Load Progress OpenEdge data to DuckDB

Progress Application Server (PAS) for OpenEdge provides a REST transport layer that enables ABL business applications to function as resource servers supporting OAuth2, JWT, and session-based authentication. Everything needed to build a working Progress OpenEdge → 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 Progress OpenEdge 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 Progress OpenEdge 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 Progress OpenEdge 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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Progress OpenEdge API at a glance

These values come from the Progress OpenEdge API documentation. Check them against the vendor's current reference before relying on them in production.

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How do I authenticate with the Progress OpenEdge API?

For OAuth2/JWT authentication, requests must include an Authorization HTTP header with the scheme set to 'Bearer' and the token. For session-based authentication, a 'Cookie' header containing the JSESSIONID is required following a successful login.

1. Get your credentials

Progress OpenEdge does not have a single, unified "API key dashboard" for end-user REST APIs. Instead, security is configured at the Application Server (PASOE) level. To secure your service, you must configure authentication within the 'oeablSecurity.properties' file (typically setting a login model like OAuth2 or Basic Auth). For management REST APIs (e.g., 'oemanager.war'), access is controlled by the security settings of the PASOE instance; you access these by providing credentials associated with an authorized user account defined in the server's identity provider (e.g., local users or LDAP). To manage these, developers typically use the 'oemanager' interface or command-line tools to deploy and secure services.

2. Add them to .dlt/secrets.toml

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[sources.progress_openedge_source]
openedge_username = "your_username"
openedge_password = "your_password"
# For custom API key implementations (often passed via custom headers):
x_api_key = "your_secret_api_key_value"

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 Progress OpenEdge data can I load into DuckDB?

These are the Progress OpenEdge endpoints dlt can load into DuckDB:

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How do I load only new Progress OpenEdge records?

Progress OpenEdge exposes skip on {service_name}/{resource_name}, 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": "data_object_read", "endpoint": {
    "path": "{service_name}/{resource_name}",
    "data_selector": "dsCustomer",
    "incremental": {"cursor_path": "skip", "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 Progress OpenEdge pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /oemanager and /rest from the Progress OpenEdge API into DuckDB:

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

@dlt.source
def progress_openedge_source(token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "http://host:port/[web-app]/rest",
            "auth": {"type": "bearer", "token": token},
        },
        "resources": [
            {"name": "data_object_read", "endpoint": {"path": "{service_name}/{resource_name}", "data_selector": "dsCustomer"}},
            {"name": "data_object_create", "endpoint": {"path": "{service_name}/{resource_name}"}}
        ],
    }
    yield from rest_api_resources(config)


def load_progress_openedge_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="progress_openedge_pipeline",
        destination="duckdb",
        dataset_name="progress_openedge_data",
    )
    load_info = pipeline.run(progress_openedge_source())
    print(load_info)


if __name__ == "__main__":
    load_progress_openedge_to_duckdb()

Run it with python progress_openedge_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 Progress OpenEdge 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("progress_openedge_pipeline").dataset()
df = data.data_object_read.df()
print(df.head())

SQL:

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SELECT * FROM progress_openedge_data.data_object_read LIMIT 10;

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

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How do I deploy the Progress OpenEdge 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 Progress OpenEdge 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 Progress OpenEdge 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