import csv
import toml
import sys
import os
import requests
from typing import List, Union
from datetime import datetime, timezone, timedelta

# LIMITATIONS - 10k rows per VTScada query - reccommend limit to minimum 10 second intervals for daily values

# ----------------------
#  Classes
# ----------------------

# HistoricalTag
# ----------------------


class HistoricalTag:
    def __init__(self,
                 row: int,
                 tag_type: str,
                 name_source: str,
                 name_dest: str,
                 scale_factor: float,
                 interval: int,
                 precision: int,
                 deadband: float):
        self.row = row
        self.tag_type = tag_type
        self.name_source = name_source
        self.name_dest = name_dest
        self.scale_factor = scale_factor
        self.interval = interval
        self.precision = precision
        self.deadband = deadband

    def __repr__(self):
        return f"({self.row}, {self.tag_type}, {self.name_source}, {self.name_dest}, {self.scale_factor}, {self.interval}, {self.precision}, {self.deadband})"


# ----------------------
#  Functions
# ----------------------

# compress_and_scale_real()
# ----------------------
def compress_and_scale_real(values: List[Union[int, float, None]], deadband: float, scale_factor: float, precision: int) -> List[Union[int, float, None]]:
    compressed_values = []
    working_value = None

    for value_pair in values:
        timestamp, value = value_pair

        if value is None:
            continue

        if working_value is None or abs(value - working_value) > deadband:
            working_value = value
            scaled_value = round(value * scale_factor, precision)
            compressed_values.append((timestamp, scaled_value))

    return compressed_values

# compress_boolean()
# ----------------------


def compress_boolean(values: List[Union[int, float, None]]) -> List[Union[int, float, None]]:
    compressed_values = []
    working_value = None

    for value_pair in values:
        timestamp, value = value_pair

        if value is None:
            continue

        if working_value is None or value != working_value:
            working_value = value
            compressed_values.append((timestamp, value))

    return compressed_values

# create_directory()
# ----------------------


def create_directory(path):
    if not os.path.exists(path):
        os.makedirs(path)

# print_text()
# ----------------------


def print_text(text: str):
    print(r'-------------------------------------------------------------------------------------------------------')
    print(text)
    print(r'-------------------------------------------------------------------------------------------------------')

# query_vtscada_tag()
# ----------------------


def query_vtscada_tag(historical_tag: HistoricalTag, ft_start_time: datetime, ft_end_time: datetime) -> List[Union[int, float, None]]:
    # Query average only for real values (Analog in VTScada)
    if historical_tag.tag_type == "real":
        value_string = ":Value:Average"
    # Otherwise, query the value at the start of the interval
    else:
        value_string = ":Value:ValueAtStart"

    query = "SELECT Timestamp, '" + historical_tag.name_source + value_string + "' FROM History_" + \
        str(historical_tag.interval) + "s" + " WHERE Timestamp BETWEEN " + \
        ft_start_time + " AND " + ft_end_time

    url = "http://" + server + ":" + realm_port + \
        "/" + realm_name + "/REST/SQLQuery?query=" + query

    # print_text(url)

    response = requests.get(url, auth=(application_user, application_pass))
    returned = response.json()

    return returned['results']['values']

# query_vtscada()
# ----------------------


def query_vtscada(historical_tags: List[HistoricalTag], start_time: datetime, end_time: datetime):
    current_start_time = start_time
    current_end_time = start_time + timedelta(days=1)

    while current_start_time < end_time:
        print("Querying data for: " + str(current_start_time.year) + " " +
              str(current_start_time.month) + " " + str(current_start_time.day))
        dir_path = output_path + str(start_time.year) + "\\"
        create_directory(dir_path)

        ft_start_time = "'" + \
            str(current_start_time.astimezone(timezone.utc)) + "'"
        ft_end_time = "'" + \
            str(current_end_time.astimezone(timezone.utc)) + "'"

        tag_mappings = []

        for tag in historical_tags:
            values = query_vtscada_tag(tag, ft_start_time, ft_end_time)
            output_file = prepare_file_for_tag(
                tag, values, dir_path, current_end_time)

            if output_file != "":
                tag_mappings.append((output_file, tag.name_dest))

        write_tagmapping_to_file(
            dir_path + "TagMapping.csv", tag_mappings)

        current_start_time += timedelta(days=1)
        current_end_time += timedelta(days=1)

# prepare_file_for_tag()
# ----------------------


def prepare_file_for_tag(tag: HistoricalTag, values: List[Union[int, float, None]], dir_path: str, current_end_time: datetime) -> str:
    if values is None:
        print("No values found")
        return ""
    else:
        output_file = ""

        if tag.tag_type == "real" or tag.tag_type == "integer":
            compressed_values = compress_and_scale_real(
                values, tag.deadband, tag.scale_factor, tag.precision)
        else:
            compressed_values = compress_boolean(values)

        if len(compressed_values) != 0:
            output_file = tag.name_source.replace('\\', '_') + "_" + str(current_end_time.year) + str(
                current_end_time.month) + str(current_end_time.day) + ".csv"
            full_output_file = dir_path + output_file
            write_values_to_file(full_output_file, compressed_values)

        return output_file

# write_values_to_file()
# ----------------------


def write_values_to_file(output_file: str, values: List[Union[int, float, None]]):
    with open(output_file, mode='w', newline='', encoding='utf-8') as csvfile:
        csv_writer = csv.writer(csvfile)

        for value_pair in values:
            timestamp, value = value_pair
            if value is not None:
                utc_dt = datetime.utcfromtimestamp(timestamp)
                formatted_timestamp = utc_dt.strftime(
                    '%Y-%m-%d %H:%M:%S.%f')[:-3]
                csv_writer.writerow([formatted_timestamp, value])

# write_tagmappings_to_file()
# ----------------------


def write_tagmapping_to_file(output_file: str, tag_mappings: List[str]):
    with open(output_file, mode='a', newline='', encoding='utf-8') as csvfile:
        csv_writer = csv.writer(csvfile)

        for mapping in tag_mappings:
            csv_writer.writerow(mapping)


# read_tags()
# ----------------------
# Read in the list of tags and set the mapping parameters for each tag and construct the groupings required for the
# query
def read_tags(file_path: str) -> List[HistoricalTag]:
    historical_tags = []

    with open(file_path, mode='r', encoding='utf-8-sig') as csvfile:
        csv_reader = csv.reader(csvfile, delimiter=',')
        next(csv_reader)  # Skip the header row

        for row, line in enumerate(csv_reader):
            name_source, name_dest, tag_type, scale_factor, interval, precision, deadband = line
            tag = HistoricalTag(row=row+1, tag_type=tag_type, name_source=name_source, name_dest=name_dest,
                                scale_factor=float(scale_factor), interval=int(interval), precision=int(precision), deadband=float(deadband))
            historical_tags.append(tag)

    return historical_tags

# ----------------------
#  Main Section
# ----------------------


print(r' _    _ _____  _____ _______ ____  _____  _____ _____          _        _______ ____   ____  _       _____ ')
print(r'| |  | |_   _|/ ____|__   __/ __ \|  __ \|_   _/ ____|   /\   | |      |__   __/ __ \ / __ \| |     / ____|')
print(r'| |__| | | | | (___    | | | |  | | |__) | | || |       /  \  | |         | | | |  | | |  | | |    | (___  ')
print(r'|  __  | | |  \___ \   | | | |  | |  _  /  | || |      / /\ \ | |         | | | |  | | |  | | |     \___ \ ')
print(r'| |  | |_| |_ ____) |  | | | |__| | | \ \ _| || |____ / ____ \| |____     | | | |__| | |__| | |____ ____) |')
print(r'|_|  |_|_____|_____/   |_|  \____/|_|  \_\_____\_____/_/    \_\______|    |_|  \____/ \____/|______|_____/ ')

config = toml.load("setup.toml")

tags_path = config['system']['tags_path']
output_path = config['system']['output_path']
system_timezone = config['system']['system_timezone']
application_user = config['user']['application_user']
application_pass = config['user']['application_pass']

server = config['vtscada']['server_name']
realm_port = config['vtscada']['realm_port']
realm_name = config['vtscada']['realm_name']

if len(sys.argv) == 4:
    query_type = sys.argv[1]

    year, month, day = map(int, str(sys.argv[2]).split("-"))
    start_time = datetime(year, month, day, 0, 0, 0)
    year, month, day = map(int, str(sys.argv[3]).split("-"))
    end_time = datetime(year, month, day, 0, 0, 0)

    print("")

    historical_tags = read_tags(tags_path)

    for tag in historical_tags:
        print(tag)

    if query_type == "VTScada":
        print_text('VTScada Data Query')
        query_vtscada(historical_tags, start_time, end_time)
    elif query_type == "AVEVA":
        print_text('AVEVA Historian - Not Implemented')
    elif query_type == "ClearSCADA":
        print_text('ClearSCADA - Not Implemented')
else:
    print("Invalid arguments!")