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WIP: Processor class
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Markus Nyman
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1 changed files with 136 additions and 0 deletions
136
TimeToTrakt.py
136
TimeToTrakt.py
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@ -347,6 +347,138 @@ class MovieSearcher(Searcher):
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)
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class Processor:
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def __init__(self, reader: csv.DictReader, rows_total: int):
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self._reader = reader
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self._rows_total = rows_total
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def process_watched(self):
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# Loop through each line/record of the CSV file
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# Ignore the header row
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next(self._reader, None)
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for rowsCount, row in enumerate(self._reader):
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# Get the name of the item
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tv_show_name = row["tv_show_name"]
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# Get the TV Time Episode id
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tv_show_episode_id = row["episode_id"]
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# Get the TV Time Season Number
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tv_show_season_number = row["episode_season_number"]
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# Get the TV Time Episode Number
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tv_show_episode_number = row["episode_number"]
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# Get the date which the show was marked 'watched' in TV Time
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tv_show_date_watched = row["updated_at"]
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# Parse the watched date value into a Python type
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tv_show_date_watched_converted = datetime.strptime(
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tv_show_date_watched, "%Y-%m-%d %H:%M:%S"
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)
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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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episode_completed_query = Query()
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query_result = syncedEpisodesTable.search(
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episode_completed_query.episodeId == tv_show_episode_id
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)
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# If the query returned no results, then continue to import it into Trakt
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if len(query_result) == 0:
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# Create a repeating loop, which will break on success, but repeats on failures
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error_streak = 0
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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 error_streak > 10:
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logging.warning(
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"An error occurred 10 times in a row... skipping episode..."
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)
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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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trakt_show = TVShowSearcher(tv_show_season_number,
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tv_show_episode_number).search(Title(tv_show_name))
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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 not trakt_show:
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break
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# Show the progress of the import on-screen
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logging.info(
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f"({rowsCount + 1}/{rows_total}) - Processing '{tv_show_name}' Season {tv_show_season_number} /"
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f"Episode {tv_show_episode_number}"
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)
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# Get the season from the Trakt API
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season = trakt_show.seasons[
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parse_season_number(tv_show_season_number, trakt_show)
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]
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# Get the episode from the season
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episode = season.episodes[int(tv_show_episode_number) - 1]
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# Mark the episode as watched!
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episode.mark_as_seen(tv_show_date_watched_converted)
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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({"episodeId": tv_show_episode_id})
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# Clear the error streak on completing the method without errors
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error_streak = 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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tv_show_slug = trakt_show.to_json()["shows"][0]["ids"]["ids"][
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"slug"
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]
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logging.warning(
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f"({rowsCount}/{rows_total}) - {tv_show_name} Season {tv_show_season_number}, "
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f"Episode {tv_show_episode_number} does not exist in Trakt! "
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f"(https://trakt.tv/shows/{tv_show_slug}/seasons/{tv_show_season_number}/episodes/{tv_show_episode_number})"
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)
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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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logging.warning(
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f"({rowsCount}/{rows_total}) - {tv_show_name} Season {tv_show_season_number}, "
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f"Episode {tv_show_episode_number} does not exist (search) in Trakt!"
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)
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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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logging.warning(
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"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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)
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time.sleep(60)
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# Mark the exception in the error streak
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error_streak += 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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logging.warning(
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f"({rowsCount}/{rows_total}) - A JSON decode error occuring whilst processing {tv_show_name} "
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+ f"Season {tv_show_season_number}, Episode {tv_show_episode_number}! 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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)
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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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error_streak += 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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logging.info(
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f"({rowsCount}/{rows_total}) - Already imported, skipping '{tv_show_name}' Season {tv_show_season_number} / Episode {tv_show_episode_number}."
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)
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def parse_season_number(season_number, trakt_show_obj):
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"""
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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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@ -385,6 +517,10 @@ def process_watched_shows() -> None:
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rows_total = len(list(shows_reader))
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# Move position to the beginning of the file
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csvfile.seek(0, 0)
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processor = Processor(shows_reader, rows_total)
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processor.process_watched()
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# Loop through each line/record of the CSV file
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# Ignore the header row
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next(shows_reader, None)
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