Added ML Model Handling and Prophet model support (#13)

Author: dominiquekleeven

.gitignore

@@ -176,15 +176,13 @@ cython_debug/
 
 # IDE - VSCode
 .vscode/*
-!.vscode/settings.json
-!.vscode/tasks.json
-!.vscode/launch.json
-!.vscode/extensions.json
+
 
 # IDE - PyCharm (additional entries)
 *.iws
 *.iml
 *.ipr
+.idea/*
 
 # OS generated files
 .DS_Store
@@ -203,5 +201,7 @@ logs/
 *.h5
 *.model
 *.joblib
-.vscode/
-.idea/
+
+# Application specific
+deployment/data/**
+**/**/.tmp

pyproject.toml

@@ -7,15 +7,22 @@ name = "service-ml-forecast"
 version = "0.1.0"
 description = "Machine Learning Forecast Service"
 readme = "README.md"
-requires-python = ">=3.10"
+requires-python = ">=3.13"
 dependencies = [
     "fastapi>=0.115.11",
     "uvicorn>=0.34.0",
     "pyyaml>=6.0.2",
     "tomli>=2.2.1",
     "httpx>=0.28.1",
+    "apscheduler>=3.11.0",
     "pydantic>=2.10.6",
     "pydantic-settings>=2.8.1",
+    "prophet>=1.1.6",
+    "plotly>=6.0.1",
+    "pandas>=2.2.3",
+    "numpy>=2.2.4",
+    "pyzmq>=26.3.0",
+    "isodate>=0.7.2",
 ]
 
 [dependency-groups]
@@ -26,6 +33,7 @@ dev = [
     "ruff>=0.11.0",
     "build>=1.2.2",
     "respx>=0.22.0",
+    "pandas-stubs>=2.2.3",
 ]
 
 [project.urls]
@@ -38,9 +46,10 @@ package-dir = {"service_ml_forecast" = "src/service_ml_forecast", "scripts" = "s
 
 [tool.ruff]
 line-length = 120
-target-version = "py310"
+target-version = "py313"
 fix = true
 unsafe-fixes = false
+indent-width = 4
 
 [tool.ruff.lint]
 select = [
@@ -58,14 +67,19 @@ select = [
     "PL",    # pylint
     "RUF",   # ruff-specific rules
 ]
+ignore = ["PLR0913"]
 fixable = ["ALL"]
 
 [tool.ruff.format]
 line-ending = "auto"
 quote-style = "double"
+docstring-code-format = true
+docstring-code-line-length = "dynamic"
+indent-style = "space"
+
 
 [tool.mypy]
-python_version = "3.10"
+python_version = "3.13"
 warn_return_any = true
 warn_unused_configs = true
 disallow_untyped_defs = true
@@ -74,10 +88,11 @@ check_untyped_defs = true
 disallow_untyped_decorators = true
 no_implicit_optional = true
 warn_redundant_casts = true
-warn_unused_ignores = true
+warn_unused_ignores = false
 warn_no_return = true
 warn_unreachable = true
 strict_optional = true
+strict = true
 ignore_missing_imports = true
 
 [tool.ruff.lint.isort]
@@ -87,6 +102,7 @@ combine-as-imports = true
 [tool.pytest.ini_options]
 testpaths = ["tests"]
 python_files = "test_*.py"
+filterwarnings = ["ignore:.*"]
 
 [project.scripts]
 service_ml_forecast = "service_ml_forecast.main:app"

scripts/tools.py

@@ -45,12 +45,12 @@ def format() -> None:
 
 def test() -> None:
     """Run tests."""
-    step(f"uv run pytest {TEST_DIR} -v --cache-clear", "tests")
+    step(f"uv run pytest {TEST_DIR} -vv --cache-clear", "tests")
 
 
 def test_coverage() -> None:
     """Run tests with coverage."""
-    step(f"uv run pytest {TEST_DIR} -v --cache-clear --cov {SRC_DIR}", "tests with coverage")
+    step(f"uv run pytest {TEST_DIR} -vv --cache-clear --cov {SRC_DIR}", "tests with coverage")
 
 
 def build() -> None:

src/service_ml_forecast/__init__.py

@@ -21,6 +21,16 @@
 from pydantic import BaseModel
 
 
+def find_project_root(start_path: Path = Path(__file__)) -> Path:
+    """Find the project root by looking for marker files."""
+    current = start_path.parent
+    while current != current.parent:
+        if any((current / marker).exists() for marker in ["pyproject.toml", ".env"]):
+            return current
+        current = current.parent
+    raise RuntimeError("Could not find project root")
+
+
 class AppInfo(BaseModel):
     """Application information."""
 
@@ -29,17 +39,14 @@ class AppInfo(BaseModel):
     version: str
 
 
-def get_app_info() -> AppInfo | None:
+def get_app_info() -> AppInfo:
     """Read app info (name, description, version) from pyproject.toml file."""
-    try:
-        pyproject_path = Path(__file__).parents[2] / "pyproject.toml"
+    pyproject_path = find_project_root() / "pyproject.toml"
 
-        with open(pyproject_path, "rb") as f:
-            pyproject_data = tomli.load(f)
+    with open(pyproject_path, "rb") as f:
+        pyproject_data = tomli.load(f)
 
-        return AppInfo(**pyproject_data["project"])
-    except (FileNotFoundError, KeyError, tomli.TOMLDecodeError):
-        return None
+    return AppInfo(**pyproject_data["project"])
 
 
 __app_info__ = get_app_info()

src/service_ml_forecast/clients/openremote/models.py

@@ -38,6 +38,7 @@ class Asset(BaseModel):
 
     def get_attribute_value(self, attribute_name: str) -> Any | None:
         """Helper method to get an attribute value."""
+
         if attribute_name in self.attributes:
             return self.attributes[attribute_name].value
         return None
@@ -58,18 +59,16 @@ class AssetDatapoint(BaseModel):
     Args:
         x: The timestamp of the data point.
         y: The value of the data point.
-
     """
 
     x: int
     y: Any
 
 
-class DatapointsRequestBody(BaseModel):
-    """Request body for retrieving either historical or predicted data points of an asset attribute."""
+class AssetDatapointQuery(BaseModel):
+    """Request body for querying asset datapoints."""
 
     fromTimestamp: int
     toTimestamp: int
     fromTime: str = ""
     toTime: str = ""
-    type: str = "string"

src/service_ml_forecast/clients/openremote/openremote_client.py

@@ -27,7 +27,7 @@
     Asset,
     AssetDatapoint,
     AssetDatapointPeriod,
-    DatapointsRequestBody,
+    AssetDatapointQuery,
 )
 
 
@@ -56,6 +56,8 @@ class OpenRemoteClient:
         service_user: The service user for the OpenRemote API.
         service_user_secret: The service user secret for the OpenRemote API.
 
+    Raises:
+        Exception: If the authentication fails
     """
 
     logger = logging.getLogger(__name__)
@@ -121,6 +123,7 @@ def health_check(self) -> bool:
         Returns:
             bool: True if healthy, False if not.
         """
+
         url = f"{self.openremote_url}/api/master/health"
 
         request = self.__build_request("GET", url)
@@ -142,6 +145,7 @@ def retrieve_assets(self, realm: str) -> list[Asset] | None:
         Returns:
             list[Asset] | None: List of assets or None
         """
+
         url = f"{self.openremote_url}/api/master/asset/query"
         asset_query = {"recursive": True, "realm": {"name": realm}}
 
@@ -167,6 +171,7 @@ def retrieve_asset_datapoint_period(self, asset_id: str, attribute_name: str) ->
         Returns:
             AssetDatapointPeriod | None: The datapoints timestamp period of the asset attribute
         """
+
         query = f"?assetId={asset_id}&attributeName={attribute_name}"
         url = f"{self.openremote_url}/api/master/asset/datapoint/periods{query}"
 
@@ -176,30 +181,34 @@ def retrieve_asset_datapoint_period(self, asset_id: str, attribute_name: str) ->
             try:
                 response = client.send(request)
                 response.raise_for_status()
-                datapoint_period = AssetDatapointPeriod(**response.json())
-                return datapoint_period
+                return AssetDatapointPeriod(**response.json())
             except (httpx.HTTPStatusError, httpx.ConnectError) as e:
                 self.logger.error(f"Error retrieving asset datapoint period: {e}")
                 return None
 
     def retrieve_historical_datapoints(
-        self, asset_id: str, attribute_name: str, from_timestamp: int, to_timestamp: int
+        self,
+        asset_id: str,
+        attribute_name: str,
+        from_timestamp: int,
+        to_timestamp: int,
     ) -> list[AssetDatapoint] | None:
         """Retrieve the historical data points of a given asset attribute.
 
         Args:
             asset_id: The ID of the asset.
             attribute_name: The name of the attribute.
-            from_timestamp: The start timestamp.
-            to_timestamp: The end timestamp.
+            from_timestamp: Epoch timestamp in milliseconds.
+            to_timestamp: Epoch timestamp in milliseconds.
 
         Returns:
             list[AssetDatapoint] | None: List of historical data points or None
         """
+
         params = f"{asset_id}/{attribute_name}"
         url = f"{self.openremote_url}/api/master/asset/datapoint/{params}"
 
-        request_body = DatapointsRequestBody(
+        request_body = AssetDatapointQuery(
             fromTimestamp=from_timestamp,
             toTimestamp=to_timestamp,
         )
@@ -227,6 +236,7 @@ def write_predicted_datapoints(self, asset_id: str, attribute_name: str, datapoi
         Returns:
             bool: True if successful
         """
+
         params = f"{asset_id}/{attribute_name}"
         url = f"{self.openremote_url}/api/master/asset/predicted/{params}"
 
@@ -244,23 +254,28 @@ def write_predicted_datapoints(self, asset_id: str, attribute_name: str, datapoi
                 return False
 
     def retrieve_predicted_datapoints(
-        self, asset_id: str, attribute_name: str, from_timestamp: int, to_timestamp: int
+        self,
+        asset_id: str,
+        attribute_name: str,
+        from_timestamp: int,
+        to_timestamp: int,
     ) -> list[AssetDatapoint] | None:
         """Retrieve the predicted data points of a given asset attribute.
 
         Args:
             asset_id: The ID of the asset.
             attribute_name: The name of the attribute.
-            from_timestamp: The start timestamp.
-            to_timestamp: The end timestamp.
+            from_timestamp: Epoch timestamp in milliseconds.
+            to_timestamp: Epoch timestamp in milliseconds.
 
         Returns:
             list[AssetDatapoint] | None: List of predicted data points or None
         """
+
         params = f"{asset_id}/{attribute_name}"
         url = f"{self.openremote_url}/api/master/asset/predicted/{params}"
 
-        request_body = DatapointsRequestBody(
+        request_body = AssetDatapointQuery(
             fromTimestamp=from_timestamp,
             toTimestamp=to_timestamp,
         )

src/service_ml_forecast/common/exceptions.py

@@ -0,0 +1,36 @@
+# Copyright 2025, OpenRemote Inc.
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU Affero General Public License as
+# published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU Affero General Public License for more details.
+#
+# You should have received a copy of the GNU Affero General Public License
+# along with this program. If not, see <https://www.gnu.org/licenses/>.
+#
+# SPDX-License-Identifier: AGPL-3.0-or-later
+
+"""Common exceptions."""
+
+
+class ResourceNotFoundError(Exception):
+    """Exception raised when a resource is not found."""
+
+    pass
+
+
+class ResourceAlreadyExistsError(Exception):
+    """Exception raised when a resource already exists."""
+
+    pass
+
+
+class ExternalApiError(Exception):
+    """Exception raised when an external API call fails."""
+
+    pass