mirror of
https://github.com/prdlk/jobyssey.git
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295 lines
12 KiB
Python
295 lines
12 KiB
Python
#!/usr/bin/env python3
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"""Enrich Twenty CRM opportunities and companies from local job-search data.
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Encodes the deterministic layers of the /sync-twenty enrichment pipeline:
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Opportunity salary (``amount``), in source priority order:
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1. seen_jobs.json ``salary_max_stated`` (stated in the posting at rank time)
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2. jobs.db postings salary_max (same company+title, stated on an ATS board)
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3. jobs.db companies levels_swe_median (levels.fyi company median - labeled estimate)
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Company fields (``domainName``, ``linkedinLink``, ``address``, ``annualRevenue``):
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- jobs.db companies row matched on normalized name, homepage domain joined
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through postings.company_domain. Stringified NaN / empty strings are absent.
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Anything these layers cannot ground is emitted in the plan's ``unresolved``
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section for the calling command to escalate to web research (scout subagents /
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Perplexity) - this script never guesses.
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Usage:
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python3 tools/twenty_enrich.py # plan -> job_scraper/enrichment_plan.json
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python3 tools/twenty_enrich.py --apply # plan + apply via REST (needs TWENTY_API_KEY)
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python3 tools/twenty_enrich.py --snapshot f.json # offline: CRM state from a JSON snapshot
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Snapshot shape (what /sync-twenty exports through MCP):
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{"opportunities": [{id, url:{primaryLinkUrl}, amount, closeDate, ...}],
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"companies": [{id, name, domainName, linkedinLink, address, ...}]}
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The plan JSON is idempotent to apply: every entry names the target record id
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and only fields that are currently empty.
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"""
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from __future__ import annotations
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import argparse
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import json
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import re
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import sqlite3
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import sys
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from pathlib import Path
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REPO = Path(__file__).resolve().parent.parent
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SEEN_JOBS = REPO / "job_scraper" / "seen_jobs.json"
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JOBS_DB = REPO / "documents" / "postings" / "jobs.db"
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PLAN_OUT = REPO / "job_scraper" / "enrichment_plan.json"
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_SUFFIXES = re.compile(r"\b(inc|llc|ltd|corp|corporation|co|labs|lab|hq|the)\b")
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def norm_company(s: str) -> str:
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"""Normalized company key: lowercase, punctuation collapsed, suffixes stripped."""
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s = re.sub(r"[^a-z0-9]+", " ", (s or "").lower()).strip()
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s = _SUFFIXES.sub("", s).strip()
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return re.sub(r"\s+", " ", s)
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def norm_title(s: str) -> str:
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return re.sub(r"[^a-z0-9]+", " ", (s or "").lower()).strip()
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def clean_domain(raw: str | None) -> str | None:
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"""Bare registrable domain or None. Rejects the stringified-NaN artifact."""
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if not raw:
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return None
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d = str(raw).strip().lower()
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for prefix in ("http://", "https://", "www."):
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d = d.removeprefix(prefix)
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d = d.rstrip("/")
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if not d or d == "nan" or "." not in d:
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return None
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return d
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def _has_link(v) -> bool:
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return bool(v and v.get("primaryLinkUrl"))
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def _has_addr(v) -> bool:
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return bool(v and (v.get("addressCity") or v.get("addressCountry")))
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def _has_amount(v) -> bool:
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return bool(v and v.get("amountMicros"))
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def load_local_sources(seen_path: Path = SEEN_JOBS, db_path: Path = JOBS_DB):
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"""Ranked jobs plus the jobs.db lookup tables the plan builders consume."""
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seen = json.loads(seen_path.read_text(encoding="utf-8"))["seen"]
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ranked = [v for v in seen.values() if v.get("status") == "ranked"]
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db_companies: dict[str, dict] = {}
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domains: dict[str, str] = {}
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postings_salary: dict[tuple[str, str], int] = {}
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levels: dict[str, int] = {}
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if db_path.exists():
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con = sqlite3.connect(db_path)
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con.row_factory = sqlite3.Row
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for r in con.execute(
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"SELECT company_id, company_name, linkedin_url, country, state, apollo_city,"
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" organization_revenue, levels_swe_median_usd, levels_median_comp_usd FROM companies"
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):
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key = norm_company(r["company_name"])
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db_companies.setdefault(key, dict(r))
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lv = r["levels_swe_median_usd"] or r["levels_median_comp_usd"]
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if lv and lv > 0:
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levels.setdefault(key, int(lv))
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for r in con.execute(
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"SELECT company_id, company_domain, COUNT(*) n FROM postings"
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" WHERE company_domain IS NOT NULL AND company_domain != ''"
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" GROUP BY company_id, company_domain ORDER BY n"
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):
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domains[r["company_id"]] = r["company_domain"] # last row = most frequent
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for r in con.execute(
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"SELECT company_name, title, salary_max, salary_currency FROM postings"
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" WHERE salary_max IS NOT NULL AND salary_max > 0"
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):
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if (r["salary_currency"] or "USD").upper() in ("USD", "$", ""):
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key = (norm_company(r["company_name"]), norm_title(r["title"]))
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postings_salary.setdefault(key, int(float(r["salary_max"])))
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con.close()
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return ranked, db_companies, domains, postings_salary, levels
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def build_salary_plan(ranked, opportunities, postings_salary, levels):
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"""(updates, unresolved): amount patches for opportunities missing one."""
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by_url = {}
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for o in opportunities:
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u = (o.get("url") or {}).get("primaryLinkUrl")
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if u:
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by_url[u] = o
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updates, unresolved = [], []
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for v in ranked:
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o = by_url.get(v.get("url"))
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if not o or _has_amount(o.get("amount")):
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continue
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amount = source = None
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if v.get("salary_max_stated"):
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amount, source = int(v["salary_max_stated"]), "seen_jobs.salary_max_stated"
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else:
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key = (norm_company(v.get("company", "")), norm_title(v.get("title", "")))
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if key in postings_salary:
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amount, source = postings_salary[key], "jobs.db postings"
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elif norm_company(v.get("company", "")) in levels:
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amount = levels[norm_company(v.get("company", ""))]
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source = "levels.fyi company SWE median (estimate)"
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if amount:
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updates.append({
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"id": o["id"],
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"source": source,
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"patch": {"amount": {"amountMicros": amount * 1_000_000, "currencyCode": "USD"}},
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})
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else:
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unresolved.append({"id": o["id"], "url": v["url"],
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"company": v.get("company"), "title": v.get("title")})
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return updates, unresolved
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def build_company_plan(companies, db_companies, domains):
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"""(updates, unresolved): fill ONLY empty company fields from jobs.db."""
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updates, unresolved = [], []
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for c in companies:
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key = norm_company(c.get("name", ""))
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m = db_companies.get(key) or {}
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patch = {}
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if not _has_link(c.get("domainName")):
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dom = clean_domain(domains.get(m.get("company_id", "")))
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if dom:
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patch["domainName"] = {"primaryLinkUrl": f"https://{dom}",
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"primaryLinkLabel": c["name"]}
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if not _has_link(c.get("linkedinLink")):
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li = (m.get("linkedin_url") or "").strip()
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if li:
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patch["linkedinLink"] = {"primaryLinkUrl": li.replace("http://", "https://"),
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"primaryLinkLabel": c["name"]}
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if not _has_addr(c.get("address")):
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addr = {k: v for k, v in [("addressCity", m.get("apollo_city")),
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("addressState", m.get("state")),
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("addressCountry", m.get("country"))] if v}
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if addr:
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patch["address"] = addr
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if patch:
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updates.append({"id": c["id"], "name": c["name"], "patch": patch})
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# Fields still empty after the local layer -> web-research escalation
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missing = []
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if not _has_link(c.get("domainName")) and "domainName" not in patch:
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missing.append("domain")
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if not _has_link(c.get("linkedinLink")) and "linkedinLink" not in patch:
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missing.append("linkedin")
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if not _has_addr(c.get("address")) and "address" not in patch:
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missing.append("address")
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if missing:
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unresolved.append({"id": c["id"], "name": c["name"], "missing": missing})
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return updates, unresolved
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def build_name_cleanup_plan(opportunities):
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"""Strip the ' — <Company>' suffix from opportunity names.
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Runs LAST, and only for opportunities whose company relation is already
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set: the suffix is the human-readable fallback while the record is
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unlinked, and becomes redundant once ``companyId`` points at the Company.
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An unlinked opportunity keeps its suffixed name so it stays identifiable.
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"""
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updates = []
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for o in opportunities:
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name = o.get("name") or ""
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if o.get("companyId") and " — " in name:
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role = name.split(" — ")[0].strip()
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if role and role != name:
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updates.append({"id": o["id"], "patch": {"name": role}})
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return updates
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def coverage(opportunities, companies) -> dict:
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n, m = len(companies), len(opportunities)
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return {
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"companies": {
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"total": n,
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"domain": sum(1 for c in companies if _has_link(c.get("domainName"))),
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"linkedin": sum(1 for c in companies if _has_link(c.get("linkedinLink"))),
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"address": sum(1 for c in companies if _has_addr(c.get("address"))),
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},
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"opportunities": {
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"total": m,
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"salary": sum(1 for o in opportunities if _has_amount(o.get("amount"))),
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"company_link": sum(1 for o in opportunities if o.get("companyId")),
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"score": sum(1 for o in opportunities if o.get("score") is not None),
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},
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}
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def main(argv=None) -> int:
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ap = argparse.ArgumentParser(description=__doc__.splitlines()[0])
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ap.add_argument("--snapshot", type=Path,
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help="CRM state JSON (offline mode; else fetched via REST)")
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ap.add_argument("--apply", action="store_true",
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help="apply the plan via Twenty REST (needs TWENTY_API_KEY)")
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ap.add_argument("--out", type=Path, default=PLAN_OUT, help="plan output path")
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args = ap.parse_args(argv)
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ranked, db_companies, domains, postings_salary, levels = load_local_sources()
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client = None
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if args.snapshot:
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snap = json.loads(args.snapshot.read_text(encoding="utf-8"))
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opportunities, companies = snap["opportunities"], snap["companies"]
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else:
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from twenty_client import TwentyClient # noqa: deferred import keeps offline mode key-free
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client = TwentyClient()
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opportunities = client.list_all("opportunities")
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companies = client.list_all("companies")
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sal_updates, sal_unresolved = build_salary_plan(ranked, opportunities, postings_salary, levels)
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comp_updates, comp_unresolved = build_company_plan(companies, db_companies, domains)
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name_updates = build_name_cleanup_plan(opportunities)
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plan = {
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"coverage_before": coverage(opportunities, companies),
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"opportunity_updates": sal_updates,
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"company_updates": comp_updates,
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"name_cleanup": name_updates,
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"unresolved": {
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"opportunities_without_salary": sal_unresolved,
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"companies_missing_fields": comp_unresolved,
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},
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}
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if args.apply:
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if client is None:
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from twenty_client import TwentyClient
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client = TwentyClient()
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for u in sal_updates:
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client.update_one("opportunities", u["id"], u["patch"])
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for u in comp_updates:
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client.update_one("companies", u["id"], u["patch"])
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# Name cleanup LAST: it must observe the post-link state.
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for u in name_updates:
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client.update_one("opportunities", u["id"], u["patch"])
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plan["applied"] = {"opportunities": len(sal_updates), "companies": len(comp_updates),
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"names_cleaned": len(name_updates)}
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args.out.parent.mkdir(parents=True, exist_ok=True)
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args.out.write_text(json.dumps(plan, indent=2), encoding="utf-8")
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cov = plan["coverage_before"]
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print(f"plan -> {args.out}")
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print(f"opportunity salary updates: {len(sal_updates)} "
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f"(coverage {cov['opportunities']['salary']}/{cov['opportunities']['total']} before)")
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print(f"company field updates: {len(comp_updates)} · name cleanups: {len(name_updates)}")
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print(f"unresolved -> web research: {len(sal_unresolved)} postings, "
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f"{len(comp_unresolved)} companies")
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if args.apply:
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print("applied via REST.")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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