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82 lines
2.7 KiB
82 lines
2.7 KiB
import pyrebase
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config = {
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"apiKey": "AIzaSyD3bXRjLxEAVOKtj8hpjO4iI3Nn32F7agU",
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"authDomain": "foodcloud-f6eb1.firebaseapp.com",
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"databaseURL": "https://foodcloud-f6eb1.firebaseio.com/",
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"storageBucket": "foodcloud-f6eb1.appspot.com"
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}
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firebase = pyrebase.initialize_app(config)
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auth = firebase.auth()
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user = auth.sign_in_with_email_and_password('yigitcolakohlu@gmail.com', 'FoodWro2018')
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db = firebase.database()
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data_format_prod = {
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'Prod_Name': None, 'BBD': None, 'Nutrients': [], 'Calories': 0, 'Allergens': [],
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'Problematic': False, 'Process': None, 'ED': None
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}
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data_format_proc = {
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'Harvested': {'Date': '', 'Location': '', 'Product': ''},
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'Transport1': {'Duration': 0, 'Moved to,from': '-', 'Condition': True, 'Stopped': False},
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'Process': {'Location': '', 'Processes': ''},
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'Transport2': {'Duration': 0, 'Moved to,from': '-', 'Condition': 0, 'Stopped': False},
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'Packaging': {'Location': '', 'Material': '', 'Cancerogen': True}
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}
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data_1_prod = {
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'Prod_Name': "Milk", 'BBD': "24.08.2018", 'Nutrients': ['Protein', 'Fat', 'Lactose', 'Glucose'],
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'Calories': 120, 'Cooked': False, 'Allergens': ['Lactose'], 'Problematic': False,
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'Process': 'Pastorized'
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}
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data_2_prod = {
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'Prod_Name': "Chocolate", 'BBD': "28.01.2019", 'Nutrients': ['Lactose', 'Glucose', 'Cocoa'],
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'Calories': 180, 'Cooked': False, 'Allergens': [""], 'Problematic': False, 'Process': ''
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}
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data_1_proc = {
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'Harvested': {
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'Date': '18.08.2018', 'Location': 'Larson Family',
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'Product': 'Raw Milk'
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},
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'Transport1': {
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'Duration': 9, 'Moved to,from': 'Larson Family-McCarty Family Farms', 'Condition': True,
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'Stopped': True
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}, 'Process': {
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'Location': 'McCarty Family Farms',
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'Processes': 'Reverse Osmosis,Nanofiltration,Ultrafiltration,Microfiltration'
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},
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'Transport2': {
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'Duration': 13, 'Moved to,from': 'McCarty Family Farms-JJX Packaging', 'Condition': True,
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'Stopped': True
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},
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'Packaging': {'Location': 'JJX Packaging', 'Material': 'Carton', 'Cancerogen': False}
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}
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data_2_proc = {
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'Harvested': {
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'Date': '27.01.2018', 'Location': 'India',
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'Product': 'Cocoa'
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},
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'Transport1': {'Duration': 71, 'Moved to,from': 'India-Nestle ', 'Condition': True, 'Stopped': True},
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'Process': {'Location': 'Nestle', 'Processes': 'Roasting,Pulp,Conching,Moulding'},
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'Transport2': {
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'Duration': 4, 'Moved to,from': 'Nestle-Ulma Packaging', 'Condition': True,
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'Stopped': False
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},
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'Packaging': {'Location': 'Ulma Packaging', 'Material': 'Foil', 'Cancerogen': False}
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}
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Products = [data_1_prod, data_2_prod]
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Processes = [data_1_proc, data_2_proc]
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for i in range(len(Products)):
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db.child("Products").child(str(i + 1)).set(Products[i])
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for i in range(len(Processes)):
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db.child("Processes").child(str(i + 1)).set(Processes[i])
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