Beaker DOS fix (#315)

* Maximum 50 concurrent requests

* Doc fixes

* Changelog

* Don't murder Beaker

* Formatting

CHANGELOG.md

@@ -11,6 +11,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 - Fixed non-deterministic behavior in `TorchTrainStep`.
 - Fixed bug in `BeakerWorkspace` where `.step_info(step)` would raise a `KeyError` if the step hasn't been registered as part of a run yet.
+- Fixed a bug in `BeakerWorkspace` where it would send too many requests to the beaker service.
+
 
 ## [v0.9.0](https://github.com/allenai/tango/releases/tag/v0.9.0) - 2022-06-01
 

CONTRIBUTING.md

@@ -9,14 +9,14 @@ Thanks for considering contributing! Please read this document to learn the vari
 First, do [a quick search](https://github.com/allenai/tango/issues) to see whether your issue has already been reported.
 If your issue has already been reported, please comment on the existing issue.
 
-Otherwise, open [a new GitHub issue](https://github.com/allenai/tango/issues).  Be sure to include a clear title
-and description.  The description should include as much relevant information as possible.  The description should
-explain how to reproduce the erroneous behavior as well as the behavior you expect to see.  Ideally you would include a
+Otherwise, open [a new GitHub issue](https://github.com/allenai/tango/issues). Be sure to include a clear title
+and description. The description should include as much relevant information as possible. The description should
+explain how to reproduce the erroneous behavior as well as the behavior you expect to see. Ideally you would include a
 code sample or an executable test case demonstrating the expected behavior.
 
 ### Do you have a suggestion for an enhancement or new feature?
 
-We use GitHub issues to track feature requests. Before you create an feature request:
+We use GitHub issues to track feature requests. Before you create a feature request:
 
 * Make sure you have a clear idea of the enhancement you would like. If you have a vague idea, consider discussing
 it first on a GitHub issue.
@@ -109,7 +109,7 @@ When you're ready to contribute code to address an open issue, please follow the
 
     <details><summary>Expand details 👇</summary><br/>
 
-    Commiting directly to the main branch of your fork is not recommended. It will be easier to keep your fork clean if you work on a seperate branch for each contribution you intend to make.
+    Committing directly to the main branch of your fork is not recommended. It will be easier to keep your fork clean if you work on a separate branch for each contribution you intend to make.
 
     You can create a new branch with
 
@@ -147,10 +147,6 @@ When you're ready to contribute code to address an open issue, please follow the
 
         pytest -v tests/a/b_test.py
 
-    Our CI will automatically check that test coverage stays above a certain threshold (around 90%). To check the coverage locally in this example, you could run
-
-        pytest -v --cov tango.a.b tests/a/b_test.py
-
     If your contribution involves additions to any public part of the API, we require that you write docstrings
     for each function, method, class, or module that you add.
     See the [Writing docstrings](#writing-docstrings) section below for details on the syntax.

tango/integrations/beaker/workspace.py

@@ -232,7 +232,9 @@ def registered_runs(self) -> Dict[str, Run]:
 
         runs: Dict[str, Run] = {}
 
-        with concurrent.futures.ThreadPoolExecutor() as executor:
+        with concurrent.futures.ThreadPoolExecutor(
+            max_workers=3, thread_name_prefix="BeakerWorkspace.registered_runs()-"
+        ) as executor:
             run_futures = []
             for dataset in self.beaker.workspace.datasets(
                 match=Constants.RUN_DATASET_PREFIX, results=False
@@ -292,7 +294,9 @@ def _get_run_from_dataset(self, dataset: Dataset) -> Optional[Run]:
 
         import concurrent.futures
 
-        with concurrent.futures.ThreadPoolExecutor() as executor:
+        with concurrent.futures.ThreadPoolExecutor(
+            max_workers=3, thread_name_prefix="BeakerWorkspace._get_run_from_dataset()-"
+        ) as executor:
             step_info_futures = []
             for step_name, unique_id in steps_info.items():
                 step_info_futures.append(executor.submit(self.step_info, unique_id))