Usage Guides

Common Workflows

L0 to Focused Product

sarpyx unzip --input /data/raw.zip --output /data/extracted
sarpyx decode --input /data/extracted/S1A_*.SAFE --output /data/decoded
sarpyx focus --input /data/decoded/product.zarr --output /data/focused

Mission Pipeline and Tiling

sarpyx worldsar   --input /data/product.SAFE   --output /data/preprocessed   --cuts-outdir /data/tiles   --grid-path /data/grid/grid_10km.geojson

Advanced Usage

  • Use --gpt-memory, --gpt-parallelism, and --gpt-timeout to tune SNAP runtime.
  • Use ProductHandler and ZarrManager APIs for selective slicing and export.
  • Use mission-specific worldsar pipelines for Sentinel, TerraSAR-X, COSMO, BIOMASS, and NISAR paths (inferred from implementation).

Integration Patterns

  • Pipeline orchestration through shell scripts or workflow managers invoking CLI commands.
  • Python-first integration importing processing modules directly for notebook or service use.
  • Containerized integration via docker compose for reproducible environments.

Performance Considerations

  • Enable slicing for large products to reduce memory pressure during focusing.
  • Prefer Zarr chunking defaults unless profiling shows bottlenecks.
  • Adjust GPT heap and worker count based on available host memory.
  • Use parallel tile extraction settings conservatively to avoid I/O saturation.