use threads to read/hash multiple datablocks at a time..

as we might have a lot of work to submit, BUT it might fail early,
don't submit too much work early on, just for it to fail, so we
limit how much work we submit..

ui/medashare/btv/__init__.py

@@ -1,5 +1,6 @@
 
 from . import bencode
+import concurrent
 import fnmatch
 from functools import reduce
 from hashlib import sha1, sha512
@@ -247,7 +248,7 @@ def validate(torrent, basedir, with_file_hashes=None):
 
 	file_hashes = dict()
 
-	def apply_fun(data, fname, offset):
+	def apply_fun(hash, data, fname, offset):
 		if with_file_hashes is not None:
 			try:
 				hio = file_hashes[fname]
@@ -262,16 +263,32 @@ def validate(torrent, basedir, with_file_hashes=None):
 	pieces = info['pieces']
 	piecescnt = len(pieces) // 20
 	valid = [ None ] * piecescnt
-	for num, i in enumerate(pieces[x:x+20] for x in range(0, len(pieces),
-	    20)):
-		hash = sha1()
+	with concurrent.futures.ThreadPoolExecutor(max_workers=os.cpu_count()) as executor:
+		futures = {}
 
-		stor.apply_piece(num, apply_fun)
+		pending_work = [ x for x in enumerate(pieces[x:x+20] for x in range(0, len(pieces), 20)) ]
 
-		if hash.digest() == i:
-			valid[num] = True
-		else:
-			valid[num] = False
+		def submit_work(num, i):
+			hash = sha1()
+
+			fut = executor.submit(stor.apply_piece, num, lambda *args: apply_fun(hash, *args))
+
+			futures[fut] = num, hash, i
+
+		for i in range(min(len(pending_work), os.cpu_count() + 1)):
+			submit_work(*pending_work.pop(0))
+
+		for future in concurrent.futures.as_completed(futures):
+			if pending_work:
+				submit_work(*pending_work.pop(0))
+
+			future.result()
+			num, hash, i = futures[future]
+
+			if hash.digest() == i:
+				valid[num] = True
+			else:
+				valid[num] = False
 
 	if files is None:
 		filesizes = { pathlib.PurePosixPath(info['name'].decode(