Basic Transformation

Plugin parameters may be specified as key-value pairs in the --trigger-arguments flag (CLI) or in the trigger_arguments field (API) when creating a trigger. Some plugins support TOML configuration files, which can be specified using the plugin’s config_file_path parameter.

If a plugin supports multiple trigger specifications, some parameters may depend on the trigger specification that you use.

Plugin metadata

This plugin includes a JSON metadata schema in its docstring that defines supported trigger types and configuration parameters. This metadata enables the InfluxDB 3 Explorer UI to display and configure the plugin.

Required parameters

Transformation parameters

Data selection parameters

TOML configuration

To use a TOML configuration file, set the PLUGIN_DIR environment variable and specify the config_file_path in the trigger arguments. This is in addition to the --plugin-dir flag when starting InfluxDB 3.

Example TOML configurations

• basic_transformation_config_scheduler.toml - for scheduled triggers
• basic_transformation_config_data_writes.toml - for data write triggers

For more information on using TOML configuration files, see the Using TOML Configuration Files section in the influxdb3_plugins/README.md.

Example 1: Temperature unit conversion

Convert temperature readings from Celsius to Fahrenheit while standardizing field names:

# Create the trigger
influxdb3 create trigger \
  --database weather \
  --path "gh:influxdata/basic_transformation/basic_transformation.py" \
  --trigger-spec "every:30m" \
  --trigger-arguments 'measurement=raw_temps,window=1h,target_measurement=temps_fahrenheit,names_transformations=Temperature:"snake",values_transformations=temperature:"convert_degC_to_degF"' \
  temp_converter

# Write test data
influxdb3 write \
  --database weather \
  "raw_temps,location=office Temperature=22.5"

# Query transformed data (after trigger runs)
influxdb3 query \
  --database weather \
  "SELECT * FROM temps_fahrenheit"

Expected output

Transformation details:

• Before: Temperature=22.5 (Celsius)
• After: temperature=72.5 (Fahrenheit, field name converted to snake_case)

Example 2: Field name standardization

Clean and standardize field names from various sensors:

# Create trigger with multiple transformations
influxdb3 create trigger \
  --database sensors \
  --path "gh:influxdata/basic_transformation/basic_transformation.py" \
  --trigger-spec "all_tables" \
  --trigger-arguments 'measurement=raw_sensors,target_measurement=clean_sensors,names_transformations=.*:"remove_special_chars snake collapse_underscore trim_underscore"' \
  field_cleaner

# Write data with inconsistent field names
influxdb3 write \
  --database sensors \
  "raw_sensors,device=sensor1 \"Room Temperature\"=20.1,\"__Humidity_%\"=45.2"

# Query cleaned data
influxdb3 query \
  --database sensors \
  "SELECT * FROM clean_sensors"

Expected output

Transformation details:

• Before: "Room Temperature"=20.1, "__Humidity_%"=45.2
• After: room_temperature=20.1, humidity=45.2 (field names standardized)

Example 3: Custom string replacements

Replace specific strings in field values:

# Create trigger with custom replacements
influxdb3 create trigger \
  --database inventory \
  --path "gh:influxdata/basic_transformation/basic_transformation.py" \
  --trigger-spec "every:1d" \
  --trigger-arguments 'measurement=products,window=7d,target_measurement=products_updated,values_transformations=status:"status_replace",custom_replacements=status_replace:"In Stock=available.Out of Stock=unavailable"' \
  status_updater