HR-ATS-Portal/backend/employment_agent/plugins.py

188 lines
5.9 KiB
Python

"""CV contact parsers — phone and LinkedIn, decorated by employment_agent.decorators.
Pure module: no FastAPI imports and no HTTPException.
Call like the rest of the backend:
fields=parse_phone({"phone":raw},resume_text)
phone=fields["phone"]
fields=parse_linkedin({"linkedin_url":raw},resume_text)
url=fields["linkedin_url"]
`scan_phone` is the digit-span scan `prefer_extracted_phone` uses so the
stacked parser cannot recurse into itself.
"""
from __future__ import annotations
import re
from employment_agent.decorators import (
clamp_linkedin_url,
clamp_phone,
prefer_extracted_phone,
)
# PDF extraction uses en/em dashes, nbsp, and bullets as digit separators.
_DASH_TO_HYPHEN=str.maketrans({
"\u2010":"-","\u2011":"-","\u2012":"-","\u2013":"-","\u2014":"-",
"\u2015":"-","\u2212":"-","\u2043":"-","\uFE58":"-","\uFE63":"-",
"\uFF0D":"-",
})
_STRIP_INVISIBLE="".join((
"\u00ad","\u200b","\u200c","\u200d","\u2060","\ufeff",
))
_DIGIT_TO_ASCII=str.maketrans({
**{chr(0x0660+i):str(i) for i in range(10)},
**{chr(0x06F0+i):str(i) for i in range(10)},
**{chr(0xFF10+i):str(i) for i in range(10)},
})
_OCR_O=re.compile(r"(?<![A-Za-z0-9])[Oo](?=3\d{2}[\s\-.\d]{6,})")
_DIGIT_GROUP=re.compile(r"\+?\d+")
_GAP_OK=re.compile(r"^[\s\-./()[\]{},:|•·∙+_]*$")
_WA_ME=re.compile(r"(?i)(?:wa\.me/|api\.whatsapp\.com/send\?phone=)(\+?\d{10,15})")
_TEL_URI=re.compile(r"(?i)tel:\s*(\+?[\d\s\-().]{8,22})")
_YEAR=re.compile(r"^(?:19|20)\d{2}$")
def _normalize_phone_text(text:str) -> str:
raw=(text or "").translate(_DIGIT_TO_ASCII).translate(_DASH_TO_HYPHEN)
raw=raw.replace("\xa0"," ").replace("\u202f"," ").replace("\u2009"," ")
raw=raw.replace("\u2007"," ").replace("\u2028","\n").replace("\u2029","\n")
for ch in _STRIP_INVISIBLE:
raw=raw.replace(ch,"")
return _OCR_O.sub("0",raw)
def _digits_only(raw:str) -> str:
return re.sub(r"\D","",_normalize_phone_text(raw or ""))
def _phone_digits(raw:str) -> str:
digits=_digits_only(raw)
if digits.startswith("00"):
digits=digits[2:]
return digits
def _phone_score(digits:str) -> int:
"""Prefer complete PK mobiles; reject CNIC-shaped 13-digit runs."""
n=len(digits)
if n<10 or n>15:
return -1
if n==13 and not digits.startswith("92"):
return -1
if digits.startswith("03") and n==11:
return 200
if digits.startswith("923") and n==12:
return 190
if digits.startswith("3") and n==10:
return 180
return n
def _phone_keys(digits:str) -> set[str]:
"""03XX / +92 3XX / 3XX national forms of the same PK mobile."""
d=_phone_digits(digits) if re.search(r"\D",digits or "") else (digits or "")
if d.startswith("00"):
d=d[2:]
keys={d}
if d.startswith("92") and len(d)>=12:
rest=d[2:]
keys.add(rest)
if rest.startswith("3"):
keys.add("0"+rest)
if d.startswith("0") and len(d)>=11:
keys.add(d[1:])
keys.add("92"+d[1:])
if d.startswith("3") and len(d)==10:
keys.add("0"+d)
keys.add("92"+d)
return {k for k in keys if len(k)>=10}
def phone_in_resume(digits:str,resume_text:str) -> bool:
"""True when this number (or its 03 / +92 twin) appears in the CV digits."""
haystack=_digits_only(resume_text)
if not haystack:
return True
return any(key in haystack for key in _phone_keys(digits))
def _tidy_raw(raw:str) -> str:
compact=re.sub(r"[\n\r]+"," ",raw or "")
compact=re.sub(r"[ \t]+"," ",compact)
return compact.strip(" \t-./()[]{},:|•·∙_")
def _consider(raw:str,best:str|None,best_score:int) -> tuple[str|None,int]:
value=_tidy_raw(raw)
score=_phone_score(_phone_digits(value))
if score>best_score:
return value,score
return best,best_score
def _scan_digit_groups(text:str,best:str|None,best_score:int) -> tuple[str|None,int]:
groups=list(_DIGIT_GROUP.finditer(text))
for i,start_g in enumerate(groups):
acc=start_g.group(0)
end=start_g.end()
best,best_score=_consider(acc,best,best_score)
for nxt in groups[i+1:]:
gap=text[end:nxt.start()]
if not _GAP_OK.match(gap):
break
nxt_digits=nxt.group(0).lstrip("+")
if _YEAR.match(nxt_digits) and len(_phone_digits(acc))>=10:
break
combined=_phone_digits(acc+nxt.group(0))
if len(combined)>15:
break
acc=text[start_g.start():nxt.end()]
end=nxt.end()
best,best_score=_consider(acc,best,best_score)
return best,best_score
def scan_phone(text:str) -> str|None:
"""Scan CV text for a complete phone — unicode separators, wrap, tel/wa.me."""
haystack=_normalize_phone_text(text or "")
best,best_score=None,-1
best,best_score=_scan_digit_groups(haystack,best,best_score)
for pattern in (_WA_ME,_TEL_URI):
for match in pattern.finditer(haystack):
best,best_score=_consider(match.group(1),best,best_score)
return best
def prefer_full_phone(*candidates) -> str|None:
"""Keep the strongest complete number. Truncated / CNIC-shaped values lose."""
best,best_score=None,-1
for raw in candidates:
value=(raw or "").strip()
if not value:
continue
best,best_score=_consider(value,best,best_score)
return best if best_score>=0 else None
def _as_str(data,key):
if not isinstance(data,dict):
return ""
value=data.get(key)
return value.strip() if isinstance(value,str) else ""
@prefer_extracted_phone
@clamp_phone
def parse_phone(data,resume_text=""):
"""Form/CV phone through clamp_phone + prefer_extracted_phone."""
return {"phone":_as_str(data,"phone")}
@clamp_linkedin_url
def parse_linkedin(data,resume_text=""):
"""Stored or pasted LinkedIn URL through clamp_linkedin_url."""
return {"linkedin_url":_as_str(data,"linkedin_url")}