Add new sensors for energy produced (via Tibbber) (#76165)

The new sensors tibber:energy_(production|profit)_<home_id> are like the
existing consumption/totalCost ones except that they report outgoing
energy instead of incomeing.

homeassistant/components/tibber/sensor.py

@@ -558,17 +558,21 @@ class TibberDataCoordinator(DataUpdateCoordinator):
     async def _async_update_data(self):
         """Update data via API."""
         await self._tibber_connection.fetch_consumption_data_active_homes()
+        await self._tibber_connection.fetch_production_data_active_homes()
         await self._insert_statistics()
 
     async def _insert_statistics(self):
         """Insert Tibber statistics."""
         for home in self._tibber_connection.get_homes():
-            if not home.hourly_consumption_data:
+            sensors = []
-                continue
+            if home.hourly_consumption_data:
-            for sensor_type in (
+                sensors.append(("consumption", False, ENERGY_KILO_WATT_HOUR))
-                "consumption",
+                sensors.append(("totalCost", False, home.currency))
-                "totalCost",
+            if home.hourly_production_data:
-            ):
+                sensors.append(("production", True, ENERGY_KILO_WATT_HOUR))
+                sensors.append(("profit", True, home.currency))
+
+            for sensor_type, is_production, unit in sensors:
                 statistic_id = (
                     f"{TIBBER_DOMAIN}:energy_"
                     f"{sensor_type.lower()}_"
@@ -581,20 +585,26 @@ class TibberDataCoordinator(DataUpdateCoordinator):
 
                 if not last_stats:
                     # First time we insert 5 years of data (if available)
-                    hourly_consumption_data = await home.get_historic_data(5 * 365 * 24)
+                    hourly_data = await home.get_historic_data(
+                        5 * 365 * 24, production=is_production
+                    )
 
                     _sum = 0
                     last_stats_time = None
                 else:
-                    # hourly_consumption_data contains the last 30 days
+                    # hourly_consumption/production_data contains the last 30 days
-                    # of consumption data.
+                    # of consumption/production data.
                     # We update the statistics with the last 30 days
                     # of data to handle corrections in the data.
-                    hourly_consumption_data = home.hourly_consumption_data
+                    hourly_data = (
+                        home.hourly_production_data
+                        if is_production
+                        else home.hourly_consumption_data
+                    )
 
-                    start = dt_util.parse_datetime(
+                    start = dt_util.parse_datetime(hourly_data[0]["from"]) - timedelta(
-                        hourly_consumption_data[0]["from"]
+                        hours=1
-                    ) - timedelta(hours=1)
+                    )
                     stat = await get_instance(self.hass).async_add_executor_job(
                         statistics_during_period,
                         self.hass,
@@ -609,7 +619,7 @@ class TibberDataCoordinator(DataUpdateCoordinator):
 
                 statistics = []
 
-                for data in hourly_consumption_data:
+                for data in hourly_data:
                     if data.get(sensor_type) is None:
                         continue
 
@@ -627,10 +637,6 @@ class TibberDataCoordinator(DataUpdateCoordinator):
                         )
                     )
 
-                if sensor_type == "consumption":
-                    unit = ENERGY_KILO_WATT_HOUR
-                else:
-                    unit = home.currency
                 metadata = StatisticMetaData(
                     has_mean=False,
                     has_sum=True,

tests/components/tibber/test_common.py

@@ -20,6 +20,24 @@ CONSUMPTION_DATA_1 = [
     },
 ]
 
+PRODUCTION_DATA_1 = [
+    {
+        "from": "2022-01-03T00:00:00.000+01:00",
+        "profit": 0.1,
+        "production": 3.1,
+    },
+    {
+        "from": "2022-01-03T01:00:00.000+01:00",
+        "profit": 0.2,
+        "production": 3.2,
+    },
+    {
+        "from": "2022-01-03T02:00:00.000+01:00",
+        "profit": 0.3,
+        "production": 3.3,
+    },
+]
+
 
 def mock_get_homes(only_active=True):
     """Return a list of mocked Tibber homes."""
@@ -32,5 +50,10 @@ def mock_get_homes(only_active=True):
     tibber_home.country = "NO"
     tibber_home.last_cons_data_timestamp = dt.datetime(2016, 1, 1, 12, 44, 57)
     tibber_home.last_data_timestamp = dt.datetime(2016, 1, 1, 12, 48, 57)
-    tibber_home.get_historic_data.return_value = CONSUMPTION_DATA_1
+
+    def get_historic_data(n_data, resolution="HOURLY", production=False):
+        return PRODUCTION_DATA_1 if production else CONSUMPTION_DATA_1
+
+    tibber_home.get_historic_data.side_effect = get_historic_data
+
     return [tibber_home]

tests/components/tibber/test_statistics.py

@@ -5,7 +5,7 @@ from homeassistant.components.recorder.statistics import statistics_during_perio
 from homeassistant.components.tibber.sensor import TibberDataCoordinator
 from homeassistant.util import dt as dt_util
 
-from .test_common import CONSUMPTION_DATA_1, mock_get_homes
+from .test_common import CONSUMPTION_DATA_1, PRODUCTION_DATA_1, mock_get_homes
 
 from tests.components.recorder.common import async_wait_recording_done
 
@@ -15,62 +15,39 @@ async def test_async_setup_entry(hass, recorder_mock):
     tibber_connection = AsyncMock()
     tibber_connection.name = "tibber"
     tibber_connection.fetch_consumption_data_active_homes.return_value = None
+    tibber_connection.fetch_production_data_active_homes.return_value = None
     tibber_connection.get_homes = mock_get_homes
 
     coordinator = TibberDataCoordinator(hass, tibber_connection)
     await coordinator._async_update_data()
     await async_wait_recording_done(hass)
 
-    # Validate consumption
+    for (statistic_id, data, key) in (
-    statistic_id = "tibber:energy_consumption_home_id"
+        ("tibber:energy_consumption_home_id", CONSUMPTION_DATA_1, "consumption"),
+        ("tibber:energy_totalcost_home_id", CONSUMPTION_DATA_1, "totalCost"),
+        ("tibber:energy_production_home_id", PRODUCTION_DATA_1, "production"),
+        ("tibber:energy_profit_home_id", PRODUCTION_DATA_1, "profit"),
+    ):
+        stats = await hass.async_add_executor_job(
+            statistics_during_period,
+            hass,
+            dt_util.parse_datetime(data[0]["from"]),
+            None,
+            [statistic_id],
+            "hour",
+            True,
+        )
 
-    stats = await hass.async_add_executor_job(
+        assert len(stats) == 1
-        statistics_during_period,
+        assert len(stats[statistic_id]) == 3
-        hass,
+        _sum = 0
-        dt_util.parse_datetime(CONSUMPTION_DATA_1[0]["from"]),
+        for k, stat in enumerate(stats[statistic_id]):
-        None,
+            assert stat["start"] == dt_util.parse_datetime(data[k]["from"])
-        [statistic_id],
+            assert stat["state"] == data[k][key]
-        "hour",
+            assert stat["mean"] is None
-        True,
+            assert stat["min"] is None
-    )
+            assert stat["max"] is None
+            assert stat["last_reset"] is None
 
-    assert len(stats) == 1
+            _sum += data[k][key]
-    assert len(stats[statistic_id]) == 3
+            assert stat["sum"] == _sum
-    _sum = 0
-    for k, stat in enumerate(stats[statistic_id]):
-        assert stat["start"] == dt_util.parse_datetime(CONSUMPTION_DATA_1[k]["from"])
-        assert stat["state"] == CONSUMPTION_DATA_1[k]["consumption"]
-        assert stat["mean"] is None
-        assert stat["min"] is None
-        assert stat["max"] is None
-        assert stat["last_reset"] is None
-
-        _sum += CONSUMPTION_DATA_1[k]["consumption"]
-        assert stat["sum"] == _sum
-
-    # Validate cost
-    statistic_id = "tibber:energy_totalcost_home_id"
-
-    stats = await hass.async_add_executor_job(
-        statistics_during_period,
-        hass,
-        dt_util.parse_datetime(CONSUMPTION_DATA_1[0]["from"]),
-        None,
-        [statistic_id],
-        "hour",
-        True,
-    )
-
-    assert len(stats) == 1
-    assert len(stats[statistic_id]) == 3
-    _sum = 0
-    for k, stat in enumerate(stats[statistic_id]):
-        assert stat["start"] == dt_util.parse_datetime(CONSUMPTION_DATA_1[k]["from"])
-        assert stat["state"] == CONSUMPTION_DATA_1[k]["totalCost"]
-        assert stat["mean"] is None
-        assert stat["min"] is None
-        assert stat["max"] is None
-        assert stat["last_reset"] is None
-
-        _sum += CONSUMPTION_DATA_1[k]["totalCost"]
-        assert stat["sum"] == _sum