Load Chart Image data to DuckDB

Image-Charts is an API service that generates chart images from URL parameters such as chart type, data, and size. Everything needed to build a working Chart Image → 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 Chart Image 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 Chart Image 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 Chart Image 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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Chart Image API at a glance

These values come from the Chart Image API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Chart Image API?

The service uses HMAC-SHA256 signing for authenticated requests, which requires an account ID and secret key to sign parameters. These are passed as URL query parameters 'icac' (account ID) and 'ichm' (HMAC signature).

1. Get your credentials

To obtain an API key for the Chart Image REST API (e.g., chart-img.com), navigate to the service homepage, sign in using your Google account (no formal registration is required), and visit the account dashboard or profile section where your personal API key will be generated and displayed.

2. Add them to .dlt/secrets.toml

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[sources.chart_image_source]
api_key = "your_actual_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 Chart Image data can I load into DuckDB?

These are the Chart Image endpoints dlt can load into DuckDB:

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How do I load only new Chart Image records?

Chart Image exposes after on v1/charts, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "hex_charts", "endpoint": {
    "path": "v1/charts",
    "data_selector": "items",
    "incremental": {"cursor_path": "after", "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 Chart Image pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /chart and /status from the Chart Image API into DuckDB:

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

@dlt.source
def chart_image_source(secret_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://image-charts.com",
            "auth": {"type": "bearer", "token": secret_key},
        },
        "resources": [
            {"name": "hex_charts", "endpoint": {"path": "v1/charts", "data_selector": "items"}},
            {"name": "hex_projects", "endpoint": {"path": "v1/projects", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def load_chart_image_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="chart_image_pipeline",
        destination="duckdb",
        dataset_name="chart_image_data",
    )
    load_info = pipeline.run(chart_image_source())
    print(load_info)


if __name__ == "__main__":
    load_chart_image_to_duckdb()

Run it with python chart_image_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 Chart Image 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("chart_image_pipeline").dataset()
df = data.hex_charts.df()
print(df.head())

SQL:

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SELECT * FROM chart_image_data.hex_charts LIMIT 10;

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

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How do I deploy the Chart Image 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 Chart Image 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 Chart Image 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