Blocking-JavaScript-without-Breaking-the-Web/requestDistribution.py at main · hadiamjad/Blocking-JavaScript-without-Breaking-the-Web · GitHub

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import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
import sys
from urllib.parse import urlparse
import os


def checkResExist(df, request_id):
    return request_id in df["request_id"].values


def getInitiatorURL(stack):
    if len(stack["callFrames"]) != 0:
        return stack["callFrames"][0]["url"]
    else:
        return getInitiatorURL(stack["parent"])


def extractDigits(lst):
    return list(map(lambda el: [el], lst))


def countDistribution(experiment):
    df1 = pd.DataFrame(
        extractDigits(
            os.listdir("" + experiment + "/webpage-crawler-extension/server/output")
        ),
        columns=["website"],
    )
    fold = "" + experiment + "/webpage-crawler-extension/"
    website = {}
    for j in df1.index:
        if df1["website"][j] not in website:
            website[df1["website"][j]] = [0, 0, 0, 0]
        # try:
        df = pd.read_json(
            fold + "server/output/" + df1["website"][j] + "/label_request.json"
        )
        res = pd.read_json(
            fold + "server/output/" + df1["website"][j] + "/responses.json", lines=True
        )
        for i in df.index:
            if checkResExist(res, df["request_id"][i]):
                if (
                    df["easylistflag"][i] == 1
                    or df["easyprivacylistflag"][i] == 1
                    or df["ancestorflag"][i] == 1
                ):
                    website[df1["website"][j]][0] += 1
                else:
                    website[df1["website"][j]][1] += 1
        df = pd.read_json(
            "Control/webpage-crawler-extension/server/output/"
            + df1["website"][j]
            + "/label_request.json"
        )
        for i in df.index:
            if (
                df["easylistflag"][i] == 1
                or df["easyprivacylistflag"][i] == 1
                or df["ancestorflag"][i] == 1
            ):
                website[df1["website"][j]][2] += 1
            else:
                website[df1["website"][j]][3] += 1
        # except:
        #         pass
    data = {
        "Website": list(website.keys()),
        "Tracking": [(item[2] - item[0]) * 100 / item[2] for item in website.values()],
        "Functional": [
            (item[3] - item[1]) * 100 / item[3] for item in website.values()
        ],
    }

    # create a pandas dataframe from the dictionary
    df = pd.DataFrame(data)
    # Use the melt function to unpivot the dataframe
    df = pd.melt(df, id_vars=["Website"], var_name="Function", value_name="Value")
    # plotting the bar plot
    colors = ["#E11916", "#3FD72D"]
    sns.displot(
        df, x="Value", hue="Function", multiple="dodge", palette=colors, bins=10
    )
    plt.show()
    plt.savefig("Figures/DistributionPlot.pdf")


def main():
    countDistribution(sys.argv[1])


main()