Load Tron Shasta Testnet data to DuckDB

TronGrid is an API platform providing HTTP/JSON-RPC node services for the TRON network, including the Shasta testnet environment. Everything needed to build a working Tron Shasta Testnet → 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.

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Build your Tron Shasta Testnet to DuckDB pipeline

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

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from Tron Shasta Testnet 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 Tron Shasta Testnet 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.

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Tron Shasta Testnet API at a glance

These values come from the Tron Shasta Testnet API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Tron Shasta Testnet API?

Authentication is handled by passing an API key in the 'TRON-PRO-API-KEY' HTTP header. While unauthenticated requests are permitted, they are subject to severe rate limits.

1. Get your credentials

To obtain an API key for the TronGrid service (which powers the Shasta Testnet API), perform the following steps: 1. Navigate to the official TronGrid website (https://www.trongrid.io/). 2. Sign up for an account or log in if you already have one. 3. Upon logging in, you will be directed to the dashboard. 4. Locate and click on the "Create API Key" button. 5. Once generated, your API key will be accessible in the API key list on your dashboard, where you can also manage settings, quotas, and security configurations. Note: While API keys are required for Mainnet production traffic, access to the Shasta Testnet via TronGrid may not strictly require one, though it is recommended for consistent usage.

2. Add them to .dlt/secrets.toml

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[sources.tron_shasta_testnet_source]
tron_shasta_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.

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What Tron Shasta Testnet data can I load into DuckDB?

These are the Tron Shasta Testnet endpoints dlt can load into DuckDB:

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How do I load only new Tron Shasta Testnet records?

The Tron Shasta Testnet 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.

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{"name": "asset_issues", "endpoint": {
    "path": "wallet/getpaginatedassetissuelist",
    # 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.

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What does the generated Tron Shasta Testnet pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading https://api.shasta.trongrid.io and https://api.shasta.trongrid.io/jsonrpc from the Tron Shasta Testnet API into DuckDB:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def tron_shasta_testnet_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.shasta.trongrid.io",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "asset_issues", "endpoint": {"path": "wallet/getpaginatedassetissuelist", "data_selector": "assetIssue"}},
            {"name": "witnesses", "endpoint": {"path": "wallet/getpaginatednowwitnesslist", "data_selector": "witnesses"}}
        ],
    }
    yield from rest_api_resources(config)


def load_tron_shasta_testnet_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="tron_shasta_testnet_pipeline",
        destination="duckdb",
        dataset_name="tron_shasta_testnet_data",
    )
    load_info = pipeline.run(tron_shasta_testnet_source())
    print(load_info)


if __name__ == "__main__":
    load_tron_shasta_testnet_to_duckdb()

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

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How do I query Tron Shasta Testnet 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):

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import dlt

data = dlt.pipeline("tron_shasta_testnet_pipeline").dataset()
df = data.asset_issues.df()
print(df.head())

SQL:

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SELECT * FROM tron_shasta_testnet_data.asset_issues LIMIT 10;

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

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How do I deploy the Tron Shasta Testnet 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 Tron Shasta Testnet loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Tron Shasta Testnet data to?

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

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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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack