[Workflow] Add Python samples to patterns doc

Signed-off-by: Chris Gillum <cgillum@microsoft.com>
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Chris Gillum 2023-06-08 10:44:05 -07:00
parent 3d8b8a6103
commit b4f1e85d4b
1 changed files with 97 additions and 10 deletions

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@ -25,9 +25,10 @@ While the pattern is simple, there are many complexities hidden in the implement
Dapr Workflow solves these complexities by allowing you to implement the task chaining pattern concisely as a simple function in the programming language of your choice, as shown in the following example. Dapr Workflow solves these complexities by allowing you to implement the task chaining pattern concisely as a simple function in the programming language of your choice, as shown in the following example.
{{< tabs ".NET" >}} {{< tabs ".NET" Python >}}
{{% codetab %}} {{% codetab %}}
<!--dotnet-->
```csharp ```csharp
// Expotential backoff retry policy that survives long outages // Expotential backoff retry policy that survives long outages
@ -45,7 +46,6 @@ try
var result1 = await context.CallActivityAsync<string>("Step1", wfInput, retryOptions); var result1 = await context.CallActivityAsync<string>("Step1", wfInput, retryOptions);
var result2 = await context.CallActivityAsync<byte[]>("Step2", result1, retryOptions); var result2 = await context.CallActivityAsync<byte[]>("Step2", result1, retryOptions);
var result3 = await context.CallActivityAsync<long[]>("Step3", result2, retryOptions); var result3 = await context.CallActivityAsync<long[]>("Step3", result2, retryOptions);
var result4 = await context.CallActivityAsync<Guid[]>("Step4", result3, retryOptions);
return string.Join(", ", result4); return string.Join(", ", result4);
} }
catch (TaskFailedException) // Task failures are surfaced as TaskFailedException catch (TaskFailedException) // Task failures are surfaced as TaskFailedException
@ -56,14 +56,61 @@ catch (TaskFailedException) // Task failures are surfaced as TaskFailedException
} }
``` ```
{{% alert title="Note" color="primary" %}}
In the example above, `"Step1"`, `"Step2"`, `"Step3"`, and `"MyCompensation"` represent workflow activities, which are functions in your code that actually implement the steps of the workflow. For brevity, these activity implementations are left out of this example.
{{% /alert %}}
{{% /codetab %}}
{{% codetab %}}
<!--python-->
```python
import dapr.ext.workflow as wf
def task_chain_workflow(ctx: wf.DaprWorkflowContext, wf_input: int):
try:
result1 = yield ctx.call_activity(step1, input=wf_input)
result2 = yield ctx.call_activity(step2, input=result1)
result3 = yield ctx.call_activity(step3, input=result2)
except Exception as e:
yield ctx.call_activity(error_handler, input=str(e))
raise
return [result1, result2, result3]
def step1(ctx, activity_input):
print(f'Step 1: Received input: {activity_input}.')
# Do some work
return activity_input + 1
def step2(ctx, activity_input):
print(f'Step 2: Received input: {activity_input}.')
# Do some work
return activity_input * 2
def step3(ctx, activity_input):
print(f'Step 3: Received input: {activity_input}.')
# Do some work
return activity_input ^ 2
def error_handler(ctx, error):
print(f'Executing error handler: {error}.')
# Do some compensating work
```
{{% alert title="Note" color="primary" %}}
Workflow retry policies will be available in a future version of the Python SDK.
{{% /alert %}}
{{% /codetab %}} {{% /codetab %}}
{{< /tabs >}} {{< /tabs >}}
{{% alert title="Note" color="primary" %}}
In the example above, `"Step1"`, `"Step2"`, `"MyCompensation"`, etc. represent workflow activities, which are functions in your code that actually implement the steps of the workflow. For brevity, these activity implementations are left out of this example.
{{% /alert %}}
As you can see, the workflow is expressed as a simple series of statements in the programming language of your choice. This allows any engineer in the organization to quickly understand the end-to-end flow without necessarily needing to understand the end-to-end system architecture. As you can see, the workflow is expressed as a simple series of statements in the programming language of your choice. This allows any engineer in the organization to quickly understand the end-to-end flow without necessarily needing to understand the end-to-end system architecture.
Behind the scenes, the Dapr Workflow runtime: Behind the scenes, the Dapr Workflow runtime:
@ -88,9 +135,10 @@ In addition to the challenges mentioned in [the previous pattern]({{< ref "workf
Dapr Workflows provides a way to express the fan-out/fan-in pattern as a simple function, as shown in the following example: Dapr Workflows provides a way to express the fan-out/fan-in pattern as a simple function, as shown in the following example:
{{< tabs ".NET" >}} {{< tabs ".NET" Python >}}
{{% codetab %}} {{% codetab %}}
<!--dotnet-->
```csharp ```csharp
// Get a list of N work items to process in parallel. // Get a list of N work items to process in parallel.
@ -114,6 +162,15 @@ await context.CallActivityAsync("PostResults", sum);
{{% /codetab %}} {{% /codetab %}}
{{% codetab %}}
<!--python-->
```python
# TODO
```
{{% /codetab %}}
{{< /tabs >}} {{< /tabs >}}
The key takeaways from this example are: The key takeaways from this example are:
@ -214,9 +271,10 @@ Depending on the business needs, there may be a single monitor or there may be m
Dapr Workflow supports this pattern natively by allowing you to implement _eternal workflows_. Rather than writing infinite while-loops ([which is an anti-pattern]({{< ref "workflow-features-concepts.md#infinite-loops-and-eternal-workflows" >}})), Dapr Workflow exposes a _continue-as-new_ API that workflow authors can use to restart a workflow function from the beginning with a new input. Dapr Workflow supports this pattern natively by allowing you to implement _eternal workflows_. Rather than writing infinite while-loops ([which is an anti-pattern]({{< ref "workflow-features-concepts.md#infinite-loops-and-eternal-workflows" >}})), Dapr Workflow exposes a _continue-as-new_ API that workflow authors can use to restart a workflow function from the beginning with a new input.
{{< tabs ".NET" >}} {{< tabs ".NET" Python >}}
{{% codetab %}} {{% codetab %}}
<!--dotnet-->
```csharp ```csharp
public override async Task<object> RunAsync(WorkflowContext context, MyEntityState myEntityState) public override async Task<object> RunAsync(WorkflowContext context, MyEntityState myEntityState)
@ -256,6 +314,15 @@ public override async Task<object> RunAsync(WorkflowContext context, MyEntitySta
{{% /codetab %}} {{% /codetab %}}
{{% codetab %}}
<!--python-->
```python
# TODO
```
{{% /codetab %}}
{{< /tabs >}} {{< /tabs >}}
A workflow implementing the monitor pattern can loop forever or it can terminate itself gracefully by not calling _continue-as-new_. A workflow implementing the monitor pattern can loop forever or it can terminate itself gracefully by not calling _continue-as-new_.
@ -284,9 +351,10 @@ The following diagram illustrates this flow.
The following example code shows how this pattern can be implemented using Dapr Workflow. The following example code shows how this pattern can be implemented using Dapr Workflow.
{{< tabs ".NET" >}} {{< tabs ".NET" Python >}}
{{% codetab %}} {{% codetab %}}
<!--dotnet-->
```csharp ```csharp
public override async Task<OrderResult> RunAsync(WorkflowContext context, OrderPayload order) public override async Task<OrderResult> RunAsync(WorkflowContext context, OrderPayload order)
@ -331,13 +399,23 @@ In the example above, `RequestApprovalActivity` is the name of a workflow activi
{{% /codetab %}} {{% /codetab %}}
{{% codetab %}}
<!--python-->
```python
# TODO
```
{{% /codetab %}}
{{< /tabs >}} {{< /tabs >}}
The code that delivers the event to resume the workflow execution is external to the workflow. Workflow events can be delivered to a waiting workflow instance using the [raise event]({{< ref "howto-manage-workflow.md#raise-an-event" >}}) workflow management API, as shown in the following example: The code that delivers the event to resume the workflow execution is external to the workflow. Workflow events can be delivered to a waiting workflow instance using the [raise event]({{< ref "howto-manage-workflow.md#raise-an-event" >}}) workflow management API, as shown in the following example:
{{< tabs ".NET" >}} {{< tabs ".NET" Python >}}
{{% codetab %}} {{% codetab %}}
<!--dotnet-->
```csharp ```csharp
// Raise the workflow event to the waiting workflow // Raise the workflow event to the waiting workflow
@ -350,6 +428,15 @@ await daprClient.RaiseWorkflowEventAsync(
{{% /codetab %}} {{% /codetab %}}
{{% codetab %}}
<!--python-->
```python
# TODO
```
{{% /codetab %}}
{{< /tabs >}} {{< /tabs >}}
External events don't have to be directly triggered by humans. They can also be triggered by other systems. For example, a workflow may need to pause and wait for a payment to be received. In this case, a payment system might publish an event to a pub/sub topic on receipt of a payment, and a listener on that topic can raise an event to the workflow using the raise event workflow API. External events don't have to be directly triggered by humans. They can also be triggered by other systems. For example, a workflow may need to pause and wait for a payment to be received. In this case, a payment system might publish an event to a pub/sub topic on receipt of a payment, and a listener on that topic can raise an event to the workflow using the raise event workflow API.