From c6a93abcee94aaa7c551479dd2dd5b6b907d06dd Mon Sep 17 00:00:00 2001 From: SinTan1729 Date: Thu, 6 Oct 2022 00:49:16 -0500 Subject: [PATCH] Merged scripts --- TimeToTrakt.py | 342 +++++++++++++++++++++++++++++- TimeToTraktMovies.py | 492 ------------------------------------------- 2 files changed, 333 insertions(+), 501 deletions(-) delete mode 100644 TimeToTraktMovies.py diff --git a/TimeToTrakt.py b/TimeToTrakt.py index a1f8b6c..f58e336 100644 --- a/TimeToTrakt.py +++ b/TimeToTrakt.py @@ -13,6 +13,7 @@ import trakt.core from tinydb import Query, TinyDB from trakt import init from trakt.tv import TVShow +from trakt.movies import Movie # Setup logger logging.basicConfig( @@ -25,10 +26,13 @@ logging.basicConfig( # Make to remain within the rate limit: https://trakt.docs.apiary.io/#introduction/rate-limiting DELAY_BETWEEN_EPISODES_IN_SECONDS = 1 -# Create a database to keep track of completed processes -database = TinyDB("localStorage.json") -syncedEpisodesTable = database.table("SyncedEpisodes") -userMatchedShowsTable = database.table("TvTimeTraktUserMatched") +# Create databases to keep track of completed processes +databaseshows = TinyDB("localStorageShows.json") +syncedEpisodesTable = databaseshows.table("SyncedEpisodes") +userMatchedShowsTable = databaseshows.table("TvTimeTraktUserMatched") +databasemovies = TinyDB("localStorageMovies.json") +syncedMoviesTable = databasemovies.table("SyncedMovies") +userMatchedMoviesTable = databasemovies.table("TvTimeTraktUserMatched") class Expando(object): @@ -64,7 +68,7 @@ def getConfiguration(): config = getConfiguration() -# Return the path to the CSV file contain the watched episode data from TV Time +# Return the path to the CSV file contain the watched episode and movie data from TV Time def getWatchedShowsPath(): @@ -75,6 +79,10 @@ def getFollowedShowsPath(): return config.GDPR_WORKSPACE_PATH + "/followed_tv_show.csv" +def getMoviesPath(): + return config.GDPR_WORKSPACE_PATH + "/tracking-prod-records.csv" + + def initTraktAuth(): if isAuthenticated(): return True @@ -206,7 +214,8 @@ def getShowByName(name, seasonNo, episodeNo): # Query the local database for existing selection userMatchedQuery = Query() - queryResult = userMatchedShowsTable.search(userMatchedQuery.ShowName == name) + 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! @@ -404,7 +413,8 @@ def processWatchedShows(): 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}) + syncedEpisodesTable.insert( + {"episodeId": tvShowEpisodeId}) # Clear the error streak on completing the method without errors errorStreak = 0 break @@ -459,12 +469,321 @@ def processWatchedShows(): ) +# Using TV Time data (Name of Movie) - find the corresponding movie +# in Trakt.TV either by automation, or asking the user to confirm. + + +def getMovieByName(name): + # Parse the Movie'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 + movieSearch = Movie.search(name) + + # Create an array of movies which have been matched + moviesWithSameName = [] + + # Go through each result from the search + for movie in movieSearch: + # Check if the title is a match, based on our conditions (e.g over 50% of words match) + if checkTitleNameMatch(name, movie.title): + # If the title included the year of broadcast, then we can be more picky in the results + # to look for a movie with a broadcast year that matches + if doesTitleIncludeYear: + # If the movie title is a 1:1 match, with the same broadcast year, then bingo! + if (name == movie.title) and (movie.year == titleObj.yearValue): + # Clear previous results, and only use this one + moviesWithSameName = [] + moviesWithSameName.append(movie) + break + + # Otherwise, only add the movie if the broadcast year matches + if movie.year == titleObj.yearValue: + moviesWithSameName.append(movie) + # If the program doesn't have the broadcast year, then add all the results + else: + moviesWithSameName.append(movie) + + # 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 moviesWithSameName: + if nameFromSearch.title == name: + completeMatchNames.append(nameFromSearch) + + if len(completeMatchNames) == 1: + moviesWithSameName = completeMatchNames + + # If the search contains multiple results, then we need to confirm with the user which movie + # the script should use, or access the local database to see if the user has already provided + # a manual selection + if len(moviesWithSameName) > 1: + + # Query the local database for existing selection + userMatchedQuery = Query() + queryResult = userMatchedMoviesTable.search( + userMatchedQuery.movie_name == 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 movie + skipMovie = firstMatch.get("SkipMovie") + # If the user did not skip, but provided an index selection, get the + # matching movie + if not skipMovie: + return moviesWithSameName[firstMatchSelectedIndex] + # Otherwise, return None, which will trigger the script to skip + # and move onto the next movie + 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 Movie '{name}' has {len(moviesWithSameName)} matching Trakt movies with the same name." + ) + + # Output each movie for manual selection + for idx, item in enumerate(moviesWithSameName): + # Display the movie'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} - 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( + "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 Exception: + logging.error( + f"Sorry! Please select a value between 0 to {len(moviesWithSameName)}" + ) + + # 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 Movie for import, so that + # manual input isn't required everytime + userMatchedMoviesTable.insert( + {"movie_name": name, "UserSelectedIndex": 0, "SkipMovie": True} + ) + + return None + # Otherwise, return the selection which the user made from the list + else: + selectedMovie = moviesWithSameName[int(indexSelected)] + + userMatchedMoviesTable.insert( + { + "movie_name": name, + "UserSelectedIndex": indexSelected, + "SkipMovie": False, + } + ) + + return selectedMovie + + else: + if len(moviesWithSameName) > 0: + # If the search returned only one result, then awesome! + # Return the movie, so the import automation can continue. + return moviesWithSameName[0] + else: + return None + + +def processMovies(): + # 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(getMoviesPath(), newline="") as csvfile: + # Create the CSV reader, which will break up the fields using the delimiter ',' + movieReaderTemp = csv.DictReader(csvfile, delimiter=",") + movieReader = filter(lambda p: '' != p['movie_name'], movieReaderTemp) + # First, list all movies with watched type so that watchlist entry for them is not created + watchedList = [] + for row in movieReader: + if row["type"] == "watch": + watchedList.append(row["movie_name"]) + # Move position to the beginning of the file + csvfile.seek(0, 0) + # Get the total amount of rows in the CSV file, + rowsTotal = len(list(movieReader)) + # 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(movieReader, None) + for rowsCount, row in enumerate(movieReader): + # Get the name of the Movie + movieName = row["movie_name"] + # Get the date which the movie was marked 'watched' in TV Time + activityType = row["type"] + movieDateWatched = row["updated_at"] + # Parse the watched date value into a Python type + movieDateWatchedConverted = datetime.strptime( + movieDateWatched, "%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 + movieQuery = Query() + queryResult = syncedMoviesTable.search( + (movieQuery.movie_name == movieName) & + (movieQuery.type == "watched") + ) + + watchlistQuery = Query() + queryResultWatchlist = syncedMoviesTable.search( + (watchlistQuery.movie_name == movieName) & + (watchlistQuery.type == "watchlist") + ) + + # 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 movie is watched but this is an entry for watchlist, then skip + if movieName in watchedList and activityType != "watch": + logging.info( + f"Skipping '{movieName}' to avoid redundant watchlist entry.") + break + # 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( + "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 Movie matching TV Time's title value + traktMovieObj = getMovieByName(movieName) + # If the method returned 'None', then this is an indication to skip the episode, and + # move onto the next one + if traktMovieObj is None: + break + # Show the progress of the import on-screen + logging.info( + f"({rowsCount+1}/{rowsTotal}) - Processing '{movieName}'" + ) + if activityType == "watch": + traktMovieObj.mark_as_seen( + movieDateWatchedConverted) + # Add the episode to the local database as imported, so it can be skipped, + # if the process is repeated + syncedMoviesTable.insert( + {"movie_name": movieName, "type": "watched"}) + logging.info(f"Marked as seen") + elif len(queryResultWatchlist) == 0: + traktMovieObj.add_to_watchlist() + # Add the episode to the local database as imported, so it can be skipped, + # if the process is repeated + syncedMoviesTable.insert( + {"movie_name": movieName, "type": "watchlist"}) + logging.info(f"Added to watchlist") + else: + logging.warning(f"Already in watchlist") + # 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 movie 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: + movieSlug = traktMovieObj.to_json()["movies"][0]["ids"]["ids"][ + "slug" + ] + logging.warning( + f"({rowsCount}/{rowsTotal}) - {movieName} does not exist in Trakt! (https://trakt.tv/movies/{movieSlug}/)" + ) + break + # Catch any errors which are raised because a movie could not be found in Trakt + except trakt.errors.NotFoundException: + logging.warning( + f"({rowsCount}/{rowsTotal}) - {movieName} 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( + "The program is running too quickly and has hit Trakt's API rate limit! Please increase the delay between " + + "movies 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}) - A JSON decode error occuring whilst processing {movieName} " + + f" 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 '{movieName}'." + ) + + def start(): # Create the initial authentication with Trakt, before starting the process if initTraktAuth(): # Display a menu selection print(">> What do you want to do?") - print(" 1) Import Watch History from TV Time") + print(" 1) Import Watch History for TV Shows from TV Time") + print(" 2) Import Watch Movies from TV Time") while True: try: @@ -472,12 +791,17 @@ def start(): menuSelection = 1 if not menuSelection else int(menuSelection) break except ValueError: - logging.warning("Invalid input. Please enter a numerical number.") + 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() + elif menuSelection == 2: + # Invoke the method which will import movies which have been watched + # from TV Time into Trakt + processMovies() else: logging.warning("Sorry - that's an unknown menu selection") else: diff --git a/TimeToTraktMovies.py b/TimeToTraktMovies.py deleted file mode 100644 index d4663e0..0000000 --- a/TimeToTraktMovies.py +++ /dev/null @@ -1,492 +0,0 @@ -#!/usr/bin/env python3 -import csv -import json -import logging -import os -import re -import sys -import time -from datetime import datetime -from pathlib import Path - -import trakt.core -from tinydb import Query, TinyDB -from trakt import init -from trakt.movies import Movie - -# Setup logger -logging.basicConfig( - format="%(asctime)s [%(levelname)7s] :: %(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 = 1 - -# Create a database to keep track of completed processes -database = TinyDB("localStorageMovies.json") -syncedMoviesTable = database.table("SyncedMovies") -userMatchedMoviesTable = database.table("TvTimeTraktUserMatched") - - -class Expando(object): - pass - - -def isAuthenticated(): - with open("pytrakt.json") as f: - data = json.load(f) - daysBeforeExpiration = ( - datetime.fromtimestamp(data["OAUTH_EXPIRES_AT"]) - datetime.now() - ).days - if daysBeforeExpiration < 1: - return False - return True - - -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 getMoviesPath(): - return config.GDPR_WORKSPACE_PATH + "/tracking-prod-records.csv" - - -def initTraktAuth(): - if isAuthenticated(): - 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 Exception: - # 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 - - -# Movies 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 Movie) - find the corresponding movie -# in Trakt.TV either by automation, or asking the user to confirm. - - -def getMovieByName(name): - # Parse the Movie'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 - movieSearch = Movie.search(name) - - # Create an array of movies which have been matched - moviesWithSameName = [] - - # Go through each result from the search - for movie in movieSearch: - # Check if the title is a match, based on our conditions (e.g over 50% of words match) - if checkTitleNameMatch(name, movie.title): - # If the title included the year of broadcast, then we can be more picky in the results - # to look for a movie with a broadcast year that matches - if doesTitleIncludeYear: - # If the movie title is a 1:1 match, with the same broadcast year, then bingo! - if (name == movie.title) and (movie.year == titleObj.yearValue): - # Clear previous results, and only use this one - moviesWithSameName = [] - moviesWithSameName.append(movie) - break - - # Otherwise, only add the movie if the broadcast year matches - if movie.year == titleObj.yearValue: - moviesWithSameName.append(movie) - # If the program doesn't have the broadcast year, then add all the results - else: - moviesWithSameName.append(movie) - - # 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 moviesWithSameName: - if nameFromSearch.title == name: - completeMatchNames.append(nameFromSearch) - - if len(completeMatchNames) == 1: - moviesWithSameName = completeMatchNames - - # If the search contains multiple results, then we need to confirm with the user which movie - # the script should use, or access the local database to see if the user has already provided - # a manual selection - if len(moviesWithSameName) > 1: - - # Query the local database for existing selection - userMatchedQuery = Query() - queryResult = userMatchedMoviesTable.search( - userMatchedQuery.movie_name == 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 movie - skipMovie = firstMatch.get("SkipMovie") - # If the user did not skip, but provided an index selection, get the - # matching movie - if not skipMovie: - return moviesWithSameName[firstMatchSelectedIndex] - # Otherwise, return None, which will trigger the script to skip - # and move onto the next movie - 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 Movie '{name}' has {len(moviesWithSameName)} matching Trakt movies with the same name." - ) - - # Output each movie for manual selection - for idx, item in enumerate(moviesWithSameName): - # Display the movie'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} - 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( - "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 Exception: - logging.error( - f"Sorry! Please select a value between 0 to {len(moviesWithSameName)}" - ) - - # 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 Movie for import, so that - # manual input isn't required everytime - userMatchedMoviesTable.insert( - {"movie_name": name, "UserSelectedIndex": 0, "SkipMovie": True} - ) - - return None - # Otherwise, return the selection which the user made from the list - else: - selectedMovie = moviesWithSameName[int(indexSelected)] - - userMatchedMoviesTable.insert( - { - "movie_name": name, - "UserSelectedIndex": indexSelected, - "SkipMovie": False, - } - ) - - return selectedMovie - - else: - if len(moviesWithSameName) > 0: - # If the search returned only one result, then awesome! - # Return the movie, so the import automation can continue. - return moviesWithSameName[0] - else: - return None - - -def processMovies(): - # 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(getMoviesPath(), newline="") as csvfile: - # Create the CSV reader, which will break up the fields using the delimiter ',' - movieReaderTemp = csv.DictReader(csvfile, delimiter=",") - movieReader = filter(lambda p: '' != p['movie_name'], movieReaderTemp) - # First, list all movies with watched type so that watchlist entry for them is not created - watchedList = [] - for row in movieReader: - if row["type"] == "watch": - watchedList.append(row["movie_name"]) - # Move position to the beginning of the file - csvfile.seek(0, 0) - # Get the total amount of rows in the CSV file, - rowsTotal = len(list(movieReader)) - # 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(movieReader, None) - for rowsCount, row in enumerate(movieReader): - # Get the name of the Movie - movieName = row["movie_name"] - # Get the date which the movie was marked 'watched' in TV Time - activityType = row["type"] - movieDateWatched = row["updated_at"] - # Parse the watched date value into a Python type - movieDateWatchedConverted = datetime.strptime( - movieDateWatched, "%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 - movieQuery = Query() - queryResult = syncedMoviesTable.search( - (movieQuery.movie_name == movieName) & - (movieQuery.type == "watched") - ) - - watchlistQuery = Query() - queryResultWatchlist = syncedMoviesTable.search( - (watchlistQuery.movie_name == movieName) & - (watchlistQuery.type == "watchlist") - ) - - # 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 movie is watched but this is an entry for watchlist, then skip - if movieName in watchedList and activityType != "watch": - break - # 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( - "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 Movie matching TV Time's title value - traktMovieObj = getMovieByName(movieName) - # If the method returned 'None', then this is an indication to skip the episode, and - # move onto the next one - if traktMovieObj is None: - break - # Show the progress of the import on-screen - logging.info( - f"({rowsCount+1}/{rowsTotal}) - Processing '{movieName}'" - ) - if activityType == "watch": - traktMovieObj.mark_as_seen( - movieDateWatchedConverted) - # Add the episode to the local database as imported, so it can be skipped, - # if the process is repeated - syncedMoviesTable.insert( - {"movie_name": movieName, "type": "watched"}) - logging.info(f"Marked as seen") - elif len(queryResultWatchlist) == 0: - traktMovieObj.add_to_watchlist() - # Add the episode to the local database as imported, so it can be skipped, - # if the process is repeated - syncedMoviesTable.insert( - {"movie_name": movieName, "type": "watchlist"}) - logging.info(f"Added to watchlist") - else: - logging.warning(f"Already in watchlist") - # 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 movie 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: - movieSlug = traktMovieObj.to_json()["movies"][0]["ids"]["ids"][ - "slug" - ] - logging.warning( - f"({rowsCount}/{rowsTotal}) - {movieName} does not exist in Trakt! (https://trakt.tv/movies/{movieSlug}/)" - ) - break - # Catch any errors which are raised because a movie could not be found in Trakt - except trakt.errors.NotFoundException: - logging.warning( - f"({rowsCount}/{rowsTotal}) - {movieName} 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( - "The program is running too quickly and has hit Trakt's API rate limit! Please increase the delay between " - + "movies 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}) - A JSON decode error occuring whilst processing {movieName} " - + f" 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 '{movieName}'." - ) - - -def start(): - # Create the initial authentication with Trakt, before starting the process - if initTraktAuth(): - # Display a menu selection - print(">> What do you want to do?") - print(" 1) Import Movies History from TV Time") - - while True: - try: - menuSelection = input("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 - processMovies() - 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( - "The 'config.json' file cannot be found - have you created it yet?" - )