---
title: Enable Dynamic Instrumentation for Python
description: >-
  Set up Dynamic Instrumentation for Python applications to add probes and
  capture data without code changes.
breadcrumbs: >-
  Docs > APM > Application Instrumentation > Dynamic Instrumentation > Enabling
  Dynamic Instrumentation > Enable Dynamic Instrumentation for Python
---

# Enable Dynamic Instrumentation for Python

{% callout %}
# Important note for users on the following Datadog sites: app.ddog-gov.com

{% alert level="danger" %}
This product is not supported for your selected [Datadog site](https://docs.datadoghq.com/getting_started/site). ().
{% /alert %}

{% /callout %}

Dynamic Instrumentation is a feature of the Datadog tracing library that lets you add instrumentation to your application at runtime without code changes or redeployments. Follow these instructions to set up Dynamic Instrumentation for Python.

## Prerequisites{% #prerequisites %}

Before you begin, review the [Dynamic Instrumentation prerequisites](https://docs.datadoghq.com/dynamic_instrumentation/#prerequisites). Python applications also require:

- Tracing library [`ddtrace`](https://github.com/DataDog/dd-trace-py) version 2.2.0 or higher. See the [installation instructions](https://docs.datadoghq.com/tracing/trace_collection/dd_libraries/python/) for setup details.

## Installation{% #installation %}

1. If you don't already have APM enabled, in your Agent configuration, set the `DD_APM_ENABLED` environment variable to `true` and listening to the port `8126/TCP`.

1. Install `ddtrace`, which provides both tracing and Dynamic Instrumentation:

   ```shell
   pip install ddtrace
   ```

1. Run your service with Dynamic Instrumentation enabled by setting the `DD_DYNAMIC_INSTRUMENTATION_ENABLED` environment variable to `true`. Specify `DD_SERVICE`, `DD_ENV`, and `DD_VERSION` Unified Service Tags so you can filter and group your instrumentations and target active clients across these dimensions.

   {% tab title="Environment variables" %}
Invoke your service:

   ```shell
   export DD_SERVICE=<YOUR_SERVICE>
   export DD_ENV=<YOUR_ENV>
   export DD_VERSION=<YOUR_VERSION>
   export DD_DYNAMIC_INSTRUMENTATION_ENABLED=true
   ddtrace-run python -m myapp.py
   ```

      {% /tab %}

   {% tab title="In code" %}

   ```python
   from ddtrace.debugging import DynamicInstrumentation
   
   DynamicInstrumentation.enable()
   ```

   {% /tab %}



1. After starting your service with Dynamic Instrumentation enabled, you can start using it on the [APM > Dynamic Instrumentation page](https://app.datadoghq.com/dynamic-instrumentation).

## Configuration{% #configuration %}

Configure Dynamic Instrumentation using the following environment variables:

| Environment variable                 | Type    | Description                                                                                                                    |
| ------------------------------------ | ------- | ------------------------------------------------------------------------------------------------------------------------------ |
| `DD_DYNAMIC_INSTRUMENTATION_ENABLED` | Boolean | Set to `true` to enable Dynamic Instrumentation.                                                                               |
| `DD_SERVICE`                         | String  | The [service](https://docs.datadoghq.com/getting_started/tagging/unified_service_tagging) name, for example, `web-backend`.    |
| `DD_ENV`                             | String  | The [environment](https://docs.datadoghq.com/getting_started/tagging/unified_service_tagging) name, for example, `production`. |
| `DD_VERSION`                         | String  | The [version](https://docs.datadoghq.com/getting_started/tagging/unified_service_tagging) of your service.                     |
| `DD_TAGS`                            | String  | Tags to apply to produced data. Must be a list of `<key>:<value>` separated by commas such as: `layer:api, team:intake`.       |

## What to do next{% #what-to-do-next %}

See [Dynamic Instrumentation](https://docs.datadoghq.com/dynamic_instrumentation/) for information about adding instrumentations and browsing and indexing the data.

## Further reading{% #further-reading %}

- [Getting Started with Datadog Agent](https://docs.datadoghq.com/agent/)