LinkedIn Analyzer

Clean and analyze your LinkedIn data exports.
_{Web app or Python CLI. File contents stay local in the web app; optional diagnostics are opt-in.}

What it does

LinkedIn's data exports are messy. This tool fixes that.

• Shares.csv has weird nested quote escaping
• Comments.csv has backslash-escaped quotes
• messages.csv has mixed participant/profile fields that need normalization
• Connections.csv often includes preamble rows and noisy identity fields

Upload your files, get clean Excel outputs. Plus analytics dashboards, relationship views from messages/connections, and rule-based insights.

Quick start

Development: Install locked Python and Node dependencies:

# Requires Python 3.11+, uv, and Node.js 22.13.x or 24+
make setup

Web: Run the Vite dev server and open the local URL:

cp .env.example .env  # optional; set VITE_SENTRY_DSN + VITE_APP_RELEASE for opt-in diagnostics
make web

CLI: For automation:

pip install linkedin-analyzer
linkedin-analyzer shares
linkedin-analyzer comments
linkedin-analyzer messages
linkedin-analyzer connections
linkedin-analyzer all

Container: Run the published CLI image:

docker run --rm -v "$PWD/data:/app/data" ghcr.io/hermione-granger-1176/linkedin-analyzer:latest --version

Tech stack

Web app

Python CLI

Dev & CI

Features

Documentation

See the docs/ folder for:

• Web App Guide
• Python CLI Reference
• Development Setup
• Project Structure
• Style Guide
• Operations and Deployment

Architecture Decision Records: docs/adr/

Contributor guide: .github/CONTRIBUTING.md

Changelog (Python package): CHANGELOG.md

Security reporting guidelines: .github/SECURITY.md

License

MIT

_{Created by Aditya Kumar Darak}