Schemas

Our API mostly provides data directly, but some fields provide URL links to larger data files that need to be downloaded seperately. We thus provide those schemas below such that code generation tools can generate code to deal with it easily.

JSON Schemas

JSON schemas for validating and documenting our data structures.

Report Schema

v1.0.0

Provides more detailed inforamtion to describe layers with more detail.

Download Schema →

GraphQL Schema

Our complete GraphQL API schema with all types, queries, and mutations.

GraphQL API

versionless

Complete GraphQL schema for code generation

Download Schema →

Parquet Schemas

Apache Parquet files for efficient data storage and analytics. We provide JSON schemas that describe the structure and contents of each Parquet file, making it easy to understand the data format before working with the files.

Mesh Schema

v1.0.0

A deeper breakdown of all element thermal data.

Download Schema →

Contacts Schema

v1.0.0

Data regarding element contacts in the print

Download Schema →

Using the Schemas

JSON Schemas

Use JSON schemas to validate data structures in your applications:

# Download a schema
curl https://api.helioadditive.com/schemas/json/material.json -o material-schema.json

# Validate with ajv-cli
npm install -g ajv-cli
ajv validate -s material-schema.json -d your-data.json

GraphQL Schema

Download and use with code generation tools:

# Download the schema
curl https://api.helioadditive.com/graphql/schema -o schema.graphqls

# Generate TypeScript types
npm run codegen

See our Code Generation guide for detailed instructions.

Parquet Schemas

Download the JSON schema to understand the Parquet file structure, then read the data:

# Download the JSON schema describing the Parquet structure
curl https://api.helioadditive.com/schemas/parquet/thermal.json -o thermal-schema.json

import pandas as pd
import json

# Review the schema to understand the data structure
with open('thermal-schema.json', 'r') as f:
    schema = json.load(f)
    print(json.dumps(schema, indent=2))

# Read Parquet file (obtain from API)
df = pd.read_parquet('thermal-data.parquet')
print(df.head())

Version Information

All schemas are versioned independently. Check the changelog for updates and breaking changes.

Need Help?

If you have questions about using our schemas or need additional formats, please contact us at support@helioadditive.com.