[beam] 01/01: Update python-pipeline-dependencies.md

[tv...@apache.org]

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tvalentyn pushed a commit to branch tvalentyn-patch-3
in repository https://gitbox.apache.org/repos/asf/beam.git

commit dc5dc93ec2216133057aecf5e1208b8d22094757
Author: tvalentyn <tv...@users.noreply.github.com>
AuthorDate: Wed Aug 16 14:22:50 2023 -0700

    Update python-pipeline-dependencies.md
    
    Update a broken link.
---
 .../content/en/documentation/sdks/python-pipeline-dependencies.md     | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/website/www/site/content/en/documentation/sdks/python-pipeline-dependencies.md b/website/www/site/content/en/documentation/sdks/python-pipeline-dependencies.md
index d41ac78161f..025540cfb52 100644
--- a/website/www/site/content/en/documentation/sdks/python-pipeline-dependencies.md
+++ b/website/www/site/content/en/documentation/sdks/python-pipeline-dependencies.md
@@ -150,7 +150,7 @@ To use the `cloudpickle` pickler, supply the `--pickle_library=cloudpickle` pipe
 By default, global imports, functions, and variables defined in the main pipeline module are not saved during the serialization of a Beam job.
 Thus, one might encounter an unexpected `NameError` when running a `DoFn` on any remote runner. To resolve this, supply the main session content with the pipeline by
 setting the `--save_main_session` pipeline option. This will load the pickled state of the global namespace onto the Dataflow workers (if using `DataflowRunner`).
-For example, see [Handling NameErrors](https://cloud.google.com/dataflow/docs/guides/common-errors#how-do-i-handle-nameerrors) to set the main session on the `DataflowRunner`.
+For example, see [Handling NameErrors](https://cloud.google.com/dataflow/docs/guides/common-errors#name-error) to set the main session on the `DataflowRunner`.
 
 Managing the main session in Python SDK is only necessary when using `dill` pickler on any remote runner. Therefore, this issue will
 not occur in `DirectRunner`.
@@ -235,4 +235,4 @@ The Apache Beam version and the Python major.minor versions must match in the su
 
 To check whether the runtime environment matches the launch environment, inspect differences in the `pip freeze` output in both environments. Update to the latest version of Beam, because environment compatibility checks are included in newer SDK versions.
 
-Finally, you can use the same environment by launching the pipeline from the  containerized environment that you use at runtime. [Dataflow Flex templates built from a custom container image](https://cloud.google.com/dataflow/docs/guides/templates/configuring-flex-templates#use_custom_container_images) offer this setup. In this scenario, you can recreate both launch and runtime environments in a reproducible manner. Because both containers are created from the same image, the launch and r [...]
\ No newline at end of file
+Finally, you can use the same environment by launching the pipeline from the  containerized environment that you use at runtime. [Dataflow Flex templates built from a custom container image](https://cloud.google.com/dataflow/docs/guides/templates/configuring-flex-templates#use_custom_container_images) offer this setup. In this scenario, you can recreate both launch and runtime environments in a reproducible manner. Because both containers are created from the same image, the launch and r [...]