Folder enumeration filtering

.github/copilot-instructions.md

@@ -0,0 +1,80 @@
+# Project Guidelines — Planetary Computer Tasks (pctasks)
+
+## Architecture
+
+Monorepo of 12 Python namespace packages under `pctasks/`, each independently installable via `hatchling`. Dependency order: `core → cli → task → client → ingest → ingest_task → dataset → run → notify → router → server → dev`. Additional code in `pctasks_funcs/` (Azure Functions), `datasets/` (~60 dataset definitions), and `deployment/` (Terraform/Helm).
+
+**Core data flow**: blob storage assets → splits (by prefix) → chunks (file listing CSVs) → `Collection.create_item()` produces pystac Items → ingest into PgSTAC via pypgstac.
+
+Key abstractions:
+- **`PCBaseModel`** (`pctasks/core/pctasks/core/models/base.py`): Pydantic v2 base with YAML serde, `by_alias=True`, `exclude_none=True`.
+- **`Task[T, U]`** (`pctasks/task/pctasks/task/task.py`): Generic abstract task, define `_input_model`/`_output_model` and `run(input, context)`.
+- **`Collection`** (`pctasks/dataset/pctasks/dataset/collection.py`): Abstract base for datasets; implement `create_item(cls, asset_uri, storage_factory) -> List[pystac.Item] | WaitTaskResult` as a classmethod.
+- **`StorageFactory`**: Creates `Storage` objects from `blob://<account>/<container>/<path>` URIs.
+- **Settings**: `pydantic-settings` with double-underscore env vars (`PCTASKS__COSMOSDB__URL`, `PCTASKS_RUN__TASK_RUNNER_TYPE`).
+
+## Code Style
+
+- **Formatter**: black (default settings) + isort. Run `scripts/format`.
+- **Linter**: flake8 with `max-line-length = 120`, ignores `E203, W503, E731, E722` (see `.flake8`).
+- **Type checking**: mypy with `disallow_untyped_defs = True` — all functions must have type annotations (see `mypy.ini`).
+- **No docstrings** unless explicitly requested.
+- All models extend `PCBaseModel` (Pydantic v2). Use `model_validate`, `model_dump`, `field_validator`, `model_validator`.
+
+## Build and Test
+
+```bash
+scripts/install              # Create venv with uv, install all packages in editable mode
+scripts/server               # Start local dev stack (Azurite, PgSTAC, server, STAC API)
+scripts/test                 # Full lint + test suite (runs in Docker via docker-compose.console.yml)
+scripts/test --subpackage core   # Test one package
+scripts/test --test-only     # Skip lint
+scripts/test --lint-only     # Skip tests
+scripts/format               # Auto-format all packages (black + isort)
+```
+
+Per-package test commands (from within `pctasks/<pkg>/`):
+```bash
+pytest tests/                        # Run package tests
+mypy --config-file ../../mypy.ini pctasks   # Type-check
+```
+
+## Project Conventions
+
+### Dataset directory pattern (`datasets/<name>/`)
+```
+dataset.yaml            # Required: dataset definition (id, image, collections, asset_storage, chunks)
+<name>.py               # Required: Collection subclass with create_item classmethod
+collection/template.json  # STAC collection Jinja2 template
+test_<name>.py          # Tests: import collection class, call create_item with blob URIs
+requirements.txt        # Optional: extra pip deps
+Dockerfile              # Optional: custom image (otherwise uses pctasks-task-base)
+```
+
+Dataset YAML references code via `${{ local.path(./<file>.py) }}` and class via `<module>:<ClassName>` (no `.py`).
+
+### Templating syntax in YAML
+- `${{ args.<name> }}` — CLI arguments
+- `${{ secrets.<key> }}` — KeyVault/dev-secrets.yaml
+- `${{ local.path(<relative>) }}` — Path relative to YAML file
+- `${{ local.file(<relative>) }}` — Inline file contents
+
+### CLI
+Click-based with plugin discovery via `pctasks.commands` entry point group. Each package registers subcommands in its `pyproject.toml`.
+
+### Testing patterns
+- pytest with `asyncio_mode = auto` (see `pytest.ini`)
+- Dataset tests are co-located: `datasets/<name>/test_<name>.py`
+- Package tests: `pctasks/<pkg>/tests/`
+- Integration tests: `tests/`
+- Use `StorageFactory()` in tests for blob access; `SimpleWorkflowExecutor` for local workflow execution.
+
+## Integration Points
+
+- **Azure Blob Storage**: All asset URIs use `blob://<account>/<container>/<path>` scheme.
+- **Cosmos DB**: Workflow/run state persistence; emulated locally via docker-compose.
+- **PgSTAC**: STAC item storage (PostgreSQL + PostGIS), port 5499 locally.
+- **Azurite**: Local Azure Storage emulator, ports 10000-10002.
+- **Argo Workflows**: Production workflow orchestration on Kubernetes.
+- **Azure Batch**: Production task execution.
+- **Kind cluster**: Local Kubernetes for Argo testing (`scripts/cluster setup`).

datasets/ecmwf-forecast/dataset.yaml

@@ -1,8 +1,9 @@
 id: ecmwf_forecast
-image: ${{ args.registry }}/pctasks-ecmwf-forecast:2026.01.12
+image: ${{ args.registry }}/pctasks-ecmwf-forecast:2026.02.26
 
 args:
   - registry
+  - year-prefix
 
 code:
   src: ${{ local.path(./ecmwf_forecast.py) }}
@@ -17,6 +18,9 @@ collections:
     asset_storage:
       - uri: blob://ai4edataeuwest/ecmwf/
         chunks:
+          splits:
+            - depth: 1
+              folder_matches: ^${{ args.year-prefix }}
           options:
             # currently excluding "aifs", in favor of "ifs"
             # Could put that in a different collection, or modify

pctasks/dataset/pctasks/dataset/models.py

@@ -42,6 +42,7 @@ class SplitDefinition(PCBaseModel):
 
     prefix: Optional[str] = None
     depth: int
+    folder_matches: Optional[str] = None
 
 
 class ChunkOptions(PCBaseModel):

pctasks/dataset/pctasks/dataset/splits/task.py

@@ -50,6 +50,7 @@ def run(
                         max_depth=split_config.depth,
                         min_depth=split_config.depth,
                         name_starts_with=split_prefix,
+                        folder_matches=split_config.folder_matches,
                     ):
                         print(".", end="", flush=True)
                         # Avoid walking through the same prefix twice