Restructured module in preparation for setuptools packaging.

lark-ui

@@ -8,11 +8,10 @@ Verify and sort game ROM images.
 import hashlib
 import sys
 import os
-import uuid
 import xdg.BaseDirectory
 
 #import dat
-import metadata
+from lark import metadata
 
 HASH_CHUNK_SIZE = 10485760 # 10mb
 SQLITE_FILENAME = 'metadata.db'
@@ -30,28 +29,8 @@ def get_sha1sum(filename):
 
     return sha1sum.hexdigest()
 
-
-'''
-smd_dat = dat(SMD_DAT_PATH)
-# TODO: Default to '.'
-# TODO: Use a proper arg parser.
-search_dir = sys.argv[1]
-for filename in os.listdir(search_dir):
-    # TODO: Ignore or descend into directories.
-    # TODO: Compare hashes
-    file_path = os.path.abspath(os.path.join(search_dir, filename))
-    file_sha1 = get_sha1sum(file_path)
-    search_result = smd_dat.search_by_sha1(file_sha1)
-    if search_result:
-        rom_data = search_result[0]
-        print('File %s matches database entry for %s.' % (filename, rom_data.filename))
-    else:
-        print('File %s is not in database.' % filename)
-'''
 # Test code! :D
 # TODO: Write test code that doesn't depend on external resources.
-SMD_DAT_PATH = '/home/lumia/Downloads/Sega - Mega Drive - Genesis (20200303-035539).dat'
-TEST_HASH = 'cfbf98c36c776677290a872547ac47c53d2761d6'
 
 def _kwargs_parse(kwargs_list):
     kwargs = {}

lark/metadata.py

@@ -91,11 +91,14 @@ def configure(db_path):
 
     db_path: Path for the SQLite database
     '''
+    global _configured
+    global _engine
     _engine = sqlalchemy.create_engine('sqlite:///%s' % db_path)
 
     _SQLBase.metadata.create_all(_engine)
     _db_session_maker.configure(bind=_engine)
     _configured = True
+    print('Database configured.')
 
 # TODO: Passing the session object is a little clunky. Maybe there's a way to infer it somehow?
 def search(session, table_object, **constraints):

readme.md

@@ -14,6 +14,9 @@ directory structure.
 * A nice, Beets-like interface
 * Grouping ROMS in archive files
 
+## Dependencies
+* SQLAlchemy
+
 ## Known issues
 * This probably isn't terribly efficient. It's Python parsing XML into an SQLite database and I only
   know pretty basic database design.