Rashid Ali
RASHID ALI
RashidBuilds
PDFDex
ROLECreator & Full-Stack Engineer
SERVICES / AREAS
Document ProcessingAWS S3 InfrastructureNode.js StreamsPython Microservices

PDFDex

© 2024
(Scroll down)
(Overview)

An independent web application hosting a collection of approximately 25 PDF utilities designed for fast, frictionless document manipulation directly in the browser.

Built with a hybrid processing architecture: lightweight document tasks are handled with Node.js streams, while compute-heavy conversions and page operations are dispatched to Python workers with AWS S3 storage.

Next.jsNode.jsExpress.jsPythonAWS S3Docker
Sections

Project Overview

PDFDex was built to provide an ad-free, intuitive web destination for everyday PDF tasks. Rather than relying on heavyweight desktop software or ad-bloated converters, users can drag and drop documents to merge, split, rotate, convert, or compress files with clean visual previews.

Project Overview
Fig 01 // Multi-Tool Document Manipulation Workspace

Document Utilities & Features

The platform encompasses approximately 25 distinct utilities categorized across document organization, conversion, optimization, and security.

KEY HIGHLIGHTS & SPECIFICATIONS
  • Document organization: Merge multiple PDFs, split files by page ranges, reorder pages visually, and rotate orientations.
  • Format conversions: PDF to image extraction, image to PDF compilation, and document text extraction.
  • Optimization tools: File size compression with selectable quality profiles and metadata stripping.
  • Document adjustments: Watermark application, page number insertion, and document unlocking workflows.

Hybrid Processing Architecture

Different PDF operations have widely varying CPU and memory profiles. A hybrid backend architecture ensures that simple operations remain near-instantaneous while resource-intensive jobs run without affecting platform responsiveness.

KEY HIGHLIGHTS & SPECIFICATIONS
  • Node.js stream processing: High-speed page rearrangement, splitting, and metadata reads execute via lightweight Node.js buffers.
  • Python processing workers: Complex document conversions, compression algorithms, and image extraction run through specialized Python libraries.
  • AWS S3 file lifecycle: Uploaded assets are held in private S3 buckets with automated lifecycle expiration rules that delete processed files after download.
Hybrid Processing Architecture
Fig 02 // Hybrid Processing and AWS S3 File Lifecycle

Technical Implementation

I architected the platform end-to-end, writing the Next.js frontend, configuring Docker containers for the processing backends, and tuning AWS S3 pre-signed upload URLs for reliable large-file transfers.

DELIVERABLES & TECHNICAL METRICS
Tools Suite

~25 Tools

Storage Layer

AWS S3

Architecture

Node + Python

File Cleanup

Automated Lifecycle

Suite of ~25 Focused Browser PDF Tools
Node.js Buffer & Stream Processing Engine
Python Document Manipulation Microservices
AWS S3 Storage Lifecycle & Pre-Signed URLs

READY TO MOVE SMARTER?

We are here to help you grow without hassle.
No call centres. No runaround. Just experienced people ready to help.