# Ray 2.32.0 — Ray-2.32.0
- Product: Ray (https://whatsnew.fyi/product/ray)
- Vendor: Anyscale
- Date: 2024-07-10
- Version: 2.32.0
- Original notes: https://github.com/ray-project/ray/releases/tag/ray-2.32.0
- Permalink: https://whatsnew.fyi/product/ray/releases/2.32.0
What's New is an index, not a publisher: every entry below links to the vendor's own release notes, which are the authoritative source. Entries are labelled where they are hand-curated sample data, pre-releases, or drawn from a secondary source such as a developer blog.
Reuse: the summaries, labels and curation here are © What's New. Quote freely with attribution and a link back; wholesale republication of the corpus is not permitted — terms: https://whatsnew.fyi/terms. The vendors' own release notes remain their publishers'.
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- **added** — aDAG Developer Preview: Ray accelerated DAGs with Ray Core-like API and extensibility to pre-compile execution paths across pre-allocated resources
- **added** — Support async callable classes in map_batches()
- **added** — APPO on new API stack with EnvRunners
- **added** — Added customizable refresh frequency for metrics on Ray Dashboard
- **changed** — Optimize ServeController.get_app_config()
- **changed** — Change default for max and target ongoing requests
- **changed** — Integrate Ray Serve with Ray structured logging
- **changed** — Allow configuring handle cache size and controller max concurrency
- **changed** — Optimize DeploymentDetails.deployment_route_prefix_not_set()
- **changed** — Allow env setup logger encoding
- **changed** — ray list tasks filter state and name on GCS side
- **changed** — Log ray version and ray commit during GCS start
- **changed** — Upgraded Dashboard to MUIv5 and React 18
- **changed** — Make Tune trial ID available in EnvRunners and callbacks
- **changed** — Add env- and agent_steps to custom evaluation function
- **changed** — Remove default-metrics from Algorithm
- **fixed** — Ensure InputDataBuffer doesn't free block references
- **fixed** — MapOperator.num_active_tasks should exclude pending actors
- **fixed** — Fix progress bars being displayed as partially completed in Jupyter notebooks
- **fixed** — Decrement lineage ref count of an actor when the actor task return object reference is deleted
#### Highlight: aDAG Developer Preview
This is a new Ray Core specific feature called Ray accelerated DAGs (aDAGs).
- aDAGs give you a Ray Core-like API but with extensibility to pre-compile execution paths across pre-allocated resources on a Ray Cluster to possible benefits for optimization on throughput and latency. Some practical examples include:
- Up to 10x lower task execution time on single-node.
- Native support for GPU-GPU communication, via NCCL.
- This is still very early, but please reach out on #ray-core on Ray Slack to learn more!
#### Ray Libraries
##### Ray Data
💫 Enhancements:
- Support async callable classes in `map_batches()` (#46129)
🔨 Fixes:
- Ensure `InputDataBuffer` doesn't free block references (#46191)
- `MapOperator.num_active_tasks` should exclude pending actors (#46364)
- Fix progress bars being displayed as partially completed in Jupyter notebooks (#46289)
📖 Documentation:
- Fix docs: `read_api.py` docstring (#45690)
- Correct API annotation for `tfrecords_datasource` (#46171)
- Fix broken links in `README` and in `ray.data.Dataset` (#45345)
##### Ray Train
📖 Documentation:
- Update PyTorch Data Ingestion User Guide (#45421)
##### Ray Serve
💫 Enhancements:
- Optimize `ServeController.get_app_config()` (#45878)
- Change default for max and target ongoing requests (#45943)
- Integrate with Ray structured logging (#46215)
- Allow configuring handle cache size and controller max concurrency (#46278)
- Optimize `DeploymentDetails.deployment_route_prefix_not_set()` (#46305)
##### RLlib
🎉 New Features:
- APPO on new API stack (w/ `EnvRunners`). (#46216)
💫 Enhancements:
- Stability: APPO, SAC, and DQN activate multi-agent learning tests (#45542, #46299)
- Make Tune trial ID available in `EnvRunners` (and callbacks). (#46294)
- Add `env-` and `agent_steps` to custom evaluation function. (#45652)
- Remove default-metrics from Algorithm (tune does NOT error anymore if any stop-metric is missing). (#46200)
🔨 Fixes:
- Various bug fixes: #45542
📖 Documentation:
- Example for new API stack: Offline RL (BC) training on single-agent, while evaluating w/ multi-agent setup. (#46251)
- Example for new API stack: Custom RLModule with an LSTM. (#46276)
#### Ray Core
🎉 New Features:
- aDAG Developer Preview.
💫 Enhancements:
- Allow env setup logger encoding (#46242)
- ray list tasks filter state and name on GCS side (#46270)
- Log ray version and ray commit during GCS start (#46341)
🔨 Fixes:
- Decrement lineage ref count of an actor when the actor task return object reference is deleted (#46230)
- Fix negative ALIVE actors metric and introduce IDLE state (#45718)
- `psutil` process attr `num_fds` is not available on Windows (#46329)
##### Dashboard
🎉 New Features:
- Added customizable refresh frequency for metrics on Ray Dashboard (#44037)
💫 Enhancements:
- Upgraded to MUIv5 and React 18 (#45789)
🔨 Fixes:
- Fix for multi-line log items breaking log viewer rendering (#46391)
- Fix for UI inconsistency when a job submission creates more than one Ray job. (#46267)
- Fix filtering by job id for tasks API not filtering correctly. (#45017)
##### Docs
🔨 Fixes:
- Re-enabled automatic cross-reference link checking for Ray documentation, with Sphinx nitpicky mode (#46279)
- Enforced naming conventions for public and private APIs to maintain accuracy, starting with Ray Data API documentation (#46261)
📖 Documentation:
- Upgrade Python 3.12 support to alpha, marking the release of the Ray wheel to PyPI and conducting a sanity check of the most critical tests.
#### Thanks
Many thanks to all those who contributed to this release!
@stephanie-wang, @MortalHappiness, @aslonnie, @ryanaoleary, @
_[Truncated at 4000 characters — full notes: https://github.com/ray-project/ray/releases/tag/ray-2.32.0]_