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https://github.com/Dispatcharr/Dispatcharr.git
synced 2026-01-23 02:35:14 +00:00
perf: optimize EPG program parsing for multi-channel sources
Dramatically improve EPG refresh performance by parsing the XML file once per source instead of once per channel. The new implementation: - Pre-filters to only process EPG entries mapped to actual channels - Parses the entire XML file in a single pass - Uses O(1) set lookups to skip unmapped channel programmes - Skips non-mapped channels entirely with minimal overhead For EPG sources with many channels but few mapped (e.g., 10,000 channels with 100 mapped to channels), this provides approximately: - 99% reduction in file open operations - 99% reduction in XML file scans - Proportional reduction in CPU and I/O overhead The parse_programs_for_tvg_id() function is retained for single-channel use cases (e.g., when a new channel is mapped via signals). Fixes inefficient repeated file parsing that was occurring with large EPG sources.
This commit is contained in:
SergeantPanda
parent
2de6ac5da1
commit
2a8ba9125c
2 changed files with 209 additions and 71 deletions
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@ -13,6 +13,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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### Changed
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- **Performance**: EPG program parsing optimized for sources with many channels but only a fraction mapped. Now parses XML file once per source instead of once per channel, dramatically reducing I/O and CPU overhead. For sources with 10,000 channels and 100 mapped, this results in ~99x fewer file opens and ~100x fewer full file scans.
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- IPv6 access now allowed by default with all IPv6 CIDRs accepted - Thanks [@adrianmace](https://github.com/adrianmace)
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- nginx.conf updated to bind to both IPv4 and IPv6 ports - Thanks [@jordandalley](https://github.com/jordandalley)
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@ -1393,11 +1393,23 @@ def parse_programs_for_tvg_id(epg_id):
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def parse_programs_for_source(epg_source, tvg_id=None):
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"""
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Parse programs for all MAPPED channels from an EPG source in a single pass.
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This is an optimized version that:
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1. Only processes EPG entries that are actually mapped to channels
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2. Parses the XML file ONCE instead of once per channel
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3. Skips programmes for unmapped channels entirely during parsing
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This dramatically improves performance when an EPG source has many channels
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but only a fraction are mapped.
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"""
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# Send initial programs parsing notification
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send_epg_update(epg_source.id, "parsing_programs", 0)
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should_log_memory = False
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process = None
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initial_memory = 0
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source_file = None
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# Add memory tracking only in trace mode or higher
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try:
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@ -1417,82 +1429,199 @@ def parse_programs_for_source(epg_source, tvg_id=None):
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should_log_memory = False
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try:
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# Process EPG entries in batches rather than all at once
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batch_size = 20 # Process fewer channels at once to reduce memory usage
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epg_count = EPGData.objects.filter(epg_source=epg_source).count()
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# Only get EPG entries that are actually mapped to channels
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mapped_epg_ids = set(
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Channel.objects.filter(
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epg_data__epg_source=epg_source,
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epg_data__isnull=False
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).values_list('epg_data_id', flat=True)
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)
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if epg_count == 0:
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logger.info(f"No EPG entries found for source: {epg_source.name}")
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# Update status - this is not an error, just no entries
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if not mapped_epg_ids:
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total_epg_count = EPGData.objects.filter(epg_source=epg_source).count()
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logger.info(f"No channels mapped to any EPG entries from source: {epg_source.name} "
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f"(source has {total_epg_count} EPG entries, 0 mapped)")
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# Update status - this is not an error, just no mapped entries
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epg_source.status = 'success'
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epg_source.save(update_fields=['status'])
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epg_source.last_message = f"No channels mapped to this EPG source ({total_epg_count} entries available)"
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epg_source.save(update_fields=['status', 'last_message'])
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send_epg_update(epg_source.id, "parsing_programs", 100, status="success")
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return True
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logger.info(f"Parsing programs for {epg_count} EPG entries from source: {epg_source.name}")
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# Get the mapped EPG entries with their tvg_ids
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mapped_epgs = EPGData.objects.filter(id__in=mapped_epg_ids).values('id', 'tvg_id')
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tvg_id_to_epg_id = {epg['tvg_id']: epg['id'] for epg in mapped_epgs if epg['tvg_id']}
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mapped_tvg_ids = set(tvg_id_to_epg_id.keys())
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failed_entries = []
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program_count = 0
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channel_count = 0
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updated_count = 0
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processed = 0
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# Process in batches using cursor-based approach to limit memory usage
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last_id = 0
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while True:
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# Get a batch of EPG entries
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batch_entries = list(EPGData.objects.filter(
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epg_source=epg_source,
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id__gt=last_id
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).order_by('id')[:batch_size])
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total_epg_count = EPGData.objects.filter(epg_source=epg_source).count()
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mapped_count = len(mapped_tvg_ids)
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if not batch_entries:
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break # No more entries to process
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logger.info(f"Parsing programs for {mapped_count} MAPPED channels from source: {epg_source.name} "
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f"(skipping {total_epg_count - mapped_count} unmapped EPG entries)")
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# Update last_id for next iteration
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last_id = batch_entries[-1].id
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# Get the file path
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file_path = epg_source.extracted_file_path if epg_source.extracted_file_path else epg_source.file_path
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if not file_path:
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file_path = epg_source.get_cache_file()
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# Process this batch
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for epg in batch_entries:
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if epg.tvg_id:
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try:
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result = parse_programs_for_tvg_id(epg.id)
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if result == "Task already running":
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logger.info(f"Program parse for {epg.id} already in progress, skipping")
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# Check if the file exists
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if not os.path.exists(file_path):
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logger.error(f"EPG file not found at: {file_path}")
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processed += 1
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progress = min(95, int((processed / epg_count) * 100)) if epg_count > 0 else 50
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send_epg_update(epg_source.id, "parsing_programs", progress)
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except Exception as e:
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logger.error(f"Error parsing programs for tvg_id={epg.tvg_id}: {e}", exc_info=True)
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failed_entries.append(f"{epg.tvg_id}: {str(e)}")
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if epg_source.url:
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# Update the file path in the database
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new_path = epg_source.get_cache_file()
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logger.info(f"Updating file_path from '{file_path}' to '{new_path}'")
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epg_source.file_path = new_path
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epg_source.save(update_fields=['file_path'])
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logger.info(f"Fetching new EPG data from URL: {epg_source.url}")
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# Force garbage collection after each batch
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batch_entries = None # Remove reference to help garbage collection
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# Fetch new data before continuing
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fetch_success = fetch_xmltv(epg_source)
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if not fetch_success:
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logger.error(f"Failed to fetch EPG data for source: {epg_source.name}")
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epg_source.status = 'error'
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epg_source.last_message = f"Failed to download EPG data"
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epg_source.save(update_fields=['status', 'last_message'])
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send_epg_update(epg_source.id, "parsing_programs", 100, status="error", error="Failed to download EPG file")
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return False
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# Update file_path with the new location
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file_path = epg_source.extracted_file_path if epg_source.extracted_file_path else epg_source.file_path
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else:
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logger.error(f"No URL provided for EPG source {epg_source.name}, cannot fetch new data")
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epg_source.status = 'error'
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epg_source.last_message = f"No URL provided, cannot fetch EPG data"
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epg_source.save(update_fields=['status', 'last_message'])
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send_epg_update(epg_source.id, "parsing_programs", 100, status="error", error="No URL provided")
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return False
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# Delete existing programs for all mapped EPGs in one query
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logger.info(f"Deleting existing programs for {mapped_count} mapped EPG entries...")
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deleted_count = ProgramData.objects.filter(epg_id__in=mapped_epg_ids).delete()[0]
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logger.info(f"Deleted {deleted_count} existing programs")
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# SINGLE PASS PARSING: Parse the XML file once and process all mapped channels
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programs_to_create = []
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programs_by_channel = {tvg_id: 0 for tvg_id in mapped_tvg_ids} # Track count per channel
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total_programs = 0
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skipped_programs = 0
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batch_size = 1000
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last_progress_update = 0
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try:
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logger.debug(f"Opening file for single-pass parsing: {file_path}")
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source_file = open(file_path, 'rb')
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# Stream parse the file using lxml's iterparse
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program_parser = etree.iterparse(source_file, events=('end',), tag='programme', remove_blank_text=True, recover=True)
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for _, elem in program_parser:
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channel_id = elem.get('channel')
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# Skip programmes for unmapped channels immediately
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if channel_id not in mapped_tvg_ids:
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skipped_programs += 1
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# Clear element to free memory
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clear_element(elem)
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continue
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# This programme is for a mapped channel - process it
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try:
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start_time = parse_xmltv_time(elem.get('start'))
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end_time = parse_xmltv_time(elem.get('stop'))
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title = None
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desc = None
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sub_title = None
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# Efficiently process child elements
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for child in elem:
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if child.tag == 'title':
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title = child.text or 'No Title'
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elif child.tag == 'desc':
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desc = child.text or ''
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elif child.tag == 'sub-title':
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sub_title = child.text or ''
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if not title:
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title = 'No Title'
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# Extract custom properties
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custom_props = extract_custom_properties(elem)
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custom_properties_json = custom_props if custom_props else None
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epg_id = tvg_id_to_epg_id[channel_id]
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programs_to_create.append(ProgramData(
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epg_id=epg_id,
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start_time=start_time,
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end_time=end_time,
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title=title,
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description=desc,
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sub_title=sub_title,
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tvg_id=channel_id,
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custom_properties=custom_properties_json
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))
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total_programs += 1
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programs_by_channel[channel_id] += 1
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# Clear the element to free memory
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clear_element(elem)
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# Batch processing
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if len(programs_to_create) >= batch_size:
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ProgramData.objects.bulk_create(programs_to_create)
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logger.debug(f"Saved batch of {len(programs_to_create)} programs (total: {total_programs})")
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programs_to_create = []
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# Send progress update (estimate based on programs processed)
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# We don't know total programs upfront, so use a rough estimate
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if total_programs - last_progress_update >= 5000:
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last_progress_update = total_programs
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# Cap at 90% until we're done
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progress = min(90, 10 + int((total_programs / max(total_programs + 10000, 1)) * 80))
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send_epg_update(epg_source.id, "parsing_programs", progress,
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processed=total_programs, channels=mapped_count)
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# Periodic garbage collection
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if total_programs % (batch_size * 5) == 0:
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gc.collect()
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except Exception as e:
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logger.error(f"Error processing program for {channel_id}: {e}", exc_info=True)
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clear_element(elem)
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continue
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# Process any remaining items
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if programs_to_create:
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ProgramData.objects.bulk_create(programs_to_create)
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logger.debug(f"Saved final batch of {len(programs_to_create)} programs")
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except etree.XMLSyntaxError as xml_error:
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logger.error(f"XML syntax error parsing program data: {xml_error}")
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epg_source.status = EPGSource.STATUS_ERROR
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epg_source.last_message = f"XML parsing error: {str(xml_error)}"
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epg_source.save(update_fields=['status', 'last_message'])
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send_epg_update(epg_source.id, "parsing_programs", 100, status="error", message=str(xml_error))
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return False
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except Exception as e:
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logger.error(f"Error parsing XML for programs: {e}", exc_info=True)
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raise
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finally:
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if source_file:
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source_file.close()
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source_file = None
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gc.collect()
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# If there were failures, include them in the message but continue
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if failed_entries:
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epg_source.status = EPGSource.STATUS_SUCCESS # Still mark as success if some processed
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error_summary = f"Failed to parse {len(failed_entries)} of {epg_count} entries"
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stats_summary = f"Processed {program_count} programs across {channel_count} channels. Updated: {updated_count}."
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epg_source.last_message = f"{stats_summary} Warning: {error_summary}"
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epg_source.updated_at = timezone.now()
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epg_source.save(update_fields=['status', 'last_message', 'updated_at'])
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# Count channels that actually got programs
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channels_with_programs = sum(1 for count in programs_by_channel.values() if count > 0)
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# Send completion notification with mixed status
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send_epg_update(epg_source.id, "parsing_programs", 100,
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status="success",
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message=epg_source.last_message)
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# Explicitly release memory of large lists before returning
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del failed_entries
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gc.collect()
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return True
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# If all successful, set a comprehensive success message
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# Success message
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epg_source.status = EPGSource.STATUS_SUCCESS
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epg_source.last_message = f"Successfully processed {program_count} programs across {channel_count} channels. Updated: {updated_count}."
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epg_source.last_message = (
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f"Parsed {total_programs:,} programs for {channels_with_programs} channels "
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f"(skipped {skipped_programs:,} programmes for {total_epg_count - mapped_count} unmapped channels)"
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)
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epg_source.updated_at = timezone.now()
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epg_source.save(update_fields=['status', 'last_message', 'updated_at'])
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@ -1500,9 +1629,10 @@ def parse_programs_for_source(epg_source, tvg_id=None):
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log_system_event(
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event_type='epg_refresh',
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source_name=epg_source.name,
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programs=program_count,
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channels=channel_count,
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updated=updated_count,
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programs=total_programs,
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channels=channels_with_programs,
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skipped_programs=skipped_programs,
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unmapped_channels=total_epg_count - mapped_count,
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)
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# Send completion notification with status
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@ -1510,7 +1640,9 @@ def parse_programs_for_source(epg_source, tvg_id=None):
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status="success",
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message=epg_source.last_message)
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logger.info(f"Completed parsing all programs for source: {epg_source.name}")
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logger.info(f"Completed parsing programs for source: {epg_source.name} - "
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f"{total_programs:,} programs for {channels_with_programs} channels, "
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f"skipped {skipped_programs:,} programmes for unmapped channels")
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return True
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except Exception as e:
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@ -1525,14 +1657,19 @@ def parse_programs_for_source(epg_source, tvg_id=None):
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return False
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finally:
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# Final memory cleanup and tracking
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if source_file:
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try:
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source_file.close()
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except:
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pass
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source_file = None
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# Explicitly release any remaining large data structures
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failed_entries = None
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program_count = None
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channel_count = None
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updated_count = None
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processed = None
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programs_to_create = None
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programs_by_channel = None
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mapped_epg_ids = None
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mapped_tvg_ids = None
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tvg_id_to_epg_id = None
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gc.collect()
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# Add comprehensive memory cleanup at the end
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