Minmax Tic Tac Toe

#!/usr/bin/env python3
from math import inf as infinity
from random import choice
import platform
import time
from os import system

HUMAN = -1
COMP = +1
board = [
    [0, 0, 0],
    [0, 0, 0],
    [0, 0, 0],
]


def evaluate(state):
    """
    Function to heuristic evaluation of state.
    :param state: the state of the current board
    :return: +1 if the computer wins; -1 if the human wins; 0 draw
    """
    if wins(state, COMP):
        score = +1
    elif wins(state, HUMAN):
        score = -1
    else:
        score = 0

    return score


def wins(state, player):
    """
    This function tests if a specific player wins. Possibilities:
    * Three rows    [X X X] or [O O O]
    * Three cols    [X X X] or [O O O]
    * Two diagonals [X X X] or [O O O]
    :param state: the state of the current board
    :param player: a human or a computer
    :return: True if the player wins
    """
    win_state = [
        [state[0][0], state[0][1], state[0][2]],
        [state[1][0], state[1][1], state[1][2]],
        [state[2][0], state[2][1], state[2][2]],
        [state[0][0], state[1][0], state[2][0]],
        [state[0][1], state[1][1], state[2][1]],
        [state[0][2], state[1][2], state[2][2]],
        [state[0][0], state[1][1], state[2][2]],
        [state[2][0], state[1][1], state[0][2]],
    ]
    if [player, player, player] in win_state:
        return True
    else:
        return False


def game_over(state):
    """
    This function test if the human or computer wins
    :param state: the state of the current board
    :return: True if the human or computer wins
    """
    return wins(state, HUMAN) or wins(state, COMP)


def empty_cells(state):
    """
    Each empty cell will be added into cells' list
    :param state: the state of the current board
    :return: a list of empty cells
    """
    cells = []

    for x, row in enumerate(state):
        for y, cell in enumerate(row):
            if cell == 0:
                cells.append([x, y])

    return cells


def valid_move(x, y):
    """
    A move is valid if the chosen cell is empty
    :param x: X coordinate
    :param y: Y coordinate
    :return: True if the board[x][y] is empty
    """
    if [x, y] in empty_cells(board):
        return True
    else:
        return False


def set_move(x, y, player):
    """
    Set the move on board, if the coordinates are valid
    :param x: X coordinate
    :param y: Y coordinate
    :param player: the current player
    """
    if valid_move(x, y):
        board[x][y] = player
        return True
    else:
        return False


def minimax(state, depth, player):
    """
    AI function that choice the best move
    :param state: current state of the board
    :param depth: node index in the tree (0 <= depth <= 9),
    but never nine in this case (see iaturn() function)
    :param player: an human or a computer
    :return: a list with [the best row, best col, best score]
    """
    if player == COMP:
        best = [-1, -1, -infinity]
    else:
        best = [-1, -1, +infinity]

    if depth == 0 or game_over(state):
        score = evaluate(state)
        return [-1, -1, score]

    for cell in empty_cells(state):
        x, y = cell[0], cell[1]
        state[x][y] = player
        score = minimax(state, depth - 1, -player)
        state[x][y] = 0
        score[0], score[1] = x, y

        if player == COMP:
            if score[2] > best[2]:
                best = score  # max value
        else:
            if score[2] < best[2]:
                best = score  # min value

    return best


def clean():
    """
    Clears the console
    """
    os_name = platform.system().lower()
    if 'windows' in os_name:
        system('cls')
    else:
        system('clear')


def render(state, c_choice, h_choice):
    """
    Print the board on console
    :param state: current state of the board
    """

    chars = {
        -1: h_choice,
        +1: c_choice,
        0: ' '
    }
    str_line = '---------------'

    print('\n' + str_line)
    for row in state:
        for cell in row:
            symbol = chars[cell]
            print(f'| {symbol} |', end='')
        print('\n' + str_line)


def ai_turn(c_choice, h_choice):
    """
    It calls the minimax function if the depth < 9,
    else it choices a random coordinate.
    :param c_choice: computer's choice X or O
    :param h_choice: human's choice X or O
    :return:
    """
    depth = len(empty_cells(board))
    if depth == 0 or game_over(board):
        return

    clean()
    print(f'Computer turn [{c_choice}]')
    render(board, c_choice, h_choice)

    if depth == 9:
        x = choice([0, 1, 2])
        y = choice([0, 1, 2])
    else:
        move = minimax(board, depth, COMP)
        x, y = move[0], move[1]

    set_move(x, y, COMP)
    time.sleep(1)


def human_turn(c_choice, h_choice):
    """
    The Human plays choosing a valid move.
    :param c_choice: computer's choice X or O
    :param h_choice: human's choice X or O
    :return:
    """
    depth = len(empty_cells(board))
    if depth == 0 or game_over(board):
        return

    # Dictionary of valid moves
    move = -1
    moves = {
        1: [0, 0], 2: [0, 1], 3: [0, 2],
        4: [1, 0], 5: [1, 1], 6: [1, 2],
        7: [2, 0], 8: [2, 1], 9: [2, 2],
    }

    clean()
    print(f'Human turn [{h_choice}]')
    render(board, c_choice, h_choice)

    while move < 1 or move > 9:
        try:
            move = int(input('Use numpad (1..9): '))
            coord = moves[move]
            can_move = set_move(coord[0], coord[1], HUMAN)

            if not can_move:
                print('Bad move')
                move = -1
        except (EOFError, KeyboardInterrupt):
            print('Bye')
            exit()
        except (KeyError, ValueError):
            print('Bad choice')


def main():
    """
    Main function that calls all functions
    """
    clean()
    h_choice = ''  # X or O
    c_choice = ''  # X or O
    first = ''  # if human is the first

    # Human chooses X or O to play
    while h_choice != 'O' and h_choice != 'X':
        try:
            print('')
            h_choice = input('Choose X or O\nChosen: ').upper()
        except (EOFError, KeyboardInterrupt):
            print('Bye')
            exit()
        except (KeyError, ValueError):
            print('Bad choice')

    # Setting computer's choice
    if h_choice == 'X':
        c_choice = 'O'
    else:
        c_choice = 'X'

    # Human may starts first
    clean()
    while first != 'Y' and first != 'N':
        try:
            first = input('First to start?[y/n]: ').upper()
        except (EOFError, KeyboardInterrupt):
            print('Bye')
            exit()
        except (KeyError, ValueError):
            print('Bad choice')

    # Main loop of this game
    while len(empty_cells(board)) > 0 and not game_over(board):
        if first == 'N':
            ai_turn(c_choice, h_choice)
            first = ''

        human_turn(c_choice, h_choice)
        ai_turn(c_choice, h_choice)

    # Game over message
    if wins(board, HUMAN):
        clean()
        print(f'Human turn [{h_choice}]')
        render(board, c_choice, h_choice)
        print('YOU WIN!')
    elif wins(board, COMP):
        clean()
        print(f'Computer turn [{c_choice}]')
        render(board, c_choice, h_choice)
        print('YOU LOSE!')
    else:
        clean()
        render(board, c_choice, h_choice)
        print('DRAW!')

    exit()

main()

Naive Learning

import itertools
import time

import numpy as np
import cv2

from moviepy.editor import VideoClip


WORLD_HEIGHT = 4
WORLD_WIDTH = 4
WALL_FRAC = .2
NUM_WINS = 5
NUM_LOSE = 10


class GridWorld:

    def __init__(self, world_height=3, world_width=4, discount_factor=.5, default_reward=-.5, wall_penalty=-.6,
                 win_reward=5., lose_reward=-10., viz=True, patch_side=120, grid_thickness=2, arrow_thickness=3,
                 wall_locs=[[1, 1], [1, 2]], win_locs=[[0, 3]], lose_locs=[[1, 3]], start_loc=[0, 0],
                 reset_prob=.2):
        self.world = np.ones([world_height, world_width]) * default_reward
        self.reset_prob = reset_prob
        self.world_height = world_height
        self.world_width = world_width
        self.wall_penalty = wall_penalty
        self.win_reward = win_reward
        self.lose_reward = lose_reward
        self.default_reward = default_reward
        self.discount_factor = discount_factor
        self.patch_side = patch_side
        self.grid_thickness = grid_thickness
        self.arrow_thickness = arrow_thickness
        self.wall_locs = np.array(wall_locs)
        self.win_locs = np.array(win_locs)
        self.lose_locs = np.array(lose_locs)
        self.at_terminal_state = False
        self.auto_reset = True
        self.random_respawn = True
        self.step = 0
        self.viz_canvas = None
        self.viz = viz
        self.path_color = (128, 128, 128)
        self.wall_color = (0, 255, 0)
        self.win_color = (0, 0, 255)
        self.lose_color = (255, 0, 0)
        self.world[self.wall_locs[:, 0], self.wall_locs[:, 1]] = self.wall_penalty
        self.world[self.lose_locs[:, 0], self.lose_locs[:, 1]] = self.lose_reward
        self.world[self.win_locs[:, 0], self.win_locs[:, 1]] = self.win_reward
        spawn_condn = lambda loc: self.world[loc[0], loc[1]] == self.default_reward
        self.spawn_locs = np.array([loc for loc in itertools.product(np.arange(self.world_height),
                                                                     np.arange(self.world_width))
                                    if spawn_condn(loc)])
        self.start_state = np.array(start_loc)
        self.bot_rc = None
        self.reset()
        self.actions = [self.up, self.left, self.right, self.down, self.noop]
        self.action_labels = ['UP', 'LEFT', 'RIGHT', 'DOWN', 'NOOP']
        self.q_values = np.ones([self.world.shape[0], self.world.shape[1], len(self.actions)]) * 1. / len(self.actions)
        if self.viz:
            self.init_grid_canvas()
            self.video_out_fpath = 'shm_dqn_gridsolver-' + str(time.time()) + '.mp4'
            self.clip = VideoClip(self.make_frame, duration=15)

    def make_frame(self, t):
        self.action()
        frame = self.highlight_loc(self.viz_canvas, self.bot_rc[0], self.bot_rc[1])
        return frame

    def check_terminal_state(self):
        if self.world[self.bot_rc[0], self.bot_rc[1]] == self.lose_reward \
                or self.world[self.bot_rc[0], self.bot_rc[1]] == self.win_reward:
            self.at_terminal_state = True
            # print('------++++---- TERMINAL STATE ------++++----')
            # if self.world[self.bot_rc[0], self.bot_rc[1]] == self.win_reward:
            #     print('GAME WON! :D')
            # elif self.world[self.bot_rc[0], self.bot_rc[1]] == self.lose_reward:
            #     print('GAME LOST! :(')
            if self.auto_reset:
                self.reset()

    def reset(self):
        # print('Resetting')
        if not self.random_respawn:
            self.bot_rc = self.start_state.copy()
        else:
            self.bot_rc = self.spawn_locs[np.random.choice(np.arange(len(self.spawn_locs)))].copy()
        self.at_terminal_state = False

    def up(self):
        action_idx = 0
        # print(self.action_labels[action_idx])
        new_r = self.bot_rc[0] - 1
        if new_r < 0 or self.world[new_r, self.bot_rc[1]] == self.wall_penalty:
            return self.wall_penalty, action_idx
        self.bot_rc[0] = new_r
        reward = self.world[self.bot_rc[0], self.bot_rc[1]]
        self.check_terminal_state()
        return reward, action_idx

    def left(self):
        action_idx = 1
        # print(self.action_labels[action_idx])
        new_c = self.bot_rc[1] - 1
        if new_c < 0 or self.world[self.bot_rc[0], new_c] == self.wall_penalty:
            return self.wall_penalty, action_idx
        self.bot_rc[1] = new_c
        reward = self.world[self.bot_rc[0], self.bot_rc[1]]
        self.check_terminal_state()
        return reward, action_idx

    def right(self):
        action_idx = 2
        # print(self.action_labels[action_idx])
        new_c = self.bot_rc[1] + 1
        if new_c >= self.world.shape[1] or self.world[self.bot_rc[0], new_c] == self.wall_penalty:
            return self.wall_penalty, action_idx
        self.bot_rc[1] = new_c
        reward = self.world[self.bot_rc[0], self.bot_rc[1]]
        self.check_terminal_state()
        return reward, action_idx

    def down(self):
        action_idx = 3
        # print(self.action_labels[action_idx])
        new_r = self.bot_rc[0] + 1
        if new_r >= self.world.shape[0] or self.world[new_r, self.bot_rc[1]] == self.wall_penalty:
            return self.wall_penalty, action_idx
        self.bot_rc[0] = new_r
        reward = self.world[self.bot_rc[0], self.bot_rc[1]]
        self.check_terminal_state()
        return reward, action_idx

    def noop(self):
        action_idx = 4
        # print(self.action_labels[action_idx])
        reward = self.world[self.bot_rc[0], self.bot_rc[1]]
        self.check_terminal_state()
        return reward, action_idx

    def qvals2probs(self, q_vals, epsilon=1e-4):
        action_probs = q_vals - q_vals.min() + epsilon
        action_probs = action_probs / action_probs.sum()
        return action_probs

    def action(self):
        # print('================ ACTION =================')
        if self.at_terminal_state:
            print('At terminal state, please call reset()')
            exit()
        # print('Start position:', self.bot_rc)
        start_bot_rc = self.bot_rc[0], self.bot_rc[1]
        q_vals = self.q_values[self.bot_rc[0], self.bot_rc[1]]
        action_probs = self.qvals2probs(q_vals)
        reward, action_idx = np.random.choice(self.actions, p=action_probs)()
        # print('End position:', self.bot_rc)
        # print('Reward:', reward)
        alpha = np.exp(-self.step / 10e9)
        self.step += 1
        qv = (1 - alpha) * q_vals[action_idx] + alpha * (reward + self.discount_factor
                                                         * self.q_values[self.bot_rc[0], self.bot_rc[1]].max())
        self.q_values[start_bot_rc[0], start_bot_rc[1], action_idx] = qv
        if self.viz:
            self.update_viz(start_bot_rc[0], start_bot_rc[1])
        if np.random.rand() < self.reset_prob:
            # print('-----> Randomly resetting to a random spawn point with probability', self.reset_prob)
            self.reset()

    def highlight_loc(self, viz_in, i, j):
        starty = i * (self.patch_side + self.grid_thickness)
        endy = starty + self.patch_side
        startx = j * (self.patch_side + self.grid_thickness)
        endx = startx + self.patch_side
        viz = viz_in.copy()
        cv2.rectangle(viz, (startx, starty), (endx, endy), (255, 255, 255), thickness=self.grid_thickness)
        return viz

    def update_viz(self, i, j):
        starty = i * (self.patch_side + self.grid_thickness)
        endy = starty + self.patch_side
        startx = j * (self.patch_side + self.grid_thickness)
        endx = startx + self.patch_side
        patch = np.zeros([self.patch_side, self.patch_side, 3]).astype(np.uint8)
        if self.world[i, j] == self.default_reward:
            patch[:, :, :] = self.path_color
        elif self.world[i, j] == self.wall_penalty:
            patch[:, :, :] = self.wall_color
        elif self.world[i, j] == self.win_reward:
            patch[:, :, :] = self.win_color
        elif self.world[i, j] == self.lose_reward:
            patch[:, :, :] = self.lose_color
        if self.world[i, j] == self.default_reward:
            action_probs = self.qvals2probs(self.q_values[i, j])
            x_component = action_probs[2] - action_probs[1]
            y_component = action_probs[0] - action_probs[3]
            magnitude = 1. - action_probs[-1]
            s = self.patch_side // 2
            x_patch = int(s * x_component)
            y_patch = int(s * y_component)
            arrow_canvas = np.zeros_like(patch)
            vx = s + x_patch
            vy = s - y_patch
            cv2.arrowedLine(arrow_canvas, (s, s), (vx, vy), (255, 255, 255), thickness=self.arrow_thickness,
                            tipLength=0.5)
            gridbox = (magnitude * arrow_canvas + (1 - magnitude) * patch).astype(np.uint8)
            self.viz_canvas[starty:endy, startx:endx] = gridbox
        else:
            self.viz_canvas[starty:endy, startx:endx] = patch

    def init_grid_canvas(self):
        org_h, org_w = self.world_height, self.world_width
        viz_w = (self.patch_side * org_w) + (self.grid_thickness * (org_w - 1))
        viz_h = (self.patch_side * org_h) + (self.grid_thickness * (org_h - 1))
        self.viz_canvas = np.zeros([viz_h, viz_w, 3]).astype(np.uint8)
        for i in range(org_h):
            for j in range(org_w):
                self.update_viz(i, j)

    def solve(self):
        if not self.viz:
            while True:
                self.action()
        else:
            self.clip.write_videofile(self.video_out_fpath, fps=460)


def gen_world_config(h, w, wall_frac=.5, num_wins=2, num_lose=3):
    n = h * w
    num_wall_blocks = int(wall_frac * n)
    wall_locs = (np.random.rand(num_wall_blocks, 2) * [h, w]).astype(np.int)
    win_locs = (np.random.rand(num_wins, 2) * [h, w]).astype(np.int)
    lose_locs = (np.random.rand(num_lose, 2) * [h, w]).astype(np.int)
    return wall_locs, win_locs, lose_locs


if __name__ == '__main__':
    wall_locs, win_locs, lose_locs = gen_world_config(WORLD_HEIGHT, WORLD_WIDTH, WALL_FRAC, NUM_WINS, NUM_LOSE)
    g = GridWorld(world_height=WORLD_HEIGHT, world_width=WORLD_WIDTH,
                  wall_locs=wall_locs, win_locs=win_locs, lose_locs=lose_locs, viz=True)
    g.solve()
    k = 0


Pygame Sprite Motion with Wrap-Around


import pygame

WIDTH = 500
HEIGHT = 500
FPS = 60

#define colors
#colors are defined in red,green,blue
#values from 0-255
WHITE = (255,255,255)
BLACK = (0,0,0)
RED = (255,0,0)
GREEN = (0,255,0)
BLUE = (0,0,255)
YELLOW = (255,255,0)

pygame.init()
pygame.mixer.init()
screen = pygame.display.set_mode((WIDTH,HEIGHT))
clock = pygame.time.Clock()

class Player(pygame.sprite.Sprite):
  
  def __init__(self):
    pygame.sprite.Sprite.__init__(self)
    self.image = pygame.Surface((50,40))
    self.image.fill(GREEN)
    self.rect = self.image.get_rect()
    self.rect.centerx = 30
    self.rect.centery = 30
    self.speedx = 0
    self.speedy = 0
    self.ticker = 0
  
  def update(self):
    speed = 5
    self.speedx = 0
    self.speedy = 0
    keystate = pygame.key.get_pressed()
    if keystate[pygame.K_LEFT]:
      self.speedx = -speed
    if keystate[pygame.K_RIGHT]:
      self.speedx = speed
    if keystate[pygame.K_UP]:
      self.speedy = -speed
      self.ticker += 1 #NEW CODE
    if keystate[pygame.K_DOWN]:
      self.speedy = speed
      self.ticker += 1 #NEW CODE
    self.rect.x += self.speedx
    
    
    #HERE IS WHERE WE 
    self.ticker = self.ticker % 20
    if self.ticker  >9:
      self.image.fill(GREEN)
    else:
      self.image.fill(BLUE)
    #HERE WE ARE GOING TO WRAP AROUND THE EDGES IF THE SPRITE
    #GOES OFF THE SCREEN
    #REMEMBER THAT X IS LEFT TO RIGHT AND Y IS UP AND DOWN
    if self.rect.x > WIDTH:
      self.rect.x = 0
    if self.rect.x < 0:
      self.rect.x = WIDTH
    self.rect.y += self.speedy
    if self.rect.y > HEIGHT:
      self.rect.y = 0
    if self.rect.y < 0:
      self.rect.y = HEIGHT
      
    

all_sprites = pygame.sprite.Group()
james = Player()
all_sprites.add(james)
running = True

while running:
  
  clock.tick(FPS)
  pygame.event.get()
  all_sprites.update()
  screen.fill(BLACK)
  all_sprites.draw(screen)
  pygame.display.flip()
    
 

Python Brickbreaker with Tkinter

 
from tkinter import *
import random
import time

tk = Tk()
tk.title("Game")
tk.resizable(0, 0)
tk.wm_attributes("-topmost", 1)
canvas = Canvas(tk, width=500, height=400, bd=0, highlightthickness=0)
canvas.pack()
tk.update()

class Ball:
    def __init__(self, canvas, paddle, color):
        self.canvas = canvas
        self.paddle = paddle
        self.id = canvas.create_oval(10, 10, 25, 25, fill=color)
        self.canvas.move(self.id, 245, 100)
        starts = [-3, -2, -1, 1, 2, 3]
        random.shuffle(starts)
        self.x = starts[0]
        self.y = -3
        self.canvas_height = self.canvas.winfo_height()
        self.canvas_width = self.canvas.winfo_width()
        
    def draw(self):
        self.canvas.move(self.id, self.x, self.y)
        pos = self.canvas.coords(self.id)
        if pos[1] <= 0:
            self.y = 3
        if pos[3] >= self.canvas_height:
            self.y = -3
        if self.hit_paddle(pos) == True:
            self.y = -3
        if pos[0] <= 0:
            self.x = 3
        if pos[2] >= self.canvas_width:
            self.x = -3
            
    def hit_paddle(self, pos):
        paddle_pos = self.canvas.coords(self.paddle.id)
        if pos[2] >= paddle_pos[0] and pos[0] <= paddle_pos[2]:
            if pos[3] >= paddle_pos[1] and pos[3] <= paddle_pos[3]:
                return True
        return False

class Paddle:
    def __init__(self, canvas, color):
        self.canvas = canvas
        self.id = canvas.create_rectangle(0, 0, 100, 10, fill=color)
        self.canvas.move(self.id, 200, 300)
        self.x = 0
        self.canvas_width = self.canvas.winfo_width()
        self.canvas.bind_all('<KeyPress-Left>', self.turn_left)
        self.canvas.bind_all('<KeyPress-Right>', self.turn_right)
        
    def turn_left(self, evt):
        self.x = -2
        
    def turn_right(self, evt):
        self.x = 2
        
    def draw(self):
        self.canvas.move(self.id, self.x, 0)
        pos = self.canvas.coords(self.id)
        if pos[0] <= 0:
            self.x = 0
        elif pos[2] >= self.canvas_width:
            self.x = 0
     
paddle = Paddle(canvas, 'blue')
ball = Ball(canvas, paddle, 'red')

while 1:
    ball.draw()
    paddle.draw()
    tk.update_idletasks()
    tk.update()
    time.sleep(0.01)

PyGame Basic Setup

 

import pygame
import random

WIDTH = 480
HEIGHT = 480
FPS = 30

# define colors
WHITE = (255, 255, 255)
BLACK = (0, 0, 0)
RED = (255, 0, 0)
GREEN = (0, 255, 0)
BLUE = (0, 0, 255)

# initialize pygame and create window
pygame.init()
pygame.mixer.init()
screen = pygame.display.set_mode((WIDTH, HEIGHT))
pygame.display.set_caption("My Game")
clock = pygame.time.Clock()

# Game loop
running = True
while running:
    # keep loop running at the right speed
    clock.tick(FPS)
    # Process input (events)
    for event in pygame.event.get():
        # check for closing window
        if event.type == pygame.QUIT:
            running = False

    # Update

    # Draw / render
    screen.fill(BLACK)
    # *after* drawing everything, flip the display
    pygame.display.flip()

pygame.quit()

 

 

Python Turtle Demo Spirograph

 <br> import random,time,turtle<br>bai = turtle.Turtle()<br>bai.pendown<br>bai.speed(10)<br>bai.tracer(300)<br>bai.hideturtle()<br>for i in range (1000):<br>  for i in range(4):<br>   for i in range (40):<br>    bai.forward(50)<br>    bai.left(100)<br>    r = random.randint(0,255)<br>    g = random.randint(0,255)<br>    b = random.randint(0,255)<br>    bai.pencolor((r,g,b))<br>    for i in range(4):<br>       bai.forward(10)<br>       bai.left(90)<br>   time.sleep(0.1)<br>  bai.penup<br>  bai.forward(100)<br>  bai.pendown  

   <br><br> import turtle<br>import time<br>import random<br>bob = turtle.Turtle()<br>bob.tracer(300)<br>bob.pendown()<br>bob.hideturtle()<br>for i in range (20):<br>  for i in range(200):<br>    bob.forward(158)<br>    bob.left(200)<br>    bob.right(1)<br>    r = random.randint(1,255)<br>    g = random.randint(1,255)<br>    b = random.randint(1,255)<br>    bob.pencolor((r,g,b))<br>  time.sleep(0.1)    <br>

Hacking 3/12

PART 1
uname = “Mufasa”
password = “Circle Of Life”
realm = “testrealm@host.com
nonce=”dcd98b7102dd2f0e8b11d0f600bfb0c093″
uri=”/dir/index.html”
nc=”00000001″ # note this is a string
cnonce=”0a4f113b”
 
ha1 = hashlib.md5((uname+’:’+realm+’:’+password).encode(‘utf-8’)).hexdigest()
ha2 = hashlib.md5((‘GET:’+uri).encode(‘utf-8’)).hexdigest()
response = hashlib.md5((ha1+’:’+nonce+’:’+nc+’:’+cnonce+’:auth:’+ha2).encode(‘utf8’)).hexdigest()
print(response)
PART 2
from string import ascii_letters, digits
import itertools
import sys
 
for len in range(1,8):
    for letters in itertools.product(ascii_letters+digits, repeat=len):
        guess=”.join(letters)
        if happy_result(guess):
            print(‘Password found:’, guess)
            sys.exit()
print(‘Epic fail! Try harder next time.’)

RSA Encryption

woE7ewVfwoAzbwXCgC5iMyRvBTvCgGBiOy4=
public key: e=5, n=133
import random
import base64

'''
Euclid's algorithm to determine the greatest common divisor
'''
def gcd(a,b):
    while b != 0:
        c = a % b
        a = b
        b = c
    return a

def egcd(a, b):
    if a == 0:
        return (b, 0, 1)
    g, y, x = egcd(b%a,a)
    return (g, x - (b//a) * y, y)

def modinv(a, m):
    g, x, y = egcd(a, m)
    if g != 1:
        raise Exception('No modular inverse')
    return x%m

def encrypt(plaintext,keypair):
    e,n = keypair

    # Encrypt the plaintext
    cipher = ''.join([chr(pow(ord(char),e,n)) for char in plaintext])
    # Encode the ciphertext so it's more readable/sharable
    encoded = base64.b64encode(cipher.encode('utf-8'))
    return str(encoded,'utf-8')

def decrypt(ciphertext,keypair):
    d,n = keypair

    # Decode the text to the original format
    decoded = base64.b64decode(ciphertext).decode('utf-8')
    # Decrypt it
    plain = (str(chr(pow(ord(char),d,n))) for char in decoded)
    return ''.join(plain)

def generate_keypair(p,q,e=None):
    n = p * q

    #Phi is the totient of n
    phi = (p-1)*(q-1)

    #Choose an integer e such that e and phi(n) are coprime
    if e is None:
        e = random.randrange(1, phi)

    #Use Euclid's Algorithm to verify that e and phi(n) are comprime
    g = gcd(e, phi)
    while g != 1:
        e = random.randrange(1, phi)
        g = gcd(e, phi)

    #Now find the multiplicative inverse of e and phi to generate the private key
    d = modinv(e, phi)

    return ((e,n),(d,n))

#Only run this part if we're not running as an imported module
if __name__ == '__main__':
    p = int(input("Enter prime number p: "))
    q = int(input("Enter prime number q: "))

    public, private = generate_keypair(p,q)

    print("Your public key is the number pair of (e=" +  str(public[0]) + ", n=" + str(public[1]) +").\n")
    print("Your private key is the number pair of (d=" +  str(private[0]) + ", n=" + str(private[1]) +").\n")

    s = input("Enter your message: ")
    encrypted = encrypt(s,public)

    print("Encrypted message: " + encrypted)
    decrypted = decrypt(encrypted,private)
    print("Decrypt: " + decrypted)  

BMP-280 with Raspberry Pi and Python Wiring/Code

Adafruit Source

Python Computer Wiring

Since there’s dozens of Linux computers/boards you can use we will show wiring for Raspberry Pi. For other platforms, please visit the guide for CircuitPython on Linux to see whether your platform is supported.

Here’s the Raspberry Pi wired with I2C:

  • adafruit_products_raspi_bmp280_i2c_bb.png
  • Pi 3V3 to sensor VIN
  • Pi GND to sensor GND
  • Pi SCL to sensor SCK
  • Pi SDA to sensor SDI

And an example on the Raspberry Pi 3 Model B wired with SPI:

  • adafruit_products_raspi_bme280_spi_bb.png
  • Pi 3V3 to sensor VIN
  • Pi GND to sensor GND
  • Pi MOSI to sensor SDI
  • Pi MISO to sensor SDO
  • Pi SCLK to sensor SCK
  • Pi #5 to sensor CS (or use any other free GPIO pin)

CircuitPython Installation of BMP280 Library

You’ll need to install the Adafruit CircuitPython BMP280 library on your CircuitPython board.

First make sure you are running the latest version of Adafruit CircuitPython for your board.

Next you’ll need to install the necessary libraries to use the hardware–carefully follow the steps to find and install these libraries from Adafruit’s CircuitPython library bundle.  Our CircuitPython starter guide has a great page on how to install the library bundle.

For non-express boards like the Trinket M0 or Gemma M0, you’ll need to manually install the necessary libraries from the bundle:

  • adafruit_bmp280.mpy
  • adafruit_bus_device

Before continuing make sure your board’s lib folder or root filesystem has the adafruit_bmp280.mpy, and adafruit_bus_device files and folders copied over.

Next connect to the board’s serial REPL so you are at the CircuitPython >>> prompt.

Python Installation of BMP280 Library

You’ll need to install the Adafruit_Blinka library that provides the CircuitPython support in Python. This may also require enabling I2C on your platform and verifying you are running Python 3. Since each platform is a little different, and Linux changes often, please visit the CircuitPython on Linux guide to get your computer ready!

Once that’s done, from your command line run the following command:

  • sudo pip3 install adafruit-circuitpython-bmp280

If your default Python is version 3 you may need to run ‘pip’ instead. Just make sure you aren’t trying to use CircuitPython on Python 2.x, it isn’t supported!

CircuitPython & Python Usage

To demonstrate the usage of the sensor we’ll initialize it and read the temperature, humidity, and more from the board’s Python REPL.

If you’re using an I2C connection run the following code to import the necessary modules and initialize the I2C connection with the sensor:

 Download: file

  1. import board
  2. import busio
  3. import adafruit_bmp280
  4. i2c = busio.I2C(board.SCL, board.SDA)
  5. sensor = adafruit_bmp280.Adafruit_BMP280_I2C(i2c)

Or if you’re using a SPI connection run this code instead to setup the SPI connection and sensor:

 Download: file

  1. import board
  2. import busio
  3. import digitalio
  4. import adafruit_bmp280
  5. spi = busio.SPI(board.SCK, MOSI=board.MOSI, MISO=board.MISO)
  6. cs = digitalio.DigitalInOut(board.D5)
  7. sensor = adafruit_bmp280.Adafruit_BMP280_SPI(spi, cs)

Now you’re ready to read values from the sensor using any of these properties:

  • temperature – The sensor temperature in degrees Celsius.
  • pressure – The pressure in hPa.
  • altitude – The altitude in meters.

For example to print temperature and pressure:

 Download: file

  1. print(‘Temperature: {} degrees C’.format(sensor.temperature))
  2. print(‘Pressure: {}hPa’.format(sensor.pressure))
adafruit_products_Screen_Shot_2017-11-10_at_3.33.47_PM.png

For altitude you’ll want to set the pressure at sea level for your location to get the most accurate measure (remember these sensors can only infer altitude based on pressure and need a set calibration point).  Look at your local weather report for a pressure at sea level reading and set the seaLevelhPA property:

 Download: file

  1. sensor.sea_level_pressure = 1013.25

Then read the altitude property for a more accurate altitude reading (but remember this altitude will fluctuate based on atmospheric pressure changes!):

 Download: file

  1. print(‘Altitude: {} meters’.format(sensor.altitude))
adafruit_products_alti.png

That’s all there is to using the BMP280 sensor with CircuitPython!

Here’s a starting example that will print out the temperature, pressure and altitude every 2 seconds:

  1. import time
  2.  
  3. import board
  4. # import digitalio # For use with SPI
  5. import busio
  6.  
  7. import adafruit_bmp280
  8.  
  9. # Create library object using our Bus I2C port
  10. i2c = busio.I2C(board.SCL, board.SDA)
  11. bmp280 = adafruit_bmp280.Adafruit_BMP280_I2C(i2c)
  12.  
  13. # OR create library object using our Bus SPI port
  14. #spi = busio.SPI(board.SCK, board.MOSI, board.MISO)
  15. #bmp_cs = digitalio.DigitalInOut(board.D10)
  16. #bmp280 = adafruit_bmp280.Adafruit_BMP280_SPI(spi, bmp_cs)
  17.  
  18. # change this to match the location’s pressure (hPa) at sea level
  19. bmp280.sea_level_pressure = 1013.25
  20.  
  21. while True:
  22. print(“\nTemperature: %0.1f C” % bmp280.temperature)
  23. print(“Pressure: %0.1f hPa” % bmp280.pressure)
  24. print(“Altitude = %0.2f meters” % bmp280.altitude)
  25. time.sleep(2)