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Codebase Map#

This page summarizes the main modules, key classes, and the public API surface of the pyramids package.

Packages and Modules#

  • pyramids.abstract_dataset
  • Abstract base class that defines the core dataset interface (read, write, metadata, windowing, reprojection scaffolding).
  • pyramids.dataset
  • Concrete raster dataset implementation with rich I/O, transformations, tiling, pyramid operations, and export utilities.
  • pyramids.datacube
  • Temporal/spatial multi-band or multi-file orchestration (data cube), aggregations, slicing, alignment.
  • pyramids.featurecollection
  • Vector data abstraction for feature collections built on GeoPandas; read/write, selection, join, spatial ops.
  • pyramids._io
  • Internal helpers for reading/serializing data and archives (zip/gzip/tar parsing, ASCII export), and file path parsing.
  • pyramids._utils
  • Utility functions (array ops, geometry helpers, indexing helpers) used across datasets and cubes.
  • pyramids._errors
  • Error/exception types used across the package.

Key Public Classes#

  • pyramids.dataset.Dataset
  • pyramids.datacube.Datacube
  • pyramids.featurecollection.FeatureCollection

Representative Public Methods#

  • Dataset
  • read_file(path, read_only=True, file_i=0)
  • to_file(path, band=0, tile_length=None)
  • read(...), write(...), crop/align/stack helpers (see API Reference)
  • Datacube
  • constructors/helpers to build from folders, patterns, and indexing; slicing and aggregation (see API Reference)
  • FeatureCollection
  • read_file(path), to_file(path, driver="geojson"), selection/clip/buffer (see API Reference)

Data Flow (High Level)#

  • External data (GeoTIFF/ASC/NetCDF/Vector) -> _io parsers -> Dataset/FeatureCollection objects
  • Datasets -> combined via Datacube for temporal/spatial operations
  • Outputs -> Dataset/FeatureCollection to_file(), ASCII/GeoTIFF/GeoJSON exports

See the Architecture section for diagrams and deeper internals, and the API Reference for exhaustive signatures.

Class & Dependency Graph#

Below is a high-level Mermaid class dependency diagram showing the main modules and their primary classes, plus key dependencies between them.

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classDiagram
  class AbstractDataset {
    <<abstract>>
    +read_file(path, read_only)
    +to_file(path, band)
  }
  class Dataset {
    +read_file(path, read_only, file_i)
    +to_file(path, band, tile_length)
    +read()
  }
  class Datacube {
    +read_multiple_files(...)
    +open_datacube(...)
    +to_file(...)
  }
  class FeatureCollection {
    +read_file(path)
    +to_file(path, driver)
  }
  class IO {
    <<module>>
  }
  class Utils {
    <<module>>
  }

  AbstractDataset <|-- Dataset
  Datacube ..> Dataset : uses
  FeatureCollection ..> IO : uses
  Dataset ..> IO : uses
  Dataset ..> Utils : uses
  FeatureCollection ..> Utils : uses

Notes: - Module nodes like _io and _utils represent internal helper modules used by multiple classes. - Method lists are illustrative; see the API Reference for complete signatures.