#!/usr/bin/env python3 import csv import json import os import logging import re import sys import time from datetime import datetime import trakt.core from trakt import init from tinydb import Query, TinyDB from trakt.tv import TVShow # Setup logger logging.basicConfig( format='%(asctime)s %(levelname)s :: %(message)s', level=logging.INFO, datefmt='%Y-%m-%d %H:%M:%S' ) # Adjust this value to increase/decrease your requests between episodes. # Make to remain within the rate limit: https://trakt.docs.apiary.io/#introduction/rate-limiting DELAY_BETWEEN_EPISODES_IN_SECONDS = 0.75 # Create a database to keep track of completed processes database = TinyDB("localStorage.json") syncedEpisodesTable = database.table("SyncedEpisodes") userMatchedShowsTable = database.table("TvTimeTraktUserMatched") class Expando(object): pass def getConfiguration(): configEx = Expando() with open("config.json") as f: data = json.load(f) configEx.TRAKT_USERNAME = data["TRAKT_USERNAME"] configEx.CLIENT_ID = data["CLIENT_ID"] configEx.CLIENT_SECRET = data["CLIENT_SECRET"] configEx.GDPR_WORKSPACE_PATH = data["GDPR_WORKSPACE_PATH"] CONFIG_SINGLETON = configEx return CONFIG_SINGLETON config = getConfiguration() # Return the path to the CSV file contain the watched episode data from TV Time def getWatchedShowsPath(): return config.GDPR_WORKSPACE_PATH + "/seen_episode.csv" def getFollowedShowsPath(): return config.GDPR_WORKSPACE_PATH + "/followed_tv_show.csv" def initTraktAuth(): return True # Set the method of authentication trakt.core.AUTH_METHOD = trakt.core.OAUTH_AUTH return init( config.TRAKT_USERNAME, store=True, client_id=config.CLIENT_ID, client_secret=config.CLIENT_SECRET, ) # With a given title, check if it contains a year (e.g Doctor Who (2005)) # and then return this value, with the title and year removed to improve # the accuracy of Trakt results. def getYearFromTitle(title): ex = Expando() try: # Use a regex expression to get the value within the brackets e.g The Americans (2017) yearSearch = re.search(r"\(([A-Za-z0-9_]+)\)", title) yearValue = yearSearch.group(1) # Then, get the title without the year value included titleValue = title.split("(")[0].strip() # Put this together into an object ex.titleWithoutYear = titleValue ex.yearValue = int(yearValue) return ex except: # If the above failed, then the title doesn't include a year # so return the object as is. ex.titleWithoutYear = title ex.yearValue = -1 return ex # Shows in TV Time are often different to Trakt.TV - in order to improve results and automation, # calculate how many words are in the title, and return true if more than 50% of the title is a match, # It seems to improve automation, and reduce manual selection.... def checkTitleNameMatch(tvTimeTitle, traktTitle): # If the name is a complete match, then don't bother comparing them! if tvTimeTitle == traktTitle: return True # Split the TvTime title tvTimeTitleSplit = tvTimeTitle.split() # Create an array of words which are found in the Trakt title wordsMatched = [] # Go through each word of the TV Time title, and check if it's in the Trakt title for word in tvTimeTitleSplit: if word in traktTitle: wordsMatched.append(word) # Then calculate what percentage of words matched quotient = len(wordsMatched) / len(traktTitle.split()) percentage = quotient * 100 # If more than 50% of words in the TV Time title exist in the Trakt title, # then return the title as a possibility to use return percentage > 50 # Using TV Time data (Name of Show, Season No and Episode) - find the corresponding show # in Trakt.TV either by automation, or asking the user to confirm. def getShowByName(name, seasonNo, episodeNo): # Parse the TV Show's name for year, if one is present in the string titleObj = getYearFromTitle(name) # Create a boolean to indicate if the title contains a year, # this is used later on to improve the accuracy of picking # from search results doesTitleIncludeYear = titleObj.yearValue != -1 # If the title contains a year, then replace the local variable with the stripped version if doesTitleIncludeYear: name = titleObj.titleWithoutYear # Request the Trakt API for search results, using the name tvSearch = TVShow.search(name) # Create an array of shows which have been matched showsWithSameName = [] # Go through each result from the search for show in tvSearch: # Check if the title is a match, based on our conditions (e.g over 50% of words match) if checkTitleNameMatch(name, show.title): # If the title included the year of broadcast, then we can be more picky in the results # to look for a show with a broadcast year that matches if doesTitleIncludeYear == True: # If the show title is a 1:1 match, with the same broadcast year, then bingo! if (name == show.title) and (show.year == titleObj.yearValue): # Clear previous results, and only use this one showsWithSameName = [] showsWithSameName.append(show) break # Otherwise, only add the show if the broadcast year matches if show.year == titleObj.yearValue: showsWithSameName.append(show) # If the program doesn't have the broadcast year, then add all the results else: showsWithSameName.append(show) # Sweep through the results once more for 1:1 title name matches, # then if the list contains one entry with a 1:1 match, then clear the array # and only use this one! completeMatchNames = [] for nameFromSearch in showsWithSameName: if nameFromSearch.title == name: completeMatchNames.append(nameFromSearch) if len(completeMatchNames) == 1: showsWithSameName = completeMatchNames # If the search contains multiple results, then we need to confirm with the user which show # the script should use, or access the local database to see if the user has already provided # a manual selection if len(showsWithSameName) > 1: # Query the local database for existing selection userMatchedQuery = Query() queryResult = userMatchedShowsTable.search(userMatchedQuery.ShowName == name) # If the local database already contains an entry for a manual selection # then don't bother prompting the user to select it again! if len(queryResult) == 1: # Get the first result from the query firstMatch = queryResult[0] # Get the value contains the selection index firstMatchSelectedIndex = int(firstMatch.get("UserSelectedIndex")) # Check if the user previously requested to skip the show skipShow = firstMatch.get("SkipShow") # If the user did not skip, but provided an index selection, get the # matching show if skipShow == False: return showsWithSameName[firstMatchSelectedIndex] # Otherwise, return None, which will trigger the script to skip # and move onto the next show else: return None # If the user has not provided a manual selection already in the process # then prompt the user to make a selection else: print( f"INFO - MANUAL INPUT REQUIRED: The TV Time data for Show '{name}' (Season {seasonNo}, Episode {episodeNo}) has {len(showsWithSameName)} matching Trakt shows with the same name." ) # Output each show for manual selection for idx, item in enumerate(showsWithSameName): # Display the show's title, broadcast year, amount of seasons and a link to the Trakt page. # This will provide the user with enough information to make a selection. print( f" ({idx + 1}) {item.title} - {item.year} - {len(item.seasons)} Season(s) - More Info: https://trakt.tv/{item.ext}" ) while True: try: # Get the user's selection, either a numerical input, or a string 'SKIP' value indexSelected = input( f"Please make a selection from above (or enter SKIP):" ) if indexSelected != "SKIP": # Since the value isn't 'skip', check that the result is numerical indexSelected = int(indexSelected) - 1 # Exit the selection loop break # Otherwise, exit the loop else: break # Still allow the user to provide the exit input, and kill the program except KeyboardInterrupt: sys.exit("Cancel requested...") # Otherwise, the user has entered an invalid value, warn the user to try again except: logging.error( f"Sorry! Please select a value between 0 to {len(showsWithSameName)}" ) # If the user entered 'SKIP', then exit from the loop with no selection, which # will trigger the program to move onto the next episode if indexSelected == "SKIP": # Record that the user has skipped the TV Show for import, so that # manual input isn't required everytime userMatchedShowsTable.insert( {"ShowName": name, "UserSelectedIndex": 0, "SkipShow": True} ) return None # Otherwise, return the selection which the user made from the list else: selectedShow = showsWithSameName[int(indexSelected)] userMatchedShowsTable.insert( { "ShowName": name, "UserSelectedIndex": indexSelected, "SkipShow": False, } ) return selectedShow else: if len(showsWithSameName) > 0: # If the search returned only one result, then awesome! # Return the show, so the import automation can continue. return showsWithSameName[0] else: return None # Since the Trakt.Py starts the indexing of seasons in the array from 0 (e.g Season 1 in Index 0), then # subtract the TV Time numerical value by 1 so it starts from 0 as well. However, when a TV series includes # a 'special' season, Trakt.Py will place this as the first season in the array - so, don't subtract, since # this will match TV Time's existing value. def parseSeasonNo(seasonNo, traktShowObj): # Parse the season number into a numerical value seasonNo = int(seasonNo) # Then get the Season Number from the first item in the array firstSeasonNo = traktShowObj.seasons[0].number # If the season number is 0, then the Trakt show contains a "special" season if firstSeasonNo == 0: # No need to modify the value, as the TV Time value will match Trakt return seasonNo # Otherwise, if the Trakt seasons start with no specials, then return the seasonNo, # but subtracted by one (e.g Season 1 in TV Time, will be 0) else: # Only subtract is the TV Time season number is greater than 0. if seasonNo != 0: return seasonNo - 1 # Otherwise, the TV Time season is a special! Then you don't need to change the starting position else: return seasonNo def processWatchedShows(): # Total amount of rows which have been processed in the CSV file rowsCount = 0 # Total amount of rows in the CSV file errorStreak = 0 # Open the CSV file within the GDPR exported data with open(getWatchedShowsPath(), newline="") as csvfile: # Create the CSV reader, which will break up the fields using the delimiter ',' showsReader = csv.DictReader(csvfile, delimiter=",") # Get the total amount of rows in the CSV file, rowsTotal = len(list(showsReader)) # Move position to the beginning of the file csvfile.seek(0, 0) # Loop through each line/record of the CSV file # Ignore the header row next(showsReader, None) for rowsCount, row in enumerate(showsReader): # Get the name of the TV show tvShowName = row["tv_show_name"] # Get the TV Time Episode Id tvShowEpisodeId = row["episode_id"] # Get the TV Time Season Number tvShowSeasonNo = row["episode_season_number"] # Get the TV Time Episode Number tvShowEpisodeNo = row["episode_number"] # Get the date which the show was marked 'watched' in TV Time tvShowDateWatched = row["updated_at"] # Parse the watched date value into a Python type tvShowDateWatchedConverted = datetime.strptime( tvShowDateWatched, "%Y-%m-%d %H:%M:%S" ) # Query the local database for previous entries indicating that # the episode has already been imported in the past. Which will # ease pressure on TV Time's API server during a retry of the import # process, and just save time overall without needing to create network requests episodeCompletedQuery = Query() queryResult = syncedEpisodesTable.search( episodeCompletedQuery.episodeId == tvShowEpisodeId ) # If the query returned no results, then continue to import it into Trakt if len(queryResult) == 0: # Create a repeating loop, which will break on success, but repeats on failures while True: # If more than 10 errors occurred in one streak, whilst trying to import the episode # then give up, and move onto the next episode, but warn the user. if errorStreak > 10: logging.warning( f"WARNING: An error occurred 10 times in a row... skipping episode..." ) break try: # Sleep for a second between each process, before going onto the next watched episode. # This is required to remain within the API rate limit, and use the API server fairly. # Other developers share the service, for free - so be considerate of your usage. time.sleep(DELAY_BETWEEN_EPISODES_IN_SECONDS) # Search Trakt for the TV show matching TV Time's title value traktShowObj = getShowByName( tvShowName, tvShowSeasonNo, tvShowEpisodeNo ) # If the method returned 'None', then this is an indication to skip the episode, and # move onto the next one if traktShowObj == None: break # Show the progress of the import on-screen logging.info( f"({rowsCount+1}/{rowsTotal}) Processing - '{tvShowName}' Season {tvShowSeasonNo} / Episode {tvShowEpisodeNo}" ) # Get the season from the Trakt API season = traktShowObj.seasons[ parseSeasonNo(tvShowSeasonNo, traktShowObj) ] # Get the episode from the season episode = season.episodes[int(tvShowEpisodeNo) - 1] # Mark the episode as watched! episode.mark_as_seen(tvShowDateWatchedConverted) # Add the episode to the local database as imported, so it can be skipped, # if the process is repeated syncedEpisodesTable.insert({"episodeId": tvShowEpisodeId}) # Clear the error streak on completing the method without errors errorStreak = 0 break # Catch errors which occur because of an incorrect array index. This occurs when # an incorrect Trakt show has been selected, with season/episodes which don't match TV Time. # It can also occur due to a bug in Trakt Py, whereby some seasons contain an empty array of episodes. except IndexError: logging.warning( f"({rowsCount}/{rowsTotal}) WARNING: {tvShowName} Season {tvShowSeasonNo}, Episode {tvShowEpisodeNo} does not exist (season/episode index) in Trakt!" ) break # Catch any errors which are raised because a show could not be found in Trakt except trakt.errors.NotFoundException: logging.warning( f"({rowsCount}/{rowsTotal}) WARNING: {tvShowName} Season {tvShowSeasonNo}, Episode {tvShowEpisodeNo} does not exist (search) in Trakt!" ) break # Catch errors because of the program breaching the Trakt API rate limit except trakt.errors.RateLimitException: logging.warning( "WARNING: The program is running too quickly and has hit Trakt's API rate limit! Please increase the delay between " + "episdoes via the variable 'DELAY_BETWEEN_EPISODES_IN_SECONDS'. The program will now wait 60 seconds before " + "trying again." ) time.sleep(60) # Mark the exception in the error streak errorStreak += 1 # Catch a JSON decode error - this can be raised when the API server is down and produces a HTML page, instead of JSON except json.decoder.JSONDecodeError: logging.warning( f"({rowsCount}/{rowsTotal}) WARNING: A JSON decode error occuring whilst processing {tvShowName} " + f"Season {tvShowSeasonNo}, Episode {tvShowEpisodeNo}! This might occur when the server is down and has produced " + "a HTML document instead of JSON. The script will wait 60 seconds before trying again." ) # Wait 60 seconds time.sleep(60) # Mark the exception in the error streak errorStreak += 1 # Catch a CTRL + C keyboard input, and exits the program except KeyboardInterrupt: sys.exit("Cancel requested...") # Skip the episode else: logging.info( f"({rowsCount}/{rowsTotal}) Already imported, skipping - '{tvShowName}' Season {tvShowSeasonNo} / Episode {tvShowEpisodeNo}." ) def start(): # Create the initial authentication with Trakt, before starting the process if initTraktAuth(): # Display a menu selection print(f">> What do you want to do?") print(f" 1) Import Watch History from TV Time") while True: try: menuSelection = input(f"Enter your menu selection: ") menuSelection = 1 if not menuSelection else int(menuSelection) break except ValueError: logging.warning("Invalid input. Please enter a numerical number.") # Start the process which is required if menuSelection == 1: # Invoke the method which will import episodes which have been watched # from TV Time into Trakt processWatchedShows() else: logging.warning("Sorry - that's an unknown menu selection") else: logging.error("ERROR: Unable to complete authentication to Trakt - please try again.") if __name__ == "__main__": # Check that the user has created the config file if os.path.exists("config.json"): # Check that the user has provided the GDPR path if os.path.isdir(config.GDPR_WORKSPACE_PATH): start() else: logging.error( "Oops! The TV Time GDPR folder '" + config.GDPR_WORKSPACE_PATH + "' does not exist on the local system. Please check it, and try again." ) else: logging.error( f"The 'config.json' file cannot be found - have you created it yet?" )