# Migration from Flyte 1 to Flyte 2

> **📝 Note**
>
> For comprehensive migration reference with detailed API mappings, parameter tables, and complete examples, see [Migration from Flyte 1](https://www.union.ai/docs/v2/union/user-guide/api-reference/migration/_index) in the Reference section.
> An LLM-optimized bundle of the full migration reference is available at [`section.md`](https://www.union.ai/docs/v2/union/user-guide/api-reference/migration/section.md).

You can migrate from Flyte 1 to Flyte 2 by following the steps below:

### 1. Move task configuration to a `TaskEnvironment` object

Instead of configuring the image, hardware resources, and so forth, directly in the task decorator. You configure it in `TaskEnvironment` object. For example:

```python
env = flyte.TaskEnvironment(name="my_task_env")
```

### 2. Replace workflow decorators

Then, you replace the `@workflow` and `@task` decorators with `@env.task` decorators.

### Flyte 1

Here's a simple hello world example with fanout.

```python
import flytekit

@flytekit.task
def hello_world(name: str) -> str:
    return f"Hello, {name}!"

@flytekit.workflow
def main(names: list[str]) -> list[str]:
    return flytekit.map(hello_world)(names)
```

### Flyte 2 Sync

Change all the decorators to `@env.task` and swap out `flytekit.map` with `flyte.map`.
Notice that `flyte.map` is a drop-in replacement for Python's built-in `map` function.

```diff
-@flytekit.task
+@env.task
def hello_world(name: str) -> str:
    return f"Hello, {name}!"

-@flytekit.workflow
+@env.task
def main(names: list[str]) -> list[str]:
    return flyte.map(hello_world, names)
```

> **📝 Note**
>
> Note that the reason our task decorator uses `env` is simply because that is the variable to which we assigned the `TaskEnvironment` above.

### Flyte 2 Async

To take advantage of full concurrency (not just parallelism), use Python async
syntax and the `asyncio` standard library to implement fa-out.

```diff
+import asyncio

@env.task
-def hello_world(name: str) -> str:
+async def hello_world(name: str) -> str:
    return f"Hello, {name}!"

@env.task
-def main(names: list[str]) -> list[str]:
+async def main(names: list[str]) -> list[str]:
-    return flyte.map(hello_world, names)
+    return await asyncio.gather(*[hello_world(name) for name in names])
```

> **📝 Note**
>
> To use Python async syntax, you need to:
> - Use `asyncio.gather()` or `flyte.map()` for parallel execution
> - Add `async`/`await` keywords where you want parallelism
> - Keep existing sync task functions unchanged
>
> Learn more about about the benefits of async in the [Asynchronous Model](https://www.union.ai/docs/v2/union/user-guide/flyte-2/migration/async) guide.

---
**Source**: https://github.com/unionai/unionai-docs/blob/main/content/user-guide/flyte-2/migration.md
**HTML**: https://www.union.ai/docs/v2/union/user-guide/flyte-2/migration/