mirror of
https://github.com/SinTan1729/TvTimeToTrakt.git
synced 2025-04-18 09:07:40 -05:00
457 lines
21 KiB
Python
457 lines
21 KiB
Python
# main.py
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from logging import error
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import sys
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from trakt import *
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import trakt.core
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import os
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import csv
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from datetime import datetime
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import time
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from tinydb import TinyDB, Query
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import json
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import re
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import sys
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from trakt.tv import TVShow
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# Adjust this value to increase/decrease your requests between episodes.
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# Make sure it's above 1 seconds to remain within the rate limit.
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DELAY_BETWEEN_EPISODES_IN_SECONDS = 5
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# Create a database to keep track of completed processes
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database = TinyDB('localStorage.json')
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syncedEpisodesTable = database.table('SyncedEpisodes')
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userMatchedShowsTable = database.table('TvTimeTraktUserMatched')
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class Expando(object):
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pass
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def getConfiguration():
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configEx = Expando()
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with open('config.json') as f:
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data = json.load(f)
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configEx.TRAKT_USERNAME = data["TRAKT_USERNAME"]
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configEx.CLIENT_ID = data["CLIENT_ID"]
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configEx.CLIENT_SECRET = data["CLIENT_SECRET"]
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configEx.GDPR_WORKSPACE_PATH = data["GDPR_WORKSPACE_PATH"]
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CONFIG_SINGLETON = configEx
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return CONFIG_SINGLETON
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config = getConfiguration()
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# Return the path to the CSV file contain the watched episode data from TV Time
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def getWatchedShowsPath():
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return config.GDPR_WORKSPACE_PATH + "/seen_episode.csv"
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def getFollowedShowsPath():
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return config.GDPR_WORKSPACE_PATH + "/followed_tv_show.csv"
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def initTraktAuth():
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# Set the method of authentication
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trakt.core.AUTH_METHOD = trakt.core.OAUTH_AUTH
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return init(config.TRAKT_USERNAME, store=True, client_id=config.CLIENT_ID, client_secret=config.CLIENT_SECRET)
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# With a given title, check if it contains a year (e.g Doctor Who (2005))
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# and then return this value, with the title and year removed to improve
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# the accuracy of Trakt results.
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def getYearFromTitle(title):
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ex = Expando()
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try:
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# Use a regex expression to get the value within the brackets e.g The Americans (2017)
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yearSearch = re.search(r"\(([A-Za-z0-9_]+)\)", title)
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yearValue = yearSearch.group(1)
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# Then, get the title without the year value included
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titleValue = title.split('(')[0].strip()
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# Put this together into an object
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ex.titleWithoutYear = titleValue
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ex.yearValue = int(yearValue)
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return ex
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except:
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# If the above failed, then the title doesn't include a year
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# so return the object as is.
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ex.titleWithoutYear = title
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ex.yearValue = -1
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return ex
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# Shows in TV Time are often different to Trakt.TV - in order to improve results and automation,
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# calculate how many words are in the title, and return true if more than 50% of the title is a match,
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# It seems to improve automation, and reduce manual selection....
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def checkTitleNameMatch(tvTimeTitle, traktTitle):
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# If the name is a complete match, then don't bother comparing them!
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if tvTimeTitle == traktTitle:
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return True
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# Split the TvTime title
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tvTimeTitleSplit = tvTimeTitle.split()
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# Create an array of words which are found in the Trakt title
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wordsMatched = []
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# Go through each word of the TV Time title, and check if it's in the Trakt title
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for word in tvTimeTitleSplit:
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if word in traktTitle:
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wordsMatched.append(word)
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# Then calculate what percentage of words matched
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quotient = len(wordsMatched) / len(traktTitle.split())
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percentage = quotient * 100
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# If more than 50% of words in the TV Time title exist in the Trakt title,
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# then return the title as a possibility to use
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return percentage > 50
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# Using TV Time data (Name of Show, Season No and Episode) - find the corresponding show
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# in Trakt.TV either by automation, or asking the user to confirm.
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def getShowByName(name, seasonNo, episodeNo):
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# Parse the TV Show's name for year, if one is present in the string
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titleObj = getYearFromTitle(name)
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# Create a boolean to indicate if the title contains a year,
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# this is used later on to improve the accuracy of picking
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# from search results
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doesTitleIncludeYear = titleObj.yearValue != -1
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# If the title contains a year, then replace the local variable with the stripped version
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if doesTitleIncludeYear:
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name = titleObj.titleWithoutYear
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# Request the Trakt API for search results, using the name
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tvSearch = TVShow.search(name)
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# Create an array of shows which have been matched
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showsWithSameName = []
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# Go through each result from the search
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for show in tvSearch:
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# Check if the title is a match, based on our conditions (e.g over 50% of words match)
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if checkTitleNameMatch(name, show.title):
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# If the title included the year of broadcast, then we can be more picky in the results
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# to look for a show with a broadcast year that matches
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if doesTitleIncludeYear == True:
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# If the show title is a 1:1 match, with the same broadcast year, then bingo!
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if (name == show.title) and (show.year == titleObj.yearValue):
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# Clear previous results, and only use this one
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showsWithSameName = []
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showsWithSameName.append(show)
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break
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# Otherwise, only add the show if the broadcast year matches
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if show.year == titleObj.yearValue:
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showsWithSameName.append(show)
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# If the program doesn't have the broadcast year, then add all the results
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else:
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showsWithSameName.append(show)
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# Sweep through the results once more for 1:1 title name matches,
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# then if the list contains one entry with a 1:1 match, then clear the array
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# and only use this one!
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completeMatchNames = []
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for nameFromSearch in showsWithSameName:
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if nameFromSearch.title == name:
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completeMatchNames.append(nameFromSearch)
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if (len(completeMatchNames) == 1):
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showsWithSameName = completeMatchNames
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# If the search contains multiple results, then we need to confirm with the user which show
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# the script should use, or access the local database to see if the user has already provided
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# a manual selection
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if len(showsWithSameName) > 1:
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# Query the local database for existing selection
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userMatchedQuery = Query()
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queryResult = userMatchedShowsTable.search(
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userMatchedQuery.ShowName == name)
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# If the local database already contains an entry for a manual selection
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# then don't bother prompting the user to select it again!
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if len(queryResult) == 1:
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# Get the first result from the query
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firstMatch = queryResult[0]
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# Get the value contains the selection index
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firstMatchSelectedIndex = int(firstMatch.get('UserSelectedIndex'))
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# Check if the user previously requested to skip the show
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skipShow = firstMatch.get('SkipShow')
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# If the user did not skip, but provided an index selection, get the
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# matching show
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if skipShow == False:
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return showsWithSameName[firstMatchSelectedIndex]
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# Otherwise, return None, which will trigger the script to skip
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# and move onto the next show
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else:
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return None
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# If the user has not provided a manual selection already in the process
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# then prompt the user to make a selection
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else:
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print(
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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.")
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# Output each show for manual selection
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for idx, item in enumerate(showsWithSameName):
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# Display the show's title, broadcast year, amount of seasons and a link to the Trakt page.
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# This will provide the user with enough information to make a selection.
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print(
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f" ({idx + 1}) {item.title} - {item.year} - {len(item.seasons)} Season(s) - More Info: https://trakt.tv/{item.ext}")
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while(True):
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try:
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# Get the user's selection, either a numerical input, or a string 'SKIP' value
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indexSelected = (input(
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f"Please make a selection from above (or enter SKIP):"))
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if indexSelected != 'SKIP':
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# Since the value isn't 'skip', check that the result is numerical
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indexSelected = int(indexSelected) - 1
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# Exit the selection loop
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break
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# Otherwise, exit the loop
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else:
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break
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# Still allow the user to provide the exit input, and kill the program
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except KeyboardInterrupt:
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sys.exit("Cancel requested...")
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# Otherwise, the user has entered an invalid value, warn the user to try again
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except:
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print(
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f"Sorry! Please select a value between 0 to {len(showsWithSameName)}")
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# If the user entered 'SKIP', then exit from the loop with no selection, which
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# will trigger the program to move onto the next episode
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if (indexSelected == 'SKIP'):
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# Record that the user has skipped the TV Show for import, so that
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# manual input isn't required everytime
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userMatchedShowsTable.insert(
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{'ShowName': name, 'UserSelectedIndex': 0, 'SkipShow': True})
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return None
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# Otherwise, return the selection which the user made from the list
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else:
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selectedShow = showsWithSameName[int(indexSelected)]
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userMatchedShowsTable.insert(
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{'ShowName': name, 'UserSelectedIndex': indexSelected, 'SkipShow': False})
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return selectedShow
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else:
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if (len(showsWithSameName) > 0):
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# If the search returned only one result, then awesome!
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# Return the show, so the import automation can continue.
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return showsWithSameName[0]
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else:
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return None
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# Since the Trakt.Py starts the indexing of seasons in the array from 0 (e.g Season 1 in Index 0), then
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# subtract the TV Time numerical value by 1 so it starts from 0 as well. However, when a TV series includes
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# a 'special' season, Trakt.Py will place this as the first season in the array - so, don't subtract, since
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# this will match TV Time's existing value.
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def parseSeasonNo(seasonNo, traktShowObj):
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# Parse the season number into a numerical value
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seasonNo = int(seasonNo)
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# Then get the Season Number from the first item in the array
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firstSeasonNo = traktShowObj.seasons[0].number
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# If the season number is 0, then the Trakt show contains a "special" season
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if firstSeasonNo == 0:
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# No need to modify the value, as the TV Time value will match Trakt
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return seasonNo
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# Otherwise, if the Trakt seasons start with no specials, then return the seasonNo,
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# but subtracted by one (e.g Season 1 in TV Time, will be 0)
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else:
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# Only subtract is the TV Time season number is greater than 0.
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if seasonNo != 0:
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return seasonNo - 1
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# Otherwise, the TV Time season is a special! Then you don't need to change the starting position
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else:
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return seasonNo
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def processWatchedShows():
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# Total amount of rows which have been processed in the CSV file
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rowsCount = 0
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# Total amount of rows in the CSV file
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rowsTotal = 0
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# Total amount of errors which have occurred in one streak
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errorStreak = 0
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# Get the total amount of rows in the CSV file,
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# which is helpful for keeping track of progress.
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# However, if you have a VERY large CSV file (e.g above 100,000 rows)
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# then it might be a good idea to remove this due to the performance
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# overhead.
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with open(getWatchedShowsPath()) as f:
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rowsTotal = sum(1 for line in f)
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# Open the CSV file within the GDPR exported data
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with open(getWatchedShowsPath(), newline='') as csvfile:
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# Create the CSV reader, which will break up the fields using the delimiter ','
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showsReader = csv.reader(csvfile, delimiter=',')
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# Loop through each line/record of the CSV file
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for row in showsReader:
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# Increment the row counter to keep track of progress completing the
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# records during the import process.
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rowsCount += 1
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# Get the name of the TV show
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tvShowName = row[8]
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# Ignore the header row
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if rowsCount > 1:
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# Get the TV Time Episode Id
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tvShowEpisodeId = row[4]
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# Get the TV Time Season Number
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tvShowSeasonNo = row[5]
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# Get the TV Time Episode Number
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tvShowEpisodeNo = row[6]
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# Get the date which the show was marked 'watched' in TV Time
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tvShowDateWatched = row[7]
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# Parse the watched date value into a Python type
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tvShowDateWatchedConverted = datetime.strptime(
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tvShowDateWatched, '%Y-%m-%d %H:%M:%S')
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# Query the local database for previous entries indicating that
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# the episode has already been imported in the past. Which will
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# ease pressure on TV Time's API server during a retry of the import
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# process, and just save time overall without needing to create network requests
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episodeCompletedQuery = Query()
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queryResult = syncedEpisodesTable.search(
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episodeCompletedQuery.episodeId == tvShowEpisodeId)
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# If the query returned no results, then continue to import it into Trakt
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if len(queryResult) == 0:
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# Create a repeating loop, which will break on success, but repeats on failures
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while True:
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# If more than 10 errors occurred in one streak, whilst trying to import the episode
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# then give up, and move onto the next episode, but warn the user.
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if (errorStreak > 10):
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print(
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f"WARNING: An error occurred 10 times in a row... skipping episode...")
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break
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try:
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# Sleep for a second between each process, before going onto the next watched episode.
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# This is required to remain within the API rate limit, and use the API server fairly.
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# Other developers share the service, for free - so be considerate of your usage.
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time.sleep(DELAY_BETWEEN_EPISODES_IN_SECONDS)
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# Search Trakt for the TV show matching TV Time's title value
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traktShowObj = getShowByName(
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tvShowName, tvShowSeasonNo, tvShowEpisodeNo)
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# If the method returned 'None', then this is an indication to skip the episode, and
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# move onto the next one
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if traktShowObj == None:
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break
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# Show the progress of the import on-screen
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print(
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f"({rowsCount}/{rowsTotal}) Processing Show {tvShowName} on Season {tvShowSeasonNo} - Episode {tvShowEpisodeNo}")
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# Get the season from the Trakt API
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season = traktShowObj.seasons[parseSeasonNo(
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tvShowSeasonNo, traktShowObj)]
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# Get the episode from the season
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episode = season.episodes[int(tvShowEpisodeNo) - 1]
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# Mark the episode as watched!
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episode.mark_as_seen(tvShowDateWatchedConverted)
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# Add the episode to the local database as imported, so it can be skipped,
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# if the process is repeated
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syncedEpisodesTable.insert(
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{'episodeId': tvShowEpisodeId})
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# Clear the error streak on completing the method without errors
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errorStreak = 0
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break
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# Catch errors which occur because of an incorrect array index. This occurs when
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# an incorrect Trakt show has been selected, with season/episodes which don't match TV Time.
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# It can also occur due to a bug in Trakt Py, whereby some seasons contain an empty array of episodes.
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except IndexError:
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print(
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f"({rowsCount}/{rowsTotal}) WARNING: {tvShowName} Season {tvShowSeasonNo}, Episode {tvShowEpisodeNo} does not exist (season/episode index) in Trakt!")
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break
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# Catch any errors which are raised because a show could not be found in Trakt
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except trakt.errors.NotFoundException:
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print(
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f"({rowsCount}/{rowsTotal}) WARNING: {tvShowName} Season {tvShowSeasonNo}, Episode {tvShowEpisodeNo} does not exist (search) in Trakt!")
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break
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# Catch errors because of the program breaching the Trakt API rate limit
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except trakt.errors.RateLimitException:
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print(
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"WARNING: The program is running too quickly and has hit Trakt's API rate limit! Please increase the delay between " +
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"episdoes via the variable 'DELAY_BETWEEN_EPISODES_IN_SECONDS'. The program will now wait 60 seconds before " +
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"trying again.")
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time.sleep(60)
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# Mark the exception in the error streak
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errorStreak += 1
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# Catch a JSON decode error - this can be raised when the API server is down and produces a HTML page, instead of JSON
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except json.decoder.JSONDecodeError:
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print(
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f"({rowsCount}/{rowsTotal}) WARNING: A JSON decode error occuring whilst processing {tvShowName} " +
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f"Season {tvShowSeasonNo}, Episode {tvShowEpisodeNo}! This might occur when the server is down and has produced " +
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"a HTML document instead of JSON. The script will wait 60 seconds before trying again.")
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# Wait 60 seconds
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time.sleep(60)
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# Mark the exception in the error streak
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errorStreak += 1
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# Catch a CTRL + C keyboard input, and exits the program
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except KeyboardInterrupt:
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sys.exit("Cancel requested...")
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# Skip the episode
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else:
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print(
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f"({rowsCount}/{rowsTotal}) Skipping '{tvShowName}' Season {tvShowSeasonNo} Episode {tvShowEpisodeNo}. It's already been imported.")
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def start():
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# Create the initial authentication with Trakt, before starting the process
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if initTraktAuth():
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# Display a menu selection
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print(f">> What do you want to do?")
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print(f" 1) Import Watch History from TV Time")
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while True:
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try:
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menuSelection = int(input(f"Enter your menu selection: "))
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break
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except ValueError:
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print("Invalid input. Please enter a numerical number.")
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# Start the process which is required
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if menuSelection == 1:
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# Invoke the method which will import episodes which have been watched
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# from TV Time into Trakt
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processWatchedShows()
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else:
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print("Sorry - that's an unknown menu selection")
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else:
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print("ERROR: Unable to complete authentication to Trakt - please try again.")
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if __name__ == "__main__":
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# Check that the user has created the config file
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if os.path.exists("config.json"):
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# Check that the user has provided the GDPR path
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if os.path.isdir(config.GDPR_WORKSPACE_PATH):
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start()
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else:
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print("Oops! The TV Time GDPR folder '" + config.GDPR_WORKSPACE_PATH +
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"' does not exist on the local system. Please check it, and try again.")
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else:
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print(f"ERROR: The 'config.json' file cannot be found - have you created it yet?")
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