Poeditor Python API Docs | dltHub

Poeditor is a translation management and localization platform providing an API to manage projects, languages, terms and translations. The REST API base URL is https://api.poeditor.com/v2 and All requests require an api_token parameter 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 Poeditor data in under 10 minutes.

---

What data can I load from Poeditor?

Here are some of the endpoints you can load from Poeditor:

---

How do I authenticate with the Poeditor API?

Authentication is done by including the api_token parameter (your API key) in every request as form data. The token is obtained from Account > API Access.

1. Get your credentials

1. Log in to POEditor.
2. Go to Account (or Organization) Settings > API Access.
3. Copy the displayed API Token.
4. Optionally regenerate or remove the token from the same page.

2. Add them to .dlt/secrets.toml

Copy
[sources.poeditor_source]
api_token = "your_api_token_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.

---

How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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

1. Install the dlt AI Workbench:

Copy
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:

Copy
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 Poeditor 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:

Copy
python poeditor_pipeline.py

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

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

Inspect your pipeline and data:

Copy
dlt pipeline poeditor_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.

---

Python pipeline example

This example loads projects and languages from the Poeditor API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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

@dlt.source
def poeditor_source(api_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.poeditor.com/v2",
            "auth": {
                "type": "api_key",
                "api_token": api_token,
            },
        },
        "resources": [
            {"name": "projects", "endpoint": {"path": "projects/list", "data_selector": "result.projects"}},
            {"name": "languages", "endpoint": {"path": "languages/list", "data_selector": "result.languages"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="poeditor_pipeline",
        destination="duckdb",
        dataset_name="poeditor_data",
    )
    load_info = pipeline.run(poeditor_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.

---

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):

Copy
import dlt

data = dlt.pipeline("poeditor_pipeline").dataset()
sessions_df = data.terms.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM poeditor_data.terms LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("poeditor_pipeline").dataset()
data.terms.df().head()

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

---

What destinations can I load Poeditor 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.

---

Troubleshooting

Authentication failures

If you omit or use an invalid api_token the API returns an error JSON with an error code and message; ensure api_token is present in every request and that you copied it from Account > API Access. Regenerate the token if compromised.

Rate limits and throttling

POEditor enforces per‑account rate limits and concurrent queue limits. Free accounts: 100 requests/min, 2000/hour, 60 concurrent queue; Paid/Enterprise have higher limits. Exceeding limits returns HTTP 429 Too many requests. For uploads there is a separate throttle (1 per 20s for free, 1 per 10s for paid).

Insufficient permissions

Some endpoints require write‑capable tokens. If token lacks write permissions the API returns an error code (e.g., 4030 Insufficient access rights). Use a token with appropriate permissions for write operations.

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

---

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.

Copy
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