[#8] adding option to generate metadata json file when extracting a s…

…pecific file type

hsextract/main.py

@@ -3,54 +3,63 @@
 
 from asyncio import run as aiorun
 
-from hsextract.utils import list_and_extract, extract_metadata
+from hsextract.utils import list_and_extract, extract_metadata, is_file_path, is_dir_path, save_metadata
 
 
 app = typer.Typer()
 
 
+def _extract_metadata(path: str, file_type: str, generate_metadata_file: bool):
+    if not is_file_path(path):
+        return
+    metadata_dict = extract_metadata(file_type, path)
+    if metadata_dict is None:
+        return
+    if generate_metadata_file:
+        save_metadata(path=path, metadata_dict=metadata_dict)
+    else:
+        print(json.dumps(metadata_dict, indent=2))
+
+
 @app.command()
-def feature(path: str):
-    metadata_dict = extract_metadata("feature", path)
-    print(json.dumps(metadata_dict, indent=2))
+def feature(path: str, generate_metadata_file: bool = False):
+    _extract_metadata(path, "feature", generate_metadata_file)
 
 
 @app.command()
-def raster(path: str):
-    metadata_dict = extract_metadata("raster", path)
-    print(json.dumps(metadata_dict, indent=2))
+def raster(path: str, generate_metadata_file: bool = False):
+    _extract_metadata(path, "raster", generate_metadata_file)
 
 
 @app.command()
-def reftimeseries(path: str):
-    metadata_dict = extract_metadata("reftimeseries", path)
-    print(json.dumps(metadata_dict, indent=2))
+def reftimeseries(path: str, generate_metadata_file: bool = False):
+    _extract_metadata(path, "reftimeseries", generate_metadata_file)
 
 
 @app.command()
-def timeseries(path: str):
-    metadata_dict = extract_metadata("timeseries", path)
-    print(json.dumps(metadata_dict, indent=2))
+def timeseries(path: str, generate_metadata_file: bool = False):
+    _extract_metadata(path, "timeseries", generate_metadata_file)
 
 
 @app.command()
-def timeseriescsv(path: str):
-    metadata_dict = extract_metadata("timeseries", path)
-    print(json.dumps(metadata_dict, indent=2))
+def timeseriescsv(path: str, generate_metadata_file: bool = False):
+    _extract_metadata(path, "timeseries", generate_metadata_file)
 
 
 @app.command()
-def netcdf(path: str):
-    metadata_dict = extract_metadata("netcdf", path)
-    print(json.dumps(metadata_dict, indent=2))
+def netcdf(path: str, generate_metadata_file: bool = False):
+    _extract_metadata(path, "netcdf", generate_metadata_file)
 
 
 async def _extract(path: str, user_metadata_filename: str, base_url: str):
+    # generates metadata json files for all files types in the given path
     await list_and_extract(path, user_metadata_filename, base_url)
 
 
 @app.command()
 def extract(path: str, base_url: str, user_metadata_filename: str = "hs_user_meta.json"):
+    if not is_dir_path(path):
+        return
     aiorun(_extract(path, user_metadata_filename, base_url))
 
 

hsextract/utils.py

@@ -22,6 +22,33 @@
 from hsextract.file_utils import file_metadata
 
 
+def is_file_path(filepath: str):
+    if not os.path.isfile(filepath):
+        logging.error(f"{filepath} is not a file or doesn't exist.")
+        return False
+    return True
+
+
+def is_dir_path(dirpath: str):
+    if not os.path.isdir(dirpath):
+        logging.error(f"{dirpath} is not a directory or doesn't exist.")
+        return False
+    return True
+
+
+def save_metadata(path: str, metadata_dict: dict):
+    file_name = Path(path).name
+    metadata_file_name = Path(file_name + ".json")
+    # save the metadata file in '.hs' folder relative to the directory of the input file
+    metadata_file_path = Path(path).parent / ".hs" / metadata_file_name
+    # create the '.hs' directory
+    metadata_file_path.parent.mkdir(parents=True, exist_ok=True)
+    with open(metadata_file_path, "w") as f:
+        json.dump(metadata_dict, f, indent=2)
+
+    print(f"Metadata was saved to file path: {metadata_file_path}")
+
+
 def _to_metadata_path(filepath: str, user_metadata_filename: str):
     if not filepath.endswith(user_metadata_filename):
         return os.path.join(".hs", filepath + ".json")
@@ -43,6 +70,9 @@ def extract_metadata(type: str, filepath, use_adapter=True):
     # use_adapter is a flag to determine if the metadata should be converted to a catalog record
     # it is set to False in tests when testing for the raw extracted metadata
 
+    print(f">> Extracting {type} metadata from {filepath}", flush=True)
+    logging.info(f"Extracting {type} metadata from {filepath}")
+
     extension = os.path.splitext(filepath)[1]
     try:
         extracted_metadata = _extract_metadata(type, filepath)