Automated Catalog Update & Reporting Pipeline

Google IT Automation with Python final project implementing an end-to-end automation workflow for maintaining an online product catalog. The solution standardizes supplier images, uploads media assets, posts structured catalog data to a web endpoint, generates a PDF summary report, emails the report automatically, and monitors system health with alerting.

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Project Scope

• Image processing: Convert supplier images from TIFF to standardized JPEG format (600×400).
• Media upload: Upload processed images to a web service.
• Catalog updates: Parse product description files and POST structured JSON records to a catalog API endpoint.
• Reporting: Generate a PDF report summarizing catalog items.
• Email automation: Send the report via email as an attachment.
• Monitoring: Check system health (CPU, memory, disk, hostname resolution) and email alerts when thresholds are exceeded.

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Tech Stack

• Python
• Pillow (image processing)
• Requests (HTTP client)
• ReportLab (PDF generation)
• SMTP email automation
• psutil (system monitoring)

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Repository Contents

• src/changeImage.py
  Converts .tiff images to .jpeg, resizes to 600×400, and standardizes output format.

• src/supplier_image_upload.py
  Uploads processed .jpeg files to the server upload endpoint via HTTP requests.

• src/run.py
  Reads product description files, extracts product attributes (including weight parsing), and POSTs JSON payloads to the catalog endpoint.

• src/reports.py
  Builds a PDF report (ReportLab) summarizing items for the daily/periodic report.

• src/report_email.py
  Generates the PDF report and sends it via email as an attachment.

• src/emails.py
  Shared email helper utilities for composing and sending messages.

• src/health_check.py
  Performs system health checks using threshold logic (CPU, disk, memory, DNS/hostname) and sends alert emails when issues are detected.

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Key Skills Demonstrated

• Python automation and scripting
• REST API interactions (POST, file upload)
• Image processing pipelines:
• Structured data extraction and transformation
• Automated reporting (PDF generation)

Highlights / Impact

• Designed an end-to-end automation pipeline integrating image processing, API communication, reporting, and monitoring into a single workflow.
• Reduced manual catalog maintenance by automating data ingestion, media handling, and structured JSON submissions.
• Improved operational reliability by implementing proactive system health checks with automated email alerts.
• Demonstrated practical DevOps-oriented automation skills including file transformation, REST integration, and monitoring logic.
• Email automation (SMTP)
• Basic monitoring/alerting and reliability checks