Python error
I was making a code for a tetris game.
Here's the code. #!/usr/bin/env python
#-- coding: utf-8 --
Very simple tetris implementation
Control keys:
Down - Drop stone faster
Left/Right - Move stone
Up - Rotate Stone clockwise
Escape - Quit game
P - Pause game
Have fun!
Copyright (c) 2010 "Kevin Chabowski"[email protected]
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
from random import randrange as rand
import pygame, sys
The configuration
config = {
'cell_size': 20,
'cols': 8,
'rows': 16,
'delay': 750,
'maxfps': 30
}
colors = [
(0, 0, 0 ),
(255, 0, 0 ),
(0, 150, 0 ),
(0, 0, 255),
(255, 120, 0 ),
(255, 255, 0 ),
(180, 0, 255),
(0, 220, 220)
]
Define the shapes of the single parts
tetris_shapes = [
[[1, 1, 1],
[0, 1, 0]],
[[0, 2, 2],
[2, 2, 0]],
[[3, 3, 0],
[0, 3, 3]],
[[4, 0, 0],
[4, 4, 4]],
[[0, 0, 5],
[5, 5, 5]],
[[6, 6, 6, 6]],
[[7, 7],
[7, 7]]
]
def rotate_clockwise(shape):
return [ [ shape[y][x]
for y in xrange(len(shape)) ]
for x in xrange(len(shape[0]) - 1, -1, -1) ]
def check_collision(board, shape, offset):
off_x, off_y = offset
for cy, row in enumerate(shape):
for cx, cell in enumerate(row):
try:
if cell and board[ cy + off_y ][ cx + off_x ]:
return True
except IndexError:
return True
return False
def remove_row(board, row):
del board[row]
return [[0 for i in xrange(config['cols'])]] + board
def join_matrixes(mat1, mat2, mat2_off):
off_x, off_y = mat2_off
for cy, row in enumerate(mat2):
for cx, val in enumerate(row):
mat1[cy+off_y-1 ][cx+off_x] += val
return mat1
def new_board():
board = [ [ 0 for x in xrange(config['cols']) ]
for y in xrange(config['rows']) ]
board += [[ 1 for x in xrange(config['cols'])]]
return board
class TetrisApp(object):
def init(self):
pygame.init()
pygame.key.set_repeat(250,25)
self.width = config['cell_size']*config['cols']
self.height = config['cell_size']*config['rows']
self.screen = pygame.display.set_mode((self.width, self.height))
pygame.event.set_blocked(pygame.MOUSEMOTION) # We do not need
# mouse movement
# events, so we
# block them.
self.init_game()
def new_stone(self):
self.stone = tetris_shapes[rand(len(tetris_shapes))]
self.stone_x = int(config['cols'] / 2 - len(self.stone[0])/2)
self.stone_y = 0
if check_collision(self.board,
self.stone,
(self.stone_x, self.stone_y)):
self.gameover = True
def init_game(self):
self.board = new_board()
self.new_stone()
def center_msg(self, msg):
for i, line in enumerate(msg.splitlines()):
msg_image = pygame.font.Font(
pygame.font.get_default_font(), 12).render(
line, False, (255,255,255), (0,0,0))
msgim_center_x, msgim_center_y = msg_image.get_size()
msgim_center_x //= 2
msgim_center_y //= 2
self.screen.blit(msg_image, (
self.width // 2-msgim_center_x,
self.height // 2-msgim_center_y+i*22))
def draw_matrix(self, matrix, offset):
off_x, off_y = offset
for y, row in enumerate(matrix):
for x, val in enumerate(row):
if val:
pygame.draw.rect(
self.screen,
colors[val],
pygame.Rect(
(off_x+x) *
config['cell_size'],
(off_y+y) *
config['cell_size'],
config['cell_size'],
config['cell_size']),0)
def move(self, delta_x):
if not self.gameover and not self.paused:
new_x = self.stone_x + delta_x
if new_x < 0:
new_x = 0
if new_x > config['cols'] - len(self.stone[0]):
new_x = config['cols'] - len(self.stone[0])
if not check_collision(self.board,
self.stone,
(new_x, self.stone_y)):
self.stone_x = new_x
def quit(self):
self.center_msg("Exiting...")
pygame.display.update()
sys.exit()
def drop(self):
if not self.gameover and not self.paused:
self.stone_y += 1
if check_collision(self.board,
self.stone,
(self.stone_x, self.stone_y)):
self.board = join_matrixes(
self.board,
self.stone,
(self.stone_x, self.stone_y))
self.new_stone()
while True:
for i, row in enumerate(self.board[:-1]):
if 0 not in row:
self.board = remove_row(
self.board, i)
break
else:
break
def rotate_stone(self):
if not self.gameover and not self.paused:
new_stone = rotate_clockwise(self.stone)
if not check_collision(self.board,
new_stone,
(self.stone_x, self.stone_y)):
self.stone = new_stone
def toggle_pause(self):
self.paused = not self.paused
def start_game(self):
if self.gameover:
self.init_game()
self.gameover = False
def run(self):
key_actions = {
'ESCAPE': self.quit,
'LEFT': lambda:self.move(-1),
'RIGHT': lambda:self.move(+1),
'DOWN': self.drop,
'UP': self.rotate_stone,
'p': self.toggle_pause,
'SPACE': self.start_game
}
self.gameover = False
self.paused = False
pygame.time.set_timer(pygame.USEREVENT+1, config['delay'])
dont_burn_my_cpu = pygame.time.Clock()
while 1:
self.screen.fill((0,0,0))
if self.gameover:
self.center_msg("""Game Over!
Press space to continue""")
else:
if self.paused:
self.center_msg("Paused")
else:
self.draw_matrix(self.board, (0,0))
self.draw_matrix(self.stone,
(self.stone_x,
self.stone_y))
pygame.display.update()
for event in pygame.event.get():
if event.type == pygame.USEREVENT+1:
self.drop()
elif event.type == pygame.QUIT:
self.quit()
elif event.type == pygame.KEYDOWN:
for key in key_actions:
if event.key == eval("pygame.K_"
+key):
key_actions[key]()
dont_burn_my_cpu.tick(config['maxfps'])
if name == 'main':
App = TetrisApp()
App.run() The output is here. 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