Load Ansys Mechanical data to DuckDB

Ansys Mechanical provides scripting and programming interfaces for automating mechanical simulation tasks and accessing application functionality through PyMechanical or gRPC-based connections. Everything needed to build a working Ansys Mechanical → 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 Ansys Mechanical 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 Ansys Mechanical 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 Ansys Mechanical 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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Ansys Mechanical API at a glance

These values come from the Ansys Mechanical API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Ansys Mechanical API?

Ansys Mechanical typically uses gRPC for remote communication, which supports secure connections via mTLS (using certificates), WNUA (Windows Named User Authentication), or insecure modes instead of standard REST API token headers.

1. Get your credentials

Ansys services typically utilize Personal Access Tokens (PATs) for programmatic authentication via Ansys ID SSO. To obtain one: 1. Sign in to the Ansys ID Portal. 2. Navigate to the token management or security settings section (often under your profile/account settings). 3. Create a new token, providing a descriptive name and appropriate scopes (select Full Access for SSO authentication). 4. Copy the generated token immediately, as it will not be displayed again. For API requests, include this token in the Authorization header using the Bearer scheme: 'Authorization: Bearer <your_access_token>'. Note that the official Ansys Mechanical remote interface currently relies on gRPC, not a documented public REST API.

2. Add them to .dlt/secrets.toml

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[sources.ansys_mechanical_source]
ansys_access_token = "your_pat_or_access_token_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 Ansys Mechanical data can I load into DuckDB?

These are the Ansys Mechanical endpoints dlt can load into DuckDB:

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How do I load only new Ansys Mechanical records?

The Ansys Mechanical 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": "models", "endpoint": {
    "path": "models",
    # 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 Ansys Mechanical pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading run_python_script and list_files (Note: These are methods of the PyMechanical gRPC interface, as Ansys Mechanical does not provide a documented public REST API.) from the Ansys Mechanical API into DuckDB:

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

@dlt.source
def ansys_mechanical_source(transport_mode=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "Typically accessed via host and port (e.g., 127.0.0.1:10000) for gRPC communication.",
            "auth": {"type": "bearer", "token": transport_mode},
        },
        "resources": [
            {"name": "models", "endpoint": {"path": "models"}},
            {"name": "results", "endpoint": {"path": "results"}}
        ],
    }
    yield from rest_api_resources(config)


def load_ansys_mechanical_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="ansys_mechanical_pipeline",
        destination="duckdb",
        dataset_name="ansys_mechanical_data",
    )
    load_info = pipeline.run(ansys_mechanical_source())
    print(load_info)


if __name__ == "__main__":
    load_ansys_mechanical_to_duckdb()

Run it with python ansys_mechanical_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 Ansys Mechanical 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("ansys_mechanical_pipeline").dataset()
df = data.models.df()
print(df.head())

SQL:

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SELECT * FROM ansys_mechanical_data.models LIMIT 10;

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

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How do I deploy the Ansys Mechanical 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 Ansys Mechanical 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 Ansys Mechanical 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