move argparser, model/benchmark retrieval, helper methods to core

brainscore_language/submission/endpoints.py

@@ -1,8 +1,9 @@
-import argparse
 from typing import List, Union, Dict
 
 from brainscore_core import Score, Benchmark
-from brainscore_core.submission import UserManager, RunScoringEndpoint, DomainPlugins
+from brainscore_core.submission import RunScoringEndpoint, DomainPlugins
+from brainscore_core.submission.endpoints import make_argparser, retrieve_models_and_benchmarks, get_user_id, \
+    send_email_to_submitter as send_email_to_submitter_core
 from brainscore_language import load_model, load_benchmark, score
 from brainscore_language.submission import config
 
@@ -22,81 +23,29 @@ def score(self, model_identifier: str, benchmark_identifier: str) -> Score:
 run_scoring_endpoint = RunScoringEndpoint(language_plugins, db_secret=config.get_database_secret())
 
 
-def send_email_to_submitter(uid: int, domain: str, pr_number: str,
-                            mail_username: str, mail_password: str):
-    """ Send submitter an email if their web-submitted PR fails. """
-    subject = "Brain-Score submission failed"
-    body = f"Your Brain-Score submission did not pass checks. Please review the test results and update the PR at https://github.com/brain-score/{domain}/pull/{pr_number} or send in an updated submission via the website."
-    user_manager = UserManager(db_secret=config.get_database_secret())
-    return user_manager.send_user_email(uid, body, mail_username, mail_password)
-
-
-def get_user_id(email: str) -> int:
-    user_manager = UserManager(db_secret=config.get_database_secret())
-    user_id = user_manager.get_uid(email)
-    return user_id
-
-
-def _get_ids(args_dict: Dict[str, Union[str, List]], key: str) -> Union[List, str, None]:
-    return args_dict[key] if key in args_dict else None
-
-
 def run_scoring(args_dict: Dict[str, Union[str, List]]):
-    """ prepares parameters for the `run_scoring_endpoint`. """
-    new_models = _get_ids(args_dict, 'new_models')
-    new_benchmarks = _get_ids(args_dict, 'new_benchmarks')
-
-    if args_dict['specified_only']:
-        assert len(new_models) > 0, "No models specified"
-        assert len(new_benchmarks) > 0, "No benchmarks specified"
-        models = new_models
-        benchmarks = new_benchmarks
-    else:
-        if new_models and new_benchmarks:
-            models = RunScoringEndpoint.ALL_PUBLIC
-            benchmarks = RunScoringEndpoint.ALL_PUBLIC
-        elif new_benchmarks:
-            models = RunScoringEndpoint.ALL_PUBLIC
-            benchmarks = new_benchmarks
-        elif new_models:
-            models = new_models
-            benchmarks = RunScoringEndpoint.ALL_PUBLIC
+    benchmarks, models = retrieve_models_and_benchmarks(args_dict)
 
     run_scoring_endpoint(domain="language", jenkins_id=args_dict["jenkins_id"],
                          models=models, benchmarks=benchmarks, user_id=args_dict["user_id"],
                          model_type="artificialsubject", public=args_dict["public"],
                          competition=args_dict["competition"])
 
 
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser()
-    parser.add_argument('jenkins_id', type=int,
-                        help='The id of the current jenkins run')
-    parser.add_argument('public', type=bool, nargs='?', default=True,
-                        help='Public (or private) submission?')
-    parser.add_argument('--competition', type=str, nargs='?', default=None,
-                        help='Name of competition for which submission is being scored')
-    parser.add_argument('--user_id', type=int, nargs='?', default=None,
-                        help='ID of submitting user in the postgres DB')
-    parser.add_argument('--author_email', type=str, nargs='?', default=None,
-                        help='email associated with PR author GitHub username')
-    parser.add_argument('--specified_only', type=bool, nargs='?', default=False,
-                        help='Only score the plugins specified by new_models and new_benchmarks')
-    parser.add_argument('--new_models', type=str, nargs='*', default=None,
-                        help='The identifiers of newly submitted models to score on all benchmarks')
-    parser.add_argument('--new_benchmarks', type=str, nargs='*', default=None,
-                        help='The identifiers of newly submitted benchmarks on which to score all models')
-    args, remaining_args = parser.parse_known_args()
-
-    return args
+def send_email_to_submitter(uid: int, domain: str, pr_number: str,
+                            mail_username: str, mail_password: str):
+    send_email_to_submitter_core(uid=uid, domain=domain, pr_number=pr_number,
+                                 db_secret=config.get_database_secret(),
+                                 mail_username=mail_username, mail_password=mail_password)
 
 
 if __name__ == '__main__':
-    args = parse_args()
+    parser = make_argparser()
+    args, remaining_args = parser.parse_known_args()
     args_dict = vars(args)
 
     if 'user_id' not in args_dict or args_dict['user_id'] is None:
-        user_id = get_user_id(args_dict['author_email'])
+        user_id = get_user_id(args_dict['author_email'], db_secret=config.get_database_secret())
         args_dict['user_id'] = user_id
 
     run_scoring(args_dict)