meta.err

Catches errors returned by other transforms and returns messages.

Settings

Field	Type	Description	Required
transform	object	Transform that is applied.	Yes

Example

sub.tf.meta.err(
  settings={transform: sub.tf.enrich.http.get([...])}
)

sub.tf.meta.err({transform: sub.tf.enrich.http.get([...])})

meta.for_each

Applies transform to every element of a JSON array.

Settings

Field	Type	Description	Required
object.source_key	string	Retrieves a value from an object for transformation.	Yes
object.target_key	string	Places a value into an object after transformation.	Yes
transform	object	Transform that is applied.	Yes

Example

sub.tf.meta.for_each(
  settings={object: {source_key: 'arr', target_key: 'arr'}, transform: sub.tf.enrich.http.get([...])}
)

sub.tf.meta.for_each({obj: {src: 'arr', trg: 'arr'}, transform: sub.tf.enrich.http.get([...])})

meta.metric.duration

Generates a metric that reports the execution time (duration) of the transform.

Settings

Field	Type	Description	Required
metric.name	string	Name of the metric.	Yes
metric.destination	object	Metrics Destination configuration that reports the metric to an external system.	Yes
transform	object	Transform that is applied.	Yes
metric.attributes	map	Map (dictionary) of strings that are included in the metric as attributes or labels.	No

Example

sub.tf.meta.metric.duration(
  settings={
    metric: { name: 'ObjectCopyDuration', destination: { type: 'aws_cloudwatch_embedded_metrics' } },
    transform: sub.tf.object.copy(
      settings={ object: { source_key: 'a', target_key: 'z' } },
    ),
  },
)

sub.tf.meta.metric.duration({
  metric: { name: 'ObjectCopyDuration', destination: { type: 'aws_cloudwatch_embedded_metrics' } },
  transform: sub.tf.object.copy({ obj: { src: 'a', trg: 'z' } }),
})

meta.pipeline

Applies multiple transform in a series.

Settings

Field	Type	Description	Required
object.source_key	string	Retrieves a value from an object for transformation.	No
object.target_key	string	Sets a value into an object after transformation.	No
transforms	object	Transforms that are applied.	Yes

Example

sub.tf.meta.pipeline(
  settings={transforms: [
    sub.tf.enrich.http.get([...]),
    sub.tf.object.copy([...]),
  ]}
)

sub.tf.meta.pipe(
  settings={transforms: [
    sub.tf.enrich.http.get([...]),
    sub.tf.obj.cp([...]),
  ]}
)

meta.switch

Conditionally applies transforms using conditional statements:

if
if ... else
if ... elif ... else

Settings

Field	Type	Description	Required
cases.condition	[]object	Array of conditions that apply a transform.	No
cases.transform	[]object	Array of transforms conditionally applied.	Yes

Example

sub.tf.meta.switch(
  settings={ cases: [
    {condition: [...], transform: [...]},
    {condition: [...], transform: [...]},
  ]}
)

Use Cases

If Statement

An if statement is created by configuring a single meta.switch statement. This examples copies a string value if it contains a specific character:

sub.tf.meta.switch(
  settings={ cases: [
    { 
      condition: sub.cnd.any(sub.cnd.string.contains(settings={object: {source_key: 'a'}, value: 'b'}),
      transform: sub.tf.object.copy(settings={object: {source_key: 'a', target_key: 'z'}}),
    }
  ]}
)

sub.tf.meta.switch(
  settings={ switch: [
    { 
      condition: sub.cnd.any(sub.cnd.str.has(settings={object: {src: 'a'}, value: 'b'}),
      transform: sub.tf.obj.cp(settings={object: {src: 'a', trg: 'z'}}),
    }
  ]}
)

sub.pattern.tf.conditional(
  // tf.conditional pattern automatically applies the ANY operator if no operator is provided.
  condition=sub.cnd.str.contains(settings={obj: {src: 'a'}, value: 'b'},
  transform=sub.tf.obj.cp(settings={obj: {src: 'a', trg: 'z'}}),
)

If ... Else Statement

An if ... else statement is created by configuring two meta.switch statements:

The first statement is configured with a condition
The second statement is configured without a condition

This example aggregates JSON text into an array, otherwise the messages are dropped if they are not valid JSON.

sub.tf.meta.switch(
  settings={ cases: [
    { 
      condition: sub.cnd.any(sub.cnd.format.json()),
      transform: sub.tf.aggregate.to.array(),
    },
    {
      transform: sub.tf.utility.drop(),
    }
  ]}
)

sub.tf.meta.switch(
  settings={ switch: [
    { 
      condition: sub.cnd.any(sub.cnd.fmt.json()),
      transform: sub.tf.agg.to.arr(),
    },
    {
      transform: sub.tf.util.drop(),
    }
  ]}
)

More statements can be added to create if ... elif ... else statements.