import sys
import os
import time
import _thread
import argparse
import requests
import subprocess
import numpy as np
import pandas as pd
import threading
from concurrent.futures import ThreadPoolExecutor
from concurrent.futures import as_completed

parser = argparse.ArgumentParser(description="Upload images")
parser.add_argument("--num_request", type=int, help="one image per request")
parser.add_argument(
    "--url",
    type=str,
    help="URL to the backend server, e.g. http://3.86.108.221/xxxx.php",
)
parser.add_argument(
    "--image_folder",
    type=str,
    help="the path of the folder where images are saved on your local machine",
)
parser.add_argument(
    "--prediction_file", type=str, help="the path of the classification results file"
)
args = parser.parse_args()

num_request = args.num_request
url = args.url
image_folder = args.image_folder
prediction_file = args.prediction_file

prediction_df = pd.read_csv(prediction_file)
responses = 0
err_responses = 0
correct_predictions = 0
wrong_predictions = 0


def send_one_request(image_path):
    global prediction_df, responses, err_responses, correct_predictions, wrong_predictions
    # Define http payload, "myfile" is the key of the http payload
    file = {"inputFile": open(image_path, "rb")}
    response = requests.post(url, files=file)

    # Print error message if failed
    if response.status_code != 200:
        print("sendErr: " + response.url)
        err_responses += 1
    else:
        filename = image_path.split("/")[-1]
        image_msg = filename + " uploaded!"
        msg = image_msg + "\n" + "Classification result: " + response.text
        print(msg)
        responses += 1
        correct_result = prediction_df.loc[
            prediction_df["Image"] == filename.split(".")[0], "Results"
        ].iloc[0]
        if correct_result == response.text.split(":")[1]:
            correct_predictions += 1
        else:
            wrong_predictions += 1


num_max_workers = 100
image_path_list = []
test_start_time = time.time()

for i, name in enumerate(os.listdir(image_folder)):
    if i == num_request:
        break
    image_path_list.append(image_folder + name)

with ThreadPoolExecutor(max_workers=num_max_workers) as executor:
    executor.map(send_one_request, image_path_list)

print("Waiting ... ")
while True:
    print(".")
    test_duration = time.time() - test_start_time
    if num_request == (responses + err_responses) or test_duration > 300:
        print(f"+++++ Test Result Statistics +++++")
        print(f"Total number of requests: {num_request}")
        print(f"Total number of requests completed successfully: {responses}")
        print(f"Total number of failed requests: {err_responses}")
        print(f"Total number of correct predictions : {correct_predictions}")
        print(f"Total number of wrong predictions: {wrong_predictions}")
        print(f"Total Test Duration: {test_duration} (seconds)")
        print("++++++++++++++++++++++++++++++++++++")
        break
    time.sleep(1)