Comparative Framework Database Search

This project provides an interactive scaling analysis for proteomics database search strategies. It uses marimo to create a notebook-style web app for exploring how hardware performance and search parameters affect estimated runtimes and memory requirements.

Features

• Interactive sliders and input boxes for hardware and search parameters
• Visualizations of asymptotic scaling, memory overhead, and runtime heatmaps
• Figures update automatically as parameters change

Requirements

• Python 3.12 or newer (see .python-version)
• marimo >= 0.15.5
• matplotlib >= 3.10.6
• numpy >= 2.3.3

Dependencies are listed in pyproject.toml.

Installation

1. Clone the repository:

   git clone https://github.com/instadeepai/database_search_scaling.git
   cd database_search_scaling

2. Install uv

Follow the official instructions.

3. Create and activate a Python 3.12 environment:

   uv venv --python 3.12
   source .venv/bin/activate

4. Install dependencies with uv:

   uv sync

Running the Interactive App

To launch the interactive notebook, run:

marimo run database_search_scaling.py

This will start a local web server and open the app in your browser. You can adjust parameters and view updated figures interactively.

Project Structure

• database_search_scaling.py: Main marimo app with all interactive cells and visualizations.
• pyproject.toml: Project metadata and dependencies.
• .python-version: Specifies required Python version.

License

Apache 2.0

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For more details on marimo, see the marimo documentation.