from services import io_services, log_services, data_services

def main():
    # File paths used to save and load the data.
    raw_data_path = "data/test-data.csv"
    rps_save_path = "data/results/readings-per-sec.csv"
    rps_above_thresh = "data/results/readings_above_threshold.csv"
    flicker_list = "data/results/flicker_list.csv"
    filtered_flickers = "data/results/filtered_flicker_entries.csv"

    # Step 1
    # ======
    # Load the raw data, taken from the exported database.
    raw_data = io_services.load_raw_data(raw_data_path)
    # log_services.print_list(raw_data)

    # Step 2
    # ======
    # Tally-up how many readings occured for each second in the
    # raw data. For example, for the period between 2021-04-23
    # 07:03:57 and 2021-04-23 07:03:58, how many readings did the
    # system take? Was it 1, 3, Etc.
    time_tallies = data_services.tally_readings_per_second(raw_data)
    # log_services.print_dictionary(time_tallies)

    # Step 3
    # ======
    # Count the number of tallies derived from step 2. So, how
    # many time did the system take 2 readings-per-second, how many
    # times did the system 3 readings-per-second Etc.
    rps_totals = data_services.total_count_for_each_reading_per_second(time_tallies)
    # log_services.print_dictionary(rps_totals)
    io_services.save_rps_totals(rps_totals, rps_save_path)

    # Step 4
    # ======
    # List out all the time periods which had more than the
    # specified readings-per-second. The default value is any time
    # period with more than 4 readings-per-second but you can change
    # it (it's a function argument).
    rps_above_hertz = data_services.get_rps_above(4, time_tallies)
    # log_services.print_list(rps_above_two)
    io_services.save_rps_above_threshold(rps_above_hertz, rps_above_thresh)

    # Step 5
    # ======
    # Using the list of time periods derived in step 4
    # (rps_above_hertz), create a new list from the raw data (step
    # 1). Filter out the time periods created in step 4 and include
    # all their readings for that time period (I.E. second). An
    # example of this is: The list created in step 4 shows the time
    # period between 2021-04-23 07:03:57 and 2021-04-23 07:03:58 has 4
    # readings so note the (start) time and how the readings recorded
    # in that period.
    flicker_entries = data_services.find_flickers(rps_above_hertz, raw_data)
    # log_services.print_dictionary(flicker_tallies)
    io_services.save_rps_totals(flicker_entries, flicker_list)

    # Step 6
    # =======
    # This step filters out the time periods which pass the hertz
    # threshold to those which have at least one reading in its (1
    # second period) grouping to cause the light to turn on in the
    # gallery ('gallery1'). If this list contains any readings, you
    # can review them to make sure the light doesn't turn on and off
    # enough times to potentially cause a photo-epileptic seizure.
    filtered_flicker_entries = data_services.find_readings_with_lights_on(flicker_entries)
    # log_services.print_list(filtered_flicker_entries)
    io_services.save_filtered_flickers(filtered_flicker_entries, filtered_flickers)
    
if __name__ == "__main__":
    main()