fricon
Data collection automation framework.
Documentation
For implementation guidance, maintainer checklists, and AI-agent starting points, see dev-docs/README.md.
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 on supported wheel platforms:
pip install fricon
Current PyPI builds may not cover every platform. If pip install fricon
cannot find a compatible wheel for your system, build from source.
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 buffered automatically
# Current scalar writes support float, int-as-float, and complex values
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.
Release files for fricon 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fricon-0.1.4.tar.gz | 1.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fricon-0.1.4-cp310-abi3-win_amd64.whl | CPython 3.10 | abi3 | Windows x86-64 | Details |
Total release size: 11.3 MB
Release files / fricon-0.1.4.tar.gz
| Download URL | fricon-0.1.4.tar.gz |
|---|---|
| Size | 1.2 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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Yes |
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Transparency logRelease files / fricon-0.1.4-cp310-abi3-win_amd64.whl
| Download URL | fricon-0.1.4-cp310-abi3-win_amd64.whl |
|---|---|
| Size | 10.2 MB |
| Tags | CPython 3.10 Windows x86-64 abi3 |
|
SHA-256 checksum How to use checksums |
8c087422a581869a905e6df30253abe3574c91cca3d9f9c3a84cb4248b73ce9d
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.13
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 5, 2026.
Transparency log