/dbt_jinjat

dbt Jinjat package

Primary LanguageMDX

jinjat-dbt (dbt Docs)

Official macros provided by Jinjat.

Contents

Installation instructions

New to dbt packages? Read more about them here.

  1. Include this package in your packages.yml file — check here for the latest version number:
packages:
  - git: https://github.com/jinjat-data/dbt_jinjat
    version: 0.2
  1. Run dbt deps to install the package.

Macros

request (source)

It's the HTTP routing macro for Jinjat that you use in analyses files. The arguments that you will pass to the macro will be used by dbt to compile your analysis files. If you have the definition the OpenAPI spec for your analysis files, Jinjat automatically generates the test values for you.

While the following arguments are optional, you need to use them to make sure dbt compiles. Therefore; you at least need to define OpenAPI spec (recommended) or pass values that make dbt compile.

Arguments

  • method: The HTTP status code. Can be one of GET, POST, PUT, PATCH, DELETE and OPTIONS. If not defined, Jinjat will forward all the status codes to the analysis
  • query: A dictionary of query parameters
  • body: The body payload of the HTTP request
  • headers: A dictionary of HTTP headers
  • params: A dictionary of path parameters

Usage:

Let's say you have ./analyses/example_endpoint.sql file as follows:

{%- set query_params = request(query={"status": "shipped"}).query %}

select  order_date, 
        count(*) as orders, 
        count(distinct customer_id) as users
from {{ ref('orders') }} 
group by order_date
where status = '{{query_params.status}}'

Let's compile your analysis:

$ dbt compile

Now, let's look at the target/analyses/example_endpoint.sql. We should see something similar to:

select  order_date, 
        count(*) as orders, 
        count(distinct customer_id) as users
from orders
group by order_date
where status = 'shipped'

Jinjat will patch this macro when you start Jinjat with jinjat serve to return the user HTTP request data instead of the parameters that you pass as arguments.

Utility Macros

The utility macros let you construct SELECT queries easily.

limit_query (source)

This macro takes a SQL query as a parameter and applies LIMIT to it.

Arguments

  • sql (required): The SQL query that you want to apply the limit
  • limit (required): The limit

Usage:

$ dbt run-operation limit_query --args 'sql: "select * from customer", limit: 1000'

> select * from (select * from customer) limit 1000

generate_select (source)

This macro generates the inner body of SELECT. It takes an array of columns and quotes them.

Arguments

  • selects: An array of columns to quote, the default is [*]

Usage:

$ dbt run-operation generate_select --args 'selects: [col1, col2]'

> "col1", "col2"

generate_where (source)

This macro takes an object with and, or properties and generates a boolean expression that can be used in a WHERE statement. The object can be nested.

Arguments

  • filter: An object that has and or or properties. Ex: {and: [{field: 'customer_type', operator: 'equals', value: ''}, {or: []}]}

Usage:

$ dbt run-operation generate_where --args 'filter: {and: [{field: 'customer_type', operator: 'equals', value: 'premium'}, {or: [{field: 'country', operator: 'equals', value: 'USA'}, {field: 'gender', operator: 'equals', value: 'male'}]}]}'

> customer_type = 'premium' AND (country = 'USA' OR gender = 'male')

quote_identifier (source)

Quotes table and column identifiers.

Arguments

  • value: The identifier to quote. col1, table_ref, etc.

quote_literal (source)

Quotes string and number literals.

Arguments

  • value: The identifier to quote. col1, table_ref, etc.

Generators

refine_app (source)

$ jinjat generate refine_app --args 'to: ref("customers")'

                               
└── analyses
    └── crud
        ├── _list_customers.sql ✔️
        ├── _id
        │   └── _get_customers.sql ✔️
        └── schema.yml ✔️
3 files will be created. Type enter to continue >

metrics_query (source)

$ jinjat generate metrics_query --args 'metric_name: revenue'

                               
└── analyses
    └── metrics
        ├── revenue.sql ✔️
        └── schema.yml ✔️
2 files will be created. Type enter to continue >