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import pandas as pd | |
import random | |
import datetime | |
# # Specify the file path of the XLS document | |
# file_path = 'consumuri.xlsx' | |
# # Read the XLS file | |
# data = pd.read_excel(file_path) | |
# data = data.fillna('<nimic>') | |
pd.set_option('display.max_rows', None) # Display all rows | |
pd.set_option('display.max_columns', None) # Display all columns | |
pd.set_option('display.width', 1000) # Set the display width for showing more information | |
pd.set_option('display.colheader_justify', 'center') # Center justify column headers | |
pd.set_option('display.precision', 3) # Set precision for decimal values | |
def format_items(dictionary): | |
"pretty string" | |
formatted_string = "Item Details:\n" | |
for key, value in dictionary.items(): | |
formatted_string += f"{key}: {value}\n" | |
return formatted_string | |
def cantitati_piesa(file, denumire_id, cantitate): | |
""" | |
Calculeaza cate piese trebuie sa fie facute de fiecare data cand intlaneste id d epiese ii aduaga cantitatea.. | |
:param file: | |
:type file: | |
:param denumire_id: | |
:type denumire_id: | |
:param cantitate: | |
:type cantitate: | |
:return: | |
:rtype: | |
""" | |
data=pd.read_excel(file) | |
products = {} | |
for index, row in data.iterrows(): | |
denumire = row[denumire_id] | |
if denumire not in ['Consumuri', '<nimic>']: | |
if denumire not in products: | |
products[denumire] = row[cantitate] | |
else: | |
products[denumire] += row[cantitate] | |
p={"produs":[], "cantitate":[]} | |
for k in products.keys(): | |
p["produs"].append(k) | |
p["cantitate"].append(products[k]) | |
df=pd.DataFrame.from_dict(p) | |
# Generate a random number and get the current date | |
random_number = random.randint(1000, 9999) | |
current_date = datetime.datetime.now().strftime("%Y%m%d") | |
filename = f"{file.name}_cantitate_{current_date}_{random_number}.xlsx" | |
df.to_excel(filename, index=False) | |
# Generate a summary string for display | |
summary_string = "Canitati produse:\n" + "\n".join(f"{prod}: {qty}" for prod, qty in products.items()) | |
# Return the summary string and the path to the Excel file | |
return summary_string, filename | |
return df |