File size: 24,569 Bytes
b4f2238 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 | """Unit tests for apps.client.services.text_parser."""
from __future__ import annotations
import pytest
from apps.client.services.text_parser import (
_determine_client_type,
_extract_address,
_extract_credit_code,
_extract_id_number,
_extract_legal_representative,
_extract_name_smart,
_extract_parties,
_extract_phone,
parse_client_text,
parse_multiple_clients_text,
)
# ── parse_client_text ─────────────────────────────────────────────────────────
FULL_NATURAL_TEXT = (
"姓名:张三\n"
"身份证号码:100000000000000001\n"
"地址:北京市朝阳区建国路1号\n"
"联系电话:00000000000"
)
FULL_LEGAL_TEXT = (
"名称:北京测试科技有限公司\n"
"统一社会信用代码:91110000MA01ABCD12\n"
"地址:北京市海淀区中关村大街1号\n"
"联系电话:010-12345678\n"
"法定代表人:李四"
)
def test_parse_client_text_natural_person() -> None:
result = parse_client_text(FULL_NATURAL_TEXT)
assert result["name"] == "张三"
assert result["id_number"] == "100000000000000001"
assert "北京市朝阳区" in result["address"]
assert result["phone"] == "00000000000"
assert result["client_type"] == "natural"
def test_parse_client_text_legal_entity() -> None:
result = parse_client_text(FULL_LEGAL_TEXT)
assert "测试科技有限公司" in result["name"]
assert result["id_number"] == "91110000MA01ABCD12"
assert result["legal_representative"] == "李四"
assert result["client_type"] == "legal"
def test_parse_client_text_empty_returns_empty_result() -> None:
result = parse_client_text("")
assert result["name"] == ""
assert result["client_type"] == "natural"
def test_parse_client_text_whitespace_only_returns_empty_result() -> None:
result = parse_client_text(" \n ")
assert result["name"] == ""
# ── parse_multiple_clients_text ───────────────────────────────────────────────
MULTI_CLIENT_TEXT = (
"原告:张三,男,身份证号码:100000000000000001,地址:北京市朝阳区建国路1号\n"
"被告:北京测试科技有限公司,统一社会信用代码:91110000MA01ABCD12,法定代表人:李四"
)
def test_parse_multiple_clients_text_returns_two_parties() -> None:
results = parse_multiple_clients_text(MULTI_CLIENT_TEXT)
assert len(results) >= 2
def test_parse_multiple_clients_text_empty_returns_empty_list() -> None:
assert parse_multiple_clients_text("") == []
def test_parse_multiple_clients_text_whitespace_returns_empty_list() -> None:
assert parse_multiple_clients_text(" ") == []
# ── _extract_name_smart ───────────────────────────────────────────────────────
def test_extract_name_smart_from_role_label() -> None:
text = "原告:张三\n身份证号码:100000000000000001"
assert _extract_name_smart(text) == "张三"
def test_extract_name_smart_legal_entity() -> None:
text = "名称:北京测试科技有限公司\n统一社会信用代码:91110000MA01ABCD12"
result = _extract_name_smart(text)
assert result is not None
assert "有限公司" in result
def test_extract_name_smart_natural_person_with_gender() -> None:
text = "李四,男,身份证号码:100000000000000001"
result = _extract_name_smart(text)
assert result == "李四"
def test_extract_name_smart_empty_returns_none() -> None:
assert _extract_name_smart("") is None
def test_extract_name_smart_only_keywords_returns_none() -> None:
result = _extract_name_smart("联系电话:00000000000")
# 不应把"联系电话"当名称
assert result != "联系电话"
# ── _extract_parties ──────────────────────────────────────────────────────────
def test_extract_parties_single_party() -> None:
text = "原告:张三\n身份证号码:100000000000000001"
parties = _extract_parties(text)
assert len(parties) >= 1
assert parties[0]["name"] == "张三"
def test_extract_parties_plaintiff_defendant() -> None:
text = (
"原告:张三\n身份证号码:100000000000000001\n"
"被告:李四\n身份证号码:200000000000000002"
)
parties = _extract_parties(text)
names = [p["name"] for p in parties]
assert "张三" in names
assert "李四" in names
def test_extract_parties_no_role_label_falls_back() -> None:
text = "张三\n身份证号码:100000000000000001"
parties = _extract_parties(text)
# 无角色标签时兜底解析,可能返回 0 或 1 个
assert isinstance(parties, list)
# ── _extract_credit_code ──────────────────────────────────────────────────────
def test_extract_credit_code_with_label() -> None:
text = "统一社会信用代码:91110000MA01ABCD12"
assert _extract_credit_code(text) == "91110000MA01ABCD12"
def test_extract_credit_code_fallback_with_letters() -> None:
text = "91110000MA01ABCD12"
assert _extract_credit_code(text) == "91110000MA01ABCD12"
def test_extract_credit_code_not_confused_with_id_number() -> None:
text = "身份证号码:100000000000000001"
# 纯数字18位不应被识别为信用代码
result = _extract_credit_code(text)
assert result is None or (result is not None and any(ch.isalpha() for ch in result))
def test_extract_credit_code_none_when_absent() -> None:
assert _extract_credit_code("张三,男") is None
# ── _extract_id_number ────────────────────────────────────────────────────────
def test_extract_id_number_with_label() -> None:
text = "身份证号码:100000000000000001"
assert _extract_id_number(text) == "100000000000000001"
def test_extract_id_number_fallback() -> None:
text = "100000000000000001"
assert _extract_id_number(text) == "100000000000000001"
def test_extract_id_number_none_when_absent() -> None:
assert _extract_id_number("北京市朝阳区") is None
# ── _extract_address ──────────────────────────────────────────────────────────
def test_extract_address_with_label() -> None:
text = "地址:北京市朝阳区建国路1号\n联系电话:00000000000"
result = _extract_address(text)
assert result is not None
assert "北京市朝阳区" in result
def test_extract_address_fallback_province_line() -> None:
text = "北京市朝阳区建国路1号院2单元301室"
result = _extract_address(text)
assert result is not None
def test_extract_address_none_when_absent() -> None:
assert _extract_address("张三,男") is None
# ── _extract_phone ────────────────────────────────────────────────────────────
def test_extract_phone_with_label() -> None:
text = "联系电话:00000000000"
assert _extract_phone(text) == "00000000000"
def test_extract_phone_fallback_mobile() -> None:
text = "张三 13900139000" # nosec
result = _extract_phone(text)
assert result == "13900139000" # nosec
def test_extract_phone_none_when_absent() -> None:
assert _extract_phone("张三,男") is None
# ── _extract_legal_representative ────────────────────────────────────────────
def test_extract_legal_representative_with_label() -> None:
text = "法定代表人:王五\n地址:北京市"
result = _extract_legal_representative(text)
assert result == "王五"
def test_extract_legal_representative_none_when_absent() -> None:
assert _extract_legal_representative("张三,男") is None
# ── _determine_client_type ────────────────────────────────────────────────────
def test_determine_client_type_legal_by_credit_code() -> None:
text = "统一社会信用代码:91110000MA01ABCD12"
assert _determine_client_type("北京测试有限公司", text) == "legal"
def test_determine_client_type_legal_by_legal_rep() -> None:
text = "法定代表人:王五"
assert _determine_client_type("某公司", text) == "legal"
def test_determine_client_type_legal_by_name_keyword() -> None:
assert _determine_client_type("北京测试有限公司", "") == "legal"
def test_determine_client_type_natural_by_id_number() -> None:
text = "身份证号码:100000000000000001"
assert _determine_client_type("张三", text) == "natural"
def test_determine_client_type_natural_default() -> None:
assert _determine_client_type("张三", "") == "natural"
# ── 边界情况 ──────────────────────────────────────────────────────────────────
def test_parse_client_text_name_only() -> None:
result = parse_client_text("张三")
# 只有名称,其他字段为空
assert result["name"] == "张三"
assert result["id_number"] == ""
assert result["phone"] == ""
def test_parse_client_text_invalid_input_no_crash() -> None:
result = parse_client_text("!!@@##$$")
assert isinstance(result, dict)
assert "name" in result
# ── _extract_name_smart 次级兜底分支 ─────────────────────────────────────────
def test_extract_name_smart_jiafang_format() -> None:
# 甲方:xxx 格式(_SMART_NAME_PATTERN)
text = "甲方:北京测试科技有限公司\n统一社会信用代码:91110000MA01ABCD12"
result = _extract_name_smart(text)
assert result is not None
assert "有限公司" in result
def test_extract_name_smart_leading_name_before_field() -> None:
# 名称直接在字段前(_LEADING_NAME_BEFORE_FIELD_PATTERN)
text = "北京测试科技有限公司统一社会信用代码:91110000MA01ABCD12"
result = _extract_name_smart(text)
assert result is not None
def test_extract_name_smart_role_no_colon() -> None:
# 无冒号角色写法:被告 张三,男(_ROLE_NAME_FALLBACK_PATTERN)
text = "被告 张三,男,地址:北京市"
result = _extract_name_smart(text)
assert result == "张三"
def test_extract_name_smart_leading_person_before_gender() -> None:
# 自然人名在性别前(_LEADING_PERSON_NAME_PATTERN)
text = "王小明,男,身份证号码:100000000000000001"
result = _extract_name_smart(text)
assert result == "王小明"
def test_extract_name_smart_first_line_fallback() -> None:
# 兜底:第一行即名称
text = "某某律师事务所\n联系电话:00000000000"
result = _extract_name_smart(text)
assert result is not None
assert "律师事务所" in result
def test_parse_client_text_falls_back_to_direct_parse() -> None:
# 无角色标签时走 _parse_fields_directly(覆盖 line 190)
text = "姓名:张三\n联系电话:00000000000"
result = parse_client_text(text)
assert result["name"] == "张三"
# ── _is_valid_name_candidate 边缘分支 ────────────────────────────────────────
def test_is_valid_name_candidate_rejects_pure_digits() -> None:
from apps.client.services.text_parser import _is_valid_name_candidate
assert not _is_valid_name_candidate("12345678")
def test_is_valid_name_candidate_rejects_id_number_format() -> None:
from apps.client.services.text_parser import _is_valid_name_candidate
assert not _is_valid_name_candidate("100000000000000001")
def test_is_valid_name_candidate_rejects_credit_code_with_letters() -> None:
from apps.client.services.text_parser import _is_valid_name_candidate
assert not _is_valid_name_candidate("91110000MA01ABCD12")
def test_is_valid_name_candidate_rejects_role_prefix() -> None:
from apps.client.services.text_parser import _is_valid_name_candidate
# "原" 是 "原告" 的前缀
assert not _is_valid_name_candidate("原告")
def test_is_valid_name_candidate_rejects_non_name_keyword() -> None:
from apps.client.services.text_parser import _is_valid_name_candidate
assert not _is_valid_name_candidate("联系电话")
# ── 补充覆盖剩余分支 ──────────────────────────────────────────────────────────
def test_extract_name_smart_smart_name_pattern_valid() -> None:
# 甲方:xxx 格式,且候选值有效(覆盖 276-278)
# 需要确保 _extract_name 和 _NAME_FIELD_PATTERN 都不先命中
text = "甲方:某律师事务所\n地址:北京市"
result = _extract_name_smart(text)
assert result is not None
assert "律师事务所" in result
def test_extract_name_smart_leading_name_valid() -> None:
# leading name before field 命中且有效(覆盖 289-291)
text = "某某贸易有限公司地址:北京市朝阳区"
result = _extract_name_smart(text)
assert result is not None
def test_extract_name_smart_role_fallback_valid() -> None:
# 无冒号角色写法命中且有效(覆盖 297)
text = "\n被告 王小二 地址:北京市"
result = _extract_name_smart(text)
assert result is not None
def test_extract_name_smart_leading_person_valid() -> None:
# leading person name 命中且有效(覆盖 302-304)
text = "赵小明,男,地址:北京市"
result = _extract_name_smart(text)
assert result == "赵小明"
def test_extract_name_smart_legal_entity_only() -> None:
# 仅公司全称,无任何标签(覆盖 309-311)
text = "深圳某某科技股份有限公司"
result = _extract_name_smart(text)
assert result is not None
assert "有限公司" in result
def test_extract_name_from_first_meaningful_line_returns_line() -> None:
# 第一行有效名称(覆盖 334)
from apps.client.services.text_parser import _extract_name_from_first_meaningful_line
result = _extract_name_from_first_meaningful_line("某某律师\n联系电话:00000000000")
assert result == "某某律师"
def test_is_valid_name_candidate_empty_compact() -> None:
# compact 为空(覆盖 345)
from apps.client.services.text_parser import _is_valid_name_candidate
assert not _is_valid_name_candidate(" ")
def test_extract_name_returns_none_when_no_role_label() -> None:
# _extract_name 无角色标签时返回 None(覆盖 458)
from apps.client.services.text_parser import _extract_name
assert _extract_name("北京市朝阳区某路1号") is None
def test_extract_credit_code_fallback_skips_near_id_keyword() -> None:
# 信用代码前有"身份证"关键词时跳过,但后面有合法信用代码(覆盖 497)
text = "91110000MA01ABCD12"
result = _extract_credit_code(text)
assert result == "91110000MA01ABCD12"
# ── 精确覆盖剩余分支 ──────────────────────────────────────────────────────────
def test_parse_client_text_no_role_label_direct_parse() -> None:
# 无角色标签,_extract_parties 返回空,走 _parse_fields_directly(覆盖 190, 226)
# 需要确保文本不含任何角色标签,且能提取到名称
text = "姓名:王小花\n联系电话:00000000000\n地址:北京市朝阳区"
result = parse_client_text(text)
assert result["name"] == "王小花"
def test_extract_name_smart_smart_pattern_no_earlier_match() -> None:
# 甲方格式,且前面所有模式都不命中(覆盖 276-278)
# 确保 _extract_name、_NAME_FIELD_PATTERN 都不命中
text = "甲方:某某律师事务所地址:北京市"
result = _extract_name_smart(text)
assert result is not None
def test_extract_name_smart_leading_before_field_no_earlier_match() -> None:
# leading name before field,且前面模式都不命中(覆盖 289-291)
text = "某某贸易公司法定代表人:王五"
result = _extract_name_smart(text)
assert result is not None
def test_extract_name_smart_role_fallback_no_earlier_match() -> None:
# 无冒号角色写法,且前面模式都不命中(覆盖 297)
text = "\n申请人 王小二\n地址:北京市"
result = _extract_name_smart(text)
assert result is not None
def test_extract_name_smart_legal_entity_no_earlier_match() -> None:
# 仅公司全称,无任何标签和字段(覆盖 309-311)
text = "广州某某贸易有限公司"
result = _extract_name_smart(text)
assert result is not None
assert "有限公司" in result
def test_extract_name_from_first_line_valid() -> None:
# 第一行是有效名称(覆盖 334)
from apps.client.services.text_parser import _extract_name_from_first_meaningful_line
result = _extract_name_from_first_meaningful_line("\n\n某某律师\n联系电话:00000000000")
assert result == "某某律师"
def test_is_valid_name_candidate_digit_string() -> None:
# compact.isdigit() 为 True(覆盖 349)
from apps.client.services.text_parser import _is_valid_name_candidate
assert not _is_valid_name_candidate("123456")
def test_is_valid_name_candidate_valid_name_returns_true() -> None:
# 所有检查通过,return True(覆盖 360)
from apps.client.services.text_parser import _is_valid_name_candidate
assert _is_valid_name_candidate("某某律师事务所")
def test_extract_name_no_role_label_returns_none() -> None:
# 无任何角色标签,_extract_name 返回 None(覆盖 458)
from apps.client.services.text_parser import _extract_name
result = _extract_name("地址:北京市朝阳区某路1号\n联系电话:00000000000")
assert result is None
def test_extract_credit_code_fallback_returns_code_with_letters() -> None:
# 无标签但含字母的18位编码,且前面没有"身份证"关键词(覆盖 497)
from apps.client.services.text_parser import _extract_credit_code
result = _extract_credit_code("企业代码:91110000MA01ABCD12")
assert result == "91110000MA01ABCD12"
# ── 精确覆盖最后剩余分支 ──────────────────────────────────────────────────────
def test_parse_client_text_no_name_falls_back_to_direct_parse() -> None:
# _extract_parties 返回空(无名称),走 _parse_fields_directly(覆盖 190, 226)
text = "联系电话:00000000000\n地址:北京市朝阳区"
result = parse_client_text(text)
# 无名称,但不崩溃
assert result["name"] == ""
assert result["phone"] == "00000000000"
def test_is_valid_name_candidate_short_digit_string() -> None:
# compact.isdigit() 为 True 且不被身份证 pattern 匹配(覆盖 349)
from apps.client.services.text_parser import _is_valid_name_candidate
assert not _is_valid_name_candidate("12345678")
# ── 精确覆盖 annotate 发现的剩余 ! 行 ────────────────────────────────────────
def test_parse_single_party_natural_with_legal_rep_upgrades_to_legal() -> None:
# natural 类型有法定代表人时升级为 legal(覆盖 _parse_single_party 中 client_type=legal)
from apps.client.services.text_parser import _parse_single_party
text = "原告:张三\n身份证号码:100000000000000001\n法定代表人:王五"
result = _parse_single_party(text, use_smart_name=True)
assert result["client_type"] == "legal"
assert result["legal_representative"] == "王五"
def test_is_valid_name_candidate_id_number_fullmatch() -> None:
# _ID_NUMBER_FALLBACK_PATTERN.fullmatch 命中(覆盖 349 的 return False)
from apps.client.services.text_parser import _is_valid_name_candidate
# 18位纯数字,符合身份证格式
assert not _is_valid_name_candidate("100000000000000001")
def test_extract_credit_code_skips_near_id_keyword() -> None:
# 信用代码前有"身份证"关键词时 continue(覆盖 497 的 continue 行)
from apps.client.services.text_parser import _extract_credit_code
# 身份证关键词在信用代码前20字符内
text = "身份证91110000MA01ABCD12"
result = _extract_credit_code(text)
# 被跳过,返回 None
assert result is None
def test_extract_name_smart_role_fallback_valid_name() -> None:
# _ROLE_NAME_FALLBACK_PATTERN 命中且 valid(覆盖 297 body)
# 需要确保 _extract_name、NAME_FIELD、SMART_NAME、LEADING_NAME 都不命中
from apps.client.services.text_parser import _extract_name_smart
# 纯角色+名称,无冒号,无其他字段
text = "被申请人 某某律师"
result = _extract_name_smart(text)
assert result is not None
def test_extract_name_smart_natural_person_pattern() -> None:
# _NATURAL_PERSON_NAME_PATTERN 命中("姓名,性别"格式)
from apps.client.services.text_parser import _extract_name_smart
# 需要前面所有模式都不命中
text = "王小明,男"
result = _extract_name_smart(text)
assert result == "王小明"
# ── 最后 9 行精确覆盖 ─────────────────────────────────────────────────────────
def test_is_valid_name_too_short() -> None:
from apps.client.services.text_parser import _is_valid_name_candidate
assert not _is_valid_name_candidate("张") # len < 2,覆盖 289 return False
def test_is_valid_name_id_number_fullmatch_rejected() -> None:
from apps.client.services.text_parser import _is_valid_name_candidate
# 15位身份证格式,fullmatch 命中(覆盖 349 return False)
assert not _is_valid_name_candidate("110101900101123")
def test_extract_credit_code_skips_when_id_keyword_before() -> None:
from apps.client.services.text_parser import _extract_credit_code
# "身份证" 在信用代码前 20 字符内,触发 continue(覆盖 497 continue)
# 后面再跟一个合法信用代码让函数能 return
text = "身份证91110000MA01ABCD12 然后 91220000MB02EFGH34"
result = _extract_credit_code(text)
assert result == "91220000MB02EFGH34"
def test_extract_name_smart_leading_name_before_field_valid() -> None:
from apps.client.services.text_parser import _extract_name_smart
# 触发 289-291:_extract_name=None, NAME_FIELD=None, SMART_NAME=None
# LEADING_NAME_BEFORE_FIELD 命中且 valid
text = "某某贸易公司\n法定代表人:王五"
result = _extract_name_smart(text)
assert result is not None
def test_extract_name_smart_legal_entity_pattern_valid() -> None:
from apps.client.services.text_parser import _extract_name_smart
# 触发 309-311:前5个模式都不命中,LEGAL_ENTITY 命中
# 纯公司名,无任何标签、字段、角色
text = "北京某某科技股份有限公司"
result = _extract_name_smart(text)
assert result is not None
assert "有限公司" in result
def test_extract_name_from_first_meaningful_line_skips_empty() -> None:
from apps.client.services.text_parser import _extract_name_from_first_meaningful_line
# 覆盖 334:跳过空行后返回有效名称
result = _extract_name_from_first_meaningful_line("\n\n\n某某律师事务所")
assert result == "某某律师事务所"
|