Пример #1
0
def start_puzzle_from(filename, index=None):
    if filename.lower().endswith(".pgn"):
        if filename.startswith("lichess_study"):
            chessfile = PGNFile(protoopen(addDataPrefix("learn/puzzles/%s" % filename), encoding="utf-8"))
        else:
            chessfile = PGNFile(protoopen(addDataPrefix("learn/puzzles/%s" % filename)))
        chessfile.limit = 1000
        chessfile.init_tag_database()
    elif filename.lower().endswith(".olv"):
        chessfile = OLVFile(protoopen(addDataPrefix("learn/puzzles/%s" % filename), encoding="utf-8"))

    records, plys = chessfile.get_records()

    progress = puzzles_solving_progress.get(filename, [0] * chessfile.count)

    if index is None:
        index = progress.index(0)

    rec = records[index]

    timemodel = TimeModel(0, 0)
    gamemodel = LearnModel(timemodel)

    chessfile.loadToModel(rec, 0, gamemodel)

    start_puzzle_game(gamemodel, filename, records, index, rec)
Пример #2
0
    def row_activated(self, widget, path, col):
        if path is None:
            return
        filename = addDataPrefix("lectures/%s" % LESSONS[path[0]][0])

        chessfile = PGNFile(protoopen(filename))
        self.importer = PgnImport(chessfile)
        chessfile.init_tag_database(self.importer)
        records, plys = chessfile.get_records()

        rec = records[random.randrange(0, len(records))]
        print(rec)

        timemodel = TimeModel(0, 0)
        gamemodel = GameModel(timemodel)
        gamemodel.set_lesson_game()

        chessfile.loadToModel(rec, -1, gamemodel)

        name = conf.get("firstName", _("You"))
        p0 = (LOCAL, Human, (WHITE, name), name)
        name = "pychessbot"
        p1 = (LOCAL, Human, (BLACK, name), name)

        gamemodel.status = WAITING_TO_START
        perspective = perspective_manager.get_perspective("games")
        asyncio. async (perspective.generalStart(gamemodel, p0, p1))
Пример #3
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def start_lesson_from(filename, index=None):
    chessfile = PGNFile(protoopen(addDataPrefix("learn/lessons/%s" %
                                                filename)))
    chessfile.limit = 1000
    chessfile.init_tag_database()
    records, plys = chessfile.get_records()

    progress = lessons_solving_progress.get(filename, [0] * chessfile.count)

    if index is None:
        index = progress.index(0)

    rec = records[index]

    timemodel = TimeModel(0, 0)
    gamemodel = LearnModel(timemodel)

    chessfile.loadToModel(rec, -1, gamemodel)

    if len(gamemodel.moves) > 0:
        start_lesson_game(gamemodel, filename, chessfile, records, index, rec)
    else:
        start_puzzle_game(gamemodel,
                          filename,
                          records,
                          index,
                          rec,
                          from_lesson=True)
Пример #4
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def start_lesson_from(filename, index=None):
    if filename.startswith("lichess_study"):
        chessfile = PGNFile(
            protoopen(addDataPrefix("learn/lessons/%s" % filename),
                      encoding="utf-8"))
    else:
        chessfile = PGNFile(
            protoopen(addDataPrefix("learn/lessons/%s" % filename)))
    chessfile.limit = 1000
    chessfile.init_tag_database()
    records, plys = chessfile.get_records()

    progress = lessons_solving_progress.get(filename, [0] * chessfile.count)

    if index is None:
        index = progress.index(0)

    rec = records[index]

    timemodel = TimeModel(0, 0)
    gamemodel = LearnModel(timemodel)
    gamemodel.set_learn_data(LESSON, filename, index, len(records))

    chessfile.loadToModel(rec, -1, gamemodel)

    color = gamemodel.boards[0].color
    player_name = conf.get("firstName", _("You"))

    w_name = player_name if color == WHITE else "PyChess"
    b_name = "PyChess" if color == WHITE else player_name

    p0 = (LOCAL, Human, (WHITE, w_name), w_name)
    p1 = (LOCAL, Human, (BLACK, b_name), b_name)

    def learn_success(gamemodel):
        chessfile.loadToModel(rec, -1, gamemodel)
        progress = lessons_solving_progress[gamemodel.source]
        progress[gamemodel.current_index] = 1
        lessons_solving_progress[gamemodel.source] = progress
        asyncio. async (gamemodel.restart_analyzer(HINT))

    gamemodel.connect("learn_success", learn_success)

    def on_game_started(gamemodel):
        perspective.activate_panel("annotationPanel")
        asyncio. async (gamemodel.start_analyzer(
            HINT, force_engine=discoverer.getEngineLearn()))

    gamemodel.connect("game_started", on_game_started)

    gamemodel.status = WAITING_TO_START
    perspective = perspective_manager.get_perspective("games")
    asyncio. async (perspective.generalStart(gamemodel, p0, p1))
Пример #5
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def start_lesson_from(filename, index=None):
    chessfile = PGNFile(protoopen(addDataPrefix("learn/lessons/%s" % filename)))
    chessfile.limit = 1000
    chessfile.init_tag_database()
    records, plys = chessfile.get_records()

    progress = lessons_solving_progress.get(filename, [0] * chessfile.count)

    if index is None:
        index = progress.index(0)

    rec = records[index]

    timemodel = TimeModel(0, 0)
    gamemodel = LearnModel(timemodel)
    gamemodel.set_learn_data(LESSON, filename, index, len(records))

    chessfile.loadToModel(rec, -1, gamemodel)

    color = gamemodel.boards[0].color
    player_name = conf.get("firstName", _("You"))

    w_name = player_name if color == WHITE else "PyChess"
    b_name = "PyChess" if color == WHITE else player_name

    p0 = (LOCAL, Human, (WHITE, w_name), w_name)
    p1 = (LOCAL, Human, (BLACK, b_name), b_name)

    def learn_success(gamemodel):
        progress = lessons_solving_progress[gamemodel.source]
        progress[gamemodel.current_index] = 1
        lessons_solving_progress[gamemodel.source] = progress
        asyncio.async(gamemodel.restart_analyzer(HINT))
    gamemodel.connect("learn_success", learn_success)

    def start_analyzer(gamemodel):
        asyncio.async(gamemodel.start_analyzer(HINT, force_engine=discoverer.getEngineLearn()))
    gamemodel.connect("game_started", start_analyzer)

    gamemodel.status = WAITING_TO_START
    perspective = perspective_manager.get_perspective("games")
    asyncio.async(perspective.generalStart(gamemodel, p0, p1))
Пример #6
0
def start_puzzle_from(filename):
    chessfile = PGNFile(protoopen(addDataPrefix("lectures/%s" % filename)))
    chessfile.limit = 1000
    importer = PgnImport(chessfile)
    chessfile.init_tag_database(importer)
    records, plys = chessfile.get_records()

    rec = records[random.randrange(0, len(records))]

    timemodel = TimeModel(0, 0)
    gamemodel = GameModel(timemodel)
    gamemodel.set_practice_game()
    gamemodel.practice = ("puzzle", filename)

    chessfile.loadToModel(rec, 0, gamemodel)

    # TODO: change colors according to FEN!
    name = rec["White"]
    p0 = (LOCAL, Human, (WHITE, name), name)

    engine = discoverer.getEngineByName(stockfish_name)
    name = rec["Black"]
    ponder_off = True
    p1 = (ARTIFICIAL, discoverer.initPlayerEngine,
          (engine, BLACK, 20, variants[NORMALCHESS], 60, 0, 0,
           ponder_off), name)

    def fix_name(gamemodel, name):
        asyncio. async (gamemodel.start_analyzer(HINT,
                                                 force_engine=stockfish_name))
        gamemodel.players[1].name = name
        gamemodel.emit("players_changed")

    gamemodel.connect("game_started", fix_name, name)

    gamemodel.variant.need_initial_board = True
    gamemodel.status = WAITING_TO_START

    perspective = perspective_manager.get_perspective("games")
    asyncio. async (perspective.generalStart(gamemodel, p0, p1))
Пример #7
0
def start_lesson_from(filename, index=None):
    chessfile = PGNFile(protoopen(addDataPrefix("learn/lessons/%s" % filename)))
    chessfile.limit = 1000
    chessfile.init_tag_database()
    records, plys = chessfile.get_records()

    progress = lessons_solving_progress.get(filename, [0] * chessfile.count)

    if index is None:
        index = progress.index(0)

    rec = records[index]

    timemodel = TimeModel(0, 0)
    gamemodel = LearnModel(timemodel)

    chessfile.loadToModel(rec, -1, gamemodel)

    if len(gamemodel.moves) > 0:
        start_lesson_game(gamemodel, filename, chessfile, records, index, rec)
    else:
        start_puzzle_game(gamemodel, filename, records, index, rec, from_lesson=True)
Пример #8
0
def start_puzzle_from(filename, index=None):
    if filename.lower().endswith(".pgn"):
        chessfile = PGNFile(protoopen(addDataPrefix("learn/puzzles/%s" % filename)))
        chessfile.limit = 1000
        chessfile.init_tag_database()
    elif filename.lower().endswith(".olv"):
        chessfile = OLVFile(protoopen(addDataPrefix("learn/puzzles/%s" % filename), encoding="utf-8"))

    records, plys = chessfile.get_records()

    progress = puzzles_solving_progress.get(filename, [0] * chessfile.count)

    if index is None:
        index = progress.index(0)

    rec = records[index]

    timemodel = TimeModel(0, 0)
    gamemodel = LearnModel(timemodel)

    chessfile.loadToModel(rec, 0, gamemodel)

    start_puzzle_game(gamemodel, filename, records, index, rec)
Пример #9
0
def start_puzzle_from(filename, index=None):
    if filename.lower().endswith(".pgn"):
        if filename.startswith("lichess_study"):
            chessfile = PGNFile(
                protoopen(addDataPrefix("learn/puzzles/%s" % filename),
                          encoding="utf-8"))
        else:
            chessfile = PGNFile(
                protoopen(addDataPrefix("learn/puzzles/%s" % filename)))
        chessfile.limit = 1000
        chessfile.init_tag_database()
    elif filename.lower().endswith(".olv"):
        chessfile = OLVFile(
            protoopen(addDataPrefix("learn/puzzles/%s" % filename),
                      encoding="utf-8"))

    records, plys = chessfile.get_records()

    progress = puzzles_solving_progress.get(filename, [0] * chessfile.count)

    if index is None:
        index = progress.index(0)

    rec = records[index]

    timemodel = TimeModel(0, 0)
    gamemodel = LearnModel(timemodel)
    gamemodel.set_learn_data(PUZZLE, filename, index, len(records))

    chessfile.loadToModel(rec, 0, gamemodel)

    engine = discoverer.getEngineByName(discoverer.getEngineLearn())
    ponder_off = True

    color = gamemodel.boards[0].color

    w_name = "" if rec["White"] is None else rec["White"]
    b_name = "" if rec["Black"] is None else rec["Black"]

    player_name = conf.get("firstName", _("You"))
    engine_name = discoverer.getName(engine)

    if rec["Event"].startswith("Lichess Practice"):
        w_name = player_name if color == WHITE else engine_name
        b_name = engine_name if color == WHITE else player_name

    opp_name = engine_name if rec["Event"].startswith(
        "Lichess Practice") else b_name

    if color == WHITE:
        p0 = (LOCAL, Human, (WHITE, w_name), w_name)
        p1 = (ARTIFICIAL, discoverer.initPlayerEngine,
              (engine, BLACK, 20, variants[NORMALCHESS], 20, 0, 0,
               ponder_off), b_name)
    else:
        p0 = (ARTIFICIAL, discoverer.initPlayerEngine,
              (engine, WHITE, 20, variants[NORMALCHESS], 20, 0, 0,
               ponder_off), w_name)
        p1 = (LOCAL, Human, (BLACK, b_name), b_name)

    def on_game_started(gamemodel, name, color):
        perspective.activate_panel("annotationPanel")
        asyncio. async (gamemodel.start_analyzer(
            HINT, force_engine=discoverer.getEngineLearn()))
        gamemodel.players[1 - color].name = name
        gamemodel.emit("players_changed")

    gamemodel.connect("game_started", on_game_started, opp_name, color)

    def goal_checked(gamemodle):
        if gamemodel.reason == PRACTICE_GOAL_REACHED:
            progress = puzzles_solving_progress[gamemodel.source]
            progress[gamemodel.current_index] = 1
            puzzles_solving_progress[gamemodel.source] = progress

    gamemodel.connect("goal_checked", goal_checked)

    gamemodel.variant.need_initial_board = True
    gamemodel.status = WAITING_TO_START

    perspective = perspective_manager.get_perspective("games")
    asyncio. async (perspective.generalStart(gamemodel, p0, p1))
Пример #10
0
def start_puzzle_from(filename, index=None):
    if filename.lower().endswith(".pgn"):
        chessfile = PGNFile(protoopen(addDataPrefix("learn/puzzles/%s" % filename)))
        chessfile.limit = 1000
        chessfile.init_tag_database()
    elif filename.lower().endswith(".olv"):
        chessfile = OLVFile(protoopen(addDataPrefix("learn/puzzles/%s" % filename), encoding="utf-8"))

    records, plys = chessfile.get_records()

    progress = puzzles_solving_progress.get(filename, [0] * chessfile.count)

    if index is None:
        index = progress.index(0)

    rec = records[index]

    timemodel = TimeModel(0, 0)
    gamemodel = LearnModel(timemodel)

    chessfile.loadToModel(rec, 0, gamemodel)
    gamemodel.set_learn_data(PUZZLE, filename, index, len(records))

    engine = discoverer.getEngineByName(discoverer.getEngineLearn())
    ponder_off = True

    color = gamemodel.boards[0].color

    w_name = "" if rec["White"] is None else rec["White"]
    b_name = "" if rec["Black"] is None else rec["Black"]

    player_name = conf.get("firstName", _("You"))
    engine_name = discoverer.getName(engine)

    if rec["Event"].startswith("Lichess Practice"):
        w_name = player_name if color == WHITE else engine_name
        b_name = engine_name if color == WHITE else player_name

    opp_name = engine_name if rec["Event"].startswith("Lichess Practice") else b_name

    if color == WHITE:
        p0 = (LOCAL, Human, (WHITE, w_name), w_name)
        p1 = (ARTIFICIAL, discoverer.initPlayerEngine,
              (engine, BLACK, 20, variants[NORMALCHESS], 20, 0, 0, ponder_off), b_name)
    else:
        p0 = (ARTIFICIAL, discoverer.initPlayerEngine,
              (engine, WHITE, 20, variants[NORMALCHESS], 20, 0, 0, ponder_off), w_name)
        p1 = (LOCAL, Human, (BLACK, b_name), b_name)

    def start_analyzer(gamemodel, name, color):
        asyncio.async(gamemodel.start_analyzer(HINT, force_engine=discoverer.getEngineLearn()))
        gamemodel.players[1 - color].name = name
        gamemodel.emit("players_changed")
    gamemodel.connect("game_started", start_analyzer, opp_name, color)

    def goal_checked(gamemodle):
        if gamemodel.reason == PRACTICE_GOAL_REACHED:
            progress = puzzles_solving_progress[gamemodel.source]
            progress[gamemodel.current_index] = 1
            puzzles_solving_progress[gamemodel.source] = progress
    gamemodel.connect("goal_checked", goal_checked)

    gamemodel.variant.need_initial_board = True
    gamemodel.status = WAITING_TO_START

    perspective = perspective_manager.get_perspective("games")
    asyncio.async(perspective.generalStart(gamemodel, p0, p1))