mirror of
https://github.com/SinTan1729/TvTimeToTrakt.git
synced 2024-12-25 21:08:37 -06:00
Change field selection to named columns instead of indexes. (csv.DictReader)
Allow empty menu input, defaulting to choice #1 Change total line count to reuse already opened CSV file Use enumerate() to track row ID
This commit is contained in:
Baptiste Roux
parent
6d8818bc14
commit
9436798e47
1 changed files with 114 additions and 125 deletions
239
TimeToTrackt.py
239
TimeToTrackt.py
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@ -1,17 +1,15 @@
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# 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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#!/usr/bin/env python3
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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 os
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import re
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import sys
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import time
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from datetime import datetime
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import trakt.core
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from tinydb import Query, TinyDB
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from trakt import Expando
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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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@ -58,6 +56,7 @@ def getFollowedShowsPath():
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def initTraktAuth():
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return True
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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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@ -291,133 +290,122 @@ 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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showsReader = csv.DictReader(csvfile, delimiter=',')
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# Get the total amount of rows in the CSV file,
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rowsTotal = len(list(showsReader))
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# Move position to the beginning of the file
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csvfile.seek(0, 0)
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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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# Ignore the header row
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next(showsReader, None)
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for rowsCount, row in enumerate(showsReader):
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# Get the name of the TV show
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tvShowName = row[8]
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tvShowName = row["tv_show_name"]
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# Get the TV Time Episode Id
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tvShowEpisodeId = row["episode_id"]
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# Get the TV Time Season Number
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tvShowSeasonNo = row["episode_season_number"]
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# Get the TV Time Episode Number
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tvShowEpisodeNo = row["episode_number"]
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# Get the date which the show was marked 'watched' in TV Time
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tvShowDateWatched = row["updated_at"]
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# Parse the watched date value into a Python type
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print(tvShowDateWatched)
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tvShowDateWatchedConverted = datetime.strptime(
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tvShowDateWatched, '%Y-%m-%d %H:%M:%S')
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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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# 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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# 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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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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# 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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# 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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# 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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# 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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@ -429,7 +417,8 @@ def start():
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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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menuSelection = input(f"Enter your menu selection: ")
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menuSelection = 1 if not menuSelection else int(menuSelection)
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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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