Data collection automation framework.
Project description
fricon
Data collection automation framework.
Documentation
Overview
Fricon is a data collection automation framework designed for managing datasets in scientific and research workflows. It provides:
- Workspace Management: Organized data storage with metadata tracking
- Dataset Operations: Arrow-format data tables with UUID and incremental ID tracking
- Desktop UI: Cross-platform Tauri application with React 19 frontend
- Server Architecture: IPC-based server for workspace operations
Quick Start
Installation
For Python users (recommended):
pip install fricon
For development or building from source:
Building from source requires several dependencies including Rust, protoc, uv, pnpm, and platform-specific libraries. See CONTRIBUTING.md for complete setup instructions.
git clone https://github.com/kahojyun/fricon.git
cd fricon
python3 scripts/setup-dev.py
Basic Usage
Create a workspace:
fricon init path/to/workspace
Launch the desktop UI:
fricon gui path/to/workspace
Or connect from Python to a workspace with a running server:
from pathlib import Path
from fricon import Workspace
workspace_path = Path("path/to/workspace")
ws = Workspace.connect(workspace_path)
# Initialize a new dataset (schema is automatically inferred)
writer = ws.dataset_manager.create("my_dataset", description="My test dataset")
# Write data - schema is inferred from the first row
# Writes are micro-batched automatically every second or when 16 rows accumulate
# MVP currently supports float and complex types only
writer.write(id=1, value=42.0, measurement=3.14 + 2j)
writer.write(id=2, value=84.0, measurement=1.618 - 1j)
writer.close()
# List all datasets
datasets = ws.dataset_manager.list_all()
print(datasets)
Contributing
We welcome contributions! Please see CONTRIBUTING.md for detailed guidelines on development environment setup, building components, testing, and contribution workflow.
License
fricon is distributed under the terms of the
MIT OR
Apache-2.0 license.
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