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Update .gitignore and modify code in Create_Browser.py, inventaireMon…
…go.py, csvReader.py, UpdatePricePromocash.py, Course.py, and remiseStockManuelle.py. Update inventory files in csv folder.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,112 @@ | ||
| from pymongo import MongoClient | ||
| from datetime import datetime, timedelta | ||
| from datetime import timezone as tz | ||
| from dotenv import load_dotenv | ||
| from csvReader import csv_reader | ||
| from csvWriter import csv_writer | ||
| from os import getenv | ||
| from bson.int64 import Int64 | ||
| import math | ||
|
|
||
| def arrondi_au_mutilple(x, a): | ||
| if a <= 0: | ||
| return x | ||
| return math.ceil(x / a) * a | ||
|
|
||
| def calcul_optimal_amount(client, magasin, days=21, security=True): | ||
| # Access a specific database | ||
| db = client["bar"] | ||
|
|
||
| # Access a specific collection within the database | ||
| collection_transactions = db["transactions"] | ||
| week_quantities = get_item_sales_weeks(collection_transactions, days) | ||
| collection_items = db["items"] | ||
|
|
||
| if magasin == "p": | ||
| produits = csv_reader(file='Inventaire_Promocash.csv', row_number=0) | ||
| nb_produits_par_lots = csv_reader(file='Inventaire_Promocash.csv', row_number=3) | ||
| elif magasin == "a": | ||
| produits = csv_reader(file='Inventaire_Auchan.csv', row_number=0) | ||
| nb_produits_par_lots = csv_reader(file='Inventaire_Auchan.csv', row_number=3) | ||
| else: | ||
| print("Magasin inconnu") | ||
| exit() | ||
|
|
||
| print("La sécurité est désactivée, vous êtes sûr de ce que vous faites" if security == False else "La sécurité est activée, vous pouvez annuler à tout moment") | ||
| update_optimal_amount = [('id', 'name', 'amount_sold', 'new_optimal_amount', 'old_optimal_amount')] | ||
| update_optimal_manquant = [('id', 'name', 'amount_left', 'optimal_amount', 'optimal_amount')] | ||
| for i in range(len(produits)): | ||
| query = { "name": { "$regex": produits[i], "$options" :'i'}, "deleted_at": None} | ||
| produit = collection_items.find_one(query) | ||
| if produit["name"] in week_quantities.keys() and produit["amount_left"] != 0: | ||
| new_optimal_amount = Int64(arrondi_au_mutilple(week_quantities[produit["name"]], int(nb_produits_par_lots[i]))) | ||
| if new_optimal_amount != produit["optimal_amount"]: | ||
| update_optimal_amount.append((produit["_id"], produit["name"], week_quantities[produit["name"]], new_optimal_amount, produit["optimal_amount"])) | ||
| if not security: | ||
| if input(f"Voulez vous modifier le montant optimal du produit {produit['name']} de {produit['optimal_amount']} pour {new_optimal_amount} (nb_produit_vendu: {int(week_quantities[produit['name']])})? (y/n)") == "y": | ||
| collection_items.update_one({"name": produit["name"]}, {"$set": {"optimal_amount": new_optimal_amount}}) | ||
| print(f"{produit['name']} Modifier") | ||
| else: | ||
| update_optimal_manquant.append((produit["_id"], produit["name"], produit["amount_left"], produit["optimal_amount"], produit["optimal_amount"])) | ||
|
|
||
| print("Modification écrite dans le fichier Update_optimal.csv et Update_optimal_manquant.csv") | ||
| print("(id, name, amount_sold, new_optimal_amount, old_optimal_amount)") | ||
| csv_writer('Update_optimal.csv', update_optimal_amount) | ||
| csv_writer('Update_optimal_manquant.csv', update_optimal_manquant) | ||
|
|
||
| def get_item_sales_weeks(transactions_collection, w): | ||
| # Calculate the date w weeks ago | ||
| three_weeks_ago = int((datetime.now(tz.utc) - timedelta(days=w)).timestamp()) | ||
| # Create the pipeline for the aggregation | ||
| pipeline = [ | ||
| { | ||
| "$match": { | ||
| "created_at": { "$gte": three_weeks_ago } | ||
| } | ||
| }, | ||
| { | ||
| "$unwind": "$items" | ||
| }, | ||
| { | ||
| "$group": { | ||
| "_id": "$items.item_id", | ||
| "totalQuantity": { "$sum": "$items.item_amount" } | ||
| } | ||
| }, | ||
| { | ||
| "$lookup": { | ||
| "from": "items", | ||
| "localField": "_id", | ||
| "foreignField": "id", | ||
| "as": "item_data" | ||
| } | ||
| }, | ||
| { | ||
| "$unwind": "$item_data" | ||
| }, | ||
| { | ||
| "$project": { | ||
| "_id": 0, | ||
| "item_name": "$item_data.name", | ||
| "totalQuantity": 1 | ||
| } | ||
| }, | ||
| { | ||
| "$group": { | ||
| "_id": "$item_name", | ||
| "totalQuantity": { "$sum": "$totalQuantity" } | ||
| } | ||
| } | ||
| ] | ||
|
|
||
| # Execute the aggregation and fetch the results | ||
| results = transactions_collection.aggregate(pipeline) | ||
| item_sales_dict = {result['_id']: result['totalQuantity'] for result in results} | ||
| return item_sales_dict | ||
|
|
||
|
|
||
| if __name__ == '__main__': | ||
| load_dotenv() | ||
| client = MongoClient(f"mongodb://bar:{getenv('MONGO_MDP')}@mongo.telecomnancy.net:443/?authMechanism=DEFAULT&authSource=bar&directConnection=true&tls=true&tlsCertificateKeyFile={getenv('MONGO_PEM')}") | ||
| calcul_optimal_amount(client, "p") | ||
| #update_optimal_amount(client, "Update_optimal.csv") |
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