Merge movie support

.gitignore

@@ -1,6 +1 @@
-watched_show_process_tracker.json
-localStorage.json
-config.json
-TimeToTrackt.py
-seen_episode.csv
-followed_tv_show.csv
+*.json

.vscode/launch.json

@@ -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"
-        }
-    ]
-}

README.md

@@ -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
 

TimeToTrakt.py

@@ -13,6 +13,7 @@ import trakt.core
 from tinydb import Query, TinyDB
 from trakt import init
 from trakt.tv import TVShow
+from trakt.movies import Movie
 
 # Setup logger
 logging.basicConfig(
@@ -25,10 +26,12 @@ 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):
@@ -64,7 +67,7 @@ def getConfiguration():
 
 config = getConfiguration()
 
-# Return the path to the CSV file contain the watched episode data from TV Time
+# Return the path to the CSV file contain the watched episode and movie data from TV Time
 
 
 def getWatchedShowsPath():
@@ -75,6 +78,10 @@ def getFollowedShowsPath():
     return config.GDPR_WORKSPACE_PATH + "/followed_tv_show.csv"
 
 
+def getMoviesPath():
+    return config.GDPR_WORKSPACE_PATH + "/tracking-prod-records.csv"
+
+
 def initTraktAuth():
     if isAuthenticated():
         return True
@@ -206,7 +213,8 @@ def getShowByName(name, seasonNo, episodeNo):
 
         # Query the local database for existing selection
         userMatchedQuery = Query()
-        queryResult = userMatchedShowsTable.search(userMatchedQuery.ShowName == name)
+        queryResult = userMatchedShowsTable.search(
+            userMatchedQuery.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!
@@ -404,7 +412,8 @@ def processWatchedShows():
                         episode.mark_as_seen(tvShowDateWatchedConverted)
                         # 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": tvShowEpisodeId})
                         # Clear the error streak on completing the method without errors
                         errorStreak = 0
                         break
@@ -459,27 +468,357 @@ def processWatchedShows():
                 )
 
 
+# Using TV Time data (Name of Movie) - find the corresponding movie
+# in Trakt.TV either by automation, or asking the user to confirm.
+
+
+def getMovieByName(name):
+    # Parse the Movie's name for year, if one is present in the string
+    titleObj = getYearFromTitle(name)
+
+    # 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
+
+    # Request the Trakt API for search results, using the name
+    movieSearch = Movie.search(name)
+
+    # Create an array of movies which have been matched
+    moviesWithSameName = []
+
+    # Go through each result from the search
+    for movie in movieSearch:
+        # Check if the title is a match, based on our conditions (e.g over 50% of words match)
+        if checkTitleNameMatch(name, movie.title):
+            # If the title included the year of broadcast, then we can be more picky in the results
+            # to look for a movie with a broadcast year that matches
+            if doesTitleIncludeYear:
+                # If the movie title is a 1:1 match, with the same broadcast year, then bingo!
+                if (name == movie.title) and (movie.year == titleObj.yearValue):
+                    # Clear previous results, and only use this one
+                    moviesWithSameName = []
+                    moviesWithSameName.append(movie)
+                    break
+
+                # Otherwise, only add the movie if the broadcast year matches
+                if movie.year == titleObj.yearValue:
+                    moviesWithSameName.append(movie)
+            # If the program doesn't have the broadcast year, then add all the results
+            else:
+                moviesWithSameName.append(movie)
+
+    # 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 moviesWithSameName:
+        if nameFromSearch.title == name:
+            completeMatchNames.append(nameFromSearch)
+
+    if len(completeMatchNames) == 1:
+        moviesWithSameName = completeMatchNames
+
+    # 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
+    if len(moviesWithSameName) > 1:
+
+        # Query the local database for existing selection
+        userMatchedQuery = Query()
+        queryResult = userMatchedMoviesTable.search(
+            userMatchedQuery.movie_name == 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:
+            # Get the first result from the query
+            firstMatch = queryResult[0]
+            # Get the value contains the selection index
+            firstMatchSelectedIndex = int(firstMatch.get("UserSelectedIndex"))
+            # Check if the user previously requested to skip the movie
+            skipMovie = firstMatch.get("SkipMovie")
+            # If the user did not skip, but provided an index selection, get the
+            # matching movie
+            if not skipMovie:
+                return moviesWithSameName[firstMatchSelectedIndex]
+            # 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(moviesWithSameName)} matching Trakt movies with the same name.\a"
+            )
+
+            # Output each movie for manual selection
+            for idx, item in enumerate(moviesWithSameName):
+                # 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
+                    indexSelected = 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:
+                        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(moviesWithSameName)}"
+                    )
+
+            # 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":
+                # Record that the user has skipped the Movie for import, so that
+                # manual input isn't required everytime
+                userMatchedMoviesTable.insert(
+                    {"movie_name": name, "UserSelectedIndex": 0, "SkipMovie": True}
+                )
+
+                return None
+            # Otherwise, return the selection which the user made from the list
+            else:
+                selectedMovie = moviesWithSameName[int(indexSelected)]
+
+                userMatchedMoviesTable.insert(
+                    {
+                        "movie_name": name,
+                        "UserSelectedIndex": indexSelected,
+                        "SkipMovie": False,
+                    }
+                )
+
+                return selectedMovie
+
+    else:
+        if len(moviesWithSameName) > 0:
+            # If the search returned only one result, then awesome!
+            # Return the movie, so the import automation can continue.
+            return moviesWithSameName[0]
+        else:
+            return None
+
+
+def processMovies():
+    # Total amount of rows which have been processed in the CSV file
+    rowsCount = 0
+    # Total amount of rows in the CSV file
+    errorStreak = 0
+    # Open the CSV file within the GDPR exported data
+    with open(getMoviesPath(), newline="") as csvfile:
+        # Create the CSV reader, which will break up the fields using the delimiter ','
+        movieReaderTemp = csv.DictReader(csvfile, delimiter=",")
+        movieReader = filter(lambda p: '' != p['movie_name'], movieReaderTemp)
+        # First, list all movies with watched type so that watchlist entry for them is not created
+        watchedList = []
+        for row in movieReader:
+            if row["type"] == "watch":
+                watchedList.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,
+        rowsTotal = len(list(movieReader))
+        # 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(movieReader, None)
+        for rowsCount, row in enumerate(movieReader):
+            # Get the name of the Movie
+            movieName = row["movie_name"]
+            # Get the date which the movie was marked 'watched' in TV Time
+            activityType = row["type"]
+            movieDateWatched = row["updated_at"]
+            # Parse the watched date value into a Python type
+            movieDateWatchedConverted = datetime.strptime(
+                movieDateWatched, "%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
+            movieQuery = Query()
+            queryResult = syncedMoviesTable.search(
+                (movieQuery.movie_name == movieName) &
+                (movieQuery.type == "watched")
+            )
+
+            watchlistQuery = Query()
+            queryResultWatchlist = syncedMoviesTable.search(
+                (watchlistQuery.movie_name == movieName) &
+                (watchlistQuery.type == "watchlist")
+            )
+
+            # If the query returned no results, then continue to import it into Trakt
+            if len(queryResult) == 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 movieName in watchedList and activityType != "watch":
+                        logging.info(
+                            f"Skipping '{movieName}' 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 errorStreak > 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
+                        traktMovieObj = getMovieByName(movieName)
+                        # If the method returned 'None', then this is an indication to skip the episode, and
+                        # move onto the next one
+                        if traktMovieObj is None:
+                            break
+                        # Show the progress of the import on-screen
+                        logging.info(
+                            f"({rowsCount+1}/{rowsTotal}) - Processing '{movieName}'"
+                        )
+                        if activityType == "watch":
+                            traktMovieObj.mark_as_seen(
+                                movieDateWatchedConverted)
+                            # Add the episode to the local database as imported, so it can be skipped,
+                            # if the process is repeated
+                            syncedMoviesTable.insert(
+                                {"movie_name": movieName, "type": "watched"})
+                            logging.info(f"Marked as seen")
+                        elif len(queryResultWatchlist) == 0:
+                            traktMovieObj.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": movieName, "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
+                        errorStreak = 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:
+                        movieSlug = traktMovieObj.to_json()["movies"][0]["ids"]["ids"][
+                            "slug"
+                        ]
+                        logging.warning(
+                            f"({rowsCount}/{rowsTotal}) - {movieName} does not exist in Trakt! (https://trakt.tv/movies/{movieSlug}/)"
+                        )
+                        break
+                    # Catch any errors which are raised because a movie could not be found in Trakt
+                    except trakt.errors.NotFoundException:
+                        logging.warning(
+                            f"({rowsCount}/{rowsTotal}) - {movieName} 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
+                        errorStreak += 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 {movieName} "
+                            + 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
+                        errorStreak += 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 '{movieName}'."
+                )
+
+
 def start():
+    # 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")
+    print("    4) Exit")
+
+    while True:
+        try:
+            menuSelection = input("Enter your menu selection: ")
+            menuSelection = 3 if not menuSelection else int(menuSelection)
+            break
+        except ValueError:
+            logging.warning(
+                "Invalid input. Please enter a numerical number.")
+        # Check if the input is valid
+    if not 1 <= menuSelection <= 4:
+        logging.warning("Sorry - that's an unknown menu selection")
+        exit()
+    # Exit if the 4th option was chosen
+    if menuSelection == 4:
+        logging.info("Exiting as per user's selection.")
+        exit()
     # 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")
-
-        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
+            logging.info("Processing watched shows.")
             processWatchedShows()
-        else:
-            logging.warning("Sorry - that's an unknown menu selection")
+            # TODO: Add support for followed shows
+        elif menuSelection == 2:
+            # Invoke the method which will import movies which have been watched
+            # from TV Time into Trakt
+            logging.info("Processing movies.")
+            processMovies()
+        elif menuSelection == 3:
+            # Invoke both the episodes and movies import methods
+            logging.info("Processing both watched shows and movies.")
+            processWatchedShows()
+            processMovies()
     else:
         logging.error(
             "ERROR: Unable to complete authentication to Trakt - please try again."