Python開發(fā)連連看，PC也可以玩啦！

版本：Python3.6

import PIL.ImageGrabimport pyautoguiimport win32apiimport win32guiimport win32conimport timeimport random

開始游戲后運(yùn)行就行了, 再次提示, 請?jiān)诰毩?xí)模式中使用, 否則可能會(huì)被其他玩家舉報(bào)。

import PIL.ImageGrabimport pyautoguiimport win32apiimport win32guiimport win32conimport timeimport random
def color_hash(color):    value = ""    for i in range(5):        value += "%d,%d,%d," % (color[0], color[1], color[2])    return hash(value)

def image_hash(img):    value = ""    for i in range(5):        c = img.getpixel((i * 3, i * 3))        value += "%d,%d,%d," % (c[0], c[1], c[2])    return hash(value)

def game_area_image_to_matrix():    pos_to_image = {}
    for row in range(ROW_NUM):        pos_to_image[row] = {}        for col in range(COL_NUM):            grid_left = col * grid_width            grid_top = row * grid_height            grid_right = grid_left + grid_width            grid_bottom = grid_top + grid_height
            grid_image = game_area_image.crop((grid_left, grid_top, grid_right, grid_bottom))
            pos_to_image[row][col] = grid_image
    pos_to_type_id = {}    image_map = {}
    empty_hash = color_hash((48, 76, 112))
    for row in range(ROW_NUM):        pos_to_type_id[row] = {}        for col in range(COL_NUM):            this_image = pos_to_image[row][col]            this_image_hash = image_hash(this_image)            if this_image_hash == empty_hash:                pos_to_type_id[row][col] = 0                continue            image_map.setdefault(this_image_hash, len(image_map) + 1)            pos_to_type_id[row][col] = image_map.get(this_image_hash)
    return pos_to_type_id

def solve_matrix_one_step():    for key in map:        arr = map[key]        arr_len = len(arr)        for index1 in range(arr_len - 1):            point1 = arr[index1]            x1 = point1[0]            y1 = point1[1]            for index2 in range(index1 + 1, arr_len):                point2 = arr[index2]                x2 = point2[0]                y2 = point2[1]                if verifying_connectivity(x1, y1, x2, y2):                    arr.remove(point1)                    arr.remove(point2)                    matrix[y1][x1] = 0                    matrix[y2][x2] = 0                    if arr_len == 2:                        map.pop(key)                    return y1, x1, y2, x2

def verifying_connectivity(x1, y1, x2, y2):    max_y1 = y1    while max_y1 + 1 < ROW_NUM and matrix[max_y1 + 1][x1] == 0:        max_y1 += 1    min_y1 = y1    while min_y1 - 1 >= 0 and matrix[min_y1 - 1][x1] == 0:        min_y1 -= 1
    max_y2 = y2    while max_y2 + 1 < ROW_NUM and matrix[max_y2 + 1][x2] == 0:        max_y2 += 1    min_y2 = y2    while min_y2 - 1 >= 0 and matrix[min_y2 - 1][x2] == 0:        min_y2 -= 1
    rg_min_y = max(min_y1, min_y2)    rg_max_y = min(max_y1, max_y2)    if rg_max_y >= rg_min_y:        for index_y in range(rg_min_y, rg_max_y + 1):            min_x = min(x1, x2)            max_x = max(x1, x2)            flag = True            for index_x in range(min_x + 1, max_x):                if matrix[index_y][index_x] != 0:                    flag = False                    break            if flag:                return True
    max_x1 = x1    while max_x1 + 1 < COL_NUM and matrix[y1][max_x1 + 1] == 0:        max_x1 += 1    min_x1 = x1    while min_x1 - 1 >= 0 and matrix[y1][min_x1 - 1] == 0:        min_x1 -= 1
    max_x2 = x2    while max_x2 + 1 < COL_NUM and matrix[y2][max_x2 + 1] == 0:        max_x2 += 1    min_x2 = x2    while min_x2 - 1 >= 0 and matrix[y2][min_x2 - 1] == 0:        min_x2 -= 1
    rg_min_x = max(min_x1, min_x2)    rg_max_x = min(max_x1, max_x2)    if rg_max_x >= rg_min_x:        for index_x in range(rg_min_x, rg_max_x + 1):            min_y = min(y1, y2)            max_y = max(y1, y2)            flag = True            for index_y in range(min_y + 1, max_y):                if matrix[index_y][index_x] != 0:                    flag = False                    break            if flag:                return True
    return False

def execute_one_step(one_step):    from_row, from_col, to_row, to_col = one_step
    from_x = game_area_left + (from_col + 0.5) * grid_width    from_y = game_area_top + (from_row + 0.5) * grid_height
    to_x = game_area_left + (to_col + 0.5) * grid_width    to_y = game_area_top + (to_row + 0.5) * grid_height
    pyautogui.moveTo(from_x, from_y)    pyautogui.click()
    pyautogui.moveTo(to_x, to_y)    pyautogui.click()

if __name__ == '__main__':
    COL_NUM = 19    ROW_NUM = 11
    screen_width = win32api.GetSystemMetrics(0)    screen_height = win32api.GetSystemMetrics(1)
    hwnd = win32gui.FindWindow(win32con.NULL, 'QQ游戲 - 連連看角色版')    if hwnd == 0:        exit(-1)
    win32gui.ShowWindow(hwnd, win32con.SW_RESTORE)    win32gui.SetForegroundWindow(hwnd)    window_left, window_top, window_right, window_bottom = win32gui.GetWindowRect(hwnd)    if min(window_left, window_top) < 0 or window_right > screen_width or window_bottom > screen_height:        exit(-1)    window_width = window_right - window_left    window_height = window_bottom - window_top
    game_area_left = window_left + 14.0 / 800.0 * window_width    game_area_top = window_top + 181.0 / 600.0 * window_height    game_area_right = window_left + 603 / 800.0 * window_width    game_area_bottom = window_top + 566 / 600.0 * window_height
    game_area_width = game_area_right - game_area_left    game_area_height = game_area_bottom - game_area_top    grid_width = game_area_width / COL_NUM    grid_height = game_area_height / ROW_NUM
    game_area_image = PIL.ImageGrab.grab((game_area_left, game_area_top, game_area_right, game_area_bottom))
    matrix = game_area_image_to_matrix()
    map = {}
    for y in range(ROW_NUM):        for x in range(COL_NUM):            grid_id = matrix[y][x]            if grid_id == 0:                continue            map.setdefault(grid_id, [])            arr = map[grid_id]            arr.append([x, y])
    pyautogui.PAUSE = 0
    while True:        one_step = solve_matrix_one_step()        if not one_step:            exit(0)        execute_one_step(one_step)        time.sleep(random.randint(0,0)/1000)