Xarray-binfile#
Read and write raw binary files using the familiar interface from the Xarray library.
Xarray-binfile provides an xarray backend for raw binary files that are not self-describing on their own. You supply the metadata needed to interpret each file, and xarray-binfile handles lazy loading, chunked parallel computation with Dask, and writing results back to raw binary when you need to interoperate with an existing file layout.
About The Backend
Learn how xarray-binfile maps raw binary files into labeled xarray datasets and data arrays.
Install And Configure
Install the package, understand the runtime dependencies, and get ready to open binary datasets lazily.
Read Lazily With Dask
Open binary files with chunking, inspect the Dask graph, and compute only the results you need.
Write Derived Results
Take a computed xarray result and write it back to raw binary files when you need to match an external format.
Parallel And Out-Of-Core
Open files in parallel, pick a Dask scheduler, and process datasets larger than memory by streaming chunks.
Benchmark Your Data
Measure read and compute performance on your own files, and see how results shift with dtype, dimension size, and hardware.
Practical Examples
Batch-convert dtypes across files, extract a probe time series to CSV, and draw quick matplotlib plots.
API Reference
See the public modules, metadata protocols, backend entrypoint, and tutorial helpers.
Further Reading
Go deeper on xarray, Dask, NumPy binary I/O, and related simulation workflows.
Important
Raw binary files usually need external metadata such as shape, coordinate values, dtype, and filename conventions. Xarray-binfile does not try to infer that information magically. Instead, it asks you to provide it explicitly so the backend can remain predictable and interoperable.
Warning
Raw binary data is machine-specific unless you control the full convention explicitly. Byte order differences (little-endian vs big-endian), numeric representation, and layout assumptions may break portability across architectures. Validate dtype and endianness before using files generated on another machine.
Note
For portable archival or data exchange workflows, prefer standard xarray-supported formats such as NetCDF or Zarr. Raw binary output is most useful when you need to read or write an existing binary convention used by a simulation code or downstream tool.