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⚡ Bolt: [performance improvement] Pre-compile regexes and use O(1) set in keyword density #267

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⚡ Bolt: [performance improvement] Pre-compile regexes and use O(1) set in keyword density #267

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110 changes: 55 additions & 55 deletions cli/utils/keyword_density.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,56 @@
from ..utils.config import Config
from ..utils.yaml_parser import ResumeYAML

_TITLE_PATTERNS = [
re.compile(r"(?:job title|position|title):\s*([^\n]+)", re.IGNORECASE | re.MULTILINE),
re.compile(r"^([^\n]+)\s*[-|]\s*[^|]+$", re.IGNORECASE | re.MULTILINE),
re.compile(r"#\s*([^\n]+)", re.IGNORECASE | re.MULTILINE),
]

_COMPANY_PATTERNS = [
re.compile(r"(?:company|organization):\s*([^\n]+)", re.IGNORECASE),
re.compile(r"(?:at|from)\s+([A-Z][^\n]+?)(?:\s+[-\u2014]|\s+$)", re.IGNORECASE),
]

_TECH_KEYWORDS = {
"python",
"javascript",
"typescript",
"react",
"vue",
"angular",
"node.js",
"django",
"flask",
"fastapi",
"kubernetes",
"docker",
"aws",
"gcp",
"azure",
"sql",
"mongodb",
"postgresql",
"redis",
"ci/cd",
"devops",
"machine learning",
"ai",
"llm",
"pytorch",
"tensorflow",
"graphql",
"rest api",
"microservices",
"java",
"go",
"rust",
"c++",
"c#",
".net",
"spring",
}

# Load environment variables from .env file if present
try:
from dotenv import load_dotenv
Expand Down Expand Up @@ -208,26 +258,15 @@ def _extract_job_details(self, job_description: str) -> Tuple[str, str]:
company = ""

# Try to extract job title (common patterns)
title_patterns = [
r"(?:job title|position|title):\s*([^\n]+)",
r"^([^\n]+)\s*[-|]\s*[^|]+$",
r"#\s*([^\n]+)", # Markdown headers often have job title
]

for pattern in title_patterns:
match = re.search(pattern, job_description, re.IGNORECASE | re.MULTILINE)
for pattern in _TITLE_PATTERNS:
match = pattern.search(job_description)
if match:
job_title = match.group(1).strip()
break

# Try to extract company name
company_patterns = [
r"(?:company|organization):\s*([^\n]+)",
r"(?:at|from)\s+([A-Z][^\n]+?)(?:\s+[-\u2014]|\s+$)",
]

for pattern in company_patterns:
match = re.search(pattern, job_description, re.IGNORECASE)
for pattern in _COMPANY_PATTERNS:
match = pattern.search(job_description)
if match:
company = match.group(1).strip()
break
Expand Down Expand Up @@ -398,46 +437,7 @@ def _suggest_sections_for_keyword(
suggestions = []

# Check if keyword is tech-related
tech_keywords = [
"python",
"javascript",
"typescript",
"react",
"vue",
"angular",
"node.js",
"django",
"flask",
"fastapi",
"kubernetes",
"docker",
"aws",
"gcp",
"azure",
"sql",
"mongodb",
"postgresql",
"redis",
"ci/cd",
"devops",
"machine learning",
"ai",
"llm",
"pytorch",
"tensorflow",
"graphql",
"rest api",
"microservices",
"java",
"go",
"rust",
"c++",
"c#",
".net",
"spring",
]

if keyword.lower() in tech_keywords:
if keyword.lower() in _TECH_KEYWORDS:
suggestions.append("Skills section")

# Check experience bullets
Expand Down
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