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Load GoFile data to DuckDB

Build a GoFile to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the GoFile API base URL, auth, endpoints, and incremental loading.

SourceGoFileGoFile API DocumentationDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

GoFile is a file storage and sharing platform that provides a REST API for managing accounts, folders, and files. Everything needed to build a working GoFile → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.


Build your GoFile to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

Prompt
Run uvx dlthub-init@latest to build a pipeline from GoFile to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the GoFile API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.


GoFile API at a glance

Base URLhttps://api.gofile.io
Example endpointGET listFiles
Records found atdata.files
Authenticationall requests require a Bearer token in the Authorization header — sent in the Authorization header, prefixed Bearer
PaginationPage-number page size via pageSize. GoFile API list/paginated endpoints document query parameters page (starts at 1) and pageSize (items per page). The provided sources do not mention cursor-style pagination tokens (e.g., nextPageToken/cursor), so no cursor parameter name or token path can be verified from the documentation.
API referencehttps://gofile.io/api

These values come from the GoFile API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the GoFile API?

Authentication is performed by passing a token in the Authorization header using the Bearer scheme: 'Authorization: Bearer '.

1. Get your credentials

To obtain your GoFile API credentials: 1. Sign in to your account at https://gofile.io. 2. Navigate to your profile page at https://gofile.io/myProfile. 3. Locate the API token section; your unique API key is displayed there. Copy this value for use in your configuration.

2. Add them to .dlt/secrets.toml

[sources.gofile_source] api_key = "your_api_key_here"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.


What GoFile data can I load into DuckDB?

These are the GoFile endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
account/accounts/{accountId}GETdataGet account information and stats
list_files/contents/{contentId}GETdataRetrieve folder contents and metadata
search_content/contents/searchGETdataSearch for files within a folder
get_server/serversGETdataGet list of available upload servers
get_file_info/contents/{contentId}GETdataRetrieve metadata for specific content

How do I load only new GoFile records?

The GoFile API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

{"name": "list_files", "endpoint": { "path": "listFiles", # Replace with a field that increases on every write. "incremental": {"cursor_path": "REPLACE_ME", "initial_value": "2024-01-01T00:00:00Z"}, }}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.


What does the generated GoFile pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /accounts/getid and /contents/{contentId} from the GoFile API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def gofile_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.gofile.io", "auth": {"type": "bearer", "token": api_key}, }, "resources": [ {"name": "list_files", "endpoint": {"path": "listFiles", "data_selector": "data.files"}}, {"name": "get_file_info", "endpoint": {"path": "getFileInfo", "data_selector": "data"}} ], } yield from rest_api_resources(config) def load_gofile_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="gofile_pipeline", destination="duckdb", dataset_name="gofile_data", ) load_info = pipeline.run(gofile_source()) print(load_info) if __name__ == "__main__": load_gofile_to_duckdb()

Run it with python gofile_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.


How do I query GoFile data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

import dlt data = dlt.pipeline("gofile_pipeline").dataset() df = data.list_files.df() print(df.head())

SQL:

SELECT * FROM gofile_data.list_files LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.


How do I deploy the GoFile to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

  • Deploy & schedule — run the pipeline as a managed job with automatic retries.
  • Monitor — observable job queues, alerting, and load metrics for every run.
  • Transform — promote raw GoFile loads into governed, documented models.
  • Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →


What other destinations can I load GoFile data to?

dlt loads into any of these — only the destination argument changes:

DestinationExample value
PostgreSQL"postgres"
BigQuery"bigquery"
Snowflake"snowflake"
Redshift"redshift"
Databricks"databricks"
Filesystem (S3, GCS, Azure)"filesystem"

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.


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