render_handlebars_template¶

render_handlebars_template(template, context)

Description¶

Render template with context using handlebars.js templating library

Usage¶

Call or Deploy render_handlebars_template ?

Call render_handlebars_template directly

The easiest way to use bigfunctions

render_handlebars_template function is deployed in 39 public datasets for all of the 39 BigQuery regions.
It can be called by anyone. Just copy / paste examples below in your BigQuery console. It just works!
(You need to use the dataset in the same region as your datasets otherwise you may have a function not found error)

Public BigFunctions Datasets

Region	Dataset
`eu`	`bigfunctions.eu`
`us`	`bigfunctions.us`
`europe-west1`	`bigfunctions.europe_west1`
`asia-east1`	`bigfunctions.asia_east1`
...	...

Deploy render_handlebars_template in your project

Why deploy?

You may prefer to deploy render_handlebars_template in your own project to build and manage your own catalog of functions.
This is particularly useful if you want to create private functions (for example calling your internal APIs).
Get started by reading the framework page

Deployment

render_handlebars_template function can be deployed with:

pip install bigfunctions
bigfun get render_handlebars_template
bigfun deploy render_handlebars_template

Examples¶

EUUSeurope-west1

select bigfunctions.eu.render_handlebars_template("Hello {{ user }}", json '{"user": "James"}')

select bigfunctions.us.render_handlebars_template("Hello {{ user }}", json '{"user": "James"}')

select bigfunctions.europe_west1.render_handlebars_template("Hello {{ user }}", json '{"user": "James"}')

+------------------+
| rendered_content |
+------------------+
| Hello James      |
+------------------+

Use cases¶

Let's say you have a BigQuery table with customer data, including their name and purchase history. You want to generate personalized email greetings for each customer, incorporating details from their purchase history. The render_handlebars_template function makes this easy.

Example Scenario:

Your table, customer_data, looks like this:

customer_id	customer_name	last_purchase_date	last_purchase_amount
1	Alice	2024-03-15	50.00
2	Bob	2024-03-22	100.00
3	Carol	2024-03-29	25.00

You could use the following query:

SELECT
    customer_id,
    bigfunctions.us.render_handlebars_template(
        """
        Hello {{customer_name}},

        Thank you for your recent purchase on {{last_purchase_date}} for ${{last_purchase_amount}}. We appreciate your business!
        """,
        TO_JSON_STRING(STRUCT(customer_name, last_purchase_date, last_purchase_amount))
    ) AS personalized_email
  FROM
    `your-project.your_dataset.customer_data`;

This query would produce a table with the customer_id and personalized_email:

customer_id	personalized_email
1	Hello Alice,\n\nThank you for your recent purchase on 2024-03-15 for $50.00. We appreciate your business!
2	Hello Bob,\n\nThank you for your recent purchase on 2024-03-22 for $100.00. We appreciate your business!
3	Hello Carol,\n\nThank you for your recent purchase on 2024-03-29 for $25.00. We appreciate your business!

Explanation:

Template: The first argument to render_handlebars_template is the template string. It uses Handlebars syntax ({{variable_name}}) to denote placeholders that will be replaced with actual values.
Context: The second argument is a JSON string representing the context. This provides the values for the placeholders in the template. TO_JSON_STRING(STRUCT(...)) is used to convert the desired columns into a JSON object.
Result: The function substitutes the values from the context into the template, generating the personalized email greeting for each customer.

Other Use Cases:

Generating dynamic reports: Create report templates with placeholders for metrics, dates, and other data, then populate them using query results.
Creating custom error messages: Craft more informative error messages by incorporating dynamic context from the data.
Formatting data for external APIs: Prepare data in specific formats required by external services using templating.

This function provides a flexible and powerful way to generate dynamic text within BigQuery, improving tasks involving personalization, reporting, and data formatting.

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