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example: Fix python formating

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This commit is contained in:
Corentin Le Molgat
2023-07-13 14:28:36 +02:00
parent 224ca64cd5
commit c368a4d9fa
11 changed files with 1149 additions and 15702 deletions
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1724
examples/python/clustering_sat.py
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1724
examples/python/prize_collecting_tsp_sat.py
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1724
examples/python/prize_collecting_vrp_sat.py
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6444
examples/python/qubo_sat.py
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253
examples/python/steel_mill_slab_sat.py
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@@ -48,236 +48,67 @@ def build_problem(problem_id):
if problem_id == 0:
capacities = [
0,
12,
14,
17,
18,
19,
20,
23,
24,
25,
26,
27,
28,
29,
30,
32,
35,
39,
42,
43,
44,
# fmt:off
0, 12, 14, 17, 18, 19, 20, 23, 24, 25, 26, 27, 28, 29, 30, 32, 35, 39, 42, 43, 44,
# fmt:on
]
num_colors = 88
num_slabs = 111
orders = [
(4, 1), # (size, color)
(22, 2),
(9, 3),
(5, 4),
(8, 5),
(3, 6),
(3, 4),
(4, 7),
(7, 4),
(7, 8),
(3, 6),
(2, 6),
(2, 4),
(8, 9),
(5, 10),
(7, 11),
(4, 7),
(7, 11),
(5, 10),
(7, 11),
(8, 9),
(3, 1),
(25, 12),
(14, 13),
(3, 6),
(22, 14),
(19, 15),
(19, 15),
(22, 16),
(22, 17),
(22, 18),
(20, 19),
(22, 20),
(5, 21),
(4, 22),
(10, 23),
(26, 24),
(17, 25),
(20, 26),
(16, 27),
(10, 28),
(19, 29),
(10, 30),
(10, 31),
(23, 32),
(22, 33),
(26, 34),
(27, 35),
(22, 36),
(27, 37),
(22, 38),
(22, 39),
(13, 40),
(14, 41),
(16, 27),
(26, 34),
(26, 42),
(27, 35),
(22, 36),
(20, 43),
(26, 24),
(22, 44),
(13, 45),
(19, 46),
(20, 47),
(16, 48),
(15, 49),
(17, 50),
(10, 28),
(20, 51),
(5, 52),
(26, 24),
(19, 53),
(15, 54),
(10, 55),
(10, 56),
(13, 57),
(13, 58),
(13, 59),
(12, 60),
(12, 61),
(18, 62),
(10, 63),
(18, 64),
(16, 65),
(20, 66),
(12, 67),
(6, 68),
(6, 68),
(15, 69),
(15, 70),
(15, 70),
(21, 71),
(30, 72),
(30, 73),
(30, 74),
(30, 75),
(23, 76),
(15, 77),
(15, 78),
(27, 79),
(27, 80),
(27, 81),
(27, 82),
(27, 83),
(27, 84),
(27, 79),
(27, 85),
(27, 86),
(10, 87),
(3, 88),
orders = [ # (size, color)
# fmt:off
(4, 1), (22, 2), (9, 3), (5, 4), (8, 5), (3, 6), (3, 4), (4, 7),
(7, 4), (7, 8), (3, 6), (2, 6), (2, 4), (8, 9), (5, 10), (7, 11),
(4, 7), (7, 11), (5, 10), (7, 11), (8, 9), (3, 1), (25, 12), (14, 13),
(3, 6), (22, 14), (19, 15), (19, 15), (22, 16), (22, 17), (22, 18),
(20, 19), (22, 20), (5, 21), (4, 22), (10, 23), (26, 24), (17, 25),
(20, 26), (16, 27), (10, 28), (19, 29), (10, 30), (10, 31), (23, 32),
(22, 33), (26, 34), (27, 35), (22, 36), (27, 37), (22, 38), (22, 39),
(13, 40), (14, 41), (16, 27), (26, 34), (26, 42), (27, 35), (22, 36),
(20, 43), (26, 24), (22, 44), (13, 45), (19, 46), (20, 47), (16, 48),
(15, 49), (17, 50), (10, 28), (20, 51), (5, 52), (26, 24), (19, 53),
(15, 54), (10, 55), (10, 56), (13, 57), (13, 58), (13, 59), (12, 60),
(12, 61), (18, 62), (10, 63), (18, 64), (16, 65), (20, 66), (12, 67),
(6, 68), (6, 68), (15, 69), (15, 70), (15, 70), (21, 71), (30, 72),
(30, 73), (30, 74), (30, 75), (23, 76), (15, 77), (15, 78), (27, 79),
(27, 80), (27, 81), (27, 82), (27, 83), (27, 84), (27, 79), (27, 85),
(27, 86), (10, 87), (3, 88),
# fmt:on
]
elif problem_id == 1:
capacities = [0, 17, 44]
num_colors = 23
num_slabs = 30
orders = [
(4, 1), # (size, color)
(22, 2),
(9, 3),
(5, 4),
(8, 5),
(3, 6),
(3, 4),
(4, 7),
(7, 4),
(7, 8),
(3, 6),
(2, 6),
(2, 4),
(8, 9),
(5, 10),
(7, 11),
(4, 7),
(7, 11),
(5, 10),
(7, 11),
(8, 9),
(3, 1),
(25, 12),
(14, 13),
(3, 6),
(22, 14),
(19, 15),
(19, 15),
(22, 16),
(22, 17),
(22, 18),
(20, 19),
(22, 20),
(5, 21),
(4, 22),
(10, 23),
orders = [ # (size, color)
# fmt:off
(4, 1), (22, 2), (9, 3), (5, 4), (8, 5), (3, 6), (3, 4), (4, 7), (7, 4),
(7, 8), (3, 6), (2, 6), (2, 4), (8, 9), (5, 10), (7, 11), (4, 7), (7, 11),
(5, 10), (7, 11), (8, 9), (3, 1), (25, 12), (14, 13), (3, 6), (22, 14),
(19, 15), (19, 15), (22, 16), (22, 17), (22, 18), (20, 19), (22, 20),
(5, 21), (4, 22), (10, 23),
# fmt:on
]
elif problem_id == 2:
capacities = [0, 17, 44]
num_colors = 15
num_slabs = 20
orders = [
(4, 1), # (size, color)
(22, 2),
(9, 3),
(5, 4),
(8, 5),
(3, 6),
(3, 4),
(4, 7),
(7, 4),
(7, 8),
(3, 6),
(2, 6),
(2, 4),
(8, 9),
(5, 10),
(7, 11),
(4, 7),
(7, 11),
(5, 10),
(7, 11),
(8, 9),
(3, 1),
(25, 12),
(14, 13),
(3, 6),
(22, 14),
(19, 15),
(19, 15),
orders = [ # (size, color)
# fmt:off
(4, 1), (22, 2), (9, 3), (5, 4), (8, 5), (3, 6), (3, 4), (4, 7), (7, 4),
(7, 8), (3, 6), (2, 6), (2, 4), (8, 9), (5, 10), (7, 11), (4, 7), (7, 11),
(5, 10), (7, 11), (8, 9), (3, 1), (25, 12), (14, 13), (3, 6), (22, 14),
(19, 15), (19, 15),
# fmt:on
]
elif problem_id == 3:
capacities = [0, 17, 44]
num_colors = 8
num_slabs = 10
orders = [
(4, 1), # (size, color)
(22, 2),
(9, 3),
(5, 4),
(8, 5),
(3, 6),
(3, 4),
(4, 7),
(7, 4),
(7, 8),
(3, 6),
orders = [ # (size, color)
# fmt:off
(4, 1), (22, 2), (9, 3), (5, 4), (8, 5), (3, 6), (3, 4), (4, 7),
(7, 4), (7, 8), (3, 6),
# fmt:on
]
return (num_slabs, capacities, num_colors, orders)

2802
examples/python/task_allocation_sat.py
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1724
examples/python/tsp_sat.py
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113
ortools/algorithms/samples/knapsack.py
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@@ -30,110 +30,19 @@ def main():
# [START data]
values = [
360,
83,
59,
130,
431,
67,
230,
52,
93,
125,
670,
892,
600,
38,
48,
147,
78,
256,
63,
17,
120,
164,
432,
35,
92,
110,
22,
42,
50,
323,
514,
28,
87,
73,
78,
15,
26,
78,
210,
36,
85,
189,
274,
43,
33,
10,
19,
389,
276,
312,
# fmt:off
360, 83, 59, 130, 431, 67, 230, 52, 93, 125, 670, 892, 600, 38, 48, 147,
78, 256, 63, 17, 120, 164, 432, 35, 92, 110, 22, 42, 50, 323, 514, 28,
87, 73, 78, 15, 26, 78, 210, 36, 85, 189, 274, 43, 33, 10, 19, 389, 276,
312
# fmt:on
]
weights = [
[
7,
0,
30,
22,
80,
94,
11,
81,
70,
64,
59,
18,
0,
36,
3,
8,
15,
42,
9,
0,
42,
47,
52,
32,
26,
48,
55,
6,
29,
84,
2,
4,
18,
56,
7,
29,
93,
44,
71,
3,
86,
66,
31,
65,
0,
79,
20,
65,
52,
13,
]
# fmt: off
[7, 0, 30, 22, 80, 94, 11, 81, 70, 64, 59, 18, 0, 36, 3, 8, 15, 42, 9, 0,
42, 47, 52, 32, 26, 48, 55, 6, 29, 84, 2, 4, 18, 56, 7, 29, 93, 44, 71, 3,
86, 66, 31, 65, 0, 79, 20, 65, 52, 13],
# fmt: on
]
capacities = [850]
# [END data]

23
ortools/algorithms/samples/simple_knapsack_program.py
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@@ -30,26 +30,9 @@ def main():
# [START data]
weights = [
[
565,
406,
194,
130,
435,
367,
230,
315,
393,
125,
670,
892,
600,
293,
712,
147,
421,
255,
]
# fmt:off
[565, 406, 194, 130, 435, 367, 230, 315, 393, 125, 670, 892, 600, 293, 712, 147, 421, 255],
# fmt:on
]
capacities = [850]
values = weights[0]

73
ortools/graph/samples/balance_min_flow.py
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@@ -31,57 +31,40 @@ def main():
team_b = [2, 4, 6]
start_nodes = (
[0, 0]
+ [11, 11, 11]
+ [12, 12, 12]
+ [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6]
+ [7, 8, 9, 10]
# fmt: off
[0, 0]
+ [11, 11, 11]
+ [12, 12, 12]
+ [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6]
+ [7, 8, 9, 10]
# fmt: on
)
end_nodes = (
[11, 12]
+ team_a
+ team_b
+ [7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10]
+ [13, 13, 13, 13]
# fmt: off
[11, 12]
+ team_a
+ team_b
+ [7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10]
+ [13, 13, 13, 13]
# fmt: on
)
capacities = (
[2, 2]
+ [1, 1, 1]
+ [1, 1, 1]
+ [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
+ [1, 1, 1, 1]
# fmt: off
[2, 2]
+ [1, 1, 1]
+ [1, 1, 1]
+ [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
+ [1, 1, 1, 1]
# fmt: on
)
costs = (
[0, 0]
+ [0, 0, 0]
+ [0, 0, 0]
+ [
90,
76,
75,
70,
35,
85,
55,
65,
125,
95,
90,
105,
45,
110,
95,
115,
60,
105,
80,
75,
45,
65,
110,
95,
]
+ [0, 0, 0, 0]
# fmt: off
[0, 0]
+ [0, 0, 0]
+ [0, 0, 0]
+ [90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60, 105, 80, 75, 45, 65, 110, 95]
+ [0, 0, 0, 0]
# fmt: on
)
source = 0

247
ortools/linear_solver/samples/stigler_diet.py
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@@ -44,174 +44,85 @@ def main():
# Calcium (g), Iron (mg), Vitamin A (KIU), Vitamin B1 (mg), Vitamin B2 (mg),
# Niacin (mg), Vitamin C (mg)
data = [
[
"Wheat Flour (Enriched)",
"10 lb.",
36,
44.7,
1411,
2,
365,
0,
55.4,
33.3,
441,
0,
],
["Macaroni", "1 lb.", 14.1, 11.6, 418, 0.7, 54, 0, 3.2, 1.9, 68, 0],
[
"Wheat Cereal (Enriched)",
"28 oz.",
24.2,
11.8,
377,
14.4,
175,
0,
14.4,
8.8,
114,
0,
],
["Corn Flakes", "8 oz.", 7.1, 11.4, 252, 0.1, 56, 0, 13.5, 2.3, 68, 0],
["Corn Meal", "1 lb.", 4.6, 36.0, 897, 1.7, 99, 30.9, 17.4, 7.9, 106, 0],
["Hominy Grits", "24 oz.", 8.5, 28.6, 680, 0.8, 80, 0, 10.6, 1.6, 110, 0],
["Rice", "1 lb.", 7.5, 21.2, 460, 0.6, 41, 0, 2, 4.8, 60, 0],
["Rolled Oats", "1 lb.", 7.1, 25.3, 907, 5.1, 341, 0, 37.1, 8.9, 64, 0],
[
"White Bread (Enriched)",
"1 lb.",
7.9,
15.0,
488,
2.5,
115,
0,
13.8,
8.5,
126,
0,
],
["Whole Wheat Bread", "1 lb.", 9.1, 12.2, 484, 2.7, 125, 0, 13.9, 6.4, 160, 0],
["Rye Bread", "1 lb.", 9.1, 12.4, 439, 1.1, 82, 0, 9.9, 3, 66, 0],
["Pound Cake", "1 lb.", 24.8, 8.0, 130, 0.4, 31, 18.9, 2.8, 3, 17, 0],
["Soda Crackers", "1 lb.", 15.1, 12.5, 288, 0.5, 50, 0, 0, 0, 0, 0],
["Milk", "1 qt.", 11, 6.1, 310, 10.5, 18, 16.8, 4, 16, 7, 177],
[
"Evaporated Milk (can)",
"14.5 oz.",
6.7,
8.4,
422,
15.1,
9,
26,
3,
23.5,
11,
60,
],
["Butter", "1 lb.", 30.8, 10.8, 9, 0.2, 3, 44.2, 0, 0.2, 2, 0],
["Oleomargarine", "1 lb.", 16.1, 20.6, 17, 0.6, 6, 55.8, 0.2, 0, 0, 0],
["Eggs", "1 doz.", 32.6, 2.9, 238, 1.0, 52, 18.6, 2.8, 6.5, 1, 0],
["Cheese (Cheddar)", "1 lb.", 24.2, 7.4, 448, 16.4, 19, 28.1, 0.8, 10.3, 4, 0],
["Cream", "1/2 pt.", 14.1, 3.5, 49, 1.7, 3, 16.9, 0.6, 2.5, 0, 17],
["Peanut Butter", "1 lb.", 17.9, 15.7, 661, 1.0, 48, 0, 9.6, 8.1, 471, 0],
["Mayonnaise", "1/2 pt.", 16.7, 8.6, 18, 0.2, 8, 2.7, 0.4, 0.5, 0, 0],
["Crisco", "1 lb.", 20.3, 20.1, 0, 0, 0, 0, 0, 0, 0, 0],
["Lard", "1 lb.", 9.8, 41.7, 0, 0, 0, 0.2, 0, 0.5, 5, 0],
["Sirloin Steak", "1 lb.", 39.6, 2.9, 166, 0.1, 34, 0.2, 2.1, 2.9, 69, 0],
["Round Steak", "1 lb.", 36.4, 2.2, 214, 0.1, 32, 0.4, 2.5, 2.4, 87, 0],
["Rib Roast", "1 lb.", 29.2, 3.4, 213, 0.1, 33, 0, 0, 2, 0, 0],
["Chuck Roast", "1 lb.", 22.6, 3.6, 309, 0.2, 46, 0.4, 1, 4, 120, 0],
["Plate", "1 lb.", 14.6, 8.5, 404, 0.2, 62, 0, 0.9, 0, 0, 0],
["Liver (Beef)", "1 lb.", 26.8, 2.2, 333, 0.2, 139, 169.2, 6.4, 50.8, 316, 525],
["Leg of Lamb", "1 lb.", 27.6, 3.1, 245, 0.1, 20, 0, 2.8, 3.9, 86, 0],
["Lamb Chops (Rib)", "1 lb.", 36.6, 3.3, 140, 0.1, 15, 0, 1.7, 2.7, 54, 0],
["Pork Chops", "1 lb.", 30.7, 3.5, 196, 0.2, 30, 0, 17.4, 2.7, 60, 0],
["Pork Loin Roast", "1 lb.", 24.2, 4.4, 249, 0.3, 37, 0, 18.2, 3.6, 79, 0],
["Bacon", "1 lb.", 25.6, 10.4, 152, 0.2, 23, 0, 1.8, 1.8, 71, 0],
["Ham, smoked", "1 lb.", 27.4, 6.7, 212, 0.2, 31, 0, 9.9, 3.3, 50, 0],
["Salt Pork", "1 lb.", 16, 18.8, 164, 0.1, 26, 0, 1.4, 1.8, 0, 0],
["Roasting Chicken", "1 lb.", 30.3, 1.8, 184, 0.1, 30, 0.1, 0.9, 1.8, 68, 46],
["Veal Cutlets", "1 lb.", 42.3, 1.7, 156, 0.1, 24, 0, 1.4, 2.4, 57, 0],
["Salmon, Pink (can)", "16 oz.", 13, 5.8, 705, 6.8, 45, 3.5, 1, 4.9, 209, 0],
["Apples", "1 lb.", 4.4, 5.8, 27, 0.5, 36, 7.3, 3.6, 2.7, 5, 544],
["Bananas", "1 lb.", 6.1, 4.9, 60, 0.4, 30, 17.4, 2.5, 3.5, 28, 498],
["Lemons", "1 doz.", 26, 1.0, 21, 0.5, 14, 0, 0.5, 0, 4, 952],
["Oranges", "1 doz.", 30.9, 2.2, 40, 1.1, 18, 11.1, 3.6, 1.3, 10, 1998],
["Green Beans", "1 lb.", 7.1, 2.4, 138, 3.7, 80, 69, 4.3, 5.8, 37, 862],
["Cabbage", "1 lb.", 3.7, 2.6, 125, 4.0, 36, 7.2, 9, 4.5, 26, 5369],
["Carrots", "1 bunch", 4.7, 2.7, 73, 2.8, 43, 188.5, 6.1, 4.3, 89, 608],
["Celery", "1 stalk", 7.3, 0.9, 51, 3.0, 23, 0.9, 1.4, 1.4, 9, 313],
["Lettuce", "1 head", 8.2, 0.4, 27, 1.1, 22, 112.4, 1.8, 3.4, 11, 449],
["Onions", "1 lb.", 3.6, 5.8, 166, 3.8, 59, 16.6, 4.7, 5.9, 21, 1184],
["Potatoes", "15 lb.", 34, 14.3, 336, 1.8, 118, 6.7, 29.4, 7.1, 198, 2522],
["Spinach", "1 lb.", 8.1, 1.1, 106, 0, 138, 918.4, 5.7, 13.8, 33, 2755],
["Sweet Potatoes", "1 lb.", 5.1, 9.6, 138, 2.7, 54, 290.7, 8.4, 5.4, 83, 1912],
["Peaches (can)", "No. 2 1/2", 16.8, 3.7, 20, 0.4, 10, 21.5, 0.5, 1, 31, 196],
["Pears (can)", "No. 2 1/2", 20.4, 3.0, 8, 0.3, 8, 0.8, 0.8, 0.8, 5, 81],
["Pineapple (can)", "No. 2 1/2", 21.3, 2.4, 16, 0.4, 8, 2, 2.8, 0.8, 7, 399],
["Asparagus (can)", "No. 2", 27.7, 0.4, 33, 0.3, 12, 16.3, 1.4, 2.1, 17, 272],
["Green Beans (can)", "No. 2", 10, 1.0, 54, 2, 65, 53.9, 1.6, 4.3, 32, 431],
["Pork and Beans (can)", "16 oz.", 7.1, 7.5, 364, 4, 134, 3.5, 8.3, 7.7, 56, 0],
["Corn (can)", "No. 2", 10.4, 5.2, 136, 0.2, 16, 12, 1.6, 2.7, 42, 218],
["Peas (can)", "No. 2", 13.8, 2.3, 136, 0.6, 45, 34.9, 4.9, 2.5, 37, 370],
["Tomatoes (can)", "No. 2", 8.6, 1.3, 63, 0.7, 38, 53.2, 3.4, 2.5, 36, 1253],
[
"Tomato Soup (can)",
"10 1/2 oz.",
7.6,
1.6,
71,
0.6,
43,
57.9,
3.5,
2.4,
67,
862,
],
["Peaches, Dried", "1 lb.", 15.7, 8.5, 87, 1.7, 173, 86.8, 1.2, 4.3, 55, 57],
["Prunes, Dried", "1 lb.", 9, 12.8, 99, 2.5, 154, 85.7, 3.9, 4.3, 65, 257],
["Raisins, Dried", "15 oz.", 9.4, 13.5, 104, 2.5, 136, 4.5, 6.3, 1.4, 24, 136],
["Peas, Dried", "1 lb.", 7.9, 20.0, 1367, 4.2, 345, 2.9, 28.7, 18.4, 162, 0],
[
"Lima Beans, Dried",
"1 lb.",
8.9,
17.4,
1055,
3.7,
459,
5.1,
26.9,
38.2,
93,
0,
],
[
"Navy Beans, Dried",
"1 lb.",
5.9,
26.9,
1691,
11.4,
792,
0,
38.4,
24.6,
217,
0,
],
["Coffee", "1 lb.", 22.4, 0, 0, 0, 0, 0, 4, 5.1, 50, 0],
["Tea", "1/4 lb.", 17.4, 0, 0, 0, 0, 0, 0, 2.3, 42, 0],
["Cocoa", "8 oz.", 8.6, 8.7, 237, 3, 72, 0, 2, 11.9, 40, 0],
["Chocolate", "8 oz.", 16.2, 8.0, 77, 1.3, 39, 0, 0.9, 3.4, 14, 0],
["Sugar", "10 lb.", 51.7, 34.9, 0, 0, 0, 0, 0, 0, 0, 0],
["Corn Syrup", "24 oz.", 13.7, 14.7, 0, 0.5, 74, 0, 0, 0, 5, 0],
["Molasses", "18 oz.", 13.6, 9.0, 0, 10.3, 244, 0, 1.9, 7.5, 146, 0],
["Strawberry Preserves", "1 lb.", 20.5, 6.4, 11, 0.4, 7, 0.2, 0.2, 0.4, 3, 0],
# fmt: off
['Wheat Flour (Enriched)', '10 lb.', 36, 44.7, 1411, 2, 365, 0, 55.4, 33.3, 441, 0],
['Macaroni', '1 lb.', 14.1, 11.6, 418, 0.7, 54, 0, 3.2, 1.9, 68, 0],
['Wheat Cereal (Enriched)', '28 oz.', 24.2, 11.8, 377, 14.4, 175, 0, 14.4, 8.8, 114, 0],
['Corn Flakes', '8 oz.', 7.1, 11.4, 252, 0.1, 56, 0, 13.5, 2.3, 68, 0],
['Corn Meal', '1 lb.', 4.6, 36.0, 897, 1.7, 99, 30.9, 17.4, 7.9, 106, 0],
['Hominy Grits', '24 oz.', 8.5, 28.6, 680, 0.8, 80, 0, 10.6, 1.6, 110, 0],
['Rice', '1 lb.', 7.5, 21.2, 460, 0.6, 41, 0, 2, 4.8, 60, 0],
['Rolled Oats', '1 lb.', 7.1, 25.3, 907, 5.1, 341, 0, 37.1, 8.9, 64, 0],
['White Bread (Enriched)', '1 lb.', 7.9, 15.0, 488, 2.5, 115, 0, 13.8, 8.5, 126, 0],
['Whole Wheat Bread', '1 lb.', 9.1, 12.2, 484, 2.7, 125, 0, 13.9, 6.4, 160, 0],
['Rye Bread', '1 lb.', 9.1, 12.4, 439, 1.1, 82, 0, 9.9, 3, 66, 0],
['Pound Cake', '1 lb.', 24.8, 8.0, 130, 0.4, 31, 18.9, 2.8, 3, 17, 0],
['Soda Crackers', '1 lb.', 15.1, 12.5, 288, 0.5, 50, 0, 0, 0, 0, 0],
['Milk', '1 qt.', 11, 6.1, 310, 10.5, 18, 16.8, 4, 16, 7, 177],
['Evaporated Milk (can)', '14.5 oz.', 6.7, 8.4, 422, 15.1, 9, 26, 3, 23.5, 11, 60],
['Butter', '1 lb.', 30.8, 10.8, 9, 0.2, 3, 44.2, 0, 0.2, 2, 0],
['Oleomargarine', '1 lb.', 16.1, 20.6, 17, 0.6, 6, 55.8, 0.2, 0, 0, 0],
['Eggs', '1 doz.', 32.6, 2.9, 238, 1.0, 52, 18.6, 2.8, 6.5, 1, 0],
['Cheese (Cheddar)', '1 lb.', 24.2, 7.4, 448, 16.4, 19, 28.1, 0.8, 10.3, 4, 0],
['Cream', '1/2 pt.', 14.1, 3.5, 49, 1.7, 3, 16.9, 0.6, 2.5, 0, 17],
['Peanut Butter', '1 lb.', 17.9, 15.7, 661, 1.0, 48, 0, 9.6, 8.1, 471, 0],
['Mayonnaise', '1/2 pt.', 16.7, 8.6, 18, 0.2, 8, 2.7, 0.4, 0.5, 0, 0],
['Crisco', '1 lb.', 20.3, 20.1, 0, 0, 0, 0, 0, 0, 0, 0],
['Lard', '1 lb.', 9.8, 41.7, 0, 0, 0, 0.2, 0, 0.5, 5, 0],
['Sirloin Steak', '1 lb.', 39.6, 2.9, 166, 0.1, 34, 0.2, 2.1, 2.9, 69, 0],
['Round Steak', '1 lb.', 36.4, 2.2, 214, 0.1, 32, 0.4, 2.5, 2.4, 87, 0],
['Rib Roast', '1 lb.', 29.2, 3.4, 213, 0.1, 33, 0, 0, 2, 0, 0],
['Chuck Roast', '1 lb.', 22.6, 3.6, 309, 0.2, 46, 0.4, 1, 4, 120, 0],
['Plate', '1 lb.', 14.6, 8.5, 404, 0.2, 62, 0, 0.9, 0, 0, 0],
['Liver (Beef)', '1 lb.', 26.8, 2.2, 333, 0.2, 139, 169.2, 6.4, 50.8, 316, 525],
['Leg of Lamb', '1 lb.', 27.6, 3.1, 245, 0.1, 20, 0, 2.8, 3.9, 86, 0],
['Lamb Chops (Rib)', '1 lb.', 36.6, 3.3, 140, 0.1, 15, 0, 1.7, 2.7, 54, 0],
['Pork Chops', '1 lb.', 30.7, 3.5, 196, 0.2, 30, 0, 17.4, 2.7, 60, 0],
['Pork Loin Roast', '1 lb.', 24.2, 4.4, 249, 0.3, 37, 0, 18.2, 3.6, 79, 0],
['Bacon', '1 lb.', 25.6, 10.4, 152, 0.2, 23, 0, 1.8, 1.8, 71, 0],
['Ham, smoked', '1 lb.', 27.4, 6.7, 212, 0.2, 31, 0, 9.9, 3.3, 50, 0],
['Salt Pork', '1 lb.', 16, 18.8, 164, 0.1, 26, 0, 1.4, 1.8, 0, 0],
['Roasting Chicken', '1 lb.', 30.3, 1.8, 184, 0.1, 30, 0.1, 0.9, 1.8, 68, 46],
['Veal Cutlets', '1 lb.', 42.3, 1.7, 156, 0.1, 24, 0, 1.4, 2.4, 57, 0],
['Salmon, Pink (can)', '16 oz.', 13, 5.8, 705, 6.8, 45, 3.5, 1, 4.9, 209, 0],
['Apples', '1 lb.', 4.4, 5.8, 27, 0.5, 36, 7.3, 3.6, 2.7, 5, 544],
['Bananas', '1 lb.', 6.1, 4.9, 60, 0.4, 30, 17.4, 2.5, 3.5, 28, 498],
['Lemons', '1 doz.', 26, 1.0, 21, 0.5, 14, 0, 0.5, 0, 4, 952],
['Oranges', '1 doz.', 30.9, 2.2, 40, 1.1, 18, 11.1, 3.6, 1.3, 10, 1998],
['Green Beans', '1 lb.', 7.1, 2.4, 138, 3.7, 80, 69, 4.3, 5.8, 37, 862],
['Cabbage', '1 lb.', 3.7, 2.6, 125, 4.0, 36, 7.2, 9, 4.5, 26, 5369],
['Carrots', '1 bunch', 4.7, 2.7, 73, 2.8, 43, 188.5, 6.1, 4.3, 89, 608],
['Celery', '1 stalk', 7.3, 0.9, 51, 3.0, 23, 0.9, 1.4, 1.4, 9, 313],
['Lettuce', '1 head', 8.2, 0.4, 27, 1.1, 22, 112.4, 1.8, 3.4, 11, 449],
['Onions', '1 lb.', 3.6, 5.8, 166, 3.8, 59, 16.6, 4.7, 5.9, 21, 1184],
['Potatoes', '15 lb.', 34, 14.3, 336, 1.8, 118, 6.7, 29.4, 7.1, 198, 2522],
['Spinach', '1 lb.', 8.1, 1.1, 106, 0, 138, 918.4, 5.7, 13.8, 33, 2755],
['Sweet Potatoes', '1 lb.', 5.1, 9.6, 138, 2.7, 54, 290.7, 8.4, 5.4, 83, 1912],
['Peaches (can)', 'No. 2 1/2', 16.8, 3.7, 20, 0.4, 10, 21.5, 0.5, 1, 31, 196],
['Pears (can)', 'No. 2 1/2', 20.4, 3.0, 8, 0.3, 8, 0.8, 0.8, 0.8, 5, 81],
['Pineapple (can)', 'No. 2 1/2', 21.3, 2.4, 16, 0.4, 8, 2, 2.8, 0.8, 7, 399],
['Asparagus (can)', 'No. 2', 27.7, 0.4, 33, 0.3, 12, 16.3, 1.4, 2.1, 17, 272],
['Green Beans (can)', 'No. 2', 10, 1.0, 54, 2, 65, 53.9, 1.6, 4.3, 32, 431],
['Pork and Beans (can)', '16 oz.', 7.1, 7.5, 364, 4, 134, 3.5, 8.3, 7.7, 56, 0],
['Corn (can)', 'No. 2', 10.4, 5.2, 136, 0.2, 16, 12, 1.6, 2.7, 42, 218],
['Peas (can)', 'No. 2', 13.8, 2.3, 136, 0.6, 45, 34.9, 4.9, 2.5, 37, 370],
['Tomatoes (can)', 'No. 2', 8.6, 1.3, 63, 0.7, 38, 53.2, 3.4, 2.5, 36, 1253],
['Tomato Soup (can)', '10 1/2 oz.', 7.6, 1.6, 71, 0.6, 43, 57.9, 3.5, 2.4, 67, 862],
['Peaches, Dried', '1 lb.', 15.7, 8.5, 87, 1.7, 173, 86.8, 1.2, 4.3, 55, 57],
['Prunes, Dried', '1 lb.', 9, 12.8, 99, 2.5, 154, 85.7, 3.9, 4.3, 65, 257],
['Raisins, Dried', '15 oz.', 9.4, 13.5, 104, 2.5, 136, 4.5, 6.3, 1.4, 24, 136],
['Peas, Dried', '1 lb.', 7.9, 20.0, 1367, 4.2, 345, 2.9, 28.7, 18.4, 162, 0],
['Lima Beans, Dried', '1 lb.', 8.9, 17.4, 1055, 3.7, 459, 5.1, 26.9, 38.2, 93, 0],
['Navy Beans, Dried', '1 lb.', 5.9, 26.9, 1691, 11.4, 792, 0, 38.4, 24.6, 217, 0],
['Coffee', '1 lb.', 22.4, 0, 0, 0, 0, 0, 4, 5.1, 50, 0],
['Tea', '1/4 lb.', 17.4, 0, 0, 0, 0, 0, 0, 2.3, 42, 0],
['Cocoa', '8 oz.', 8.6, 8.7, 237, 3, 72, 0, 2, 11.9, 40, 0],
['Chocolate', '8 oz.', 16.2, 8.0, 77, 1.3, 39, 0, 0.9, 3.4, 14, 0],
['Sugar', '10 lb.', 51.7, 34.9, 0, 0, 0, 0, 0, 0, 0, 0],
['Corn Syrup', '24 oz.', 13.7, 14.7, 0, 0.5, 74, 0, 0, 0, 5, 0],
['Molasses', '18 oz.', 13.6, 9.0, 0, 10.3, 244, 0, 1.9, 7.5, 146, 0],
['Strawberry Preserves', '1 lb.', 20.5, 6.4, 11, 0.4, 7, 0.2, 0.2, 0.4, 3, 0],
# fmt: on
]
# [END data_model]