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PROJECT NOTES / BACKEND & SYSTEMS

DocuFlow

Unstructured web pages, organized into useful data.

A distributed crawling and content-processing project that extracts page-level information, stores structured documents, and exposes search and retrieval APIs.

PythonFastAPIMongoDBDocker
BACKEND & SYSTEMS↗
01Crawl
02Extract
03Clean + deduplicate
04MongoDB
SYSTEM ARCHITECTURE
01 / THE CHALLENGE

The problem

Website content is easy to browse but difficult to reuse systematically. Repeat crawls also need to distinguish changes from duplicate work.

02 / THE APPROACH

How it comes together

Crawling, extraction, cleanup, and storage are separated into a pipeline. Each page becomes a structured MongoDB document with content, links, and metadata that the API can retrieve.

03 / UNDER THE HOOD

Follow the flow.

SIMPLIFIED ARCHITECTURE
01Crawl
02Extract
03Clean + deduplicate
04MongoDB
05Search API
04 / BUILD HIGHLIGHTS

Page-level extraction of text, images, links, and metadata.

Incremental updates and deduplication.

Distributed processing and containerized services.

FastAPI interfaces for search, retrieval, and analytics.

THE ENGINEERING CHOICE

Why this approach?

Store content at page granularity with a consistent schema, preserving the relationship between source URLs and extracted material.

Explore the project’s supporting sources.Project repository
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Vijayshree Vaibhav
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