Method store

pyfair/utility/database.py:141–192

Store a model or metamodel in the database Thie function takes a model or metamodel, checks whether the appropriate calculations have been completed, and then stores that model. The data is stored in two tables: 1) first the aggregate statistics about the risk are st

(self, model_or_metamodel)

        return model

    def store(self, model_or_metamodel):
        """Store a model or metamodel in the database

        Thie function takes a model or metamodel, checks whether the
        appropriate calculations have been completed, and then stores that
        model. The data is stored in two tables: 1) first the aggregate
        statistics about the risk are stored in the 'results' table, and 2)
        the model data is stored in the 'models' table.

        Raises
        ------
        FairException
            If model or metamodel is not yet calculated

        """
        m = model_or_metamodel
        # If incomplete and not ready for storage, throw error
        if not m.calculation_completed():
            raise FairException("Model is uncalculated and won't be stored.")
        # Export from model
        meta = json.loads(m.to_json())
        json_data = m.to_json()
        results = m.export_results()['Risk']
        # Write to database
        with sqlite3.connect(self._path) as conn:
            cursor = conn.cursor()
            # Write model data
            cursor.execute(
                """INSERT OR REPLACE INTO models VALUES(?, ?, ?, ?)""",
                (
                    meta['model_uuid'], 
                    meta['name'], 
                    meta['creation_date'], 
                    json_data
                )
            )
            # Write cached results
            cursor.execute(
                """INSERT OR REPLACE INTO results VALUES(?, ?, ?, ?, ?)""",
                (
                    meta['model_uuid'], 
                    results.mean(axis=0),
                    results.std(axis=0),
                    results.min(axis=0),
                    results.max(axis=0)
                )
            )
        # Vacuum database
        conn = sqlite3.connect(self._path)
        conn.execute("VACUUM")
        conn.commit()
        conn.close()

    def query(self, query, params=None):
        """Function for querying the underlying database.