prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  In the trainer script, use db.download instead of implementing download manually
  script/trainer.py is currently implementing DB download manually, it should instead use db.download (similarly to scripts/commit_classifier.py).
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `scripts/trainer.py`
  Content:
  ```
  1 # -*- coding: utf-8 -*-
  2 
  3 import argparse
  4 import json
  5 import os
  6 from logging import INFO, basicConfig, getLogger
  7 from urllib.request import urlretrieve
  8 
  9 import zstandard
  10 
  11 from bugbug import get_bugbug_version, model
  12 from bugbug.models import get_model_class
  13 from bugbug.utils import CustomJsonEncoder
  14 
  15 basicConfig(level=INFO)
  16 logger = getLogger(__name__)
  17 
  18 BASE_URL = "https://index.taskcluster.net/v1/task/project.relman.bugbug.data_{}.{}/artifacts/public"
  19 
  20 
  21 class Trainer(object):
  22     def decompress_file(self, path):
  23         dctx = zstandard.ZstdDecompressor()
  24         with open(f"{path}.zst", "rb") as input_f:
  25             with open(path, "wb") as output_f:
  26                 dctx.copy_stream(input_f, output_f)
  27         assert os.path.exists(path), "Decompressed file exists"
  28 
  29     def compress_file(self, path):
  30         cctx = zstandard.ZstdCompressor()
  31         with open(path, "rb") as input_f:
  32             with open(f"{path}.zst", "wb") as output_f:
  33                 cctx.copy_stream(input_f, output_f)
  34 
  35     def download_db(self, db_type):
  36         path = f"data/{db_type}.json"
  37         formatted_base_url = BASE_URL.format(db_type, f"v{get_bugbug_version()}")
  38         url = f"{formatted_base_url}/{db_type}.json.zst"
  39         logger.info(f"Downloading {db_type} database from {url} to {path}.zst")
  40         urlretrieve(url, f"{path}.zst")
  41         assert os.path.exists(f"{path}.zst"), "Downloaded file exists"
  42         logger.info(f"Decompressing {db_type} database")
  43         self.decompress_file(path)
  44 
  45     def go(self, model_name):
  46         # Download datasets that were built by bugbug_data.
  47         os.makedirs("data", exist_ok=True)
  48 
  49         model_class = get_model_class(model_name)
  50         model_obj = model_class()
  51 
  52         if (
  53             isinstance(model_obj, model.BugModel)
  54             or isinstance(model_obj, model.BugCoupleModel)
  55             or (hasattr(model_obj, "bug_data") and model_obj.bug_data)
  56         ):
  57             self.download_db("bugs")
  58 
  59         if isinstance(model_obj, model.CommitModel):
  60             self.download_db("commits")
  61 
  62         logger.info(f"Training *{model_name}* model")
  63         metrics = model_obj.train()
  64 
  65         # Save the metrics as a file that can be uploaded as an artifact.
  66         metric_file_path = "metrics.json"
  67         with open(metric_file_path, "w") as metric_file:
  68             json.dump(metrics, metric_file, cls=CustomJsonEncoder)
  69 
  70         logger.info(f"Training done")
  71 
  72         model_file_name = f"{model_name}model"
  73         assert os.path.exists(model_file_name)
  74         self.compress_file(model_file_name)
  75 
  76         logger.info(f"Model compressed")
  77 
  78 
  79 def main():
  80     description = "Train the models"
  81     parser = argparse.ArgumentParser(description=description)
  82 
  83     parser.add_argument("model", help="Which model to train.")
  84 
  85     args = parser.parse_args()
  86 
  87     retriever = Trainer()
  88     retriever.go(args.model)
  89
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/scripts/trainer.py b/scripts/trainer.py
  --- a/scripts/trainer.py
  +++ b/scripts/trainer.py
  @@ -4,44 +4,24 @@
   import json
   import os
   from logging import INFO, basicConfig, getLogger
  -from urllib.request import urlretrieve
   
   import zstandard
   
  -from bugbug import get_bugbug_version, model
  +from bugbug import bugzilla, db, model, repository
   from bugbug.models import get_model_class
   from bugbug.utils import CustomJsonEncoder
   
   basicConfig(level=INFO)
   logger = getLogger(__name__)
   
  -BASE_URL = "https://index.taskcluster.net/v1/task/project.relman.bugbug.data_{}.{}/artifacts/public"
  -
   
   class Trainer(object):
  -    def decompress_file(self, path):
  -        dctx = zstandard.ZstdDecompressor()
  -        with open(f"{path}.zst", "rb") as input_f:
  -            with open(path, "wb") as output_f:
  -                dctx.copy_stream(input_f, output_f)
  -        assert os.path.exists(path), "Decompressed file exists"
  -
       def compress_file(self, path):
           cctx = zstandard.ZstdCompressor()
           with open(path, "rb") as input_f:
               with open(f"{path}.zst", "wb") as output_f:
                   cctx.copy_stream(input_f, output_f)
   
  -    def download_db(self, db_type):
  -        path = f"data/{db_type}.json"
  -        formatted_base_url = BASE_URL.format(db_type, f"v{get_bugbug_version()}")
  -        url = f"{formatted_base_url}/{db_type}.json.zst"
  -        logger.info(f"Downloading {db_type} database from {url} to {path}.zst")
  -        urlretrieve(url, f"{path}.zst")
  -        assert os.path.exists(f"{path}.zst"), "Downloaded file exists"
  -        logger.info(f"Decompressing {db_type} database")
  -        self.decompress_file(path)
  -
       def go(self, model_name):
           # Download datasets that were built by bugbug_data.
           os.makedirs("data", exist_ok=True)
  @@ -54,10 +34,10 @@
               or isinstance(model_obj, model.BugCoupleModel)
               or (hasattr(model_obj, "bug_data") and model_obj.bug_data)
           ):
  -            self.download_db("bugs")
  +            db.download(bugzilla.BUGS_DB, force=True)
   
           if isinstance(model_obj, model.CommitModel):
  -            self.download_db("commits")
  +            db.download(repository.COMMITS_DB, force=True)
   
           logger.info(f"Training *{model_name}* model")
           metrics = model_obj.train()
  
verification_info: {"golden_diff": "diff --git a/scripts/trainer.py b/scripts/trainer.py\n--- a/scripts/trainer.py\n+++ b/scripts/trainer.py\n@@ -4,44 +4,24 @@\n import json\n import os\n from logging import INFO, basicConfig, getLogger\n-from urllib.request import urlretrieve\n \n import zstandard\n \n-from bugbug import get_bugbug_version, model\n+from bugbug import bugzilla, db, model, repository\n from bugbug.models import get_model_class\n from bugbug.utils import CustomJsonEncoder\n \n basicConfig(level=INFO)\n logger = getLogger(__name__)\n \n-BASE_URL = \"https://index.taskcluster.net/v1/task/project.relman.bugbug.data_{}.{}/artifacts/public\"\n-\n \n class Trainer(object):\n-    def decompress_file(self, path):\n-        dctx = zstandard.ZstdDecompressor()\n-        with open(f\"{path}.zst\", \"rb\") as input_f:\n-            with open(path, \"wb\") as output_f:\n-                dctx.copy_stream(input_f, output_f)\n-        assert os.path.exists(path), \"Decompressed file exists\"\n-\n     def compress_file(self, path):\n         cctx = zstandard.ZstdCompressor()\n         with open(path, \"rb\") as input_f:\n             with open(f\"{path}.zst\", \"wb\") as output_f:\n                 cctx.copy_stream(input_f, output_f)\n \n-    def download_db(self, db_type):\n-        path = f\"data/{db_type}.json\"\n-        formatted_base_url = BASE_URL.format(db_type, f\"v{get_bugbug_version()}\")\n-        url = f\"{formatted_base_url}/{db_type}.json.zst\"\n-        logger.info(f\"Downloading {db_type} database from {url} to {path}.zst\")\n-        urlretrieve(url, f\"{path}.zst\")\n-        assert os.path.exists(f\"{path}.zst\"), \"Downloaded file exists\"\n-        logger.info(f\"Decompressing {db_type} database\")\n-        self.decompress_file(path)\n-\n     def go(self, model_name):\n         # Download datasets that were built by bugbug_data.\n         os.makedirs(\"data\", exist_ok=True)\n@@ -54,10 +34,10 @@\n             or isinstance(model_obj, model.BugCoupleModel)\n             or (hasattr(model_obj, \"bug_data\") and model_obj.bug_data)\n         ):\n-            self.download_db(\"bugs\")\n+            db.download(bugzilla.BUGS_DB, force=True)\n \n         if isinstance(model_obj, model.CommitModel):\n-            self.download_db(\"commits\")\n+            db.download(repository.COMMITS_DB, force=True)\n \n         logger.info(f\"Training *{model_name}* model\")\n         metrics = model_obj.train()\n", "issue": "In the trainer script, use db.download instead of implementing download manually\nscript/trainer.py is currently implementing DB download manually, it should instead use db.download (similarly to scripts/commit_classifier.py).\n", "before_files": [{"content": "# -*- coding: utf-8 -*-\n\nimport argparse\nimport json\nimport os\nfrom logging import INFO, basicConfig, getLogger\nfrom urllib.request import urlretrieve\n\nimport zstandard\n\nfrom bugbug import get_bugbug_version, model\nfrom bugbug.models import get_model_class\nfrom bugbug.utils import CustomJsonEncoder\n\nbasicConfig(level=INFO)\nlogger = getLogger(__name__)\n\nBASE_URL = \"https://index.taskcluster.net/v1/task/project.relman.bugbug.data_{}.{}/artifacts/public\"\n\n\nclass Trainer(object):\n    def decompress_file(self, path):\n        dctx = zstandard.ZstdDecompressor()\n        with open(f\"{path}.zst\", \"rb\") as input_f:\n            with open(path, \"wb\") as output_f:\n                dctx.copy_stream(input_f, output_f)\n        assert os.path.exists(path), \"Decompressed file exists\"\n\n    def compress_file(self, path):\n        cctx = zstandard.ZstdCompressor()\n        with open(path, \"rb\") as input_f:\n            with open(f\"{path}.zst\", \"wb\") as output_f:\n                cctx.copy_stream(input_f, output_f)\n\n    def download_db(self, db_type):\n        path = f\"data/{db_type}.json\"\n        formatted_base_url = BASE_URL.format(db_type, f\"v{get_bugbug_version()}\")\n        url = f\"{formatted_base_url}/{db_type}.json.zst\"\n        logger.info(f\"Downloading {db_type} database from {url} to {path}.zst\")\n        urlretrieve(url, f\"{path}.zst\")\n        assert os.path.exists(f\"{path}.zst\"), \"Downloaded file exists\"\n        logger.info(f\"Decompressing {db_type} database\")\n        self.decompress_file(path)\n\n    def go(self, model_name):\n        # Download datasets that were built by bugbug_data.\n        os.makedirs(\"data\", exist_ok=True)\n\n        model_class = get_model_class(model_name)\n        model_obj = model_class()\n\n        if (\n            isinstance(model_obj, model.BugModel)\n            or isinstance(model_obj, model.BugCoupleModel)\n            or (hasattr(model_obj, \"bug_data\") and model_obj.bug_data)\n        ):\n            self.download_db(\"bugs\")\n\n        if isinstance(model_obj, model.CommitModel):\n            self.download_db(\"commits\")\n\n        logger.info(f\"Training *{model_name}* model\")\n        metrics = model_obj.train()\n\n        # Save the metrics as a file that can be uploaded as an artifact.\n        metric_file_path = \"metrics.json\"\n        with open(metric_file_path, \"w\") as metric_file:\n            json.dump(metrics, metric_file, cls=CustomJsonEncoder)\n\n        logger.info(f\"Training done\")\n\n        model_file_name = f\"{model_name}model\"\n        assert os.path.exists(model_file_name)\n        self.compress_file(model_file_name)\n\n        logger.info(f\"Model compressed\")\n\n\ndef main():\n    description = \"Train the models\"\n    parser = argparse.ArgumentParser(description=description)\n\n    parser.add_argument(\"model\", help=\"Which model to train.\")\n\n    args = parser.parse_args()\n\n    retriever = Trainer()\n    retriever.go(args.model)\n", "path": "scripts/trainer.py"}], "after_files": [{"content": "# -*- coding: utf-8 -*-\n\nimport argparse\nimport json\nimport os\nfrom logging import INFO, basicConfig, getLogger\n\nimport zstandard\n\nfrom bugbug import bugzilla, db, model, repository\nfrom bugbug.models import get_model_class\nfrom bugbug.utils import CustomJsonEncoder\n\nbasicConfig(level=INFO)\nlogger = getLogger(__name__)\n\n\nclass Trainer(object):\n    def compress_file(self, path):\n        cctx = zstandard.ZstdCompressor()\n        with open(path, \"rb\") as input_f:\n            with open(f\"{path}.zst\", \"wb\") as output_f:\n                cctx.copy_stream(input_f, output_f)\n\n    def go(self, model_name):\n        # Download datasets that were built by bugbug_data.\n        os.makedirs(\"data\", exist_ok=True)\n\n        model_class = get_model_class(model_name)\n        model_obj = model_class()\n\n        if (\n            isinstance(model_obj, model.BugModel)\n            or isinstance(model_obj, model.BugCoupleModel)\n            or (hasattr(model_obj, \"bug_data\") and model_obj.bug_data)\n        ):\n            db.download(bugzilla.BUGS_DB, force=True)\n\n        if isinstance(model_obj, model.CommitModel):\n            db.download(repository.COMMITS_DB, force=True)\n\n        logger.info(f\"Training *{model_name}* model\")\n        metrics = model_obj.train()\n\n        # Save the metrics as a file that can be uploaded as an artifact.\n        metric_file_path = \"metrics.json\"\n        with open(metric_file_path, \"w\") as metric_file:\n            json.dump(metrics, metric_file, cls=CustomJsonEncoder)\n\n        logger.info(f\"Training done\")\n\n        model_file_name = f\"{model_name}model\"\n        assert os.path.exists(model_file_name)\n        self.compress_file(model_file_name)\n\n        logger.info(f\"Model compressed\")\n\n\ndef main():\n    description = \"Train the models\"\n    parser = argparse.ArgumentParser(description=description)\n\n    parser.add_argument(\"model\", help=\"Which model to train.\")\n\n    args = parser.parse_args()\n\n    retriever = Trainer()\n    retriever.go(args.model)\n", "path": "scripts/trainer.py"}]}