feat: IMAP mail sync with thread-to-contact matching (PRD §6.1)
Real IMAP connection via imapflow library: - Connects to IMAP server (IMAPFlow, TLS on port 993) - Fetches recent messages (configurable limit, default 20) - Extracts: from, fromEmail, subject, date, snippet (200 chars) - Thread-to-contact matching (PRD §6.1): 1. Match sender email against persons table 2. If no person match, extract domain and match against company.website 3. Returns matchedCompany + matchedPerson for each email - Audit-logged (action: crm.mailsync:imap) - Zod validated (host, port, user, password, folder, limit) - 502 on IMAP connection failure with detail - 400 on validation failure Tested: invalid creds → 502 'IMAP connection failed', missing host → 400
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#!/usr/bin/env python3
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"""批量测试 batch/list 接口：各省 × 正确/错误 classify × 高/低分。"""
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from __future__ import annotations
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import json
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import sys
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import time
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from pathlib import Path
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from urllib.error import HTTPError, URLError
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from urllib.parse import urlencode
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from urllib.request import Request, urlopen
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# 允许从 scripts/ 目录直接运行
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sys.path.insert(0, str(Path(__file__).resolve().parent))
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from province_config import ( # noqa: E402
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MODE_312,
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MODE_33,
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MODE_OLD,
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UNSUPPORTED_PROVINCES,
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batch_list_query_params,
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infer_grade_type,
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)
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BASE_URL = "https://publicapi.chatglm.cn/chatglm_public/skill-test"
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BATCH_LIST_PATH = "/zp/volunteer/batch/list"
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PROVINCE_CLASSIFY: dict[str, list[str]] = {}
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for p in MODE_33:
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PROVINCE_CLASSIFY[p] = ["综合"]
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for p in MODE_312:
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PROVINCE_CLASSIFY[p] = ["物理", "历史"]
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for p in MODE_OLD:
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PROVINCE_CLASSIFY[p] = ["文科", "理科"]
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for p in UNSUPPORTED_PROVINCES:
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PROVINCE_CLASSIFY[p] = ["综合"]
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WRONG_CLASSIFY = {
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"综合": "物理",
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"物理": "综合",
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"历史": "理科",
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"文科": "物理",
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"理科": "历史",
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}
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HIGH_SCORE = 650
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LOW_SCORE = 280
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def call_batch_from_payload(payload: dict) -> dict:
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params = batch_list_query_params(dict(payload))
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query = urlencode(params)
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url = f"{BASE_URL.rstrip('/')}{BATCH_LIST_PATH}?{query}"
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req = Request(url, method="GET", headers={"Accept": "*/*"})
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try:
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with urlopen(req, timeout=30) as resp:
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text = resp.read().decode(resp.headers.get_content_charset() or "utf-8")
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except HTTPError as e:
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return {"http": e.code, "body": e.read().decode("utf-8", errors="replace")}
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except URLError as e:
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return {"error": str(e.reason)}
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try:
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return json.loads(text)
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except json.JSONDecodeError:
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return {"error": "invalid json", "body": text[:200]}
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def summarize_result(raw: dict) -> str:
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if "error" in raw or "http" in raw:
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return f"FAIL:{raw.get('http') or raw.get('error')}"
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status = raw.get("status")
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msg = raw.get("message", "")
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result = raw.get("result")
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if status != 0:
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return f"FAIL:status={status},{msg}"
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if not isinstance(result, list):
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return "FAIL:result not list"
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if not result:
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return "OK:empty[]"
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batches = [f"{x.get('batch')}({x.get('gradeType')}/{x.get('type')})" for x in result[:3]]
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extra = f"+{len(result)-3}" if len(result) > 3 else ""
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return f"OK:{len(result)}项 [{', '.join(batches)}{extra}]"
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def main() -> int:
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rows: list[dict] = []
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provinces = sorted(PROVINCE_CLASSIFY.keys(), key=lambda x: (x not in UNSUPPORTED_PROVINCES, x))
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print("=== 正确 classify × 高分/低分（京沪津含 gradeType）===")
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for province in provinces:
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classifies = PROVINCE_CLASSIFY[province]
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primary = classifies[0]
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for score_label, score in [("高", HIGH_SCORE), ("低", LOW_SCORE)]:
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payload = {
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"province": province,
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"classify": primary,
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"score": score,
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"batch": "本科批",
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}
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if province in ("北京", "上海", "天津"):
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payload["gradeType"] = infer_grade_type(province, score, batch_pref="本科批")
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try:
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raw = call_batch_from_payload(payload)
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except ValueError as e:
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raw = {"status": -1, "message": str(e)}
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summary = summarize_result(raw)
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rows.append({
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"province": province,
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"classify": primary,
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"score": score,
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"score_label": score_label,
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"gradeType": payload.get("gradeType"),
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"wrong_classify": False,
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"summary": summary,
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"status": raw.get("status"),
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"message": raw.get("message"),
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"count": len(raw.get("result") or []) if isinstance(raw.get("result"), list) else None,
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})
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mark = "✓" if summary.startswith("OK") and "empty" not in summary else "✗"
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gt = payload.get("gradeType") or ""
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print(f" {mark} {province:4s} {primary} {gt:2s} {score_label}分({score}) → {summary}")
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time.sleep(0.12)
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print("\n=== 错误 classify 探测（高分）===")
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for province in provinces:
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if province in UNSUPPORTED_PROVINCES:
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continue
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primary = PROVINCE_CLASSIFY[province][0]
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wrong = WRONG_CLASSIFY.get(primary, "综合" if primary != "综合" else "物理")
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ok_payload = {"province": province, "classify": primary, "score": HIGH_SCORE, "batch": "本科批"}
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wrong_payload = dict(ok_payload, classify=wrong)
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if province in ("北京", "上海", "天津"):
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ok_payload["gradeType"] = infer_grade_type(province, HIGH_SCORE, batch_pref="本科批")
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wrong_payload["gradeType"] = ok_payload["gradeType"]
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try:
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raw_ok = call_batch_from_payload(ok_payload)
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raw_wrong = call_batch_from_payload(wrong_payload)
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except ValueError as e:
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print(f" ! {province}: validate error {e}")
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continue
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ok_s = summarize_result(raw_ok)
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wrong_s = summarize_result(raw_wrong)
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if wrong_s != ok_s:
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print(f" ! {province}: 正确({primary})={ok_s} vs 错误({wrong})={wrong_s}")
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time.sleep(0.12)
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out = Path(__file__).resolve().parent.parent / "output" / "batch_api_test_results.json"
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out.parent.mkdir(parents=True, exist_ok=True)
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out.write_text(json.dumps(rows, ensure_ascii=False, indent=2), encoding="utf-8")
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print(f"\n详细结果已保存: {out}")
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fails = [
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r for r in rows
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if not r["summary"].startswith("OK") or "empty[]" in r["summary"]
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if not r.get("wrong_classify")
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]
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print(f"\n=== 汇总: 正确参数异常 {len(fails)} 项 ===")
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for r in fails:
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print(f" {r['province']} {r['classify']} {r['score_label']}分 → {r['summary']} | {r.get('message')}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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