segrails.monitoring.tracker
===========================

.. py:module:: segrails.monitoring.tracker

.. autoapi-nested-parse::

   Monitoring tracker — writes inference metrics to Azure Table Storage.

   Mode no-op if azure-data-tables is not installed or no connection is configured.
   Writes are fire-and-forget in a background thread to avoid blocking predict().

   Environment variables:
       AZURE_TABLES_CONNECTION_STRING: Storage account connection string.
           When set, used for direct authentication (local dev, CI).
       AZURE_TABLES_ACCOUNT_URL: Storage account table endpoint URL
           (e.g. ``https://deployment4dev.table.core.windows.net``).
           When set without a connection string, authenticates via
           DefaultAzureCredential (Managed Identity, az login, SP env vars).
       AZURE_TABLES_TABLE_NAME: Table name. Default: ``SegrailsInferences``.



Classes
-------

.. autoapisummary::

   segrails.monitoring.tracker.TableTracker


Module Contents
---------------

.. py:class:: TableTracker(table_name: str = 'SegrailsInferences', env: str = 'dev', connection_string: str = '', account_url: str = '')

   Écrit les métriques d'inférence dans Azure Table Storage (une ligne par appel).

   Auth (par ordre de priorité) : connection string → DefaultAzureCredential (MI/az login).

   :param table_name: Nom de la table Azure (créée automatiquement si absente).
   :param env: Environnement de déploiement (dev / test / beta / prod).
   :param connection_string: Surcharge ``AZURE_TABLES_CONNECTION_STRING``.
   :param account_url: Surcharge ``AZURE_TABLES_ACCOUNT_URL`` (utilisé avec DefaultAzureCredential).

   .. rubric:: Example

   >>> tracker = TableTracker(table_name="SegrailsInferences", env="dev")
   >>> tracker.log_inference(result)


   .. py:attribute:: _table_name
      :value: 'SegrailsInferences'



   .. py:attribute:: _env
      :value: 'dev'



   .. py:attribute:: _session_id


   .. py:attribute:: _client
      :type:  Any
      :value: None



   .. py:property:: enabled
      :type: bool


      Return True if the tracker is connected and ready to write.


   .. py:method:: log_inference(result: altametris.segrails.result.SegrailsResult, session_id: str | None = None, pipeline_name: str | None = None, env: str | None = None, end_time: str | None = None) -> None

      Write one inference row to the table (background thread).

      No-op if the tracker is disabled. Errors during write are caught
      and logged as warnings — they never propagate to the caller.

      :param result: SegrailsResult returned by SegrailsClient.predict().
      :param session_id: Logical session identifier used as PartitionKey.
                         Defaults to the machine hostname (``socket.gethostname()``).
      :param pipeline_name: Calling pipeline identifier.
      :param env: Override the tracker's env tag for this row only.
      :param end_time: ISO 8601 timestamp of when predict() returned.
                       Used to compute End_time and Duration columns.



   .. py:method:: _build_client(connection_string: str, account_url: str, table_name: str) -> Any

      Build and return a TableClient, or None on failure.



   .. py:method:: _write(entity: dict[str, Any]) -> None

      Write entity to the table. Logs warning on error.



   .. py:method:: _build_entity(result: altametris.segrails.result.SegrailsResult, session_id: str, pipeline_name: str | None = None, env: str | None = None, end_time: str | None = None) -> dict[str, Any]

      Build the table entity dict from a SegrailsResult.