Added basic tag example to the code

Author: Martin

README.md

@@ -94,6 +94,9 @@ df_phys = proc.extract_phys(df_raw, tp_type=tp_type)
 ...
 ```
 
+### Add InfluxDB tags 
+You can add tags to your data when using InfluxDB. This effectively adds additional dimensions to your data that you can e.g. use to color timeseries based on events or to further segment your queries when visualizing the data. The `utils_db.py` contains a basic example via the `add_signal_tags` functions that you can use as outset for building your own logic. 
+
 ---
 ### Regarding InfluxDB and S3 usage costs
 Note that if you use the paid InfluxDB cloud and a paid S3 server, we recommend that you monitor usage during your tests early on to ensure that no unexpected cost developments occur.

dashboard-writer/utils_db.py

@@ -49,13 +49,30 @@ def get_start_times(self, devices, default_start, dynamic):
 
         return start_times
 
+    def add_signal_tags(self, df_signal):
+        """Advanced: This can be used to add custom tags to the signals
+        based on a specific use case logic. In effect, this will
+        split the signal into multiple timeseries
+        """
+        tag_columns = ["my_tag"]
+
+        def event_test(row):
+            return "event" if row[0] > 1200 else "no event"
+
+        for tag in tag_columns:
+            df_signal[tag] = df_signal.apply(lambda row: event_test(row), axis=1)
+
+        return tag_columns, df_signal
+
     def write_signals(self, device_id, df_phys):
         """Given a device ID and a dataframe of physical values,
         resample and write each signal to a time series database
 
         :param device_id:   ID of device (used as the 'measurement name')
         :param df_phys:     Dataframe of physical values (e.g. as per output of can_decoder)
         """
+        tag_columns = []
+
         if not df_phys.empty:
             for signal, group in df_phys.groupby("Signal")["Physical Value"]:
                 df_signal = group.to_frame().rename(columns={"Physical Value": signal})
@@ -68,9 +85,11 @@ def write_signals(self, device_id, df_phys):
                         f"Signal: {signal} (mean: {round(df_signal[signal].mean(),2)} | records: {len(df_signal)} | resampling: {self.res})"
                     )
 
-                self.write_influx(device_id, df_signal)
+                # tag_columns, df_signal = self.add_signal_tags(df_signal)
 
-    def write_influx(self, name, df):
+                self.write_influx(device_id, df_signal, tag_columns)
+
+    def write_influx(self, name, df, tag_columns):
         """Helper function to write signal dataframes to InfluxDB
         """
         from influxdb_client import WriteOptions
@@ -83,9 +102,7 @@ def write_influx(self, name, df):
             write_options=WriteOptions(batch_size=5000, flush_interval=1_000, jitter_interval=2_000, retry_interval=5_000,)
         )
 
-        _write_client.write(
-            self.influx_bucket, record=df, data_frame_measurement_name=name,
-        )
+        _write_client.write(self.influx_bucket, record=df, data_frame_measurement_name=name, data_frame_tag_columns=tag_columns)
 
         if self.verbose:
             print(f"- SUCCESS: {len(df.index)} records of {name} written to InfluxDB\n\n")