mirror of
https://github.com/SinTan1729/TvTimeToTrakt.git
synced 2025-04-11 14:16:03 -05:00
01ab7897c2
* Initial working * Removed .vscode * Cleanup * Merged scripts * Updated README.md * Present menu before authentication. add entries * Just use one database * Remove irrelevant entries * Add bell on manual input prompt (suggested by @WeirdAlex03) * Separate file is no longer used for movies * Config to dataclass * Prompt config if it doesn't exist * Naming to snake_case * Remove use of Exodus class * Remove old Title fields * Specify TV Shows and Movies as default action * Extract menu selection to own function * Fix movie query * Simple refactor * Extract getting same name items to common function * Remove unnecessary param * Fix TinyDB movie name Co-authored-by: Markus Nyman <markus@nyman.dev>
797 lines
36 KiB
Python
797 lines
36 KiB
Python
#!/usr/bin/env python3
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import csv
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import json
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import logging
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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 dataclasses import dataclass
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from datetime import datetime
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from typing import Optional, Callable, TypeVar, Union, List
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import trakt.core
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from tinydb import Query, TinyDB
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from trakt import init
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from trakt.movies import Movie
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from trakt.tv import TVShow
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# Setup logger
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logging.basicConfig(
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format="%(asctime)s [%(levelname)7s] :: %(message)s",
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level=logging.INFO,
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datefmt="%Y-%m-%d %H:%M:%S",
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)
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# Adjust this value to increase/decrease your requests between episodes.
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# Make to remain within the rate limit: https://trakt.docs.apiary.io/#introduction/rate-limiting
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DELAY_BETWEEN_EPISODES_IN_SECONDS = 1
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# Create databases 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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syncedMoviesTable = database.table("SyncedMovies")
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userMatchedMoviesTable = database.table("TvTimeTraktUserMatchedMovies")
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@dataclass
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class Config:
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trakt_username: str
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client_id: str
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client_secret: str
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gdpr_workspace_path: str
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def is_authenticated() -> bool:
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with open("pytrakt.json") as f:
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data = json.load(f)
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days_before_expiration = (
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datetime.fromtimestamp(data["OAUTH_EXPIRES_AT"]) - datetime.now()
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).days
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return days_before_expiration >= 1
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def get_configuration() -> Config:
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try:
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with open("config.json") as f:
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data = json.load(f)
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return Config(
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data["TRAKT_USERNAME"],
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data["CLIENT_ID"],
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data["CLIENT_SECRET"],
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data["GDPR_WORKSPACE_PATH"],
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)
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except FileNotFoundError:
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logging.info("config.json not found prompting user for input")
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return Config(
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input("Enter your Trakt.tv username: "),
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input("Enter you Client id: "),
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input("Enter your Client secret: "),
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input("Enter your GDPR workspace path: ")
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)
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config = get_configuration()
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WATCHED_SHOWS_PATH = config.gdpr_workspace_path + "/seen_episode.csv"
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FOLLOWED_SHOWS_PATH = config.gdpr_workspace_path + "/followed_tv_show.csv"
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MOVIES_PATH = config.gdpr_workspace_path + "/tracking-prod-records.csv"
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def init_trakt_auth() -> bool:
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if is_authenticated():
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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(
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config.trakt_username,
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store=True,
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client_id=config.client_id,
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client_secret=config.client_secret,
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)
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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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@dataclass
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class Title:
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name: str
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without_year: str
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year: Optional[int]
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def __init__(self, title: str):
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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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year_search = re.search(r"\(([A-Za-z0-9_]+)\)", title)
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year_value = year_search.group(1)
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# Then, get the title without the year value included
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title_value = title.split("(")[0].strip()
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# Put this together into an object
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self.name = title
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self.without_year = title_value
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self.year = int(year_value)
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except Exception:
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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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self.name = title
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self.without_year = title
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self.year = None
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def get_year_from_title(title) -> Title:
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return Title(title)
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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 check_title_name_match(tv_time_title: str, trakt_title: str) -> bool:
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# If the name is a complete match, then don't bother comparing them!
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if tv_time_title == trakt_title:
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return True
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# Split the TvTime title
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tv_time_title_split = tv_time_title.split()
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# Create an array of words which are found in the Trakt title
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words_matched = []
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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 tv_time_title_split:
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if word in trakt_title:
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words_matched.append(word)
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# Then calculate what percentage of words matched
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quotient = len(words_matched) / len(trakt_title.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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TraktTVShow = TypeVar("TraktTVShow")
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TraktMovie = TypeVar("TraktMovie")
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SearchResult = Union[TraktTVShow, TraktMovie]
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def get_items_with_same_name(title: Title, items: List[SearchResult]) -> List[SearchResult]:
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shows_with_same_name = []
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for item in items:
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if check_title_name_match(title.name, item.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 an item with a broadcast year that matches
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if title.year:
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# If the item title is a 1:1 match, with the same broadcast year, then bingo!
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if (title.name == item.title) and (item.year == title.year):
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# Clear previous results, and only use this one
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shows_with_same_name = [item]
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break
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# Otherwise, only add the item if the broadcast year matches
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if item.year == title.year:
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shows_with_same_name.append(item)
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# If the item doesn't have the broadcast year, then add all the results
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else:
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shows_with_same_name.append(item)
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return shows_with_same_name
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def get_show_by_name(name: str, season_number: str, episode_number: str):
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# Parse the TV Show's name for year, if one is present in the string
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title = get_year_from_title(name)
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# If the title contains a year, then replace the local variable with the stripped version
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if title.year:
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name = title.without_year
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shows_with_same_name = get_items_with_same_name(title, TVShow.search(name))
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complete_match_names = [name_from_search for name_from_search in shows_with_same_name if
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name_from_search.title == name]
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if len(complete_match_names) == 1:
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return complete_match_names[0]
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elif len(shows_with_same_name) == 1:
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return shows_with_same_name[0]
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elif len(shows_with_same_name) < 1:
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return None
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else:
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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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# Query the local database for existing selection
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user_matched_query = Query()
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query_result = userMatchedShowsTable.search(user_matched_query.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(query_result) == 1:
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# Get the first result from the query
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first_match = query_result[0]
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# Get the value contains the selection index
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first_match_selected_index = int(first_match.get("UserSelectedIndex"))
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# Check if the user previously requested to skip the show
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skip_show = first_match.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 not skip_show:
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return shows_with_same_name[first_match_selected_index]
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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 {season_number},"
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f"Episode {episode_number}) has {len(shows_with_same_name)} matching Trakt shows with the same name.\a "
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)
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# Output each show for manual selection
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for idx, item in enumerate(shows_with_same_name):
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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)} "
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f"Season(s) - More Info: https://trakt.tv/{item.ext}"
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)
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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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index_selected = input(
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"Please make a selection from above (or enter SKIP):"
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)
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# Exit the loop
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if index_selected == "SKIP":
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break
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# Since the value isn't 'skip', check that the result is numerical
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index_selected = int(index_selected) - 1
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# Exit the selection loop
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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 Exception:
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logging.error(
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f"Sorry! Please select a value between 0 to {len(shows_with_same_name)}"
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)
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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 index_selected == "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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)
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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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selected_show = shows_with_same_name[int(index_selected)]
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userMatchedShowsTable.insert(
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{
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"ShowName": name,
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"UserSelectedIndex": index_selected,
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"SkipShow": False,
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}
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)
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return selected_show
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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 parse_season_number(season_number, trakt_show_obj):
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# Parse the season number into a numerical value
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season_number = int(season_number)
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# Then get the Season Number from the first item in the array
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first_season_no = trakt_show_obj.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 first_season_no == 0:
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# No need to modify the value, as the TV Time value will match Trakt
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return season_number
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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 if the TV Time season number is greater than 0.
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if season_number != 0:
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return season_number - 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 season_number
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def process_watched_shows() -> None:
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# Open the CSV file within the GDPR exported data
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with open(WATCHED_SHOWS_PATH, newline="") as csvfile:
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# Create the CSV reader, which will break up the fields using the delimiter ','
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shows_reader = csv.DictReader(csvfile, delimiter=",")
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# Get the total amount of rows in the CSV file,
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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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# 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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for rowsCount, row in enumerate(shows_reader):
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# Get the name of the TV show
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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 = get_show_by_name(
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tv_show_name, tv_show_season_number, tv_show_episode_number
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)
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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}."
|
|
)
|
|
|
|
|
|
# Using TV Time data (Name of Movie) - find the corresponding movie
|
|
# in Trakt.TV either by automation, or asking the user to confirm.
|
|
|
|
|
|
def get_movie_by_name(name: str):
|
|
# Parse the Movie's name for year, if one is present in the string
|
|
title = get_year_from_title(name)
|
|
|
|
# If the title contains a year, then replace the local variable with the stripped version
|
|
if title.year:
|
|
name = title.without_year
|
|
|
|
movies_with_same_name = get_items_with_same_name(title, Movie.search(name))
|
|
|
|
complete_match_names = [name_from_search for name_from_search in movies_with_same_name if
|
|
name_from_search.title == name]
|
|
if len(complete_match_names) == 1:
|
|
return complete_match_names[0]
|
|
elif len(movies_with_same_name) == 1:
|
|
return movies_with_same_name[0]
|
|
elif len(movies_with_same_name) < 1:
|
|
return None
|
|
else:
|
|
# 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
|
|
|
|
# Query the local database for existing selection
|
|
user_matched_query = Query()
|
|
query_result = userMatchedMoviesTable.search(user_matched_query.MovieName == 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(query_result) == 1:
|
|
# Get the first result from the query
|
|
first_match = query_result[0]
|
|
# Get the value contains the selection index
|
|
first_match_selected_index = int(first_match.get("UserSelectedIndex"))
|
|
# Check if the user previously requested to skip the movie
|
|
skip_movie = first_match.get("SkipMovie")
|
|
# If the user did not skip, but provided an index selection, get the
|
|
# matching movie
|
|
if not skip_movie:
|
|
return movies_with_same_name[first_match_selected_index]
|
|
# 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(movies_with_same_name)} "
|
|
f"matching Trakt movies with the same name.\a"
|
|
)
|
|
|
|
# Output each movie for manual selection
|
|
for idx, item in enumerate(movies_with_same_name):
|
|
# 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
|
|
index_selected = input(
|
|
"Please make a selection from above (or enter SKIP):"
|
|
)
|
|
|
|
if index_selected != "SKIP":
|
|
# Since the value isn't 'skip', check that the result is numerical
|
|
index_selected = int(index_selected) - 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(movies_with_same_name)}"
|
|
)
|
|
|
|
# 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 index_selected == "SKIP":
|
|
# Record that the user has skipped the Movie for import, so that
|
|
# manual input isn't required everytime
|
|
userMatchedMoviesTable.insert(
|
|
{"MovieName": name, "UserSelectedIndex": 0, "SkipMovie": True}
|
|
)
|
|
|
|
return None
|
|
# Otherwise, return the selection which the user made from the list
|
|
else:
|
|
selected_movie = movies_with_same_name[int(index_selected)]
|
|
|
|
userMatchedMoviesTable.insert(
|
|
{
|
|
"MovieName": name,
|
|
"UserSelectedIndex": index_selected,
|
|
"SkipMovie": False,
|
|
}
|
|
)
|
|
|
|
return selected_movie
|
|
|
|
|
|
def process_movies():
|
|
# Total amount of rows which have been processed in the CSV file
|
|
# Total amount of rows in the CSV file
|
|
error_streak = 0
|
|
# Open the CSV file within the GDPR exported data
|
|
with open(MOVIES_PATH, newline="") as csvfile:
|
|
# Create the CSV reader, which will break up the fields using the delimiter ','
|
|
movie_reader_temp = csv.DictReader(csvfile, delimiter=",")
|
|
movie_reader = filter(lambda p: "" != p["movie_name"], movie_reader_temp)
|
|
# First, list all movies with watched type so that watchlist entry for them is not created
|
|
watched_list = []
|
|
for row in movie_reader:
|
|
if row["type"] == "watch":
|
|
watched_list.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,
|
|
rows_total = len(list(movie_reader))
|
|
# 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(movie_reader, None)
|
|
for rows_count, row in enumerate(movie_reader):
|
|
# Get the name of the Movie
|
|
movie_name = row["movie_name"]
|
|
# Get the date which the movie was marked 'watched' in TV Time
|
|
activity_type = row["type"]
|
|
movie_date_watched = row["updated_at"]
|
|
# Parse the watched date value into a Python type
|
|
movie_date_watched_converted = datetime.strptime(
|
|
movie_date_watched, "%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
|
|
movie_query = Query()
|
|
query_result = syncedMoviesTable.search(
|
|
(movie_query.movie_name == movie_name) & (movie_query.type == "watched")
|
|
)
|
|
|
|
watchlist_query = Query()
|
|
query_result_watchlist = syncedMoviesTable.search(
|
|
(watchlist_query.movie_name == movie_name)
|
|
& (watchlist_query.type == "watchlist")
|
|
)
|
|
|
|
# If the query returned no results, then continue to import it into Trakt
|
|
if len(query_result) == 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 movie_name in watched_list and activity_type != "watch":
|
|
logging.info(
|
|
f"Skipping '{movie_name}' 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 error_streak > 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
|
|
trakt_movie_obj = get_movie_by_name(movie_name)
|
|
# If the method returned 'None', then this is an indication to skip the episode, and
|
|
# move onto the next one
|
|
if trakt_movie_obj is None:
|
|
break
|
|
# Show the progress of the import on-screen
|
|
logging.info(
|
|
f"({rows_count + 1}/{rows_total}) - Processing '{movie_name}'"
|
|
)
|
|
if activity_type == "watch":
|
|
trakt_movie_obj.mark_as_seen(movie_date_watched_converted)
|
|
# Add the episode to the local database as imported, so it can be skipped,
|
|
# if the process is repeated
|
|
syncedMoviesTable.insert(
|
|
{"movie_name": movie_name, "type": "watched"}
|
|
)
|
|
logging.info(f"Marked as seen")
|
|
elif len(query_result_watchlist) == 0:
|
|
trakt_movie_obj.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": movie_name, "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
|
|
error_streak = 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:
|
|
movie_slug = trakt_movie_obj.to_json()["movies"][0]["ids"]["ids"][
|
|
"slug"
|
|
]
|
|
logging.warning(
|
|
f"({rows_count}/{rows_total}) - {movie_name} "
|
|
f"does not exist in Trakt! (https://trakt.tv/movies/{movie_slug}/)"
|
|
)
|
|
break
|
|
# Catch any errors which are raised because a movie could not be found in Trakt
|
|
except trakt.errors.NotFoundException:
|
|
logging.warning(
|
|
f"({rows_count}/{rows_total}) - {movie_name} 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
|
|
error_streak += 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"({rows_count}/{rows_total}) - A JSON decode error occuring whilst processing {movie_name} "
|
|
+ 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
|
|
error_streak += 1
|
|
# Catch a CTRL + C keyboard input, and exits the program
|
|
except KeyboardInterrupt:
|
|
sys.exit("Cancel requested...")
|
|
|
|
# Skip the episode
|
|
else:
|
|
logging.info(
|
|
f"({rows_count}/{rows_total}) - Already imported, skipping '{movie_name}'."
|
|
)
|
|
|
|
|
|
def menu_selection() -> int:
|
|
# Display a menu selection
|
|
print(">> What do you want to do?")
|
|
print(" 1) Import Watch History for TV Shows from TV Time")
|
|
print(" 2) Import Watch Movies from TV Time")
|
|
print(" 3) Do both 1 and 2 (default)")
|
|
print(" 4) Exit")
|
|
|
|
while True:
|
|
try:
|
|
selection = input("Enter your menu selection: ")
|
|
selection = 3 if not selection else int(selection)
|
|
break
|
|
except ValueError:
|
|
logging.warning("Invalid input. Please enter a numerical number.")
|
|
# Check if the input is valid
|
|
if not 1 <= selection <= 4:
|
|
logging.warning("Sorry - that's an unknown menu selection")
|
|
exit()
|
|
# Exit if the 4th option was chosen
|
|
if selection == 4:
|
|
logging.info("Exiting as per user's selection.")
|
|
exit()
|
|
|
|
return selection
|
|
|
|
|
|
def start():
|
|
selection = menu_selection()
|
|
|
|
# Create the initial authentication with Trakt, before starting the process
|
|
if not init_trakt_auth():
|
|
logging.error(
|
|
"ERROR: Unable to complete authentication to Trakt - please try again."
|
|
)
|
|
|
|
# Start the process which is required
|
|
if selection == 1:
|
|
# Invoke the method which will import episodes which have been watched
|
|
# from TV Time into Trakt
|
|
logging.info("Processing watched shows.")
|
|
process_watched_shows()
|
|
# TODO: Add support for followed shows
|
|
elif selection == 2:
|
|
# Invoke the method which will import movies which have been watched
|
|
# from TV Time into Trakt
|
|
logging.info("Processing movies.")
|
|
process_movies()
|
|
elif selection == 3:
|
|
# Invoke both the episodes and movies import methods
|
|
logging.info("Processing both watched shows and movies.")
|
|
process_watched_shows()
|
|
process_movies()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
# 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."
|
|
)
|