meltano-map-transform 0.11.2

Singer-compatible inline map transformer, built with the Meltano SDK for Singer Taps.

meltano-map-transformer

A map transformer to duplicate, filter, hash, mask and do many more small transformations in your extract & load pipelines. Implements the Stream Maps capability.

This mapper plugin is fully compliant with the Singer Spec and can be placed in between any Singer tap and target.

Requirements

• Python 3.10+

meltano-map-transformer in action

For a collection of examples, take a look at examples/README.md.

Settings

Setting	Required	Default	Description
stream_maps	True	None	Stream maps
flattening_enabled	False	None	'True' to enable schema flattening and automatically expand nested properties.
flattening_max_depth	False	None	The max depth to flatten schemas.
stream_map_config	False	None	User-defined config values to be used within map expressions.

A full list of supported settings and capabilities is available by running: meltano-map-transformer --about

Installation

We recommend using GitHub release tags when installing with pip. We also recommend using pipx or meltano instead of installing with pip directly.

You can see a full list of published releases here.

For example:

# Use `uv` so that virtual environments are managed automatically:
uv tool install meltano-map-transform==0.10.0

# Alternatively, use `pipx`:
pipx install meltano-map-transform==0.10.0

Meltano installation instructions

1. Add this plugin to your Meltano project

   meltano add mapper meltano-map-transformer
   

2. Install the plugin

   meltano install
   

3. Configure the plugin

   # meltano.yml
   plugins:
     mappers:
     - name: meltano-map-transformer
       pip_url: meltano-map-transform
       executable: meltano-map-transform
       mappings:
       - name: hash_email
         config:
           stream_maps:
             customers:
               email: null # drop the PII field from RECORD and SCHEMA messages
               email_domain: email.split('@')[-1]
               email_hash: md5(config['hash_seed'] + email)
               __else__: null # drop all other fields
           stream_map_config:
             hash_seed: 01AWZh7A6DzGm6iJZZ2T
   

4. Use the plugin in your pipelines

   meltano run tap-csv hash_email target-sqlite
   

Capabilities

• stream-maps

Settings

Setting	Required	Default	Description
stream_maps	True	None	Stream maps

A full list of supported settings and capabilities is available by running: meltano-map-transformer --about