Rank channel search results by relevance, run search off the event loop

list_channel previously matched every playlist with one unranked
".*keyword.*" regex, so a specific channel name could be buried pages
behind unrelated names that merely contained the keyword mid-word.
Split matches into two tiers (word-boundary match first, then
anywhere-else) using a cheap count+skip/limit per tier so pagination
still avoids pulling every match into memory.

Also found while testing against a 1.19M-channel playlist: searching
scans an unindexed regex and can take several seconds, and it was
running synchronously inside the async handler, freezing every other
request/socket for that whole time. Moved it to run_in_executor;
verified a concurrent request now returns in ~2ms while a 3.6s search
is in flight.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
ubuntu
2026-08-31 01:33:27 +00:00
co-authored by Claude Sonnet 5
parent 685bbb1683
commit 4e596114c1
+49 -22
View File
@@ -892,31 +892,44 @@ async def get_source(request):
# List Channels
async def list_channel(request):
def _search_channels_sync(channel_to_search, current_page):
MAX_RECORDS = 30
data = await request.post()
channel_to_search = unquote(data['keyword'])
current_page = int(data['num_page'])
escaped_keyword = re.escape(channel_to_search)
# Channel names are typically prefixed with a country/format tag (e.g.
# "AR - BEIN SPORTS 1 FHD"), so match at word boundaries rather than the
# start of the string to rank those above unrelated names that merely
# contain the keyword mid-word.
prefix_pattern = re.compile(r'\b' + escaped_keyword, re.IGNORECASE)
contains_pattern = re.compile(escaped_keyword, re.IGNORECASE)
logger.info("Search keyword='%s' page=%s", channel_to_search, current_page)
regex_pattern = ".*" + re.escape(channel_to_search) + ".*"
# First pass: compute totals without pulling all docs into memory
total_records = 0
active_playlists = list(playlists.find({"activation": 1}))
per_playlist_counts = []
# Two relevance tiers, most relevant first: names starting with the keyword,
# then everything else that merely contains it. Counted per tier/playlist so
# pagination stays a cheap count+skip/limit instead of pulling every match
# into memory to sort it.
tiers = []
for playlist in active_playlists:
collection_channels = db_iptv['channels_' + playlist['id_playlist']]
count = collection_channels.count_documents({
prefix_filter = {'id_playlist': playlist['id_playlist'], 'Name': prefix_pattern}
count = collection_channels.count_documents(prefix_filter)
if count:
tiers.append((playlist, prefix_filter, count))
for playlist in active_playlists:
collection_channels = db_iptv['channels_' + playlist['id_playlist']]
contains_only_filter = {
'id_playlist': playlist['id_playlist'],
'Name': {'$regex': regex_pattern, '$options': "i"}
})
per_playlist_counts.append((playlist, count))
total_records += count
'$and': [{'Name': contains_pattern}, {'Name': {'$not': prefix_pattern}}],
}
count = collection_channels.count_documents(contains_only_filter)
if count:
tiers.append((playlist, contains_only_filter, count))
total_records = sum(count for _, _, count in tiers)
if total_records == 0:
return web.json_response({'num_total_page': 0, 'current_page': 1, 'data': []})
return {'num_total_page': 0, 'current_page': 1, 'data': []}
num_total_page = max(1, (total_records + MAX_RECORDS - 1) // MAX_RECORDS)
current_page = max(1, min(current_page, num_total_page))
@@ -926,7 +939,7 @@ async def list_channel(request):
# Second pass: fetch only the page slice
serialized_data = []
offset = 0
for playlist, count in per_playlist_counts:
for playlist, mongo_filter, count in tiers:
if remaining == 0:
break
if offset + count <= begin:
@@ -936,16 +949,30 @@ async def list_channel(request):
local_skip = max(0, begin - offset)
fetch_limit = min(remaining, count - local_skip)
collection_channels = db_iptv['channels_' + playlist['id_playlist']]
cursor = collection_channels.find({
'id_playlist': playlist['id_playlist'],
'Name': {'$regex': regex_pattern, '$options': "i"}
}).skip(local_skip).limit(fetch_limit)
cursor = collection_channels.find(mongo_filter).skip(local_skip).limit(fetch_limit)
serialized_data.extend(serialize_doc(doc) for doc in cursor)
remaining = MAX_RECORDS - len(serialized_data)
offset += count
return web.json_response({'num_total_page': num_total_page, 'current_page': current_page, 'data': serialized_data})
return {'num_total_page': num_total_page, 'current_page': current_page, 'data': serialized_data}
async def list_channel(request):
data = await request.post()
channel_to_search = unquote(data['keyword'])
current_page = int(data['num_page'])
logger.info("Search keyword='%s' page=%s", channel_to_search, current_page)
# Searching can mean scanning a multi-hundred-thousand-channel collection
# with an unindexed regex (several seconds); run it off the event loop so
# it doesn't stall every other request/socket while it works.
result = await asyncio.get_running_loop().run_in_executor(
None, _search_channels_sync, channel_to_search, current_page
)
return web.json_response(result)