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Apache License

Stripe

This package models Stripe data from Fivetran's connector. It uses data in the format described by this ERD.

This package enriches your Fivetran data by doing the following:

  • Add descriptions to tables and columns that are synced using Fivetran
  • Add freshness tests to source data
  • Add column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
  • Model staging tables, which will be used in our transform package

Models

This package contains staging models, designed to work simultaneously with our Stripe modeling package. The staging models are designed to:

  • Remove any rows that are soft-deleted
  • Name columns consistently across all packages:
    • Boolean fields are prefixed with is_ or has_
    • Timestamps are appended with _at
    • ID primary keys are prefixed with the name of the table. For example, the card table's ID column is renamed card_id.

Installation Instructions

Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages.

Include in your packages.yml

packages:
  - package: fivetran/stripe_source
    version: [">=0.5.0", "<0.6.0"]

Configuration

By default, this package will look for your Stripe data in the stripe schema of your target database. If this is not where your Stripe data is, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

...
config-version: 2

vars:
    stripe_schema: your_schema_name
    stripe_database: your_database_name 

Disabling Models

This package takes into consideration that not every Stripe account utilizes the invoice, invoice_line_item, payment_method, payment_method_card, plan, subscription, or credit_note features, and allows you to disable the corresponding functionality. By default, all variables' values are assumed to be true with the exception of credit_note. Add variables for only the tables you want to disable or enable respectively:

# dbt_project.yml

...
vars:
    using_invoices:        False  #Disable if you are not using the invoice and invoice_line_item tables
    using_payment_method:  False  #Disable if you are not using the payment_method and payment_method_card tables
    using_subscriptions:   False  #Disable if you are not using the subscription and plan tables.
    using_credit_notes:    True   #Enable if you are using the credit note tables.

Changing the Build Schema

By default this package will build the Stripe staging models within a schema titled (<target_schema> + _stg_stripe). If this is not where you would like your Stripe staging models to be written to, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

...
models:
  stripe_source:
    +schema: my_new_staging_models_schema # leave blank for just the target_schema

Read more about using custom schemas in dbt here.

Running on Live vs Test Customers

By default, this package will run on non-test data (where livemode = true) from the source Stripe tables. However, you may want to include and focus on test data when testing out the package or developing your analyses. To run on only test data, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

vars:
    stripe_source:
        using_livemode: false  # Default = true

Including sub Invoice Line Items

By default, this package will filter out any records from the invoice_line_item source table which include the string sub_. This is due to a legacy Stripe issue where sub_ records were found to be duplicated. However, if you highly utilize these records you may wish they be included in the final output of the stg_stripe__invoice_line_item model. To do, so you may include the below variable configuration:

# dbt_project.yml

vars:
    stripe_source:
        using_invoice_line_sub_filter: false # Default = true

Pivoting out Metadata Properties

By default, this package selects the metadata JSON field within the customer, charge, invoice, payment_intent, payment_method, payout, plan, refund, and subscription source tables. However, you likely have properties within the metadata JSON field you would like to pivot out and include in the respective downstream staging model.

If there are properties in the metadata JSON field that you'd like to pivot out into columns, add the respective variable(s) to your dbt_project.yml file:

# dbt_project.yml

vars:
    stripe__charge_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
    stripe__invoice_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
    stripe__payment_intent_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
    stripe__payment_method_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
    stripe__payout_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
    stripe__plan_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
    stripe__refund_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
    stripe__subscription_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON
    stripe__customer_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON

Contributions

Additional contributions to this package are very welcome! Please create issues or open PRs against master. Check out this post on the best workflow for contributing to a package.

Database support

This package has been tested on BigQuery, Snowflake, Postgres, and Redshift.

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