# Python SDK

The primary mechanism for submitting data to Distributional is through our Python SDK.  This section servers as a reference for the various functionalities available for interacting with DBNL via the SDK.

## Example Usage

Below is a basic working example that highlights the SDK workflow.  If you have not yet installed the SDK, follow [these instructions](/v0.23.x/install-sdk.md#installing-distributional).

```python
import dbnl
import numpy as np
import pandas as pd


num_results = 500
test_data = pd.DataFrame({
    "idx": np.arange(num_results),
    "age": np.random.randint(5,95, num_results),
    "loc": np.random.choice(["NY", "CA", "FL"], num_results),
    "churn_gtruth": np.random.choice([True, False], num_results)
})

# example user ml app / model
def churn_predictor(input):
    return 1.0 / (1.0 + np.exp(-(input["age"] / 10.0 - 3.5)))

def evaluate_predicton(data):
    return (data["churn_score"] > 0.5 and data["churn_gtruth"]) or \
            (data["churn_score"] < 0.5 and not data["churn_gtruth"])

test_data["churn_score"] = test_data.apply(churn_predictor, axis=1)
test_data["pred_correct"] = test_data.apply(evaluate_predicton, axis=1)
test_data = test_data.astype({"age": "int", "loc": "category"})

# Use DBNL
dbnl.login(api_token="<COPY_PASTE_DBNL_API_TOKEN>")
proj = dbnl.get_or_create_project(name="example_churn_predictor")
run = dbnl.report_run_with_results(
    project=proj,
    column_data=test_data,
    row_id=["idx"],
)
```


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.dbnl.com/v0.23.x/reference/python-sdk.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.