CSV import implementation

ucsinfer/__main__.py

@@ -1,6 +1,9 @@
 import os
 import logging
 from itertools import chain
+import csv
+
+from typing import Generator
 
 import click
 
@@ -49,8 +52,8 @@ def ucsinfer(ctx, verbose, no_model_cache, model, complete_ucs):
         stream_handler.setLevel(logging.WARNING)
 
     os.environ['TOKENIZERS_PARALLELISM'] = 'false'
-    logger.info("Setting TOKENIZERS_PARALLELISM environment variable to `false"
-                " explicitly")
+    logger.info("Setting TOKENIZERS_PARALLELISM environment variable to "
+                "`false` explicitly")
 
     ctx.ensure_object(dict)
     ctx.obj['model_cache'] = not no_model_cache
@@ -132,7 +135,30 @@ def recommend(ctx, text, paths, interactive, skip_ucs):
                 print(f"Renaming {path} \n      to {new_path}")
                 os.rename(path, new_path)
                 break
-        
+
+def csv_to_data(paths, description_key, filename_key, catid_list) -> Generator[tuple[str, str], None, None]:
+    """
+    Accepts a list of paths and returns an iterator of (sentence, class) 
+    tuples.
+    """
+    for path in paths:
+        with open(path, 'r') as f:
+            records = csv.DictReader(f)
+
+            assert filename_key in records.fieldnames, \
+                    (f"Filename key `{filename_key}` not present in file "
+                     "{path}")
+
+            assert description_key in records.fieldnames, \
+                    (f"Description key `{description_key}` not present in "
+                     "file {path}")
+
+            for record in records:
+                ucs_comps = parse_ucs(record[filename_key], catid_list)
+                if ucs_comps:
+                    yield (record[description_key], ucs_comps.cat_id)                    
+
+
 @ucsinfer.command('csv')
 @click.option('--filename-col', default="FileName", 
               help="Heading or index of the column containing filenames",
@@ -143,7 +169,7 @@ def recommend(ctx, text, paths, interactive, skip_ucs):
 @click.option('--out', default='dataset/', show_default=True)
 @click.argument('paths', nargs=-1)
 @click.pass_context
-def csv(ctx, paths, out, filename_col, description_col):
+def import_csv(ctx, paths: list[str], out, filename_col, description_col):
     """
     Scan training data from CSV files 
 
@@ -152,16 +178,29 @@ def csv(ctx, paths, out, filename_col, description_col):
     file system it builds a dataset from descriptions and UCS filenames in 
     columns of a CSV file.
     """
-    pass
+    logger.debug("CSV mode")
+
+    logger.debug(f"Loading category list...")
+    ucs = load_ucs(full_ucs=ctx.obj['complete_ucs'])
+
+    catid_list = [cat.catid for cat in ucs]
+
+    logger.info("Building dataset from csv...")
+
+    dataset = build_sentence_class_dataset(
+            chain(csv_to_data(paths, description_col, filename_col, catid_list), 
+                  ucs_definitions_generator(ucs)),catid_list)
+
+    logger.info(f"Saving dataset to disk at {out}")
+    print_dataset_stats(dataset, catid_list)
+    dataset.save_to_disk(out)
+
 
 @ucsinfer.command('gather')
 @click.option('--out', default='dataset/', show_default=True)
-# @click.option('--ucs-data', flag_value=True, help="Create a dataset based "
-#               "on the UCS category explanations and synonymns (PATHS will "
-#               "be ignored.)")
 @click.argument('paths', nargs=-1)
 @click.pass_context
-def gather(ctx, paths, out, ucs_data):
+def gather(ctx, paths, out):
     """
     Scan training data from audio files
     
@@ -184,20 +223,16 @@ def gather(ctx, paths, out, ucs_data):
     scan_list: list[tuple[str,str]] = []
     catid_list = [cat.catid for cat in ucs]
 
-    if ucs_data:
-        logger.info('Creating dataset for UCS categories instead of from PATH')
-        paths = []
-
     for path in paths:
         scan_list += walk_path(path, catid_list)
 
     logger.info(f"Found {len(scan_list)} files to process.")
 
-    logger.info("Building dataset...")
+    logger.info("Building dataset files...")
 
     dataset = build_sentence_class_dataset(
-            chain(scan_metadata(scan_list, catid_list),                               
-                  ucs_definitions_generator(ucs)),                              
+            chain(scan_metadata(scan_list, catid_list),
+                  ucs_definitions_generator(ucs)),
             catid_list)
  
     logger.info(f"Saving dataset to disk at {out}")