Digital Human Project — Echo

Echo turns your personal platform exports into a private, self-hosted dashboard about your own digital habits. It reads the raw JSON you download from Instagram, Threads, Chrome, and YouTube, aggregates it locally, and renders a small static website — your most-liked accounts, most-visited domains, peak browsing/watching hours, and search & watch trends over time.

Everything runs 100% locally. No data leaves your machine, and no personal data is stored in this repository.

Screens

• Dashboard — a summary across all sources.
• Instagram — accounts you like most + advertisers targeting you.
• Threads — accounts you like most.
• Chrome — most-visited domains, most-frequent page titles, peak hour.
• YouTube — top searches & channels, peak hours, monthly/yearly trends.

The charts and tables ship with placeholder sample data so the site renders out of the box. Running the pipeline replaces them with your own results locally.

Requirements

• Python 3.9+ (standard library only — no pip install needed)
• A modern web browser

Getting started

1. Clone the repo

   git clone https://github.com/nemexxx/Digital-Human-Project.git
   cd Digital-Human-Project

2. Add your export data. Download your data from each platform and place the JSON files under data/ following the structure described in data/README.md. This folder is git-ignored, so your data stays local.

3. Run the pipeline from the project root:

   python master.py

   This runs every analysis, injects the results into the HTML templates in website/, and opens the dashboard in your browser.

   Prefer a different data location? Point the pipeline at it:

   DHP_DATA_DIR=/path/to/your/exports python master.py

You can also run any single analysis module on its own to print results to the terminal, e.g.:

python -m data_analysis.chrome_history

Project structure

.
├── master.py                 # Orchestrates all analyses and updates the website
├── data_analysis/            # One module per data source
│   ├── config.py             # Resolves the data directory (DHP_DATA_DIR)
│   ├── instagram_likes.py
│   ├── threads_likes.py
│   ├── instagram_advertisers.py
│   ├── chrome_history.py
│   └── youtube_history.py
├── website/                  # Static dashboard (HTML/CSS/JS + Chart.js)
├── data/                     # Your local exports (git-ignored)
└── README.md

How it works

Each module in data_analysis/ reads one export file and returns aggregated counts. master.py formats those into HTML table rows and injects them between named <!-- marker --> / <!-- End of marker --> comments in the pages under website/, so re-running the pipeline simply refreshes the numbers.

Privacy

• Your raw exports live under data/, which is excluded from git via .gitignore.
• The committed HTML/JS contains only neutral placeholder sample data.
• Nothing is uploaded anywhere — the dashboard is a local static site.

License

Released under the MIT License.