* Remove all __future__ imports from RLlib.
* Remove (object) again from tf_run_builder.py::TFRunBuilder.
* Fix 2xLINT warnings.
* Fix broken appo_policy import (must be appo_tf_policy)
* Remove future imports from all other ray files (not just RLlib).
* Remove future imports from all other ray files (not just RLlib).
* Remove future import blocks that contain `unicode_literals` as well.
Revert appo_tf_policy.py to appo_policy.py (belongs to another PR).
* Add two empty lines before Schedule class.
* Put back __future__ imports into determine_tests_to_run.py. Fails otherwise on a py2/print related error.
* Skeleton for SubmitTask proto
* Pass through node manager port, connect in raylet client
* Switch submit task to grpc
* Check port in use
* doc
* Remove default port, set port randomly from driver
* update
* Fix test
* Fix object manager test
Executes tasks via the event loop in the C++ core worker. Also properly handles signals (including KeyboardInterrupt), so ctrl-C in a python interactive shell works now (if connecting to an existing cluster).
* Make full use of node
implement local node
fix bugs mentioned in comments
* Add more tests
* Use more specific exception handling
* fix, lint
* fix for py2.x
* Implement Node class and move most of services.py into it.
* Wait for nodes as they are added to the cluster.
* Fix Redis authentication bug.
* Fix bug in client table ordering.
* Address comments.
* Kill raylet before plasma store in test.
* Minor
## What do these changes do?
1. Separate the log related code to logger.py from services.py.
2. Allow users to modify logging formatter in `ray start`.
## Related issue number
https://github.com/ray-project/ray/pull/2664
* Fix documentation indentation.
* Add error table to GCS and push error messages through node manager.
* Add type to error data.
* Linting
* Fix failure_test bug.
* Linting.
* Enable one more test.
* Attempt to fix doc building.
* Restructuring
* Fixes
* More fixes.
* Move current_time_ms function into util.h.
* Integrate worker with raylet.
* Begin allowing worker to attach to cluster.
* Fix linting and documentation.
* Fix linting.
* Comment tests back in.
* Fix type of worker command.
* Remove xray python files and tests.
* Fix from rebase.
* Add test.
* Copy over raylet executable.
* Small cleanup.
* Treat actor creation like a regular task.
* Small cleanups.
* Change semantics of actor resource handling.
* Bug fix.
* Minor linting
* Bug fix
* Fix jenkins test.
* Fix actor tests
* Some cleanups
* Bug fix
* Fix bug.
* Remove cached actor tasks when a driver is removed.
* Add more info to taskspec in global state API.
* Fix cyclic import bug in tune.
* Fix
* Fix linting.
* Fix linting.
* Don't schedule any tasks (especially actor creaiton tasks) on local schedulers with 0 CPUs.
* Bug fix.
* Add test for 0 CPU case
* Fix linting
* Address comments.
* Fix typos and add comment.
* Add assertion and fix test.
* Check version info in ray start for non-head nodes.
* Small fix.
* Fix
* Push error to all drivers when worker has version mismatch.
* Linting
* Linting
* Fix
* Unify methods.
* Fix bug.
* Give error if a worker has a version mismatch for Python Ray, or cloudpickle.
* Check version when attaching driver to cluster.
* Only do check if the version info is present.
* Bug fix.
* Fix typo.
* Revert Python actor reconstruction
* Actor reconstruction using object lineage
* Add dummy arguments and return values for actor tasks
* Pin dummy outputs for actor tasks
* Skip checkpointing test for now
* TODOs
* minor edits
* Generate dummy object dependencies in Python, not C
* Fix linting.
* Move actor counter and dummy objects inside of the actor handle
* Refactor Worker._process_task, suppress exception propagation for
sequential actor tasks
* Reconstruct actor state when local schedulers fail.
* Simplify construction of arguments to pass into default_worker.py from local scheduler.
* Remove deprecated ray.actor.
* Simplify actor reconstruction method.
* Fix linting.
* Small fixes.
* 4 space indentation for actor.py.
* 4 space indentation for worker.py.
* 4 space indentation for more files.
* 4 space indentation for some test files.
* Check indentation in Travis.
* 4 space indentation for some rl files.
* Fix failure test.
* Fix multi_node_test.
* 4 space indentation for more files.
* 4 space indentation for remaining files.
* Fixes.
* Implement actor field for tasks
* Implement actor management in local scheduler.
* initial python frontend for actors
* import actors on worker
* IPython code completion and tests
* prepare creating actors through local schedulers
* add actor id to PyTask
* submit actor calls to local scheduler
* starting to integrate
* simple fix
* Fixes from rebasing.
* more work on python actors
* Improve local scheduler actor handlers.
* Pass actor ID to local scheduler when connecting a client.
* first working version of actors
* fixing actors
* fix creating two copies of the same actor
* fix actors
* remove sleep
* get rid of export synchronization
* update
* insert actor methods into the queue in the right order
* remove print statements
* make it compile again after rebase
* Minor updates.
* fix python actor ids
* Pass actor_id to start_worker.
* add test
* Minor changes.
* Update actor tests.
* Temporary plan for import counter.
* Temporarily fix import counters.
* Fix some tests.
* Fixes.
* Make actor creation non-blocking.
* Fix test?
* Fix actors on Python 2.
* fix rare case.
* Fix python 2 test.
* More tests.
* Small fixes.
* Linting.
* Revert tensorflow version to 0.12.0 temporarily.
* Small fix.
* Enhance inheritance test.
Stephanie Wang