Backend API Extraction & Automation
Overview
Automated data retrieval from client websites by reverse-engineering their backend APIs. Network traffic was monitored to identify endpoints, then custom Python scripts were built to fetch, clean, and process the responses. Outcome: Provided the client with continuous, reliable data extraction integrated directly into their backend workflows.
Architecture & Pipeline
flowchart LR
n0["Network Traffic MonitorInspect site calls"]
n1["Identify APIs3 private endpoints"]
n2["Custom Python ClientRequests · Selenium"]
n3["Parse + CleanStructured output"]
n4["Ready-to-Use DataBackend integration"]
n0 --> n1
n1 --> n2
n2 --> n3
n3 --> n4
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classDef step1 fill:#ecfeff,stroke:#06b6d4,color:#1e293b,stroke-width:2px,rx:10,ry:10;
classDef step2 fill:#f0fdfa,stroke:#0d9488,color:#1e293b,stroke-width:2px,rx:10,ry:10;
classDef step3 fill:#ecfdf5,stroke:#10b981,color:#1e293b,stroke-width:2px,rx:10,ry:10;
classDef step4 fill:#fffbeb,stroke:#f59e0b,color:#1e293b,stroke-width:2px,rx:10,ry:10;
class n0 step0;
class n1 step1;
class n2 step2;
class n3 step3;
class n4 step4;
End-to-end flow derived from this project's scope and tech stack. Tap View Fullscreen for a larger view, or scroll horizontally on small screens.
Key Features
- Three private APIs identified through traffic monitoring
- Custom Python scripts for requests, parsing, and cleanup
- Web scraping and data processing across multiple sources
- Reliable, ready-to-consume output for client applications
- Tech Stack:** Python, Requests, Selenium