prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Bioclim data missing hdr files when downloaded to path
   retriever download Bioclim -p
  
  
  --- 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/bioclim_2pt5.py`
  Content:
  ```
  1 #retriever
  2 
  3 """Retriever script for direct download of Bioclim data"""
  4 
  5 from retriever.lib.templates import Script
  6 
  7 
  8 class main(Script):
  9     def __init__(self, **kwargs):
  10         Script.__init__(self, **kwargs)
  11         self.name = "Bioclim 2.5 Minute Climate Data"
  12         self.shortname = "Bioclim"
  13         self.ref = "http://worldclim.org/bioclim"
  14         self.urls = {"climate": "http://biogeo.ucdavis.edu/data/climate/worldclim/1_4/grid/cur/bio_2-5m_bil.zip"}
  15         self.description = "Bioclimatic variables that are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables."
  16         self.citation = "Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978."
  17         self.tags = ["Data Type > Compilation"]
  18         
  19     def download(self, engine=None, debug=False):
  20         if engine.name != "Download Only":
  21             raise Exception("The Bioclim dataset contains only non-tabular data files, and can only be used with the 'download only' engine.")
  22         Script.download(self, engine, debug)
  23         file_names = ["bio%s.bil" % file_num for file_num in range(1, 20)]
  24         self.engine.download_files_from_archive(self.urls["climate"], file_names)
  25         self.engine.register_files(file_names)
  26 
  27 SCRIPT = main()
  28
  ```
  --- 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/bioclim_2pt5.py b/scripts/bioclim_2pt5.py
  --- a/scripts/bioclim_2pt5.py
  +++ b/scripts/bioclim_2pt5.py
  @@ -20,8 +20,12 @@
           if engine.name != "Download Only":
               raise Exception("The Bioclim dataset contains only non-tabular data files, and can only be used with the 'download only' engine.")
           Script.download(self, engine, debug)
  -        file_names = ["bio%s.bil" % file_num for file_num in range(1, 20)]
  +        file_names = []
  +        for file_num in range(1, 20):
  +            for ext in (['bil', 'hdr']):
  +                file_names += ["bio{0}.{1}".format(file_num, ext)]
           self.engine.download_files_from_archive(self.urls["climate"], file_names)
           self.engine.register_files(file_names)
   
   SCRIPT = main()
  +
  
verification_info: {"golden_diff": "diff --git a/scripts/bioclim_2pt5.py b/scripts/bioclim_2pt5.py\n--- a/scripts/bioclim_2pt5.py\n+++ b/scripts/bioclim_2pt5.py\n@@ -20,8 +20,12 @@\n         if engine.name != \"Download Only\":\n             raise Exception(\"The Bioclim dataset contains only non-tabular data files, and can only be used with the 'download only' engine.\")\n         Script.download(self, engine, debug)\n-        file_names = [\"bio%s.bil\" % file_num for file_num in range(1, 20)]\n+        file_names = []\n+        for file_num in range(1, 20):\n+            for ext in (['bil', 'hdr']):\n+                file_names += [\"bio{0}.{1}\".format(file_num, ext)]\n         self.engine.download_files_from_archive(self.urls[\"climate\"], file_names)\n         self.engine.register_files(file_names)\n \n SCRIPT = main()\n+\n", "issue": "Bioclim data missing hdr files when downloaded to path\n retriever download Bioclim -p\n\n", "before_files": [{"content": "#retriever\n\n\"\"\"Retriever script for direct download of Bioclim data\"\"\"\n\nfrom retriever.lib.templates import Script\n\n\nclass main(Script):\n    def __init__(self, **kwargs):\n        Script.__init__(self, **kwargs)\n        self.name = \"Bioclim 2.5 Minute Climate Data\"\n        self.shortname = \"Bioclim\"\n        self.ref = \"http://worldclim.org/bioclim\"\n        self.urls = {\"climate\": \"http://biogeo.ucdavis.edu/data/climate/worldclim/1_4/grid/cur/bio_2-5m_bil.zip\"}\n        self.description = \"Bioclimatic variables that are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables.\"\n        self.citation = \"Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\"\n        self.tags = [\"Data Type > Compilation\"]\n        \n    def download(self, engine=None, debug=False):\n        if engine.name != \"Download Only\":\n            raise Exception(\"The Bioclim dataset contains only non-tabular data files, and can only be used with the 'download only' engine.\")\n        Script.download(self, engine, debug)\n        file_names = [\"bio%s.bil\" % file_num for file_num in range(1, 20)]\n        self.engine.download_files_from_archive(self.urls[\"climate\"], file_names)\n        self.engine.register_files(file_names)\n\nSCRIPT = main()\n", "path": "scripts/bioclim_2pt5.py"}], "after_files": [{"content": "#retriever\n\n\"\"\"Retriever script for direct download of Bioclim data\"\"\"\n\nfrom retriever.lib.templates import Script\n\n\nclass main(Script):\n    def __init__(self, **kwargs):\n        Script.__init__(self, **kwargs)\n        self.name = \"Bioclim 2.5 Minute Climate Data\"\n        self.shortname = \"Bioclim\"\n        self.ref = \"http://worldclim.org/bioclim\"\n        self.urls = {\"climate\": \"http://biogeo.ucdavis.edu/data/climate/worldclim/1_4/grid/cur/bio_2-5m_bil.zip\"}\n        self.description = \"Bioclimatic variables that are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables.\"\n        self.citation = \"Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\"\n        self.tags = [\"Data Type > Compilation\"]\n        \n    def download(self, engine=None, debug=False):\n        if engine.name != \"Download Only\":\n            raise Exception(\"The Bioclim dataset contains only non-tabular data files, and can only be used with the 'download only' engine.\")\n        Script.download(self, engine, debug)\n        file_names = []\n        for file_num in range(1, 20):\n            for ext in (['bil', 'hdr']):\n                file_names += [\"bio{0}.{1}\".format(file_num, ext)]\n        self.engine.download_files_from_archive(self.urls[\"climate\"], file_names)\n        self.engine.register_files(file_names)\n\nSCRIPT = main()\n\n", "path": "scripts/bioclim_2pt5.py"}]}