How to Automate Shopify Sales Reports with Python (No Servers Needed)

The Problem with Manual E-commerce Reporting

If you run a Shopify store, you likely start your day the same way: logging in, navigating to Analytics, downloading a CSV, opening it in Excel, and doing mental math to figure out your true margin for yesterday.

This manual data pull wastes 15-20 minutes every morning. Over a year, that's nearly 3 work weeks lost to repetitive data entry.

What you actually want is a simple email in your inbox at 8:00 AM every morning:
"Yesterday's Gross Sales: $4,200 | Net Profit: $1,100 | Top Product: Blue Hoodie."

In this guide, we'll write a Python script to do exactly that, and deploy it on LiteLambda so it runs automatically every morning—without you having to configure a server, setup AWS Lambda, or keep your laptop open.

Step 1: Getting your Shopify API Keys

To pull your store's data securely, you need a Custom App token:
1. Go to your Shopify Admin Dashboard.
2. Navigate to Settings > Apps and sales channels > Develop apps.
3. Click Create an app and name it "Daily Reporter".
4. Under Configuration > Admin API integration, grant read_orders and read_products permissions.
5. Click Install app and copy your Admin API access token.

Step 2: The Python Script

We'll use Python and the requests library to fetch the data. This script grabs orders from the past 24 hours, sums up the totals, and uses a free email service to send you a report.

import os
import requests
import datetime

def handler(event, context):
    """
    LiteLambda automated handler for Shopify Reporting
    """
    SHOPIFY_STORE = os.environ.get('SHOPIFY_STORE_NAME') # e.g., 'my-cool-store'
    SHOPIFY_TOKEN = os.environ.get('SHOPIFY_API_TOKEN')

    # Calculate timestamps for the last 24 hours
    now = datetime.datetime.utcnow()
    yesterday = now - datetime.timedelta(days=1)

    url = f"https://{SHOPIFY_STORE}.myshopify.com/admin/api/2024-01/orders.json"

    headers = {
        "X-Shopify-Access-Token": SHOPIFY_TOKEN,
        "Content-Type": "application/json"
    }

    params = {
        "status": "any",
        "created_at_min": yesterday.isoformat(),
        "created_at_max": now.isoformat()
    }

    print("Fetching recent orders...")
    response = requests.get(url, headers=headers, params=params)
    response.raise_for_status()

    orders = response.json().get('orders', [])

    total_sales = 0.0
    for order in orders:
        total_sales += float(order.get('total_price', 0))

    report = f"Daily Report: You had {len(orders)} orders in the last 24h, totaling ${total_sales:.2f}."
    print(report)

    # Optional: Send this report via Telegram, Email, or Slack
    # send_to_slack(report)

    return {
        "status": "success",
        "total_orders": len(orders),
        "total_sales": total_sales
    }

Step 3: Automating it forever

Running this script locally works, but you have to remember to run it. Instead, deploy it instantly on LiteLambda:

1. Log into your LiteLambda Dashboard.
2. Create a new Cron Job and paste the code above.
3. In the Packages box, type requests.
4. In the Environment Variables box, paste your SHOPIFY_API_TOKEN and SHOPIFY_STORE_NAME.
5. Set the CRON schedule to 0 8 * * * (8:00 AM daily).
6. Click Save & Run Manually to test.

That's it. No servers to provision, no Dockerfiles to write, and no complex AWS IAM roles to manage. You now have an enterprise-grade reporting pipeline running for less than a cup of coffee a month.

[!TIP]
Want to extend this? You can easily connect the OpenAI or Anthropic API to have an LLM write a summary of the sales trends before emailing it to you.