Since inherit_from can also be used to inherit from another plugin in the project, Note that the -variant option and variant property are crucial here: The resulting inheriting plugin definitions in meltano.yml project file will look as follows: plugins: Meltano add loader target-snowflake -variant =meltano -as target-snowflake-meltanoĪssuming a regular (shadowing) target-snowflake was added before using meltano add loader target-snowflake,
![pip install slack-cleaner pip install slack-cleaner](https://pygot.files.wordpress.com/2018/08/1-3_oauthandpermissions2.png)
Meltano add loader target-snowflake -variant =transferwise -as target-snowflake-transferwise To explicitly inherit from the discoverable plugin instead: You can use the -inherit-from (or -as) option on meltano add In the examples we’ve considered so far, plugins in your project implicitly inherit theirīase plugin descriptions from discoverable plugins by reusing their names, which is known as shadowing.Īlternatively, if you’d like to give the plugin a more descriptive name in your project, If you’ve already added one variant to your project and would like to switch to another, refer to the “Switching from one variant to another” section below. If you’d like to use multiple variants of the same discoverable plugin in your project at the same time, refer to “Multiple variants” under “Explicit inheritance” below. Meltano add loader target-postgres -variant =transferwiseĪs you might expect, this will be reflected in the variant and pip_url properties in your meltano.yml project file: plugins: You can choose a specific (non-default) variant using the -variant option on meltano add: If multiple variants of a discoverable plugin are available,
![pip install slack-cleaner pip install slack-cleaner](https://cdn.ilovefreesoftware.com/wp-content/uploads/2020/05/slack-dm-purge-pip-install.png)
Has the same effect as adding it using meltano add. If this property is omitted, it is inherited from the discoverable base plugin description identified by the name (and variant) instead.Īs mentioned above, directly adding a plugin to your meltano.yml project fileĪnd installing it using meltano install Point at a (custom) fork or to pin a package to a specific version.
![pip install slack-cleaner pip install slack-cleaner](https://venturebeat.com/wp-content/uploads/2019/04/google-cloud-7-open-source-partners.png)
PIP INSTALL SLACK CLEANER UPDATE
Is repeated here for convenience, since you may want to update it to The package’s pip_url (its pip install argument) If the variant property were omitted from the definition, Meltano would fall back on the original supported variant instead, which does not necessarily match the default. So that your project is pinned to a specific package and its base plugin description. (which is known to work well and recommended for new users), The variant property is automatically set to the name of the default variant If multiple variants of the discoverable plugin are available, This will add a shadowing plugin definition to your meltano.yml project file under the plugins property, inside an array named after the plugin type: plugins: Discoverable pluginsĭiscoverable plugins can be added to your project by simply providing Refer to the “Plugin inheritance” section. So that it can reuse the same package but override (parts of) its configuration, Like an arbitrary Singer tap or target, refer to the “Custom plugins” section.įinally, if you’d like your new plugin to inherit from an existing plugin in your project, Refer to the “Discoverable plugins” section below.Īlternatively, if you’d like to add a custom plugin that Meltano isn’t familiar with yet, Like one of the extractors and loaders listed on the Extractors and Loaders pages, If you’d like to add a discoverable plugin that’s supported by Meltano out of the box, You can add a new plugin to your project using meltano add, orīy directly modifying your meltano.yml project fileĪnd installing the new plugin using meltano install. They can be managed using various CLI commands as well as the UI. Your project’s plugins are defined in your meltano.yml project file,Īnd are installed inside the. Orchestrators (currently Airflow, with Dagster in development). Where your project and pipelines are composed of plugins of different types, most notably extractors ( Singer taps), loaders ( Singer targets), transformers ( dbt and dbt models), and Meltano takes a modular approach to data engineering in general and EL(T) in particular, Installing plugins from a custom Python Package Index (PyPi).