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3 changes: 3 additions & 0 deletions .jules/bolt.md
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Expand Up @@ -67,3 +67,6 @@
## 2025-02-12 - [Fast Path Execution in Directory Traversal and Log Parsing]
**Learning:** Checking for string existence (`if "silence_" not in stderr`) before invoking regex matchers provides significant speed improvements when parsing large blocks of text. Similarly, moving expensive I/O operations like `os.path.realpath` inside conditional blocks prevents redundant disk access when configuration (like path exclusions) isn't utilized.
**Action:** When working on large text processing or disk operations, verify if early exit conditions or conditional execution can bypass the expensive system or library calls.
## 2026-06-25 - [Fast Path for Alphanumeric Regex Replacements]
**Learning:** Using regex substitution (e.g. `re.sub(r"^\W+|\W+$", "")`) in tight tokenization loops is extremely CPU-bound and slow. However, the majority of tokens in standard text are purely alphanumeric without any punctuation.
**Action:** When tokenizing or processing text using regular expressions to strip non-word characters, prepend a fast-path check using `str.isalnum()` (or `str.isalpha()`) to bypass the regex overhead for purely alphanumeric words. This safely yields significant performance gains for most valid text inputs.
8 changes: 8 additions & 0 deletions summarize.py
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Expand Up @@ -94,6 +94,14 @@ def _content_words(sentence):
"""
words = []
for raw in sentence.split():
# Fast path check: if raw is alphanumeric, skip regex overhead.
# This significantly improves performance because most tokens
# do not contain punctuation and safely bypass the regex substitution.
if raw.isalnum():
token = raw.lower()
if token not in _STOPWORDS:
words.append(token)
continue
token = _TOKEN_STRIP_RE.sub("", raw).lower()
if token and token not in _STOPWORDS:
words.append(token)
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