Refactoring of gather

pyproject.toml

@@ -26,3 +26,6 @@ build-backend = "poetry.core.masonry.api"
 ipython = "^9.4.0"
 jupyter = "^1.1.1"
 
+[tool.poetry.scripts]
+ucsinfer = "ucsinfer.__main__:ucsinfer"
+

ucsinfer/__main__.py

@@ -1,7 +1,6 @@
 import os
 # import csv
 import logging
-from subprocess import CalledProcessError
 from itertools import chain
 
 import tqdm
@@ -9,7 +8,8 @@ import click
 # from tabulate import tabulate, SEPARATING_LINE
 
 from .inference import InferenceContext, load_ucs
-from .gather import build_sentence_class_dataset, print_dataset_stats 
+from .gather import (build_sentence_class_dataset, print_dataset_stats, 
+                     ucs_definitions_generator, scan_metadata, walk_path)
 from .recommend import print_recommendation
 from .util import ffmpeg_description, parse_ucs
 
@@ -103,6 +103,11 @@ def recommend(ctx, text, paths, interactive, skip_ucs):
     catlist = [x.catid for x in inference_ctx.catlist]
 
     for path in paths:
+        _, ext = os.path.splitext(path) 
+        
+        if ext not in (".wav", ".flac"):
+            continue
+
         basename = os.path.basename(path)
         if skip_ucs and parse_ucs(basename, catlist):
             continue 
@@ -152,67 +157,30 @@ def gather(ctx, paths, out, ucs_data):
     """
     logger.debug("GATHER mode")
 
-    types = ['.wav', '.flac']
-
     logger.debug(f"Loading category list...")
     ucs = load_ucs(full_ucs=ctx.obj['complete_ucs'])
 
-    scan_list = []
+    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 = []
 
-    walker_p = tqdm.tqdm(total=None, unit='dir', desc="Walking filesystem...")
     for path in paths:
-        for dirpath, _, filenames in os.walk(path):
+        scan_list += walk_path(path, catid_list)
-            logger.info(f"Walking directory {dirpath}")
-            for filename in filenames:
-                walker_p.update()
-                root, ext = os.path.splitext(filename)
-                if ext not in types or filename.startswith("._"):
-                    continue 
-
-                if (ucs_components := parse_ucs(root, catid_list)):
-                    p = os.path.join(dirpath, filename)
-                    logger.info(f"Adding path to scan list {p}")
-                    scan_list.append((ucs_components.cat_id, p))
-    walker_p.close()
 
     logger.info(f"Found {len(scan_list)} files to process.")
 
-    def scan_metadata():
-        for pair in tqdm.tqdm(scan_list, unit='files'):
-            logger.info(f"Scanning file with ffprobe: {pair[1]}")
-            try:
-                desc = ffmpeg_description(pair[1])
-            except CalledProcessError as e:
-                logger.error(f"ffprobe returned error (){e.returncode}): " \
-                        + e.stderr)
-                continue
-
-            if desc:
-                yield desc, str(pair[0])
-            else:
-                comps = parse_ucs(os.path.basename(pair[1]), catid_list)
-                assert comps
-                yield comps.fx_name, str(pair[0])
-
-    def ucs_metadata():
-        for cat in ucs:
-            yield cat.explanations, cat.catid
-            yield ", ".join(cat.synonymns), cat.catid
-
     logger.info("Building dataset...")
 
-    dataset = build_sentence_class_dataset(chain(scan_metadata(), 
+    dataset = build_sentence_class_dataset(
-                                                 ucs_metadata()),
+            chain(scan_metadata(scan_list, catid_list),                               
-                                           catid_list)
+                  ucs_definitions_generator(ucs)),                              
- 
+            catid_list)
  
     logger.info(f"Saving dataset to disk at {out}")
-    print_dataset_stats(dataset)
+    print_dataset_stats(dataset, catid_list)
     dataset.save_to_disk(out)
     
 

ucsinfer/gather.py

@@ -1,9 +1,63 @@
+from .inference import Ucs
+from .util import ffmpeg_description, parse_ucs
+
+from subprocess import CalledProcessError
+import os.path
+
 from datasets import Dataset, Features, Value, ClassLabel, DatasetInfo
 from datasets.dataset_dict import DatasetDict
 
-from typing import Iterator
+from typing import Iterator, Generator
 
 from tabulate import tabulate
+import logging
+import tqdm
+
+def walk_path(path:str, catid_list) -> list[tuple[str,str]]:
+    types = ['.wav', '.flac']
+    logger = logging.getLogger('ucsinfer')
+    walker_p = tqdm.tqdm(total=None, unit='dir', desc="Walking filesystem...")
+    scan_list = []
+
+    for dirpath, _, filenames in os.walk(path):
+        logger.info(f"Walking directory {dirpath}")
+        for filename in filenames:
+            walker_p.update()
+            root, ext = os.path.splitext(filename)
+            if ext not in types or filename.startswith("._"):
+                continue 
+
+            if (ucs_components := parse_ucs(root, catid_list)):
+                p = os.path.join(dirpath, filename)
+                logger.info(f"Adding path to scan list {p}")
+                scan_list.append((ucs_components.cat_id, p))
+
+    return scan_list
+
+def scan_metadata(scan_list: list[tuple[str,str]], catid_list: list[str]):
+    logger = logging.getLogger('ucsinfer')
+    for pair in tqdm.tqdm(scan_list, unit='files'):
+        logger.info(f"Scanning file with ffprobe: {pair[1]}")
+        try:
+            desc = ffmpeg_description(pair[1])
+        except CalledProcessError as e:
+            logger.error(f"ffprobe returned error (){e.returncode}): " \
+                    + e.stderr)
+            continue
+
+        if desc:
+            yield desc, str(pair[0])
+        else:
+            comps = parse_ucs(os.path.basename(pair[1]), catid_list)
+            assert comps
+            yield comps.fx_name, str(pair[0])
+
+
+def ucs_definitions_generator(ucs: list[Ucs]) \
+        -> Generator[tuple[str,str],None, None]:
+    for cat in ucs:
+        yield cat.explanations, cat.catid
+        yield ", ".join(cat.synonymns), cat.catid
 
 def print_dataset_stats(dataset: DatasetDict, catlist: list[str]):
     

ucsinfer/recommend.py

@@ -1,10 +1,13 @@
 # recommend.py
 
 from re import match
+
 from .inference import InferenceContext
 
+from tabulate import tabulate
+
 def print_recommendation(path: str | None, text: str, ctx: InferenceContext, 
-                         interactive_rename: bool):
+                         interactive_rename: bool, recommend_limit=10):
     """
     Print recommendations interactively.
 
@@ -16,7 +19,7 @@ def print_recommendation(path: str | None, text: str, ctx: InferenceContext,
               `print_recommendation` should be called again with this argument.
             - if retval[2] is a str, this is the catid the user has selected.
     """
-    recs = ctx.classify_text_ranked(text)
+    recs = ctx.classify_text_ranked(text, limit=recommend_limit)
     print("----------")
     if path:
         print(f"Path: {path}")
@@ -28,7 +31,7 @@ def print_recommendation(path: str | None, text: str, ctx: InferenceContext,
         print(f"- {i}: {r} ({cat}-{subcat})")
 
     if interactive_rename and path is not None:
-        response = input("#, t [text], ?, q > ")
+        response = input("(n#), t, c, b, ?, q > ")
         
         if m := match(r'^([0-9]+)', response):
             selection = int(m.group(1))
@@ -43,16 +46,27 @@ def print_recommendation(path: str | None, text: str, ctx: InferenceContext,
             text = m.group(1)
             return True, text, None
         
-        elif m := match(r'^c (.*)', response):
+        elif m := match(r'^c (.+)', response):
             return True, None, m.group(1)
 
+        elif m := match(r'^b (.+)', response):
+            expt = []
+            for cat in ctx.catlist:
+                if cat.catid.startswith(m.group(1)):
+                    expt.append([f"{cat.catid}: ({cat.category}-{cat.subcategory})", 
+                              cat.explanations])
+            
+            print(tabulate(expt, maxcolwidths=80))
+            return True, text, None
+            
         elif response.startswith("?"):
             print("""
 Choices:
 - Enter recommendation number to rename file,
-- "t [text]" to search for new recommendations based on [text]
+- "t <text>" to search for new recommendations based on <text>
 - "p" re-use the last selected cat-id
-- "c [cat]" to type in a category by hand
+- "c <cat>" to type in a category by hand 
+- "b <cat>" browse category list for categories starting with <cat>
 - "?" for this message
 - "q" to quit
 - or any other key to skip this file and continue to next file
@@ -60,6 +74,8 @@ Choices:
             return True, text, None
         elif response.startswith('q'):
             return (False, None, None)
+        else:
+            print()
     else:
         return None