-
Notifications
You must be signed in to change notification settings - Fork 0
/
load_and_transform_data.py
190 lines (161 loc) · 8.58 KB
/
load_and_transform_data.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
import json
import pandas as pd
import pickle
from itertools import combinations_with_replacement
from print_output import print_choice
products_data = pd.read_excel("products.xlsx")
def append_options(options, name, price, *args):
options[0].append(name)
options[1].append(price)
for i in range(2, 10):
macro_sum = 0
for one_id in args:
macro_sum += products_data.iloc[one_id - 1, i]
options[i].append(round(macro_sum, 2))
def load_and_transform_data(excluded_types=()):
"""
The function combines McDonald's menu data from .json file and McDonald's macronutrients data from .xlsx file
and returns placed in lists data of every possible single dish/option you can order at McDonald's.
"""
with open("offers.json", "r", encoding="utf-8") as f:
offers_data = json.load(f)
options_data = ([], [], [], [], [], [], [], [], [], [])
# 0 - name
# 1 - cost
# 2 - kcal
# 3 - fat
# 4 - sfa
# 5 - carbohydrates
# 6 - sugars
# 7 - fiber
# 8 - protein
# 9 - salt
for dish in offers_data['dishes'].keys():
dish_id = offers_data['dishes'][dish].get("id")
dish_types = offers_data['dishes'][dish]["types"]
for dish_type in dish_types:
if dish_type in excluded_types:
continue
match dish_type:
case 0: # single
append_options(
options_data,
dish,
offers_data['dishes'][dish]["price"],
dish_id
)
case 1: # standard-combo
for combo_type in ['standard-combo', 'standard-combo-plus']:
for d_id in offers_data[combo_type]['drink']:
for s_id in offers_data["fries-sauces"] + offers_data["salad-sauces"]:
if s_id in offers_data["fries-sauces"]:
a_id = 174 if combo_type == 'standard-combo' else 175
else:
a_id = 143
append_options(
options_data,
dish + f" {combo_type} " + products_data.iloc[a_id - 1, 1] + " " + products_data.iloc[s_id - 1, 1] + " " + products_data.iloc[d_id - 1, 1],
offers_data['dishes'][dish]["combo-price"] + (0.00 if combo_type == 'standard-combo' else 3.00),
dish_id, a_id, s_id, d_id
)
case 2: # 2forU
for combo_type in ['2forU', '2forU-plus']:
cost = 9.00 if combo_type == "2forU" else 11.00
for a_id in offers_data[combo_type]['addition']:
if a_id in [173, 174, 175]:
for s_id in offers_data["fries-sauces"]:
append_options(
options_data,
dish + f" {combo_type} " + products_data.iloc[a_id - 1, 1] + " " + products_data.iloc[s_id - 1, 1],
cost,
dish_id, a_id, s_id
)
else:
append_options(
options_data,
dish + f" {combo_type} " + products_data.iloc[a_id - 1, 1],
cost,
dish_id, a_id
)
case 3: # salad
for s_ids in combinations_with_replacement(offers_data["salad-sauces"], offers_data["dishes"][dish]["sauces"]):
append_options(
options_data,
dish + " " + " ".join(map(lambda a: products_data.iloc[a - 1, 1], s_ids)),
offers_data["dishes"][dish]["price"],
dish_id, *s_ids
)
case 4: # chicken
for s_ids in combinations_with_replacement(offers_data["nuggets-sauces"], offers_data["dishes"][dish]["sauces"]):
append_options(
options_data,
dish + " " + " ".join(map(lambda a: products_data.iloc[a - 1, 1], s_ids)),
offers_data["dishes"][dish]["price"],
dish_id, *s_ids
)
case 5: # chicken box
for s1_ids in combinations_with_replacement(offers_data["nuggets-sauces"], 2):
for s2_ids in combinations_with_replacement(offers_data["fries-sauces"], 2):
append_options(
options_data,
dish + " " + products_data.iloc[s1_ids[0] - 1, 1] + " " + products_data.iloc[s1_ids[1] - 1, 1] +
" " + products_data.iloc[s2_ids[0] - 1, 1] + " " + products_data.iloc[s2_ids[1] - 1, 1],
offers_data["dishes"][dish]["price"],
*offers_data["dishes"][dish]["ids"], *s1_ids, *s2_ids
)
case 6: # fries
for s_id in offers_data["fries-sauces"]:
append_options(
options_data,
dish + " " + products_data.iloc[s_id - 1, 1],
offers_data["dishes"][dish]["price"],
dish_id, s_id
)
case 7: # happy meal
for m_id in offers_data["happy-meal"]["dish"]:
for a1_id in offers_data["happy-meal"]["addition-1"]:
for a2_id in offers_data["happy-meal"]["addition-2"]:
for d_id in offers_data["happy-meal"]["drink"]:
if a2_id == 173:
for s_id in offers_data["fries-sauces"]:
append_options(
options_data,
dish + " " + products_data.iloc[m_id - 1, 1] + " " + products_data.iloc[a1_id - 1, 1] +
" " + products_data.iloc[a2_id - 1, 1] + " " + products_data.iloc[s_id - 1, 1] +
" " + products_data.iloc[d_id - 1, 1],
offers_data["dishes"][dish]["price"],
m_id, a1_id, a2_id, s_id, d_id
)
else:
append_options(
options_data,
dish + " " + products_data.iloc[m_id - 1, 1] + " " + products_data.iloc[a1_id - 1, 1] +
" " + products_data.iloc[a2_id - 1, 1] + " " + products_data.iloc[d_id - 1, 1],
offers_data["dishes"][dish]["price"],
m_id, a1_id, a2_id, d_id
)
case 8: # drink
cost = {"small-drink": "price", "medium-drink": "medium-price", "large-drink": "large-price"}
for drink_type in ["small-drink", "medium-drink", "large-drink"]:
for d_id in offers_data["drink"][drink_type]:
append_options(
options_data,
products_data.iloc[d_id - 1, 1],
offers_data["dishes"][dish][cost[drink_type]],
d_id,
)
case _:
pass
return options_data
def pickle_to_file(content, filename):
with open(filename, "wb") as f:
pickle.dump(content, f)
if __name__ == "__main__":
options = load_and_transform_data(excluded_types=[])
for i in range(0, 10):
print(len(options[i]), end=" ")
print()
# print(options[0])
# print(options[1])
# print(options[2])
pickle_to_file(options, "options.pkl")