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https://github.com/fivetran/dbt_recharge_source

Fivetran's Recharge Source dbt package
https://github.com/fivetran/dbt_recharge_source

dbt dbt-packages fivetran fivetran-subscription-analytics recharge-payments

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Fivetran's Recharge Source dbt package

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# Recharge Source dbt package ([Docs](https://fivetran.github.io/dbt_recharge_source/))

## What does this dbt package do?

- Materializes [Recharge staging tables](https://fivetran.github.io/dbt_recharge_source/#!/overview/recharge_source/models/?g_v=1&g_e=seeds), which leverage data in the format described by [this ERD](https://fivetran.com/docs/applications/recharge#schemainformation). These staging tables clean, test, and prepare your Recharge data from [Fivetran's connector](https://fivetran.com/docs/applications/recharge) for analysis by doing the following:

  - Naming columns for consistency across all packages and easier analysis

  - Adding freshness tests to source data

  - Adding column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.

- Generates a comprehensive data dictionary of your Recharge data through the [dbt docs site](https://fivetran.github.io/dbt_recharge_source/).

- These tables are designed to work simultaneously with our [Recharge transformation package](https://github.com/fivetran/dbt_recharge).



## How do I use the dbt package?

### Step 1: Prerequisites

To use this dbt package, you must have the following:

- At least one Fivetran Recharge connector syncing data into your destination

- A **BigQuery**, **Snowflake**, **Redshift**, **PostgreSQL**, or **Databricks** destination



#### Databricks dispatch configuration

If you are using a Databricks destination with this package, you must add the following dispatch configuration (or a variation of thereof) within your `dbt_project.yml`. This is required in order for the package to accurately search for macros within the `dbt-labs/spark_utils` package, then within the `dbt-labs/dbt_utils` package, respectively.

```yml

dispatch:

  - macro_namespace: dbt_utils

    search_order: ['spark_utils', 'dbt_utils']

```



### Step 2: Install the package (skip if also using the `recharge` transformation package)

If you are **not** using the [Recharge transformation package](https://github.com/fivetran/dbt_recharge), include the following package version in your `packages.yml` file. If you are installing the transform package, the source package is automatically installed as a dependency.



Include the following recharge_source package version in your `packages.yml` file.

> TIP: Check [dbt Hub](https://hub.getdbt.com/) for the latest installation instructions, or [read dbt's Package Management documentation](https://docs.getdbt.com/docs/package-management) for more information on installing packages.

```yml

packages:

  - package: fivetran/recharge_source

    version: [">=0.3.0", "<0.4.0"] # we recommend using ranges to capture non-breaking changes automatically

```



### Step 3: Define database and schema variables

By default, this package runs using your destination and the `recharge` schema. If this is not where your Recharge data is (for example, if your Recharge schema is named `recharge_fivetran`), add the following configuration to your root `dbt_project.yml` file:



```yml

vars:

  recharge_database: your_database_name

  recharge_schema: your_schema_name 

```



### Step 4: Enable/disable models and sources

Your Recharge connector may not sync every table that this package expects. If you do not have the `CHECKOUT`, `ONE_TIME_PRODUCT` and/or `CHARGE_TAX_LINE` tables synced, add the corresponding variable(s) to your root `dbt_project.yml` file to disable these sources:



```yml

vars:

  recharge__one_time_product_enabled: false # Disables if you do not have the ONE_TIME_PRODUCT table. Default is True.

  recharge__charge_tax_line_enabled: false # Disables if you do not have the CHARGE_TAX_LINE table. Default is True.

  recharge__checkout_enabled: true # Enables if you do have the CHECKOUT table. Default is False.

```



### (Optional) Step 5: Additional configurations

Expand/collapse section.



#### Leveraging `orders` vs `order` source

For Fivetran Recharge connectors created on or after June 18, 2024, the `ORDER` source table has been renamed to `ORDERS`. Refer to the [June 2024 connector release notes](https://fivetran.com/docs/connectors/applications/recharge/changelog#june2024) for more information.



The package will default to use the `ORDERS` table if it exists and then `ORDER` if not. If you have both versions but wish to use the `ORDER` table instead, you can set the variable `recharge__using_orders` to false in your `dbt_project.yml` file.

```yml

vars:

  recharge__using_orders: false # default is true, which will use the `orders` version of the source.

```



#### Passing Through Additional Columns

This package includes all source columns defined in the macros folder. If you would like to pass through additional columns to the staging models, add the following configurations to your `dbt_project.yml` file. These variables allow for the pass-through fields to be aliased (`alias`) and casted (`transform_sql`) if desired, but not required. Datatype casting is configured via a SQL snippet within the `transform_sql` key. You may add the desired SQL while omitting the `as field_name` at the end, and your custom pass-though fields will be casted accordingly. Use the below format for declaring the respective pass-through variables in your root `dbt_project.yml`.

```yml

vars:

    recharge__address_passthrough_columns: 

      - name: "new_custom_field"

        alias: "custom_field_name"

        transform_sql:  "cast(custom_field_name as int64)"

      - name: "a_second_field"

        transform_sql:  "cast(a_second_field as string)"

    # a similar pattern can be applied to the rest of the following variables.

    recharge__charge_passthrough_columns:

    recharge__charge_line_item_passthrough_columns:

    recharge__checkout_passthrough_columns:

    recharge__order_passthrough_columns:

    recharge__order_line_passthrough_columns:

    recharge__subscription_passthrough_columns:

    recharge__subscription_history_passthrough_columns:

```



#### Changing the Build Schema

By default, this package will build the Recharge staging models within a schema titled ( + `recharge_source`) in your destination. If this is not where you would like your Recharge staging data written, add the following configuration to your root `dbt_project.yml` file:



```yml

models:

    recharge_source:

      +schema: my_new_schema_name # leave blank for just the target_schema

```



#### Change the source table references

If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable:



> IMPORTANT: See this project's [`dbt_project.yml`](https://github.com/fivetran/dbt_recharge_source/blob/main/dbt_project.yml) variable declarations to see the expected names.



```yml

vars:

    recharge__identifier: your_table_name 

```

##### Snowflake Users

You may need to provide the case-sensitive spelling of your source tables that are also Snowflake reserved words.



In this package, this would apply to the `ORDER` source. If you are receiving errors for this source, include the following in your `dbt_project.yml` file. (**Note:** This should not be necessary for the `ORDERS` source table.)

```yml

vars:

  recharge_order_identifier: '"Order"' # as an example, must include this quoting pattern and adjust for your exact casing

```



**Note:** If you have sources defined in your project's yml, the above will not work. Instead you will need to add the following where your order table is defined in your yml:

```yml

sources:

  tables:

    - name: order 

      # Add the below

      identifier: ORDER # Or what your order table is named, being mindful of casing

      quoting:

        identifier: true

```



### (Optional) Step 6: Orchestrate your models with Fivetran Transformations for dbt Core™

Expand for more details



Fivetran offers the ability for you to orchestrate your dbt project through [Fivetran Transformations for dbt Core™](https://fivetran.com/docs/transformations/dbt). Learn how to set up your project for orchestration through Fivetran in our [Transformations for dbt Core™ setup guides](https://fivetran.com/docs/transformations/dbt#setupguide).

    



## Does this package have dependencies?

This dbt package is dependent on the following dbt packages. These dependencies are installed by default within this package. For more information on the following packages, refer to the [dbt hub](https://hub.getdbt.com/) site.

> IMPORTANT: If you have any of these dependent packages in your own `packages.yml` file, we highly recommend that you remove them from your root `packages.yml` to avoid package version conflicts.

```yml

packages:

    - package: fivetran/fivetran_utils

      version: [">=0.4.0", "<0.5.0"]



    - package: dbt-labs/dbt_utils

      version: [">=1.0.0", "<2.0.0"]

```

          

## How is this package maintained and can I contribute?

### Package Maintenance

The Fivetran team maintaining this package _only_ maintains the latest version of the package. We highly recommend that you stay consistent with the [latest version](https://hub.getdbt.com/fivetran/recharge_source/latest/) of the package and refer to the [CHANGELOG](https://github.com/fivetran/dbt_recharge_source/blob/main/CHANGELOG.md) and release notes for more information on changes across versions.



### Contributions

A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions.



We highly encourage and welcome contributions to this package. Check out [this dbt Discourse article](https://discourse.getdbt.com/t/contributing-to-a-dbt-package/657) to learn how to contribute to a dbt package.



## Are there any resources available?

- If you have questions or want to reach out for help, see the [GitHub Issue](https://github.com/fivetran/dbt_recharge_source/issues/new/choose) section to find the right avenue of support for you.

- If you would like to provide feedback to the dbt package team at Fivetran or would like to request a new dbt package, fill out our [Feedback Form](https://www.surveymonkey.com/r/DQ7K7WW).