bigquery

BigQuery can be both a source and a destination for an automation: read a table or a query's results into a spreadsheet, or load a spreadsheet's rows into a BigQuery table.

These endpoints are the discovery half — list the projects, datasets and tables the authorized Google account can see, read one table's typed schema, and dry-run a query to check it parses and see what it would cost before you create the automation. All of it is read-only: validate-query runs nothing.

Authorizing BigQuery is a Google consent screen in the Sheetgo web app and cannot be driven from an API key. Until it is granted, these endpoints answer 412.

Base URL: https://dev-api.sheetgo.com. Start page: https://dev-api.sheetgo.com/rest/reference.md

This page documents every endpoint of the group. Request and response shapes link to model pages; fetch the model pages an endpoint links before building a body.

Guide: Rate Limiting

Every endpoint is rate limited; see the guide Rate Limiting.

GET /rest/beta/bigquery/projects

List BigQuery projects

Every GCP project the authorized Google account can see.

id is the string project id — the value an automation's project field expects. numeric_id is the same project's numeric form, accepted too.

An empty list means the account genuinely has no BigQuery projects. A missing authorization is a 412, never an empty list.

Authentication, any one of: default; Developer Access; sheetgo-api-key.

Parameters

Name In Type Required Description Allowed values / default / constraints
page query integer no 1-based page number default: 1; min: 1
per_page query integer no Items per page, max 100 default: 50; min: 1; max: 100

Responses

Read next: BigQueryProjectListResponse, HTTPValidationError.

GET /rest/beta/bigquery/projects/{project}/datasets

List a project's datasets

Datasets in one project. id is what an automation's dataset expects.

A bigquery destination writes into an existing dataset — Sheetgo creates the table if it is missing, but never the dataset.

Authentication, any one of: default; Developer Access; sheetgo-api-key.

Parameters

Name In Type Required Description Allowed values / default / constraints
project path string yes Project id, as returned by GET /bigquery/projects
page query integer no 1-based page number default: 1; min: 1
per_page query integer no Items per page, max 100 default: 50; min: 1; max: 100

Responses

Read next: BigQueryDatasetListResponse, HTTPValidationError.

GET /rest/beta/bigquery/projects/{project}/datasets/{dataset}/tables

List a dataset's tables

Tables in one dataset. id is what an automation's table expects.

A destination may also name a table that does not exist yet — it is created on the first run — so this listing is a convenience, not a constraint.

Authentication, any one of: default; Developer Access; sheetgo-api-key.

Parameters

Name In Type Required Description Allowed values / default / constraints
project path string yes Project id, as returned by GET /bigquery/projects
dataset path string yes Dataset id
page query integer no 1-based page number default: 1; min: 1
per_page query integer no Items per page, max 100 default: 50; min: 1; max: 100

Responses

Read next: BigQueryTableListResponse, HTTPValidationError.

GET /rest/beta/bigquery/projects/{project}/datasets/{dataset}/tables/{table}

Read one table's schema

One table's column types, row and byte counts, and partitioning.

The types matter for a bigquery destination: partition.field must name a column, and BigQuery infers the partition type from that column rather than taking it from the payload.

partitioning describes the table as it exists today. An existing table keeps its own partitioning no matter what a destination payload asks for — only write_mode: "recreate" replaces it.

Authentication, any one of: default; Developer Access; sheetgo-api-key.

Parameters

Name In Type Required Description Allowed values / default / constraints
project path string yes Project id, as returned by GET /bigquery/projects
dataset path string yes Dataset id
table path string yes Table id

Responses

Read next: BigQueryTableDetail, HTTPValidationError.

POST /rest/beta/bigquery/projects/{project}/validate-query

Validate a query without running it

Dry-run a query: check it parses, see what it would return and cost.

Nothing is scanned and nothing can be mutated, so this is safe to call freely — which is why it needs only the bigquery.read scope despite being a POST.

Invalid SQL answers 200 with valid: false, not a 4xx: "is this query valid?" has no as a legitimate answer. A 4xx/5xx here means the request could not be answered at all — missing authorization, no permission, or BigQuery being unreachable.

Use total_bytes_processed to size an uncapped source query before creating the automation. A bigquery source's generated SQL has no LIMIT, so this is how you find out what a full scan will cost.

Authentication, any one of: default; Developer Access; sheetgo-api-key.

Parameters

Name In Type Required Description Allowed values / default / constraints
project path string yes Project id, as returned by GET /bigquery/projects

Request body

Content type application/json. Required.

Body: ValidateQueryRequest

Responses

Read next: HTTPValidationError, ValidateQueryRequest, ValidateQueryResponse.

More: start page https://dev-api.sheetgo.com/rest/reference.md, everything in one file https://dev-api.sheetgo.com/rest/llms-full.txt, OpenAPI https://dev-api.sheetgo.com/rest/openapi.json.