Espo-crm Python API Docs | dltHub

EspoCRM is a web-based CRM platform exposing a REST API to create, read, update and delete CRM entities and metadata. The REST API base URL is https://{your-espocrm-site}/api/v1 and all requests require an API user credential (X-Api-Key or HMAC header) or valid Basic/Espo-Authorization token..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Espo-crm data in under 10 minutes.

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What data can I load from Espo-crm?

Here are some of the endpoints you can load from Espo-crm:

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How do I authenticate with the Espo-crm API?

EspoCRM supports API Key authentication using the header X-Api-Key: <API_KEY>. Basic authentication uses Authorization: Basic <base64(username:password)> or the Espo-Authorization token header.

1. Get your credentials

1. Log in to EspoCRM as an administrator.
2. Navigate to Administration > Roles, create or select a role that includes API permissions.
3. Go to Administration > API Users and click Create API User.
4. Assign the role created in step 2 to the new API user.
5. Choose the authentication method (API Key or HMAC). For API Key, a key is generated automatically.
6. Copy the generated API key and store it securely; it will be used in the X-Api-Key header for all API requests.

2. Add them to .dlt/secrets.toml

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[sources.espo_crm_source]
api_key = "your_api_key_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

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dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Espo-crm API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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python espo_crm_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline espo_crm_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset espo_crm_data
The duckdb destination used duckdb:/espo_crm.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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dlt pipeline espo_crm_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads app_user and Contact from the Espo-crm API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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

@dlt.source
def espo_crm_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{your-espocrm-site}/api/v1",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "app_user", "endpoint": {"path": "App/user"}},
            {"name": "contact", "endpoint": {"path": "Contact"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="espo_crm_pipeline",
        destination="duckdb",
        dataset_name="espo_crm_data",
    )
    load_info = pipeline.run(espo_crm_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("espo_crm_pipeline").dataset()
sessions_df = data.contact.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM espo_crm_data.contact LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("espo_crm_pipeline").dataset()
data.contact.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load Espo-crm data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Troubleshooting

Authentication failures

If you receive 401 Unauthorized: verify the X-Api-Key header value or Espo‑Authorization credentials; ensure the API User has the correct role and scopes; check token validity by calling GET App/user.

Permission / 403 Forbidden

403 indicates insufficient permissions for the API user. Adjust the user's role in Administration > Roles to grant access to the required entity or action.

Not found / 404

404 means the requested record does not exist or the path is incorrect. Verify entity name and ID formatting.

Conflict / 409

409 signals a conflict such as a locked record or duplicate entry. Review the response message and server logs (data/log).

Pagination and OpenAPI

Espo supports query parameters (select, where, order, limit, offset) for listing endpoints. Retrieve the instance‑specific OpenAPI spec at /api/v1/OpenApi for exact schemas and response keys.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack