space-weather

Space weather indices and parsers for aerospace applications. no_std compatible (with alloc).

Parses space weather data from CelesTrak and SET (Space Environment Technologies), stores it in an efficient in-memory index, and supports date-based queries.

Quick Start (Rust)

use space_weather::parsers::celestrak;
use space_weather::store::SpaceWeatherStore;
use space_weather::{Date, SpaceWeatherIndex};

// Parse a CelesTrak CSV file
let bytes = std::fs::read("SW-Last5Years.csv").unwrap();
let records = celestrak::parse(&bytes).unwrap();
let store = SpaceWeatherStore::new(records);

// Query by date
let date = Date { year: 2023, month: 6, day: 15 };
if let Some(record) = store.get(date) {
    println!("F10.7 observed: {:?}", record.f10_7_obs);
    println!("Ap daily:       {:?}", record.ap_daily);
}

Quick Start (Python)

Requires the python feature (built via maturin).

from space_weather import SpaceWeather

sw = SpaceWeather.from_celestrak_csv("SW-Last5Years.csv")

from datetime import date
record = sw.get(date(2023, 6, 15))
print(record["f10_7_obs"], record["ap_daily"])

# NumPy export for bulk analysis
arrays = sw.to_numpy()
print(arrays["f10_7_obs"].mean())

Feature Flags

Flag	Description	Dependencies
std	Enables std library support (off by default for no_std)	—
fetch	Async HTTP fetching for CelesTrak and SET files	reqwest (rustls)
fetch-blocking	Blocking HTTP fetching	reqwest/blocking
python	Python bindings via PyO3	pyo3, numpy

Data Sources

Source	File	Indices
CelesTrak	SW-Last5Years.csv, SW-All.csv	F10.7 (observed/adjusted), Ap (daily + 3-hr), Kp (3-hr)
SET	SOLFSMY.TXT	F10.7 (JB2008), S10.7, M10.7, Y10.7 + 81-day averages
SET	DTCFILE.TXT	Dtc temperature correction coefficients

Use SpaceWeatherStore::merge to combine records from multiple sources into a single queryable store.

License

MIT OR Apache-2.0