---
title: "Learn: shape data with Python | Grafana Cloud documentation"
description: "A runnable example of the Python step. Reshapes a list of alerts, finds noisy services, and passes the result to the next step as JSON. No setup needed."
---

> For a curated documentation index, see [llms.txt](/llms.txt). For the complete documentation index, see [llms-full.txt](/llms-full.txt).

# Learn: shape data with Python

> Note
> 
> Grafana Workflows is currently in [public preview](https://grafana.com/docs/release-life-cycle/). Grafana Labs offers limited support, and breaking changes might occur prior to the feature being made generally available.

A runnable example of the Python step. Reshapes a list of alerts, finds noisy services, and passes the result to the next step as JSON. No setup needed.

This Grafana Workflows blueprint is in the **Basics** category of the Blueprints library.

## Before you begin

This blueprint needs no integrations or secrets.

## Steps

Steps run in order from first to last. A step inside a switch branch runs only when Workflows chooses that branch.

Expand table

| Step                      | ID              | Type           | Description                                                                                              |
|---------------------------|-----------------|----------------|----------------------------------------------------------------------------------------------------------|
| Group alerts by service   | `shape`         | `code.execute` | Counts alerts per service and flags services at or above `noisyThreshold`. Change the threshold in args. |
| Fail if the script failed | `check-success` | `filter`       | Fails the run when the Python code raised an exception. Check the stderr and error outputs for details.  |
| Read the Python output    | `report`        | `transform`    | Parses the script’s stdout with `json_parse()` and reads fields from it.                                 |

For the inputs and outputs of each step type, refer to [Step and trigger types reference](https://grafana.com/docs/grafana-cloud/platform/workflows/reference/step-trigger-types).

Before you turn on the workflow, customize any steps that need input from you, such as a channel ID or a schedule name. Each step’s description says what to set.

## Workflow definition

Save this definition as a YAML file to create the workflow with gcx, the Workflows API, or Terraform, or give it to a coding agent as an example. Replace *FOLDER\_UID* with the UID of the folder for the workflow. Blueprints start disabled, so finish customizing the steps before you set `enabled` to `true`. For details, refer to [Manage workflows as code](https://grafana.com/docs/grafana-cloud/platform/workflows/as-code).

YAML ![Copy code to clipboard](https://grafana.com/media/images/icons/icon-copy-small-2.svg) Copy

```yaml
apiVersion: workflows.ext.grafana.app/v1alpha1
kind: Definition
metadata:
  name: learn-python-data-shaping
  annotations:
    grafana.app/folder: <FOLDER_UID>
spec:
  name: 'Learn: shape data with Python'
  enabled: false
  startWhen:
    matchingRules: []
    schedules: []
  steps:
    - id: shape
      type: code.execute
      name: Group alerts by service
      description: Counts alerts per service and flags services at or above noisyThreshold. Change the threshold in args.
      inputs:
        language: 'python'
        args: '{"noisyThreshold": 2}'
        code: |
          import json
          from collections import Counter

          alerts = context["inputs"].get("data", {}).get("alerts", [])
          per_service = Counter(alert.get("service", "unknown") for alert in alerts)
          threshold = args.get("noisyThreshold", 2)

          print(json.dumps({
              "total": len(alerts),
              "perService": dict(per_service),
              "noisyServices": sorted(s for s, n in per_service.items() if n >= threshold),
          }))
    - id: check-success
      type: filter
      name: Fail if the script failed
      description: Fails the run when the Python code raised an exception. Check the stderr and error outputs for details.
      inputs:
        condition: 'steps.shape.outputs.success == true'
        failOnExit: 'true'
    - id: report
      type: transform
      name: Read the Python output
      description: Parses the script's stdout with json_parse() and reads fields from it.
      inputs:
        template: "${string(json_parse(steps.shape.outputs.stdout).total)} alerts. Noisy services: ${json_stringify(json_parse(steps.shape.outputs.stdout).noisyServices)}"
```

## How it works

This section explains when the workflow runs and how its steps work together.

### When it runs

This blueprint has no event or schedule trigger, so it runs only when you start it manually.

### How the steps fit together

These notes cover how the steps connect and which Workflows behaviors the blueprint relies on.

- Manual-only workflow that needs no integrations.
- Suggested test payload data: {“alerts”: \[{“service”: “checkout”, “severity”: “critical”}, {“service”: “checkout”, “severity”: “warning”}, {“service”: “search”, “severity”: “warning”}, {“service”: “checkout”, “severity”: “critical”}]}.
- It shows the `code.execute` contract.
- The workflow context is available as a dict named context, with inputs, steps, and resources (secrets are removed).
- args is a JSON string input, deserialized into a dict named args, and its values can contain `${...}` expressions.
- The script prints a single JSON object to stdout, and later steps read it with `json_parse(steps.<id>.outputs.stdout)`.
- A filter with `failOnExit` turns a Python exception (success false) into a failed run.
- The sandbox has no network access, so pair it with `http.call` to process API responses.

## Next steps

- [Blueprints](https://grafana.com/docs/grafana-cloud/platform/workflows/reference/blueprints)
- [Start from a blueprint](https://grafana.com/docs/grafana-cloud/platform/workflows/build/use-blueprints)
- [Manage workflows as code](https://grafana.com/docs/grafana-cloud/platform/workflows/as-code)
- [Step and trigger types reference](https://grafana.com/docs/grafana-cloud/platform/workflows/reference/step-trigger-types)