id: python-generate-outputs
namespace: company.team

variables:
  file: orders.csv

tasks:
  - id: analyze_orders
    type: io.kestra.plugin.scripts.python.Script
    warningOnStdErr: false
    beforeCommands:
      - pip install faker kestra > /dev/null
    outputFiles:
      - "*.csv"
    script: >
      import csv import random import time from faker import Faker from kestra
      import Kestra

      start_time = time.time()

      fake = Faker()

      # list of columns for the CSV file columns = [
          "order_id",
          "customer_name",
          "customer_email",
          "product_id",
          "price",
          "quantity",
          "total",
      ]

      filename = "{{ vars.file }}" tags = {'file': filename}

      # Generate 100 random orders orders = [] for i in range(100):
          order_id = i + 1
          customer_name = fake.name()
          customer_email = fake.email()
          product_id = random.randint(1, 20)
          price = round(random.uniform(10.0, 200.0), 2)
          quantity = random.randint(1, 10)
          total = round(price * quantity, 2)
          orders.append(
              [order_id, customer_name, customer_email, product_id, price, quantity, total]
          )

      # Write the orders to a CSV file with open(filename, "w", newline="") as
      file:
          writer = csv.writer(file)
          writer.writerow(columns)
          writer.writerows(orders)

      # Calculate and print the sum and average of the "total" column total_sum
      = sum(order[6] for order in orders) average_order = round(total_sum /
      len(orders), 2) print(f"Total sum: {total_sum}") print(f"Average Order
      value: {average_order}")

      Kestra.outputs({"total_sum": total_sum, "average_order": average_order})
      Kestra.counter('total_sum', total_sum, tags)
      Kestra.counter('average_order', average_order, tags)

      end_time = time.time()   processing_time = end_time - start_time
      Kestra.timer('processing_time', processing_time, tags)

      print(f"The script execution took: {processing_time} seconds")