ericm-db opened a new pull request, #57684:
URL: https://github.com/apache/spark/pull/57684

   ### What changes were proposed in this pull request?
   
   This patch extracts the reusable pieces of local Spark Connect server 
startup from the
   persistent-server reuse path:
   
   - expose the per-user runtime directory and startup seed configuration as 
module helpers;
   - add `LocalConnectServer.start()` as the common lifecycle-owned launch 
entry point; and
   - let the launcher use an ephemeral port and a precomputed startup 
configuration when requested.
   
   The existing reuse path now calls the same `LocalConnectServer.start()` 
method. Focused tests
   cover seed configuration and delegation of the new launch options.
   
   This is the behavior-preserving foundation for #57102, which uses it to 
start isolated pool
   members without reaching through `LocalConnectServer` or duplicating daemon 
launch logic.
   
   ### Why are the changes needed?
   
   The persistent reuse mode currently combines reusable local-server lifecycle 
handling with
   assumptions specific to its one fixed daemon. The single-use server pool 
needs the same secure
   configuration seeding, process launch, discovery, and readiness handling, 
but with independent
   runtime directories and ephemeral ports. Sharing one launch path keeps those 
behaviors
   consistent and isolates the larger feature from the already-working reuse 
implementation.
   
   ### Does this PR introduce _any_ user-facing change?
   
   No.
   
   ### How was this patch tested?
   
   Added focused unit coverage to
   
`pyspark.sql.tests.connect.test_connect_local_server.LocalConnectServerReuseTests`
 and ran the
   full suite, including real daemon startup, reuse, session isolation, and 
static configuration
   seeding:
   
   ```bash
   python -m unittest -v pyspark.sql.tests.connect.test_connect_local_server
   ```
   
   All 15 tests passed.
   
   ### Was this patch authored or co-authored using generative AI tooling?
   
   Generated-by: Claude Code (Fable 5) and OpenAI Codex (GPT-5)
   


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