HASTE Core Library (hastegeo)

HASTE Core Library (hastegeo)#

The hastegeo package is the shared Python library used by all HASTE API services. It provides data models, storage backends, processing pipelines, and utilities for geospatial machine learning workflows.

Package Structure#

hastegeo/
├── core/
│   ├── config.py              — Environment-aware configuration
│   ├── artifact_storage/      — Artifact storage abstraction
│   │   ├── abstract_artifact_storage.py
│   │   ├── azure_blob_artifact_storage.py
│   │   ├── local_file_system_artifact_storage.py
│   │   └── unified_artifact_storage.py
│   ├── data_layer/            — Multi-backend data storage
│   │   ├── abstract_data_layer.py
│   │   ├── azure_blob_storage_data_layer.py
│   │   ├── azure_cosmos_db_data_layer.py
│   │   ├── azure_data_lake_data_layer.py
│   │   ├── azure_postgresql_data_layer.py
│   │   ├── local_file_system_data_layer.py
│   │   └── unified.py
│   ├── models/                — Pydantic data models
│   │   ├── admin.py
│   │   ├── projects.py
│   │   ├── stats.py
│   │   ├── training.py
│   │   ├── uploader.py
│   │   ├── users.py
│   │   └── visualizer.py
│   ├── processors/            — Business logic processors
│   │   ├── artifacts.py
│   │   ├── imagery.py
│   │   ├── inference.py
│   │   ├── labels.py
│   │   ├── metadata.py
│   │   ├── stats.py
│   │   ├── train.py
│   │   └── uploader.py
│   ├── runners/               — Task execution backends
│   │   ├── base.py
│   │   ├── azure_batch.py
│   │   ├── local.py
│   │   └── unified_runner.py
│   └── utils/                 — Shared utilities
│       ├── artifacts.py
│       ├── data.py
│       ├── downloader.py
│       ├── exceptions.py
│       ├── imagery.py
│       ├── logs.py
│       ├── metadata.py
│       ├── queues.py
│       ├── tbparser.py
│       └── user.py
└── workflows/                 — CLI workflow entry points
    ├── prepare_imagery.py
    └── zip_artifacts.py

Installation#

The package is installed as an editable dependency from the repository root:

pip install -e hastelib/

Or via the conda environment:

conda env create -f env.yml
conda activate haste_env
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