Avrotize

EXPERIMENTAL. USE AT YOUR OWN RISK.

Avrotize is a "Rosetta Stone" for data structure definitions, allowing you to convert between numerous data and database schema formats and to generate code for different programming languages.

The tool leans on the Apache Avro-derived "Avrotize Schema" as its schema model.

Screenshot

Requirements

Avrotize requires Python 3.10 or later to be installed on your system first.

You can let the extension install Avrotize or you can install it with PIP:

pip install avrotize

If you only want to run the tool in a virtual environment, you can create one, install Avrotize in it, and then start Visual Studio Code from within the virtual environment context.

Once Avrotize is installed, the extension will detect whether the Avrotize version is current and will automatically update it to match the extension version if necessary.

Features

Avrotize lets you convert different file formats to and from Avro(-tize) schemas directly from the VS Code explorer context menu. The extension will add a new "Convert to" menu item with subitems based on the file type you are working with. Below is a guide to what commands are available for which file types and what happens when you select them.

Supported File Types and Available Commands

From Avrotize Schema

File Extension	Context Menu Command	Description	Steps
`.avsc`	Convert to > Parquet	Converts an Avro schema to a Parquet file and saves the output.	- Provide output file name and location
`.avsc`	Convert to > JSON	Converts an Avro schema to a JSON schema and saves the output.	- Provide output file name and location
`.avsc`	Convert to > XML	Converts an Avro schema to an XML schema and saves the output.	- Provide output file name and location
`.avsc`	Convert to > SQL Schema	Converts an Avro schema to a SQL schema and saves the output.	- Select the SQL dialect - Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > MongoDB Schema	Converts an Avro schema to a MongoDB schema and saves the output.	- Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > Cassandra Schema	Converts an Avro schema to a Cassandra schema and saves the output.	- Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > DynamoDB Schema	Converts an Avro schema to a DynamoDB schema and saves the output.	- Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > Elasticsearch Schema	Converts an Avro schema to an Elasticsearch schema and saves the output.	- Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > CouchDB Schema	Converts an Avro schema to a CouchDB schema and saves the output.	- Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > Neo4j Schema	Converts an Avro schema to a Neo4j schema and saves the output.	- Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > Firebase Schema	Converts an Avro schema to a Firebase schema and saves the output.	- Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > CosmosDB Schema	Converts an Avro schema to a CosmosDB schema and saves the output.	- Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > HBase Schema	Converts an Avro schema to an HBase schema and saves the output.	- Decide if you want to add CloudEvents columns - Provide output file name and location
`.avsc`	Convert to > C# Classes	Converts an Avro schema to C# classes and saves the output.	- Provide C# root namespace - Decide if you want to use Avro annotations - Decide if you want to use System.Text.Json annotations - Provide output file name and location
`.avsc`	Convert to > Java Classes	Converts an Avro schema to Java classes and saves the output.	- Decide if you want to use Avro annotations - Decide if you want to use Jackson annotations - Decide if you want to use PascalCase properties - Provide output file name and location
`.avsc`	Convert to > Python Classes	Converts an Avro schema to Python classes and saves the output.	- Decide if you want to use dataclasses-json annotations - Decide if you want to use Avro annotations - Provide output file name and location
`.avsc`	Convert to > TypeScript Classes	Converts an Avro schema to TypeScript classes and saves the output.	- Decide if you want to use Avro annotations - Decide if you want to use TypedJSON annotations - Provide output file name and location
`.avsc`	Convert to > JavaScript Classes	Converts an Avro schema to JavaScript classes and saves the output.	- Decide if you want to use Avro annotations - Provide output file name and location
`.avsc`	Convert to > C++ Classes	Converts an Avro schema to C++ classes and saves the output.	- Provide root namespace - Decide if you want to use Avro annotations - Decide if you want to use JSON annotations - Provide output file name and location
`.avsc`	Convert to > Go Classes	Converts an Avro schema to Go classes and saves the output.	- Decide if you want to use Avro annotations - Decide if you want to use JSON annotations - Provide Go package name, site, and username (optional) - Provide output file name and location
`.avsc`	Convert to > Rust Classes	Converts an Avro schema to Rust classes and saves the output.	- Provide Rust package name (optional) - Decide if you want to use Avro annotations - Decide if you want to use JSON annotations - Provide output file name and location
`.avsc`	Convert to > Data Pipeline JSON	Converts an Avro schema to Data Pipeline JSON and saves the output.	- Provide record type (optional) - Provide output file name and location
`.avsc`	Convert to > Markdown Documentation	Converts an Avro schema to Markdown documentation and saves the output.	- Provide output file name and location

From Other Formats

File Extension	Context Menu Command	Description	Steps
`.parquet`	Convert to > Avro Schema	Converts a Parquet file to an Avro schema and saves the output.	- Provide namespace for the Avro schema - Provide output file name and location
`.json`	Convert to > Avro Schema	Converts a JSON schema to an Avro schema and saves the output.	- Provide namespace for the Avro schema - Decide if you want to split top-level records - Provide output file name and location
`.xml`	Convert to > Avro Schema	Converts an XML schema to an Avro schema and saves the output.	- Provide namespace for the Avro schema - Provide output file name and location
`.asn`	Convert to > Avro Schema	Converts an ASN schema to an Avro schema and saves the output.	- Provide output file name and location
`.csv`	Convert to > Avro Schema	Converts a CSV header schema to an Avro schema and saves the output.	- Provide namespace for the Avro schema - Provide output file name and location

Right-Click on a File: In the VS Code explorer, right-click on a file with a supported extension.
Select "Convert to" Menu: Hover over the "Convert to" menu item to see the available conversion options for the selected file.
Select the Conversion Option: Click on the desired conversion option.
Provide Output Details: You will be prompted to provide details such as the output file name and location. Fill in the necessary information.
View Output: The conversion process will run, and the output will be saved to the specified location. If the output is a file, it will be opened in the editor. If it is a directory, a new window will be opened with the directory.

By following these steps, you can easily convert between various data formats and Avro schemas using the Avrotize extension in Visual Studio Code.

Release Notes

Refer to the Avrotize repository for the release notes of the Avrotize tool.

Avrotize

Clemens Vasters

Avrotize

Requirements

Features

Supported File Types and Available Commands

From Avrotize Schema

From Other Formats

Using the Context Menu Commands

Release Notes