.utility.utility_functions import *6def load_network_node_from_csv_file_and_save_it_to_pickle_file(path_to_csv: str):7    all_nodes = []8    nodes_csv = pd.read_csv(path_to_csv)9    num_of_nodes = nodes_csv.shape[0]10    print(f"[INFO] num_of_nodes {nodes_csv.shape}")11    print(nodes_csv.head(2))12    for idx in range(num_of_nodes):13        node = Pos()14        node.node_id = int(nodes_csv.iloc[idx]["id"])15        node.lon = nodes_csv.iloc[idx]["lng"]16        node.lat = nodes_csv.iloc[idx]["lat"]17        all_nodes.append(node)18    path_to_pickle = path_to_csv.replace(".csv", ".pickle")19    with open(path_to_pickle, 'wb') as f:20        pickle.dump(all_nodes, f)21def load_path_table_from_csv_file_and_save_it_to_pickle(path_to_csv: str):22    path_table_csv = pd.read_csv(path_to_csv, index_col=0).values23    path_to_pickle = path_to_csv.replace(".csv", ".pickle")24    with open(path_to_pickle, 'wb') as f:25        pickle.dump(path_table_csv, f)26def load_request_data_from_csv_file_and_save_it_to_pickle_file(path_to_csv: str):27    all_requests = []28    requests_csv = pd.read_csv(path_to_csv)29    num_of_requests = requests_csv.shape[0]30    print(f"[INFO] num_of_requests {requests_csv.shape}")31    print(requests_csv.head(2))32    for idx in tqdm(range(num_of_requests), "loading requests"):33        request = Request()34        request.origin_node_id = int(requests_csv.iloc[idx]["onid"])35        request.destination_node_id = int(requests_csv.iloc[idx]["dnid"])36        request.request_time_date = requests_csv.iloc[idx]["ptime"]37        request.request_time_ms = compute_the_accumulated_seconds_from_0_clock(request.request_time_date) * 100038        all_requests.append(request)39    path_to_pickle = path_to_csv.replace(".csv", ".pickle")40    with open(path_to_pickle, 'wb') as f:41        pickle.dump(all_requests, f)42if __name__ == '__main__':43    vehicle_stations = f"{ROOT_PATH}/datalog-gitignore/map-data/stations-101.csv"44    network_nodes = f"{ROOT_PATH}/datalog-gitignore/map-data/nodes.csv"45    mean_table = f"{ROOT_PATH}/datalog-gitignore/map-data/mean-table.csv"46    dist_table = f"{ROOT_PATH}/datalog-gitignore/map-data/dist-table.csv"47    path_table = f"{ROOT_PATH}/datalog-gitignore/map-data/path-table.csv"48    for node_file in [vehicle_stations, network_nodes]:49        load_network_node_from_csv_file_and_save_it_to_pickle_file(node_file)50    for table_file in [mean_table, dist_table, path_table]:51        load_path_table_from_csv_file_and_save_it_to_pickle(table_file)52    for day in ["03", "04", "05", "10", "11", "12", "17", "19", "24", "25", "26"]:53        taxi_data = f"{ROOT_PATH}/datalog-gitignore/taxi-data/manhattan-taxi-201605{day}-peak.csv"...

process_requests.py

Source:process_requests.py

1import os2from tess_requests import Request3def process(folder):4    requests_csv = []5    # folder = '/Users/wolfson/Desktop/homework/molbi/molbi_asv'  # testing6    directory = fr'{folder}'7    for entry in os.scandir(directory):8        if (entry.path.endswith('.jpg')) and entry.is_file():9            obj = Request(entry.path)10            print(entry)11            for _ in obj.csv_data:12                requests_csv.append(_)13            os.rename(entry, f'{directory}/{obj.case_number}.jpg')...

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