opensemantic.base 0.42.7.post1000002003002

Library with Python models derived from the page package world.opensemantic.base

opensemantic.base

Python models and controllers for the world.opensemantic.base page package.

Builds on oold-python (BaseController, LinkedBaseModel, cast(), _types registry) and opensemantic (OswBaseModel, compute_scoped_uuid).

Overview

• Auto-generated Pydantic models (v1 and v2): Database, WebService, DataTool, DataChannel, Person, Organization, etc.
• DataToolController - generic controller for any DataTool
• TimeSeriesDatabaseController - SQLite and PostgREST backends for time series storage

Architecture

opensemantic.base/
  _model.py            # auto-generated v2 Pydantic models (DO NOT EDIT)
  _controller_mixin.py # DataToolMixin, TimeSeriesDatabaseController mixins
  _controller.py       # v2 controllers
  __init__.py           # re-exports model + controller classes
  v1/                   # same structure for Pydantic v1

DataToolController

Extends DataTool with channel management, subdevice traversal, and data archiving.

from opensemantic.base import DataToolController

tool = DataToolController(
    name="sensor",
    label=[...],
    data_channels=[ch1, ch2],
    storage_locations=[db],
    auto_archive=True,  # auto-creates archive DB from storage_locations[0]
)

tool.get_all_channels()       # recursive across subdevices
tool.get_channel_owner(ch)    # find which device owns a channel
tool.to_json()                # only model fields (controller fields stripped)

Auto-archive from storage_locations

When auto_archive=True and no explicit archive_database is set, the controller auto-creates a LocalTimeSeriesDatabaseController from the first storage_locations entry (resolved via oold backend).

Typed read/write

Channels with a characteristic IRI enable typed serialization:

# Write: converts to base unit, strips defaults for compact storage
await tool.store_typed_data(DataToolMixin.StoreTypedDataParams(
    tool_osw_id=tool.get_osw_id(),
    rows=[DataToolMixin.TypedDataRow(ts=now, channel=ch, value=Temperature(value=300.0))],
))

# Read: resolves characteristic class via oold's _types registry
results = await tool.read_typed_data(DataToolMixin.ReadTypedDataParams(
    tool_osw_id=tool.get_osw_id(), channel=ch,
))
# results[0] is a Temperature instance with defaults restored

Subobject ID auto-computation

Inline subobject osw_id fields are auto-prefixed with the parent's osw_id:

Parent:  OSW<parent_uuid>
Channel: OSW<parent_uuid>#OSW<channel_uuid>

Fields with range in json_schema_extra are references to separate entities and are not prefixed.

Unloaded characteristic warning

On init, DataToolController checks if channel characteristic IRIs are present in oold's _types registry. Missing entries produce a warning with guidance to import the corresponding package.

TimeSeriesDatabaseController

Abstract base for time series storage, with SQLite and PostgREST implementations.

from opensemantic.base import LocalTimeSeriesDatabaseController

db = LocalTimeSeriesDatabaseController(name="archive", label=[...], db_path="./data.sqlite")
await db.create_tool(params)
await db.write_tool_channel_raw(params)
await db.read_tool_channel_raw(params)

Installation

pip install opensemantic.base            # models only
pip install opensemantic.base[controller] # + aiosqlite, postgrest

Testing

pytest tests/test_controller.py

PostgREST integration tests require a running pgstack instance. To enable them:

1. Start pgstack: docker compose -f docker-compose.yml -f docker-compose.example-tsdb.override.yml up -d
2. Copy tests/.env.example to tests/.env and fill in TEST_PGRST_URL and TEST_PGRST_JWT_SECRET
3. Run tests - PostgREST tests are skipped unless both env vars are set