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https://issues.apache.org/jira/browse/BEAM-8280?focusedWorklogId=418778&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-418778
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ASF GitHub Bot logged work on BEAM-8280:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 08/Apr/20 18:22
            Start Date: 08/Apr/20 18:22
    Worklog Time Spent: 10m 
      Work Description: udim commented on pull request #11232: [BEAM-8280] 
Document Python 3 annotations support
URL: https://github.com/apache/beam/pull/11232#discussion_r405715326
 
 

 ##########
 File path: website/src/documentation/sdks/python-type-safety.md
 ##########
 @@ -23,38 +23,58 @@ Python is a dynamically-typed language with no static type 
checking. Because of
 
 The Apache Beam SDK for Python uses **type hints** during pipeline 
construction and runtime to try to emulate the correctness guarantees achieved 
by true static typing. Additionally, using type hints lays some groundwork that 
allows the backend service to perform efficient type deduction and registration 
of `Coder` objects.
 
-Python version 3.5 introduces a module called **typing** to provide hints for 
type validators in the language. The Beam SDK for Python, based on Python 
version 2.7, implements a subset of [PEP 
484](https://www.python.org/dev/peps/pep-0484/) and aims to follow it as 
closely as possible in its own typehints module.
+Python version 3.5 introduces a module called **typing** to provide hints for 
type validators in the language.
+The Beam SDK for Python implements a subset of [PEP 
484](https://www.python.org/dev/peps/pep-0484/) and aims to follow it as 
closely as possible in its own typehints module.
+
+These flags control Beam type safety:
+- `--no_pipeline_type_check`
+
+  Disables type checking during pipeline construction.
+  Default is to perform these checks.
+- `--runtime_type_check`
+
+  Enables runtime type checking of every element.
+  This may affect pipeline performance, so the default is to skip these checks.
 
 ## Benefits of Type Hints
 
-The Beam SDK for Python includes some automatic type checking: for example, 
some `PTransform`s, such as `Create` and simple `ParDo` transforms, attempt to 
deduce their output type given their input. However, the Beam cannot infer 
types in all cases. Therefore, the recommendation is that you declare type 
hints to aid you in performing your own type checks if necessary.
+The Beam SDK for Python includes some automatic type checking: for example, 
some `PTransforms`, such as `Create` and simple `ParDo` transforms, attempt to 
deduce their output type given their input. However, the Beam cannot infer 
types in all cases. Therefore, the recommendation is that you declare type 
hints to aid you in performing your own type checks if necessary.
 
-When you use type hints, the runner raises exceptions during pipeline 
construction time, rather than runtime. For example, the runner generates an 
exception if it detects that your pipeline applies mismatched `PTransforms` 
(where the expected outputs of one transform do not match the expected inputs 
of the following transform). These exceptions are raised at pipeline 
construction time, regardless of where your pipeline will execute. Introducing 
type hints for the `PTransform`s you define allows you to catch potential bugs 
up front in the local runner, rather than after minutes of execution into a 
deep, complex pipeline.
+When you use type hints, the runner raises exceptions during pipeline 
construction time, rather than runtime. For example, the runner generates an 
exception if it detects that your pipeline applies mismatched `PTransforms` 
(where the expected outputs of one transform do not match the expected inputs 
of the following transform). These exceptions are raised at pipeline 
construction time, regardless of where your pipeline will execute. Introducing 
type hints for the `PTransforms` you define allows you to catch potential bugs 
up front in the local runner, rather than after minutes of execution into a 
deep, complex pipeline.
 
 Review comment:
   Done. Also reworded this paragraph a bit.
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 418778)
    Time Spent: 12h 10m  (was: 12h)

> re-enable IOTypeHints.from_callable
> -----------------------------------
>
>                 Key: BEAM-8280
>                 URL: https://issues.apache.org/jira/browse/BEAM-8280
>             Project: Beam
>          Issue Type: Bug
>          Components: sdk-py-core
>            Reporter: Udi Meiri
>            Assignee: Udi Meiri
>            Priority: Major
>          Time Spent: 12h 10m
>  Remaining Estimate: 0h
>
> See https://issues.apache.org/jira/browse/BEAM-8279



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