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0.7.3

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# Stream-Mapparr Plugin Changelog (v0.7.2 -> v0.7.3)

### Matching Logic Improvements
- Implemented a length ratio check (75%) for substring matches to prevent partial word false positives (e.g., preventing "story" from matching "history").
- Added strict validation for numeric tokens; streams must now explicitly contain matching numbers if the channel name includes them (e.g., prevents "BBC1" from matching "CBBC").

### Features
- Added the underlying FuzzyMatcher library version number to the header of generated CSV export files for better debugging.

### Maintenance
- Updated the minimum required FuzzyMatcher version to 25.358.0200.
This commit is contained in:
Pirates IRC
2025-12-28 07:34:00 -06:00
committed by GitHub
parent bcf9cebbc3
commit 833ba094fc
2 changed files with 125 additions and 35 deletions
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129
Stream-Mapparr/fuzzy_matcher.py
View File

@@ -12,7 +12,7 @@ import unicodedata
from glob import glob
# Version: YY.DDD.HHMM (Julian date format: Year.DayOfYear.Time)
__version__ = "25.354.1835"
__version__ = "25.358.0200"
# Setup logging
LOGGER = logging.getLogger("plugins.fuzzy_matcher")
@@ -398,7 +398,20 @@ class FuzzyMatcher:
patterns_to_apply.extend(GEOGRAPHIC_PATTERNS)
if ignore_misc:
patterns_to_apply.extend(MISC_PATTERNS)
# CRITICAL FIX: Only apply MISC_PATTERNS (which removes ALL parentheses) if we're also
# ignoring regional tags. Otherwise, MISC_PATTERNS would strip regional indicators like
# "(WEST)" even when the user has set ignore_regional=False.
# This ensures that "BBC America" won't match "BBC AMERICA (WEST)" when ignore_regional=False
if ignore_regional:
# Safe to remove ALL parentheses since regional indicators are already being ignored
patterns_to_apply.extend(MISC_PATTERNS)
else:
# User wants to preserve regional indicators - skip MISC_PATTERNS to avoid
# removing parenthetical content that might be regional indicators
# Note: This means some misc tags like (CX), (B), (PRIME) won't be removed
# when ignore_regional=False, but this is the correct behavior to preserve
# regional tags like (WEST), (EAST), etc.
pass
# Apply selected hardcoded patterns
for pattern in patterns_to_apply:
@@ -406,22 +419,42 @@ class FuzzyMatcher:
# Apply user-configured ignored tags with improved handling
for tag in user_ignored_tags:
escaped_tag = re.escape(tag)
# Check if tag contains brackets or parentheses - if so, match literally
if '[' in tag or ']' in tag or '(' in tag or ')' in tag:
# Literal match for bracketed/parenthesized tags
escaped_tag = re.escape(tag)
name = re.sub(escaped_tag, '', name, flags=re.IGNORECASE)
# Literal match for bracketed/parenthesized tags, remove with trailing whitespace
name = re.sub(escaped_tag + r'\s*', '', name, flags=re.IGNORECASE)
else:
# Word boundary match for simple word tags to avoid partial matches
# e.g., "East" won't match the "east" in "Feast"
escaped_tag = re.escape(tag)
name = re.sub(r'\b' + escaped_tag + r'\b', '', name, flags=re.IGNORECASE)
# CRITICAL FIX: Word boundaries (\b) only work with alphanumeric characters
# Tags with Unicode/special characters (like ┃NLZIET┃) fail with word boundaries
# Check if tag contains only word characters (alphanumeric + underscore)
if re.match(r'^\w+$', tag):
# Safe to use word boundaries for pure word tags
# This prevents "East" from matching the "east" in "Feast"
name = re.sub(r'\b' + escaped_tag + r'\b', '', name, flags=re.IGNORECASE)
else:
# Tag contains special/Unicode characters - can't use word boundaries
# Match the tag followed by optional whitespace
name = re.sub(escaped_tag + r'\s*', '', name, flags=re.IGNORECASE)
# Remove callsigns in parentheses
name = re.sub(r'\([KW][A-Z]{3}(?:-(?:TV|CD|LP|DT|LD))?\)', '', name, flags=re.IGNORECASE)
# CRITICAL FIX: Don't remove regional indicators like (WEST), (EAST), etc. when ignore_regional=False
# The callsign pattern \([KW][A-Z]{3}...\) accidentally matches (WEST), (WETA), (KOMO), etc.
# We need to exclude known regional indicators even when matching callsigns
if ignore_regional:
# Safe to remove callsigns without checking for regional indicators
name = re.sub(r'\([KW][A-Z]{3}(?:-(?:TV|CD|LP|DT|LD))?\)', '', name, flags=re.IGNORECASE)
else:
# Only remove callsigns that are NOT regional indicators
# Use negative lookahead to exclude WEST, EAST, etc.
# Pattern matches (K or W) + 3 letters, but NOT if those 3 letters form a regional word
name = re.sub(r'\([KW](?!EST\)|ACIFIC\)|ENTRAL\)|OUNTAIN\)|TLANTIC\))[A-Z]{3}(?:-(?:TV|CD|LP|DT|LD))?\)', '', name, flags=re.IGNORECASE)
# Remove other tags in parentheses
name = re.sub(r'\([A-Z0-9]+\)', '', name)
# Remove other tags in parentheses (but only if we're also ignoring regional tags)
# Otherwise this would remove regional indicators like (WEST), (EAST), etc.
if ignore_regional:
name = re.sub(r'\([A-Z0-9]+\)', '', name)
# Remove common pattern fixes
name = re.sub(r'^The\s+', '', name, flags=re.IGNORECASE)
@@ -569,7 +602,8 @@ class FuzzyMatcher:
tokens = sorted([token for token in cleaned_s.split() if token])
return " ".join(tokens)
def find_best_match(self, query_name, candidate_names, user_ignored_tags=None, remove_cinemax=False):
def find_best_match(self, query_name, candidate_names, user_ignored_tags=None, remove_cinemax=False,
ignore_quality=True, ignore_regional=True, ignore_geographic=True, ignore_misc=True):
"""
Find the best fuzzy match for a name among a list of candidate names.
@@ -578,6 +612,10 @@ class FuzzyMatcher:
candidate_names: List of candidate names to match against
user_ignored_tags: User-configured tags to ignore
remove_cinemax: If True, remove "Cinemax" from candidate names
ignore_quality: If True, remove ALL quality indicators during normalization
ignore_regional: If True, remove regional indicator patterns during normalization
ignore_geographic: If True, remove ALL country code patterns during normalization
ignore_misc: If True, remove ALL content within parentheses during normalization
Returns:
Tuple of (matched_name, score) or (None, 0) if no match found
@@ -589,7 +627,11 @@ class FuzzyMatcher:
user_ignored_tags = []
# Normalize the query (channel name - don't remove Cinemax from it)
normalized_query = self.normalize_name(query_name, user_ignored_tags)
normalized_query = self.normalize_name(query_name, user_ignored_tags,
ignore_quality=ignore_quality,
ignore_regional=ignore_regional,
ignore_geographic=ignore_geographic,
ignore_misc=ignore_misc)
if not normalized_query:
return None, 0
@@ -602,7 +644,12 @@ class FuzzyMatcher:
for candidate in candidate_names:
# Normalize candidate (stream name) with Cinemax removal if requested
candidate_normalized = self.normalize_name(candidate, user_ignored_tags, remove_cinemax=remove_cinemax)
candidate_normalized = self.normalize_name(candidate, user_ignored_tags,
ignore_quality=ignore_quality,
ignore_regional=ignore_regional,
ignore_geographic=ignore_geographic,
ignore_misc=ignore_misc,
remove_cinemax=remove_cinemax)
# Skip candidates that normalize to empty or very short strings
if not candidate_normalized or len(candidate_normalized) < 2:
@@ -623,7 +670,8 @@ class FuzzyMatcher:
return None, 0
def fuzzy_match(self, query_name, candidate_names, user_ignored_tags=None, remove_cinemax=False):
def fuzzy_match(self, query_name, candidate_names, user_ignored_tags=None, remove_cinemax=False,
ignore_quality=True, ignore_regional=True, ignore_geographic=True, ignore_misc=True):
"""
Generic fuzzy matching function that can match any name against a list of candidates.
This is the main entry point for fuzzy matching.
@@ -633,6 +681,10 @@ class FuzzyMatcher:
candidate_names: List of candidate names to match against (stream names)
user_ignored_tags: User-configured tags to ignore
remove_cinemax: If True, remove "Cinemax" from candidate names (for channels with "max")
ignore_quality: If True, remove ALL quality indicators during normalization
ignore_regional: If True, remove regional indicator patterns during normalization
ignore_geographic: If True, remove ALL country code patterns during normalization
ignore_misc: If True, remove ALL content within parentheses during normalization
Returns:
Tuple of (matched_name, score, match_type) or (None, 0, None) if no match found
@@ -644,7 +696,11 @@ class FuzzyMatcher:
user_ignored_tags = []
# Normalize query (channel name - don't remove Cinemax from it)
normalized_query = self.normalize_name(query_name, user_ignored_tags)
normalized_query = self.normalize_name(query_name, user_ignored_tags,
ignore_quality=ignore_quality,
ignore_regional=ignore_regional,
ignore_geographic=ignore_geographic,
ignore_misc=ignore_misc)
if not normalized_query:
return None, 0, None
@@ -659,7 +715,12 @@ class FuzzyMatcher:
for candidate in candidate_names:
# Normalize candidate (stream name) with Cinemax removal if requested
candidate_normalized = self.normalize_name(candidate, user_ignored_tags, remove_cinemax=remove_cinemax)
candidate_normalized = self.normalize_name(candidate, user_ignored_tags,
ignore_quality=ignore_quality,
ignore_regional=ignore_regional,
ignore_geographic=ignore_geographic,
ignore_misc=ignore_misc,
remove_cinemax=remove_cinemax)
# Skip candidates that normalize to empty or very short strings (< 2 chars)
# This prevents false positives where multiple streams all normalize to ""
@@ -686,7 +747,12 @@ class FuzzyMatcher:
# Stage 2: Substring matching
for candidate in candidate_names:
# Normalize candidate (stream name) with Cinemax removal if requested
candidate_normalized = self.normalize_name(candidate, user_ignored_tags, remove_cinemax=remove_cinemax)
candidate_normalized = self.normalize_name(candidate, user_ignored_tags,
ignore_quality=ignore_quality,
ignore_regional=ignore_regional,
ignore_geographic=ignore_geographic,
ignore_misc=ignore_misc,
remove_cinemax=remove_cinemax)
# Skip candidates that normalize to empty or very short strings
if not candidate_normalized or len(candidate_normalized) < 2:
@@ -696,18 +762,29 @@ class FuzzyMatcher:
# Check if one is a substring of the other
if normalized_query_lower in candidate_lower or candidate_lower in normalized_query_lower:
# Calculate similarity score
ratio = self.calculate_similarity(normalized_query_lower, candidate_lower)
if ratio > best_ratio:
best_match = candidate
best_ratio = ratio
match_type = "substring"
# CRITICAL FIX: Add length ratio requirement to prevent false positives
# like "story" matching "history" (story is 5 chars, history is 7 chars)
# Require strings to be within 75% of same length for substring match
# This ensures substring matches are semantically meaningful
length_ratio = min(len(normalized_query_lower), len(candidate_lower)) / max(len(normalized_query_lower), len(candidate_lower))
if length_ratio >= 0.75:
# Calculate similarity score
ratio = self.calculate_similarity(normalized_query_lower, candidate_lower)
if ratio > best_ratio:
best_match = candidate
best_ratio = ratio
match_type = "substring"
if best_match and int(best_ratio * 100) >= self.match_threshold:
return best_match, int(best_ratio * 100), match_type
# Stage 3: Fuzzy matching with token sorting
fuzzy_match, score = self.find_best_match(query_name, candidate_names, user_ignored_tags, remove_cinemax=remove_cinemax)
fuzzy_match, score = self.find_best_match(query_name, candidate_names, user_ignored_tags,
remove_cinemax=remove_cinemax,
ignore_quality=ignore_quality,
ignore_regional=ignore_regional,
ignore_geographic=ignore_geographic,
ignore_misc=ignore_misc)
if fuzzy_match:
return fuzzy_match, score, f"fuzzy ({score})"

29
Stream-Mapparr/plugin.py
View File

@@ -21,6 +21,8 @@ import threading
# Import FuzzyMatcher from the same directory
from .fuzzy_matcher import FuzzyMatcher
# Import fuzzy_matcher version for CSV header
from . import fuzzy_matcher
# Django model imports - same approach as Event Channel Managarr
from apps.channels.models import Channel, ChannelProfileMembership, ChannelStream, Stream
@@ -63,8 +65,8 @@ class PluginConfig:
"""
# === PLUGIN METADATA ===
PLUGIN_VERSION = "0.7.2"
FUZZY_MATCHER_MIN_VERSION = "25.354.1835" # Requires complete regional patterns support
PLUGIN_VERSION = "0.7.3"
FUZZY_MATCHER_MIN_VERSION = "25.358.0200" # Requires custom ignore tags Unicode fix
# === MATCHING SETTINGS ===
DEFAULT_FUZZY_MATCH_THRESHOLD = 85 # Minimum similarity score (0-100)
@@ -2021,7 +2023,9 @@ class Plugin:
if self.fuzzy_matcher:
stream_names = [stream['name'] for stream in working_streams]
matched_stream_name, score, match_type = self.fuzzy_matcher.fuzzy_match(
channel_name, stream_names, ignore_tags, remove_cinemax=channel_has_max
channel_name, stream_names, ignore_tags, remove_cinemax=channel_has_max,
ignore_quality=ignore_quality, ignore_regional=ignore_regional,
ignore_geographic=ignore_geographic, ignore_misc=ignore_misc
)
if matched_stream_name:
@@ -2055,10 +2059,16 @@ class Plugin:
# Substring match: stream contains channel OR channel contains stream
if stream_lower in channel_lower or channel_lower in stream_lower:
# Calculate similarity to ensure it meets threshold
similarity = self.fuzzy_matcher.calculate_similarity(stream_lower, channel_lower)
if int(similarity * 100) >= self.fuzzy_matcher.match_threshold:
matching_streams.append(stream)
# CRITICAL FIX: Add length ratio requirement to prevent false positives
# like "story" matching "history" (story is 5 chars, history is 7 chars)
# Require strings to be within 75% of same length for substring match
# This ensures substring matches are semantically meaningful
length_ratio = min(len(stream_lower), len(channel_lower)) / max(len(stream_lower), len(channel_lower))
if length_ratio >= 0.75:
# Calculate similarity to ensure it meets threshold
similarity = self.fuzzy_matcher.calculate_similarity(stream_lower, channel_lower)
if int(similarity * 100) >= self.fuzzy_matcher.match_threshold:
matching_streams.append(stream)
continue
# Token-based matching: check if significant tokens overlap
@@ -2245,7 +2255,9 @@ class Plugin:
try:
stream_names = [stream['name'] for stream in all_streams]
matched_stream_name, score, match_type = self.fuzzy_matcher.fuzzy_match(
channel_name, stream_names, ignore_tags, remove_cinemax=channel_has_max
channel_name, stream_names, ignore_tags, remove_cinemax=channel_has_max,
ignore_quality=ignore_quality, ignore_regional=ignore_regional,
ignore_geographic=ignore_geographic, ignore_misc=ignore_misc
)
if matched_stream_name:
@@ -3279,6 +3291,7 @@ class Plugin:
# Build header with all settings except login credentials
header_lines = [
f"# Stream-Mapparr Export v{self.version}",
f"# FuzzyMatcher Version: {fuzzy_matcher.__version__}",
f"# Export Date: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}",
"#",
"# === Action Performed ===",