⚙️ Installation¶
This page explains how to install node-fdm, configure optional dependencies, and set up the directory structure required for the data pipelines.
🧩 Prerequisites¶
Before installing, ensure your environment meets the following requirements:
- Python 3.11+
- OpenSky Trino access (Required only if you plan to run the full OpenSky 2025 data collection pipeline).
BADA 4.2 Model Files
Support for the BADA 4.2 physical model is optional but recommended for benchmarking.
- You must obtain the model files separately (due to licensing).
- You will need to set their location in the relevant
config.yamllater.
📦 Install the Package¶
Choose the installation method that matches your needs.
Recommended for running existing pipelines and training models.
1. Core Installation Install the core library:
2. Optional Dependencies (Recommended) To install support for traffic data processing, fast meteorology, and visualization:
3. BADA Baseline Support (Optional)
The pybada wrapper has restrictive dependencies. Use these specific commands to force installation:
Recommended if you plan to modify the code or create custom architectures.
1. Clone the repository
git clone [https://github.com/eurocontrol-asu/node-fdm.git](https://github.com/eurocontrol-asu/node-fdm.git)
cd node-fdm
2. Editable Installation Install the package in editable mode along with all development dependencies:
📁 Configuration & Directories¶
node-fdm relies on configuration files to locate data and artifacts. You must configure these paths before running a pipeline.
Where to configure
Edit the configuration file specific to your target pipeline:
- 📂 OpenSky:
scripts/opensky/config.yaml - 📂 QAR:
scripts/qar/config.yaml
| Parameter | Description | Requirement |
|---|---|---|
paths.data_dir |
The root directory for all data artifacts. | Required |
paths.era5_cache_dir |
Local cache directory for meteorological fields. | Required |
bada.bada_4_2_dir |
Path to the folder containing BADA 4.2 files. | Optional |
paths.download_dir |
Destination for raw downloaded data. | Auto-managed |
paths.models_dir |
Directory where trained models are saved. | Auto-managed |
✔️ Verification¶
Run this quick check to verify that node_fdm and torch are correctly installed and importable.
import torch
import node_fdm
import sys
print(f"Python version: {sys.version.split()[0]}")
print(f"Torch version: {torch.__version__}")
print("✅ node_fdm import successful")
Next Step
Once installation is verified, head to the Core Concepts to understand how node-fdm works.