SYSTRAN Translate API Python API Docs | dltHub

SYSTRAN Translate API is a RESTful translation service that programmatically translates text and files between languages. The REST API base URL is https://api-translate.systran.net and All requests require either a Bearer access token or an API Key for authentication..

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 SYSTRAN Translate API data in under 10 minutes.

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What data can I load from SYSTRAN Translate API?

Here are some of the endpoints you can load from SYSTRAN Translate API:

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How do I authenticate with the SYSTRAN Translate API API?

The API accepts either a Bearer access token via the Authorization header (Authorization: Bearer YOUR_ACCESS_TOKEN) or an API Key provided either in the Authorization header as "Key YOUR_API_KEY" or as the query parameter key=YOUR_API_KEY.

1. Get your credentials

1. Sign in to SYSTRAN Translate at https://translate.systran.net or to the SYSTRAN authorization server (ses-console).\n2. Navigate to My Account → Settings → API Keys.\n3. Create a new API Key and copy its value.\n4. (Optional) Register an OAuth client to obtain client credentials.\n5. For OAuth, request an access token using the Client Credentials flow or PKCE and use the returned access_token as a Bearer token in the Authorization header.

2. Add them to .dlt/secrets.toml

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[sources.systran_translate_api_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 SYSTRAN Translate API 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 systran_translate_api_pipeline.py

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

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Pipeline systran_translate_api_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset systran_translate_api_data
The duckdb destination used duckdb:/systran_translate_api.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 systran_translate_api_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 supported_languages and supported_formats from the SYSTRAN Translate API 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 systran_translate_api_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api-translate.systran.net",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "supported_languages", "endpoint": {"path": "translation/supportedLanguages"}},
            {"name": "supported_formats", "endpoint": {"path": "translation/supportedFormats", "data_selector": "formats"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="systran_translate_api_pipeline",
        destination="duckdb",
        dataset_name="systran_translate_api_data",
    )
    load_info = pipeline.run(systran_translate_api_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("systran_translate_api_pipeline").dataset()
sessions_df = data.supported_languages.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM systran_translate_api_data.supported_languages LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("systran_translate_api_pipeline").dataset()
data.supported_languages.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 SYSTRAN Translate API 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 400 Bad Request or 401 Unauthorized: ensure you include either Authorization: Bearer <token> or Authorization: Key <api_key> header, or append ?key=<api_key>. Verify the key/token is active and associated with a valid subscription.

Rate limits and subscription

API access is granted only for API and INFINITE subscriptions; calls may be rate limited. If you receive 429 Too Many Requests, contact SYSTRAN support or upgrade your plan.

Async file translation quirks

For async file translations use async=true on submit, poll /translation/file/status with requestId until status=="finished" then GET /translation/file/result. Result may be the raw translated document or a multipart/mixed response when withInfo=true.

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