<gh_stars>100-1000
import json
import pandas as pd
from time import time

from django.urls import reverse
from django.http import HttpResponse
from django.http import HttpResponseRedirect
from django.shortcuts import render

import synthesizer.lib.DataSynthesizerWrapper as wrapper
from DataSynthesizer.lib.utils import read_json_file
from .models import DataDescriberUI
from .models import save_uploaded_file
from .models import getSizeOfDataset


def index(request):
    play_data_list = ["adult_reduced","adult_with_missing_values","compas_reduced"]
    context = {"passed_play_data": play_data_list}
    # NOTICE: no .csv suffix in current passed file name
    server_data_names_map = {"adult_reduced": "AR", "adult_with_missing_values": "AM", "compas_reduced": "CR"}
    # create a time stamp for current uploading
    data_server_path = "./media/"
    play_data_server_path = "./playdata/synthesizer/"
    cur_time_stamp = str(int(time()*1e7))
    upload_data_size_threshold = 20
    if request.POST:
        if request.FILES:
            # get user upload file
            upload_csvfile = request.FILES['user_upload_data']
            current_data_name = data_server_path + cur_time_stamp
            save_uploaded_file(upload_csvfile, current_data_name)
            # get the size of uploaded data
            upload_data_size = getSizeOfDataset(current_data_name)
            context_size = {"passed_play_data": play_data_list, "passed_size_flag":"false"}
            # if upload data size less than the threshold, back to upload page and alert user
            if upload_data_size <= upload_data_size_threshold:
                return render(request, "synthesizer/index.html", context_size)

            request.session['passed_data_name'] = current_data_name
        else:
            selected_data = request.POST["dataset_select"]
            # create a copy of current play data set on server to allow differentiate multiple users at the same time
            cur_data = pd.read_csv(play_data_server_path + selected_data + ".csv")
            new_stamped_name = data_server_path + server_data_names_map[selected_data] + cur_time_stamp
            cur_data.to_csv(new_stamped_name + ".csv", index=False)
            request.session['passed_data_name'] = new_stamped_name
        return HttpResponseRedirect(reverse('synthesizer:proc_data_dash'))
    else:
        return render(request, "synthesizer/index.html", context)

def proc_data_dash(request):
    passed_data_name = request.session.get('passed_data_name')
    json_cate_info = wrapper.get_dataset_info(passed_data_name + ".csv")
    att_list = json_cate_info["attribute_list"]
    cat_att_list = json_cate_info["categorical_attributes"]
    key_att_list = json_cate_info['candidate_attributes']
    # json_header = []
    # for i in range(len(att_list)):
    #     json_header.append({"data": str(att_list[i])})
    # initialize json data and header for dataTables
    json_data_table = []
    json_header_table = []
    for i in range(len(att_list)):
        json_data_table.append({"data": str(att_list[i])})
        json_header_table.append({"title": str(att_list[i]), "targets": i})

    request.session['passed_json_columns'] = json_data_table
    request.session['passed_column_name'] = att_list

    data_type_list = []
    for i in att_list:
        data_type_list.append(json_cate_info["attribute_datatypes"][i])
    tuple_n = json_cate_info["number_of_tuples"]

    context = {'passed_data_name': passed_data_name, "passed_json_columns": json_data_table,
               "passed_column_name": att_list, "passed_json_columns_header": json_header_table,
               "passed_cat_atts": cat_att_list, "passed_att_types": data_type_list, "tuple_n": tuple_n,
               "passed_key_atts": key_att_list}

    return render(request, "synthesizer/proc_data_dash.html", context)


def proc_json_processing(request):
    passed_data_name = request.session.get('passed_data_name')

    up_data = DataDescriberUI()
    up_data.read_dataset_from_csv(passed_data_name)
    up_data.get_json_data()

    total_json = up_data.json_data

    return HttpResponse(total_json, content_type='application/json')


def res_json_processing(request):
    passed_data_name = request.session.get('passed_data_name')

    up_data = DataDescriberUI()
    up_data.read_dataset_from_csv(passed_data_name)
    up_data.get_json_data()

    total_json = up_data.json_data

    return HttpResponse(total_json, content_type='application/json')


def res_json_processing_after(request):
    passed_data_name = request.session.get('passed_data_name')

    up_data = DataDescriberUI()
    up_data.read_dataset_from_csv('{}_synthetic_data'.format(passed_data_name))
    up_data.get_json_data()

    total_json = up_data.json_data

    return HttpResponse(total_json, content_type='application/json')


def res_json_processing_plot(request):
    passed_data_name = request.session.get('passed_data_name')
    description_file = passed_data_name + "_plot.json"
    plot_json = read_json_file(description_file)
    return HttpResponse(json.dumps(plot_json), content_type='application/json')


def synthesizer_display(request):
    passed_data_name = request.session.get('passed_data_name')
    passed_json_columns = request.session.get('passed_json_columns')
    passed_column_name = request.session.get('passed_column_name')
    # generate dataTable data
    json_header_table = []
    for i in range(len(passed_column_name)):
        json_header_table.append({"title": str(passed_column_name[i]), "targets": i})


    mode_name = request.session.get('mode_name')
    passed_download_data = request.session.get('passed_download_data')
    passed_download_desp = request.session.get('passed_download_desp')


    context = {'passed_data_name': passed_data_name, "passed_json_columns": passed_json_columns,
               "passed_json_columns_header": json_header_table, "mode_name": mode_name,
               "passed_download_data": passed_download_data, "passed_download_desp": passed_download_desp}

    return render(request, 'synthesizer/com_data.html', context)


def com_data(request):
    passed_data_name = request.session.get('passed_data_name')
    passed_json_columns = request.session.get('passed_json_columns')
    passed_column_name = request.session.get('passed_column_name')
    # generate dataTable data
    json_header_table = []
    for i in range(len(passed_column_name)):
        json_header_table.append({"title": str(passed_column_name[i]), "targets": i})

    # get user input
    chosen_mode = request.POST['chose_mode']
    mode_id = chosen_mode.replace("mode", "")
    json_parameter = {}
    json_parameter["chose_mode"] = chosen_mode
    json_parameter["tuple_n"] = request.POST['tuple_N_m' + mode_id]
    json_parameter["categorical_atts"] = request.POST.getlist('checks_m' + mode_id)
    json_parameter["candidate_atts"] = request.POST.getlist('key_checks_m' + mode_id)
    # json_parameter["categorical_threshold"] = request.POST['cate_threshold_m' + mode_id]
    json_parameter["seed"] = request.POST['seed_m' + mode_id]

    mode_name = ""
    if mode_id != "1":
        json_parameter["histogram_size"] = request.POST['hist_size_m' + mode_id]
        json_parameter["epsilon"] = request.POST['epsilon_m' + mode_id]
        user_type_atts = {}
        for atti in passed_column_name:
            user_type_atts[atti] = request.POST[atti + "_m" + mode_id]

        json_parameter["type_atts"] = user_type_atts
    if mode_id == "3":
        json_parameter["max_degree"] = request.POST['max_degree']
    if mode_id == "1":
        mode_name = "Random Mode"
    if mode_id == "2":
        mode_name = "Independent Attribute Mode"
    if mode_id == "3":
        mode_name = "Correlated Attribute Mode"
    request.session["mode_name"] = mode_name
    # save user input parameters to server
    json_parameter_outputfn = passed_data_name + "_parameters.json"
    with open(json_parameter_outputfn, 'w') as outfile:
        json.dump(json_parameter, outfile, indent=4)

    wrapper.generate_data(passed_data_name)

    synthetic_data_name = passed_data_name + "_synthetic_data.csv"
    description_file = passed_data_name + "_description.json"
    wrapper.get_plot_data(passed_data_name + ".csv", synthetic_data_name, description_file)

    passed_download_data = synthetic_data_name.split("/media/")[1]
    passed_download_desp = description_file.split("/media/")[1]

    request.session["passed_download_data"] = passed_download_data
    request.session["passed_download_desp"] = passed_download_desp

    context = {'passed_data_name': passed_data_name, "passed_json_columns": passed_json_columns,
               "passed_json_columns_header": json_header_table, "mode_name": mode_name,
               "passed_download_data": passed_download_data, "passed_download_desp": passed_download_desp}
    return render(request, 'synthesizer/com_data.html', context)


def com_histogram(request):
    passed_data = request.session.get('passed_data_name')
    passed_json_columns = request.session.get('passed_json_columns')
    passed_column_name = request.session.get('passed_column_name')
    mode_name = request.session.get('mode_name')
    passed_download_data = request.session.get('passed_download_data')
    passed_download_desp = request.session.get('passed_download_desp')

    # get categorical attributes list
    cate_atts = wrapper.get_categorical_attributes(passed_data + '_plot.json')
    draw_atts = wrapper.get_drawable_attributes(passed_data + '_plot.json')
    context = {'passed_data_name': passed_data, "passed_json_columns": passed_json_columns,
               "passed_column_name": passed_column_name, "cate_column_name": cate_atts,
               "mode_name": mode_name, "drawable_atts": draw_atts,
               "passed_download_data": passed_download_data, "passed_download_desp": passed_download_desp}
    return render(request, 'synthesizer/com_histogram.html', context)


def com_hitmap(request):
    passed_data = request.session.get('passed_data_name')
    passed_json_columns = request.session.get('passed_json_columns')
    passed_column_name = request.session.get('passed_column_name')
    mode_name = request.session.get('mode_name')
    passed_download_data = request.session.get('passed_download_data')
    passed_download_desp = request.session.get('passed_download_desp')

    context = {'passed_data_name': passed_data, "passed_json_columns": passed_json_columns,
               "passed_column_name": passed_column_name, "mode_name": mode_name,
               "passed_download_data": passed_download_data, "passed_download_desp": passed_download_desp}
    return render(request, 'synthesizer/com_hitmap.html', context)
