How to use inverted_test method in hypothesis

Best Python code snippet using hypothesis

trench.py

Source: trench.py Github

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1with open('data.txt', 'r') as file:2 data = file.read().split('\n')3# cut trailing newline4data.pop(-1)5# Further data processing6algorithm_line = data.pop(0)7# discard the blank line8data.pop(0)9lit_pixels = set()10for row, row_data in enumerate(data):11 for col, col_data in enumerate(row_data):12 if col_data == '#':13 lit_pixels.add((row, col))14# breakpoint()15# Part 116def enhance(lit_pixels, algorithm_line, steps):17 inverted = False18 tracked_pixels = lit_pixels19 for _ in range(steps):20 new_tracked_pixels = set()21 neighbor_pixels = set()22 # add unlit pixels neighboring neighbor pixels to set to evaluate23 # this might be a problem for the real algorithm, looks like 0 = lit24 # can solve by flipping it every other time25 for tracked_pixel in tracked_pixels:26 for i in range (-1, 2, 1):27 for k in range(-1, 2, 1):28 # breakpoint()29 row_i = tracked_pixel[0] + i30 col_k = tracked_pixel[1] + k31 if (row_i, col_k) not in tracked_pixels:32 neighbor_pixels.add((row_i, col_k))33 tracked_symbol = "." if not inverted else "#"34 # If inverted, we are tracking dark pixels because of algo[0] = On35 for tracked_pixel in tracked_pixels:36 # Find the correct number, regardless of inversion37 number = get_pixel_number(tracked_pixel, tracked_pixels, inverted)38 enhanced_pixel = algorithm_line[number]39 if enhanced_pixel == tracked_symbol:40 new_tracked_pixels.add(tracked_pixel)41 for neighbor_pixel in neighbor_pixels:42 number = get_pixel_number(neighbor_pixel, tracked_pixels, inverted)43 enhanced_pixel = algorithm_line[number]44 if enhanced_pixel == tracked_symbol:45 new_tracked_pixels.add(neighbor_pixel)46 tracked_pixels = new_tracked_pixels47 print(len(tracked_pixels))48 inverted = not inverted49 # print(tracked_pixels)50 return len(tracked_pixels)51def get_pixel_number(pixel, tracked_pixels, inverted):52 neighbors = []53 for i in range (-1, 2, 1):54 for k in range(-1, 2, 1):55 # breakpoint()56 row_i = pixel[0] + i57 col_k = pixel[1] + k58 # TODO: DRY59 if not inverted:60 if (row_i, col_k) in tracked_pixels:61 neighbors.append('1')62 else:63 neighbors.append('0')64 else:65 if (row_i, col_k) in tracked_pixels:66 neighbors.append('0')67 else:68 neighbors.append('1')69 # breakpoint()70 return int("".join(neighbors), 2)71normal_test = set([(1, 0), (2, 1)])72inverted_test = set([(0, 0),73 (0, 1),74 (0, 2),75 (1, 1),76 (1, 2),77 (2, 0),78 (2, 2)]79)80# print(get_pixel_number((1, 1), normal_test, False))81# print(get_pixel_number((1, 1), inverted_test, True))82# print(get_pixel_number((2, 2), lit_pixels))83print(f"Result: {enhance(lit_pixels, algorithm_line, 50)}")84# incorrect = {(3, -1), (3, 1), (5, 4), (5, 1), (0, 5), (2, 2), (1, 6), (1, 3), (6, 2), (-1, -2), (-1, 4), (-2, 4), (-2, -1), (-2, 1), (4, 2), (4, 5), (3, 3), (3, 6), (5, 3), (0, -2), (2, -1), (2, -2), (1, 2), (2, 4), (-2, 5), (6, 4), (-2, 2), (5, 2), (4, 4), (0, 0), (0, 3), (0, 6), (6, 3), (-1, 5)}85# correct = {(4, 0), (3, -1), (3, 4), (4, 3), (3, 1), (5, 4), (4, 6), (5, 1), (0, 5), (1, 3), (6, 2), (-1, -1), (-1, 4), (4, 2), (4, 5), (3, 3), (0, -2), (2, -2), (2, 4), (1, 2), (0, 4), (1, 5), (6, 4), (3, 2), (-1, 2), (3, 5), (5, 2), (4, 4), (5, 5), (0, 0), (1, -2), (0, 6), (2, 6), (6, 3), (-2, 5)}86# for pair in correct:87# if pair not in incorrect:...

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utils.py

Source: utils.py Github

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...44 return45def fails_with(e):46 def accepts(f):47 @proxies(f)48 def inverted_test(*arguments, **kwargs):49 with raises(e):50 f(*arguments, **kwargs)51 return inverted_test52 return accepts...

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