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데이터 및 연구 · SKILL.md

rasterio

rasterio

Routes Rasterio dataset I/O, windowed processing, in-memory files, raster/vector feature workflows, reprojection and mosaicking, and rio CLI tasks.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: rasterio description: "Routes Rasterio dataset I/O, windowed processing, in-memory files, raster/vector feature workflows, reprojection and mosaicking, and rio CLI tasks." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

Rasterio

Rasterio reads and writes geospatial raster data with a NumPy-friendly API and a rio command-line interface.

Start here when a user wants to open a raster, inspect metadata, crop or mask by geometry, reproject into a new CRS, merge overlapping scenes, process a raster in windows, or choose the right rio command.

Install and verify

For a local checkout, install from the repository root:

python -m pip install -e .

For a released environment, install the package directly:

python -m pip install rasterio

Rasterio 1.5.x requires Python 3.12+ and a working GDAL/PROJ-backed build or wheel. Optional extras exist for cloud access, plotting, and IPython-based inspection.

Minimal verification:

python -I -c "import rasterio; print(rasterio.__version__)"
rio --help

For a repo-independent smoke check, use scripts/check_install.py.

Read references/repo-provenance.md when you need to confirm whether this skill still matches the current checkout.

How to route a user request

If a request spans several topics, pick the most specific sub-skill first and then follow the cross-links inside that sub-skill.

Runtime map

dataset-io-profiles

Use this for ordinary raster inspection and creation tasks:

  • rasterio.open
  • DatasetReader / DatasetWriter
  • profile / meta
  • dtypes, nodata, compression, band count, dimensions, and simple round trips

windows-memory-vsi

Use this for data that should be processed in chunks, kept in memory, or opened through archive/path abstractions:

  • Window
  • block_windows
  • MemoryFile
  • ZipMemoryFile
  • zip:// / file:// / GDAL VSI path handling

features-masks

Use this for geometry-driven raster/vector conversion and mask cleanup:

  • shapes
  • rasterize
  • sieve
  • geometry_window
  • mask / raster_geometry_mask
  • GDAL valid masks vs NumPy masked arrays

reprojection-merge-vrt

Use this for CRS changes and mosaics:

  • transform / transform_geom / transform_bounds
  • calculate_default_transform
  • reproject
  • WarpedVRT
  • merge / stack

rio-cli

Use this for shell workflows:

  • rio info, bounds, transform, clip, warp, mask, rasterize, shapes, merge, stack, create, convert, env, and insp

Shared references and tools

Common prerequisites

  • Python 3.12 or newer.
  • GDAL/PROJ available through a wheel, conda environment, or equivalent local installation.
  • Optional extras only when needed:
    • rasterio[s3] for cloud/object storage access.
    • rasterio[plot] for plotting helpers.
    • rasterio[ipython] for rio insp --ipython.

What not to do

  • Do not tell users to run or read examples/, tests/, or docs/ in the original checkout at runtime.
  • Do not claim GPU-specific capability for the selected workflows; the package paths here are CPU/GDAL based.
  • Do not rely on the current repository path remaining available after this skill is imported.
  • Do not duplicate full API tables in this file; use the nearest reference file instead.

Refresh signal

If the repo commit, public package version, or CLI/API surface changes, refresh this skill before relying on it.

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