SinTan1729/TvTimeToTrakt
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Added support for movies (#17)

Browse source 
* 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>
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7
.gitignore vendored
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@ -1,6 +1 @@
watched_show_process_tracker.json
localStorage.json
config.json
TimeToTrackt.py
seen_episode.csv
followed_tv_show.csv
*.json

15
.vscode/launch.json vendored
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@ -1,15 +0,0 @@
{
// Use IntelliSense to learn about possible attributes.
// Hover to view descriptions of existing attributes.
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
"version": "0.2.0",
"configurations": [
{
"name": "Python: Current File",
"type": "python",
"request": "launch",
"program": "${file}",
"console": "integratedTerminal"
}
]
}

8
README.md
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@ -2,13 +2,13 @@
![](https://loch.digital/image_for_external_apps/4342799-01.png)
A Python script to import TV Time tracked episode data into Trakt.TV - using data export provided by TV Time through a GDPR request.
A Python script to import TV Time tracked episode and movie data into Trakt.TV - using data export provided by TV Time through a GDPR request.
# Notes
1. The script is using limited data provided from a GDPR request - so the accuracy isn't 100%. But you will be prompted to manually pick the Trakt show, when it can't be determined automatically.
2. A delay of 1 second is added between each episode to ensure fair use of Trakt's API server. You can adjust this for your own import, but make sure it's at least 0.75 second to remain within the rate limit: https://trakt.docs.apiary.io/#introduction/rate-limiting
3. Episodes which have been processed will be saved to a TinyDB file `localStorage.json` - when you restart the script, the program will skip those episodes which have been marked 'imported'.
1. The script is using limited data provided from a GDPR request - so the accuracy isn't 100%. But you will be prompted to manually pick the Trakt show/movie, when it can't be determined automatically.
2. A delay of 1 second is added between each episode/movie to ensure fair use of Trakt's API server. You can adjust this for your own import, but make sure it's at least 0.75 second to remain within the rate limit: https://trakt.docs.apiary.io/#introduction/rate-limiting
3. Episodes which have been processed will be saved to a TinyDB file `localStorage.json` - when you restart the script, the program will skip those episodes which have been marked 'imported'. Processed movies are also stored in the same file.
# Setup

739
TimeToTrakt.py
View file

@ -6,12 +6,14 @@ import os
import re
import sys
import time
from dataclasses import dataclass
from datetime import datetime
from pathlib import Path
from typing import Optional, Callable, TypeVar, Union, List
import trakt.core
from tinydb import Query, TinyDB
from trakt import init
from trakt.movies import Movie
from trakt.tv import TVShow
# Setup logger
@ -25,66 +27,69 @@ logging.basicConfig(
# Make to remain within the rate limit: https://trakt.docs.apiary.io/#introduction/rate-limiting
DELAY_BETWEEN_EPISODES_IN_SECONDS = 1
# Create a database to keep track of completed processes
# Create databases to keep track of completed processes
database = TinyDB("localStorage.json")
syncedEpisodesTable = database.table("SyncedEpisodes")
userMatchedShowsTable = database.table("TvTimeTraktUserMatched")
syncedMoviesTable = database.table("SyncedMovies")
userMatchedMoviesTable = database.table("TvTimeTraktUserMatchedMovies")
class Expando(object):
pass
@dataclass
class Config:
trakt_username: str
client_id: str
client_secret: str
gdpr_workspace_path: str
def isAuthenticated():
def is_authenticated() -> bool:
with open("pytrakt.json") as f:
data = json.load(f)
daysBeforeExpiration = (
datetime.fromtimestamp(data["OAUTH_EXPIRES_AT"]) - datetime.now()
days_before_expiration = (
datetime.fromtimestamp(data["OAUTH_EXPIRES_AT"]) - datetime.now()
).days
if daysBeforeExpiration < 1:
return False
return True
return days_before_expiration >= 1
def getConfiguration():
configEx = Expando()
def get_configuration() -> Config:
try:
with open("config.json") as f:
data = json.load(f)
with open("config.json") as f:
data = json.load(f)
configEx.TRAKT_USERNAME = data["TRAKT_USERNAME"]
configEx.CLIENT_ID = data["CLIENT_ID"]
configEx.CLIENT_SECRET = data["CLIENT_SECRET"]
configEx.GDPR_WORKSPACE_PATH = data["GDPR_WORKSPACE_PATH"]
CONFIG_SINGLETON = configEx
return CONFIG_SINGLETON
return Config(
data["TRAKT_USERNAME"],
data["CLIENT_ID"],
data["CLIENT_SECRET"],
data["GDPR_WORKSPACE_PATH"],
)
except FileNotFoundError:
logging.info("config.json not found prompting user for input")
return Config(
input("Enter your Trakt.tv username: "),
input("Enter you Client id: "),
input("Enter your Client secret: "),
input("Enter your GDPR workspace path: ")
)
config = getConfiguration()
config = get_configuration()
# Return the path to the CSV file contain the watched episode data from TV Time
WATCHED_SHOWS_PATH = config.gdpr_workspace_path + "/seen_episode.csv"
FOLLOWED_SHOWS_PATH = config.gdpr_workspace_path + "/followed_tv_show.csv"
MOVIES_PATH = config.gdpr_workspace_path + "/tracking-prod-records.csv"
def getWatchedShowsPath():
return config.GDPR_WORKSPACE_PATH + "/seen_episode.csv"
def getFollowedShowsPath():
return config.GDPR_WORKSPACE_PATH + "/followed_tv_show.csv"
def initTraktAuth():
if isAuthenticated():
def init_trakt_auth() -> bool:
if is_authenticated():
return True
# Set the method of authentication
trakt.core.AUTH_METHOD = trakt.core.OAUTH_AUTH
return init(
config.TRAKT_USERNAME,
config.trakt_username,
store=True,
client_id=config.CLIENT_ID,
client_secret=config.CLIENT_SECRET,
client_id=config.client_id,
client_secret=config.client_secret,
)
@ -92,26 +97,33 @@ def initTraktAuth():
# and then return this value, with the title and year removed to improve
# the accuracy of Trakt results.
@dataclass
class Title:
name: str
without_year: str
year: Optional[int]
def getYearFromTitle(title):
ex = Expando()
def __init__(self, title: str):
try:
# Use a regex expression to get the value within the brackets e.g. The Americans (2017)
year_search = re.search(r"\(([A-Za-z0-9_]+)\)", title)
year_value = year_search.group(1)
# Then, get the title without the year value included
title_value = title.split("(")[0].strip()
# Put this together into an object
self.name = title
self.without_year = title_value
self.year = int(year_value)
except Exception:
# If the above failed, then the title doesn't include a year
# so return the object as is.
self.name = title
self.without_year = title
self.year = None
try:
# Use a regex expression to get the value within the brackets e.g The Americans (2017)
yearSearch = re.search(r"\(([A-Za-z0-9_]+)\)", title)
yearValue = yearSearch.group(1)
# Then, get the title without the year value included
titleValue = title.split("(")[0].strip()
# Put this together into an object
ex.titleWithoutYear = titleValue
ex.yearValue = int(yearValue)
return ex
except Exception:
# If the above failed, then the title doesn't include a year
# so return the object as is.
ex.titleWithoutYear = title
ex.yearValue = -1
return ex
def get_year_from_title(title) -> Title:
return Title(title)
# Shows in TV Time are often different to Trakt.TV - in order to improve results and automation,
@ -119,24 +131,24 @@ def getYearFromTitle(title):
# It seems to improve automation, and reduce manual selection....
def checkTitleNameMatch(tvTimeTitle, traktTitle):
def check_title_name_match(tv_time_title: str, trakt_title: str) -> bool:
# If the name is a complete match, then don't bother comparing them!
if tvTimeTitle == traktTitle:
if tv_time_title == trakt_title:
return True
# Split the TvTime title
tvTimeTitleSplit = tvTimeTitle.split()
tv_time_title_split = tv_time_title.split()
# Create an array of words which are found in the Trakt title
wordsMatched = []
words_matched = []
# Go through each word of the TV Time title, and check if it's in the Trakt title
for word in tvTimeTitleSplit:
if word in traktTitle:
wordsMatched.append(word)
for word in tv_time_title_split:
if word in trakt_title:
words_matched.append(word)
# Then calculate what percentage of words matched
quotient = len(wordsMatched) / len(traktTitle.split())
quotient = len(words_matched) / len(trakt_title.split())
percentage = quotient * 100
# If more than 50% of words in the TV Time title exist in the Trakt title,
@ -147,80 +159,76 @@ def checkTitleNameMatch(tvTimeTitle, traktTitle):
# Using TV Time data (Name of Show, Season No and Episode) - find the corresponding show
# in Trakt.TV either by automation, or asking the user to confirm.
TraktTVShow = TypeVar("TraktTVShow")
TraktMovie = TypeVar("TraktMovie")
def getShowByName(name, seasonNo, episodeNo):
# Parse the TV Show's name for year, if one is present in the string
titleObj = getYearFromTitle(name)
SearchResult = Union[TraktTVShow, TraktMovie]
# Create a boolean to indicate if the title contains a year,
# this is used later on to improve the accuracy of picking
# from search results
doesTitleIncludeYear = titleObj.yearValue != -1
# If the title contains a year, then replace the local variable with the stripped version
if doesTitleIncludeYear:
name = titleObj.titleWithoutYear
def get_items_with_same_name(title: Title, items: List[SearchResult]) -> List[SearchResult]:
shows_with_same_name = []
# Request the Trakt API for search results, using the name
tvSearch = TVShow.search(name)
# Create an array of shows which have been matched
showsWithSameName = []
# Go through each result from the search
for show in tvSearch:
# Check if the title is a match, based on our conditions (e.g over 50% of words match)
if checkTitleNameMatch(name, show.title):
for item in items:
if check_title_name_match(title.name, item.title):
# If the title included the year of broadcast, then we can be more picky in the results
# to look for a show with a broadcast year that matches
if doesTitleIncludeYear:
# If the show title is a 1:1 match, with the same broadcast year, then bingo!
if (name == show.title) and (show.year == titleObj.yearValue):
# to look for an item with a broadcast year that matches
if title.year:
# If the item title is a 1:1 match, with the same broadcast year, then bingo!
if (title.name == item.title) and (item.year == title.year):
# Clear previous results, and only use this one
showsWithSameName = []
showsWithSameName.append(show)
shows_with_same_name = [item]
break
# Otherwise, only add the show if the broadcast year matches
if show.year == titleObj.yearValue:
showsWithSameName.append(show)
# If the program doesn't have the broadcast year, then add all the results
# Otherwise, only add the item if the broadcast year matches
if item.year == title.year:
shows_with_same_name.append(item)
# If the item doesn't have the broadcast year, then add all the results
else:
showsWithSameName.append(show)
shows_with_same_name.append(item)
# Sweep through the results once more for 1:1 title name matches,
# then if the list contains one entry with a 1:1 match, then clear the array
# and only use this one!
completeMatchNames = []
for nameFromSearch in showsWithSameName:
if nameFromSearch.title == name:
completeMatchNames.append(nameFromSearch)
return shows_with_same_name
if len(completeMatchNames) == 1:
showsWithSameName = completeMatchNames
# If the search contains multiple results, then we need to confirm with the user which show
# the script should use, or access the local database to see if the user has already provided
# a manual selection
if len(showsWithSameName) > 1:
def get_show_by_name(name: str, season_number: str, episode_number: str):
# Parse the TV Show'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
shows_with_same_name = get_items_with_same_name(title, TVShow.search(name))
complete_match_names = [name_from_search for name_from_search in shows_with_same_name if
name_from_search.title == name]
if len(complete_match_names) == 1:
return complete_match_names[0]
elif len(shows_with_same_name) == 1:
return shows_with_same_name[0]
elif len(shows_with_same_name) < 1:
return None
else:
# If the search contains multiple results, then we need to confirm with the user which show
# 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
userMatchedQuery = Query()
queryResult = userMatchedShowsTable.search(userMatchedQuery.ShowName == name)
user_matched_query = Query()
query_result = userMatchedShowsTable.search(user_matched_query.ShowName == name)
# If the local database already contains an entry for a manual selection
# then don't bother prompting the user to select it again!
if len(queryResult) == 1:
if len(query_result) == 1:
# Get the first result from the query
firstMatch = queryResult[0]
first_match = query_result[0]
# Get the value contains the selection index
firstMatchSelectedIndex = int(firstMatch.get("UserSelectedIndex"))
first_match_selected_index = int(first_match.get("UserSelectedIndex"))
# Check if the user previously requested to skip the show
skipShow = firstMatch.get("SkipShow")
skip_show = first_match.get("SkipShow")
# If the user did not skip, but provided an index selection, get the
# matching show
if not skipShow:
return showsWithSameName[firstMatchSelectedIndex]
if not skip_show:
return shows_with_same_name[first_match_selected_index]
# Otherwise, return None, which will trigger the script to skip
# and move onto the next show
else:
@ -229,44 +237,46 @@ def getShowByName(name, seasonNo, episodeNo):
# then prompt the user to make a selection
else:
print(
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.\a"
f"INFO - MANUAL INPUT REQUIRED: The TV Time data for Show '{name}' (Season {season_number},"
f"Episode {episode_number}) has {len(shows_with_same_name)} matching Trakt shows with the same name.\a "
)
# Output each show for manual selection
for idx, item in enumerate(showsWithSameName):
for idx, item in enumerate(shows_with_same_name):
# Display the show'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} - {len(item.seasons)} Season(s) - More Info: https://trakt.tv/{item.ext}"
f" ({idx + 1}) {item.title} - {item.year} - {len(item.seasons)} "
f"Season(s) - More Info: https://trakt.tv/{item.ext}"
)
while True:
try:
# Get the user's selection, either a numerical input, or a string 'SKIP' value
indexSelected = input(
index_selected = input(
"Please make a selection from above (or enter SKIP):"
)
if indexSelected != "SKIP":
# Since the value isn't 'skip', check that the result is numerical
indexSelected = int(indexSelected) - 1
# Exit the selection loop
break
# Otherwise, exit the loop
else:
# Exit the loop
if index_selected == "SKIP":
break
# Since the value isn't 'skip', check that the result is numerical
index_selected = int(index_selected) - 1
# Exit the selection loop
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(showsWithSameName)}"
f"Sorry! Please select a value between 0 to {len(shows_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 indexSelected == "SKIP":
if index_selected == "SKIP":
# Record that the user has skipped the TV Show for import, so that
# manual input isn't required everytime
userMatchedShowsTable.insert(
@ -276,103 +286,92 @@ def getShowByName(name, seasonNo, episodeNo):
return None
# Otherwise, return the selection which the user made from the list
else:
selectedShow = showsWithSameName[int(indexSelected)]
selected_show = shows_with_same_name[int(index_selected)]
userMatchedShowsTable.insert(
{
"ShowName": name,
"UserSelectedIndex": indexSelected,
"UserSelectedIndex": index_selected,
"SkipShow": False,
}
)
return selectedShow
else:
if len(showsWithSameName) > 0:
# If the search returned only one result, then awesome!
# Return the show, so the import automation can continue.
return showsWithSameName[0]
else:
return None
return selected_show
# Since the Trakt.Py starts the indexing of seasons in the array from 0 (e.g Season 1 in Index 0), then
# subtract the TV Time numerical value by 1 so it starts from 0 as well. However, when a TV series includes
# Since the Trakt.Py starts the indexing of seasons in the array from 0 (e.g. Season 1 in Index 0), then
# subtract the TV Time numerical value by 1, so it starts from 0 as well. However, when a TV series includes
# a 'special' season, Trakt.Py will place this as the first season in the array - so, don't subtract, since
# this will match TV Time's existing value.
def parseSeasonNo(seasonNo, traktShowObj):
def parse_season_number(season_number, trakt_show_obj):
# Parse the season number into a numerical value
seasonNo = int(seasonNo)
season_number = int(season_number)
# Then get the Season Number from the first item in the array
firstSeasonNo = traktShowObj.seasons[0].number
first_season_no = trakt_show_obj.seasons[0].number
# If the season number is 0, then the Trakt show contains a "special" season
if firstSeasonNo == 0:
if first_season_no == 0:
# No need to modify the value, as the TV Time value will match Trakt
return seasonNo
return season_number
# Otherwise, if the Trakt seasons start with no specials, then return the seasonNo,
# but subtracted by one (e.g Season 1 in TV Time, will be 0)
else:
# Only subtract if the TV Time season number is greater than 0.
if seasonNo != 0:
return seasonNo - 1
if season_number != 0:
return season_number - 1
# Otherwise, the TV Time season is a special! Then you don't need to change the starting position
else:
return seasonNo
return season_number
def processWatchedShows():
# Total amount of rows which have been processed in the CSV file
rowsCount = 0
# Total amount of rows in the CSV file
errorStreak = 0
def process_watched_shows() -> None:
# Open the CSV file within the GDPR exported data
with open(getWatchedShowsPath(), newline="") as csvfile:
with open(WATCHED_SHOWS_PATH, newline="") as csvfile:
# Create the CSV reader, which will break up the fields using the delimiter ','
showsReader = csv.DictReader(csvfile, delimiter=",")
shows_reader = csv.DictReader(csvfile, delimiter=",")
# Get the total amount of rows in the CSV file,
rowsTotal = len(list(showsReader))
rows_total = len(list(shows_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(showsReader, None)
for rowsCount, row in enumerate(showsReader):
next(shows_reader, None)
for rowsCount, row in enumerate(shows_reader):
# Get the name of the TV show
tvShowName = row["tv_show_name"]
# Get the TV Time Episode Id
tvShowEpisodeId = row["episode_id"]
tv_show_name = row["tv_show_name"]
# Get the TV Time Episode id
tv_show_episode_id = row["episode_id"]
# Get the TV Time Season Number
tvShowSeasonNo = row["episode_season_number"]
tv_show_season_number = row["episode_season_number"]
# Get the TV Time Episode Number
tvShowEpisodeNo = row["episode_number"]
tv_show_episode_number = row["episode_number"]
# Get the date which the show was marked 'watched' in TV Time
tvShowDateWatched = row["updated_at"]
tv_show_date_watched = row["updated_at"]
# Parse the watched date value into a Python type
tvShowDateWatchedConverted = datetime.strptime(
tvShowDateWatched, "%Y-%m-%d %H:%M:%S"
tv_show_date_watched_converted = datetime.strptime(
tv_show_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
episodeCompletedQuery = Query()
queryResult = syncedEpisodesTable.search(
episodeCompletedQuery.episodeId == tvShowEpisodeId
episode_completed_query = Query()
query_result = syncedEpisodesTable.search(
episode_completed_query.episodeId == tv_show_episode_id
)
# If the query returned no results, then continue to import it into Trakt
if len(queryResult) == 0:
if len(query_result) == 0:
# Create a repeating loop, which will break on success, but repeats on failures
error_streak = 0
while True:
# If more than 10 errors occurred in one streak, whilst trying to import the episode
# then give up, and move onto the next episode, but warn the user.
if errorStreak > 10:
if error_streak > 10:
logging.warning(
"An error occurred 10 times in a row... skipping episode..."
)
@ -383,46 +382,50 @@ def processWatchedShows():
# Other developers share the service, for free - so be considerate of your usage.
time.sleep(DELAY_BETWEEN_EPISODES_IN_SECONDS)
# Search Trakt for the TV show matching TV Time's title value
traktShowObj = getShowByName(
tvShowName, tvShowSeasonNo, tvShowEpisodeNo
trakt_show = get_show_by_name(
tv_show_name, tv_show_season_number, tv_show_episode_number
)
# If the method returned 'None', then this is an indication to skip the episode, and
# move onto the next one
if traktShowObj is None:
if not trakt_show:
break
# Show the progress of the import on-screen
logging.info(
f"({rowsCount+1}/{rowsTotal}) - Processing '{tvShowName}' Season {tvShowSeasonNo} / Episode {tvShowEpisodeNo}"
f"({rowsCount + 1}/{rows_total}) - Processing '{tv_show_name}' Season {tv_show_season_number} /"
f"Episode {tv_show_episode_number}"
)
# Get the season from the Trakt API
season = traktShowObj.seasons[
parseSeasonNo(tvShowSeasonNo, traktShowObj)
season = trakt_show.seasons[
parse_season_number(tv_show_season_number, trakt_show)
]
# Get the episode from the season
episode = season.episodes[int(tvShowEpisodeNo) - 1]
episode = season.episodes[int(tv_show_episode_number) - 1]
# Mark the episode as watched!
episode.mark_as_seen(tvShowDateWatchedConverted)
episode.mark_as_seen(tv_show_date_watched_converted)
# Add the episode to the local database as imported, so it can be skipped,
# if the process is repeated
syncedEpisodesTable.insert({"episodeId": tvShowEpisodeId})
syncedEpisodesTable.insert({"episodeId": tv_show_episode_id})
# Clear the error streak on completing the method without errors
errorStreak = 0
error_streak = 0
break
# Catch errors which occur because of an incorrect array index. This occurs when
# an incorrect Trakt show 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:
tvShowSlug = traktShowObj.to_json()["shows"][0]["ids"]["ids"][
tv_show_slug = trakt_show.to_json()["shows"][0]["ids"]["ids"][
"slug"
]
logging.warning(
f"({rowsCount}/{rowsTotal}) - {tvShowName} Season {tvShowSeasonNo}, Episode {tvShowEpisodeNo} does not exist in Trakt! (https://trakt.tv/shows/{tvShowSlug}/seasons/{tvShowSeasonNo}/episodes/{tvShowEpisodeNo})"
f"({rowsCount}/{rows_total}) - {tv_show_name} Season {tv_show_season_number}, "
f"Episode {tv_show_episode_number} does not exist in Trakt! "
f"(https://trakt.tv/shows/{tv_show_slug}/seasons/{tv_show_season_number}/episodes/{tv_show_episode_number})"
)
break
# Catch any errors which are raised because a show could not be found in Trakt
except trakt.errors.NotFoundException:
logging.warning(
f"({rowsCount}/{rowsTotal}) - {tvShowName} Season {tvShowSeasonNo}, Episode {tvShowEpisodeNo} does not exist (search) in Trakt!"
f"({rowsCount}/{rows_total}) - {tv_show_name} Season {tv_show_season_number}, "
f"Episode {tv_show_episode_number} does not exist (search) in Trakt!"
)
break
# Catch errors because of the program breaching the Trakt API rate limit
@ -435,12 +438,12 @@ def processWatchedShows():
time.sleep(60)
# Mark the exception in the error streak
errorStreak += 1
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"({rowsCount}/{rowsTotal}) - A JSON decode error occuring whilst processing {tvShowName} "
+ f"Season {tvShowSeasonNo}, Episode {tvShowEpisodeNo}! This might occur when the server is down and has produced "
f"({rowsCount}/{rows_total}) - A JSON decode error occuring whilst processing {tv_show_name} "
+ f"Season {tv_show_season_number}, Episode {tv_show_episode_number}! 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."
)
@ -448,57 +451,347 @@ def processWatchedShows():
time.sleep(60)
# Mark the exception in the error streak
errorStreak += 1
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"({rowsCount}/{rowsTotal}) - Already imported, skipping '{tvShowName}' Season {tvShowSeasonNo} / Episode {tvShowEpisodeNo}."
f"({rowsCount}/{rows_total}) - Already imported, skipping '{tv_show_name}' Season {tv_show_season_number} / Episode {tv_show_episode_number}."
)
def start():
# Create the initial authentication with Trakt, before starting the process
if initTraktAuth():
# Display a menu selection
print(">> What do you want to do?")
print(" 1) Import Watch History from TV Time")
# Using TV Time data (Name of Movie) - find the corresponding movie
# in Trakt.TV either by automation, or asking the user to confirm.
while True:
try:
menuSelection = input("Enter your menu selection: ")
menuSelection = 1 if not menuSelection else int(menuSelection)
break
except ValueError:
logging.warning("Invalid input. Please enter a numerical number.")
# Start the process which is required
if menuSelection == 1:
# Invoke the method which will import episodes which have been watched
# from TV Time into Trakt
processWatchedShows()
else:
logging.warning("Sorry - that's an unknown menu selection")
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 created the config file
if os.path.exists("config.json"):
# Check that the user has provided the GDPR path
if os.path.isdir(config.GDPR_WORKSPACE_PATH):
start()
else:
logging.error(
"Oops! The TV Time GDPR folder '"
+ config.GDPR_WORKSPACE_PATH
+ "' does not exist on the local system. Please check it, and try again."
)
# Check that the user has provided the GDPR path
if os.path.isdir(config.gdpr_workspace_path):
start()
else:
logging.error(
"The 'config.json' file cannot be found - have you created it yet?"
"Oops! The TV Time GDPR folder '"
+ config.gdpr_workspace_path
+ "' does not exist on the local system. Please check it, and try again."
)