408 lines
14 KiB
Python
408 lines
14 KiB
Python
import os
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import subprocess
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import threading
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import time
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from concurrent.futures import ThreadPoolExecutor
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from typing import Dict, List
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from thefuzz import fuzz
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import utils.icons as icons
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from modules.launcher.plugin_base import PluginBase
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from modules.launcher.result import Result
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class FilesPlugin(PluginBase):
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"""
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High-performance plugin for searching files only (excludes directories).
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Uses advanced fuzzy matching, caching, and threading for optimal performance.
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"""
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def __init__(self):
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super().__init__()
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self.display_name = "Files"
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self.description = "Search for files only"
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# Performance-optimized search paths - focus on user directories
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self.search_paths = [
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os.path.expanduser("~/Documents"),
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os.path.expanduser("~/Downloads"),
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os.path.expanduser("~/Desktop"),
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os.path.expanduser("~/Pictures"),
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os.path.expanduser("~/Videos"),
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os.path.expanduser("~/Music"),
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os.path.expanduser("~"), # Home directory but with limited depth
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]
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# Performance settings
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self.max_results = 15
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self.max_depth = 2 # Reduced depth for better performance
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self.search_timeout = 0.5 # Reduced timeout
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self.min_query_length = 1 # Allow single character searches
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# Fuzzy search settings - optimized for performance
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self.fuzzy_thresholds = {
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"ratio": 70, # Increased for better precision
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"partial": 80, # Increased for better precision
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"token_sort": 75, # Increased for better precision
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"token_set": 75, # Increased for better precision
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}
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# Enhanced caching
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self.file_cache: Dict[str, List[str]] = {}
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self.cache_timestamp: Dict[str, float] = {}
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self.cache_ttl = 300
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self.cache_lock = threading.Lock()
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# Thread pool for concurrent searches
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self.executor = ThreadPoolExecutor(
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max_workers=4, thread_name_prefix="files-search"
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)
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def initialize(self):
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"""Initialize the files plugin."""
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self.set_triggers(
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[
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"file",
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"find",
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]
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)
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self._warm_cache()
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def cleanup(self):
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"""Cleanup the files plugin."""
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if hasattr(self, "executor"):
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self.executor.shutdown(wait=False)
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with self.cache_lock:
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self.file_cache.clear()
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self.cache_timestamp.clear()
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def query(self, query_string: str) -> List[Result]:
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"""Fast search for files matching the query."""
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query = query_string.strip()
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if len(query) < self.min_query_length:
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return []
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# Handle special path queries
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if query.startswith("/") or query.startswith("~"):
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return self._handle_path_query(query)
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# Always search for files only since this is the files plugin
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# triggered by "file" or "find" keywords
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is_file_only = True
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# Use cached search for better performance
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results = self._fast_search(query, file_only=is_file_only)
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# Sort by relevance and limit results
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results.sort(key=lambda r: r.relevance, reverse=True)
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return results[: self.max_results]
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def _warm_cache(self):
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"""Pre-warm cache for common directories in background."""
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def warm_directory(path):
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try:
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if os.path.exists(path) and os.path.isdir(path):
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self._get_cached_files(path)
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except:
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pass
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for path in self.search_paths:
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threading.Thread(target=warm_directory, args=(path,), daemon=True).start()
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def _handle_path_query(self, query: str) -> List[Result]:
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"""Handle path-based queries like '/home' or '~/Documents'."""
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try:
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expanded_path = (
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os.path.expanduser(query) if query.startswith("~") else query
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)
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if os.path.isdir(expanded_path):
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return self._list_directory_contents(expanded_path)
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parent_dir = os.path.dirname(expanded_path)
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if os.path.isdir(parent_dir):
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basename = os.path.basename(expanded_path)
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return self._search_in_directory(parent_dir, basename, max_results=10)
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except Exception:
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pass
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return []
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def _fast_search(self, query: str, file_only: bool = False) -> List[Result]:
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"""Fast search using cached file lists and optimized matching."""
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results = []
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query_lower = query.lower()
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# Early exit for empty queries
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if len(query_lower) < self.min_query_length:
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return results
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# Search in cached directories with early termination
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for search_path in self.search_paths:
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if not os.path.exists(search_path):
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continue
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# Skip home directory if we already have enough results from specific folders
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if (
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search_path == os.path.expanduser("~")
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and len(results) >= self.max_results
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):
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continue
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cached_files = self._get_cached_files(search_path)
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for file_path in cached_files:
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if file_only and os.path.isdir(file_path):
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continue
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filename = os.path.basename(file_path)
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# Fast pre-filter: check if query is in filename before expensive fuzzy matching
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if query_lower not in filename.lower():
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# Only do fuzzy matching if simple substring match fails
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if not self._simple_fuzzy_match(query_lower, filename):
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continue
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relevance = self._calculate_relevance(filename, query_lower)
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result = self._create_file_result(file_path, relevance)
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if result:
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results.append(result)
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# Early termination when we have enough results
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if len(results) >= self.max_results * 3:
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return results
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return results
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def _get_cached_files(self, directory: str) -> List[str]:
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"""Get cached file list for directory, refresh if needed."""
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current_time = time.time()
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with self.cache_lock:
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if (
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directory in self.file_cache
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and directory in self.cache_timestamp
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and current_time - self.cache_timestamp[directory] < self.cache_ttl
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):
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return self.file_cache[directory]
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files = self._scan_directory_fast(directory)
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self.file_cache[directory] = files
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self.cache_timestamp[directory] = current_time
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return files
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def _scan_directory_fast(self, directory: str) -> List[str]:
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"""Fast directory scan with optimized depth and early termination."""
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files = []
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current_depth = 0
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max_files_per_dir = 1000 # Limit files per directory to prevent memory issues
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def scan_dir(path: str, depth: int):
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if depth > self.max_depth or len(files) >= max_files_per_dir:
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return
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try:
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with os.scandir(path) as entries:
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for entry in entries:
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try:
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if entry.name.startswith("."):
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continue
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# Skip common large directories that are unlikely to contain user files
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if entry.is_dir() and entry.name in {
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"node_modules",
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".git",
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".cache",
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"__pycache__",
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".npm",
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".cargo",
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".rustup",
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"target",
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"build",
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".vscode",
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".idea",
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"venv",
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".env",
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}:
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continue
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files.append(entry.path)
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# Early termination if we have too many files
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if len(files) >= max_files_per_dir:
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return
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# Only recurse into directories if we're not at max depth
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# and for home directory, be more selective
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if entry.is_dir() and depth < self.max_depth:
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if path == os.path.expanduser("~"):
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# For home directory, only scan important subdirectories
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if self._is_important_directory(entry.name):
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scan_dir(entry.path, depth + 1)
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else:
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scan_dir(entry.path, depth + 1)
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except (PermissionError, OSError):
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continue
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except (PermissionError, OSError):
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pass
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scan_dir(directory, current_depth)
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return files
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def _is_important_directory(self, dirname: str) -> bool:
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"""Check if directory is important enough to scan deeper."""
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important_dirs = {
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"Documents",
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"Downloads",
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"Desktop",
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"Pictures",
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"Videos",
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"Music",
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"Projects",
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"Code",
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"Development",
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"Work",
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"src",
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"bin",
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}
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return dirname in important_dirs
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def _search_in_directory(
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self, directory: str, query: str, max_results: int = 10
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) -> List[Result]:
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"""Search for files in a specific directory."""
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results = []
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query_lower = query.lower()
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try:
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with os.scandir(directory) as entries:
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for entry in entries:
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if self._simple_fuzzy_match(query_lower, entry.name):
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relevance = self._calculate_relevance(entry.name, query_lower)
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result = self._create_file_result(entry.path, relevance)
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if result:
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results.append(result)
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if len(results) >= max_results:
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break
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except (PermissionError, OSError):
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pass
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return results
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def _list_directory_contents(
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self, directory: str, max_results: int = 15
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) -> List[Result]:
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"""List contents of a directory."""
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results = []
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try:
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with os.scandir(directory) as entries:
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for entry in entries:
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if not entry.name.startswith("."):
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result = self._create_file_result(entry.path, 0.8)
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if result:
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results.append(result)
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if len(results) >= max_results:
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break
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except (PermissionError, OSError):
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pass
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return results
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def _create_file_result(self, file_path: str, relevance: float) -> Result:
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"""Create a Result object for a file or directory."""
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try:
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filename = os.path.basename(file_path)
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is_dir = os.path.isdir(file_path)
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return Result(
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title=filename,
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subtitle=file_path,
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icon_markup=icons.file,
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action=lambda p=file_path: self._open_path(p),
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relevance=relevance,
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plugin_name=self.display_name,
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data={"path": file_path, "type": "directory" if is_dir else "file"},
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)
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except Exception:
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return None
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def _open_path(self, path: str):
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"""Open a file or directory with the default application."""
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try:
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subprocess.Popen(
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["xdg-open", path], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL
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)
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except Exception as e:
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print(f"Failed to open {path}: {e}")
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def _open_file(self, file_path: str):
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"""Open a file with the default application."""
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self._open_path(file_path)
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def _open_directory(self, dir_path: str):
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"""Open a directory in the file manager."""
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self._open_path(dir_path)
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def _simple_fuzzy_match(self, query: str, text: str) -> bool:
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"""Optimized fuzzy matching with performance improvements."""
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text_lower = text.lower()
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query_lower = query.lower()
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# Fast exact substring match
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if query_lower in text_lower:
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return True
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# Fast prefix match
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if text_lower.startswith(query_lower):
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return True
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# Only do expensive fuzzy matching for longer queries
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if len(query_lower) >= 3:
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# Use only the most effective fuzzy matching methods
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return (
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fuzz.partial_ratio(query_lower, text_lower)
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>= self.fuzzy_thresholds["partial"]
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or fuzz.ratio(query_lower, text_lower) >= self.fuzzy_thresholds["ratio"]
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)
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return False
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def _calculate_relevance(self, filename: str, query: str) -> float:
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"""Calculate relevance score with optimized performance."""
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filename_lower = filename.lower()
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query_lower = query.lower()
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# Fast exact match
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if query_lower == filename_lower:
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return 1.0
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# Fast prefix match
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if filename_lower.startswith(query_lower):
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return 0.95
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# Fast substring match
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if query_lower in filename_lower:
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# Calculate position-based relevance
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position = filename_lower.index(query_lower)
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position_score = 1.0 - (position / len(filename_lower))
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return 0.8 + (position_score * 0.1)
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# Only do expensive fuzzy matching for longer queries
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if len(query_lower) >= 3:
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partial = fuzz.partial_ratio(query_lower, filename_lower)
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ratio = fuzz.ratio(query_lower, filename_lower)
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# Simplified relevance calculation
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relevance = (partial * 0.6 + ratio * 0.4) / 100.0
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return max(relevance, 0.3) # Minimum relevance for fuzzy matches
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return 0.3 # Default relevance for short queries
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