remove pin

rubenfiszel · rubenfiszel · commit 9e724226ac0d · 2024-04-04T19:00:43.000+02:00
diff --git a/docs/core_concepts/31_workflows_as_code/index.mdx b/docs/core_concepts/31_workflows_as_code/index.mdx
@@ -5,7 +5,7 @@ import TabItem from '@theme/TabItem';
 
 [Flows](../../flows/1_flow_editor.mdx) are not the only way to write distributed programs that execute distinct jobs. Another approach is to write a program that defines the jobs and their dependencies, and then execute that program. This is known as workflows as code.
 
-![Script in python executing workflow as code](./python_editor.png "Script in python executing workflow as code")
+![Script in python executing workflow as code](./python_editor.png 'Script in python executing workflow as code')
 
 One way of doing this is to use the [API of Windmill](https://app.windmill.dev/openapi.html) itself, to run jobs imperatively, using run_script and run_flow (their sync or async counterparts). This is a powerful way to define workflows, but it can be complex and verbose.
 
@@ -24,12 +24,6 @@ from wmill import task
 import pandas as pd
 import numpy as np
 
-# The pin is important since task is a decorator available only from 1.286.2
-
-#extra_requirements:
-#wmill>=1.286.2
-
-
 @task()
 # You can specify tag to run the task on a specific type of worker, e.g. @task(tag="custom_tag")
 def heavy_compute(n: int):
diff --git a/src/landing/FlowLightSection.tsx b/src/landing/FlowLightSection.tsx
@@ -56,12 +56,6 @@ const features = [
 import pandas as pd
 import numpy as np
 
-# The pin is important since task is a decorator available only from 1.286.2
-
-#extra_requirements:
-#wmill>=1.286.2
-
-
 @task()
 # You can specify tag to run the task on a specific type of worker, e.g. @task(tag="custom_tag")
 def heavy_compute(n: int):
