116 lines
8.8 KiB
Python
116 lines
8.8 KiB
Python
"""Summarize observed research coverage; does not claim an exhaustive AI census."""
|
|
import argparse
|
|
from collections import Counter
|
|
import json
|
|
from pathlib import Path
|
|
import sys
|
|
from urllib.parse import urlsplit
|
|
|
|
ROOT = Path(__file__).resolve().parents[1]
|
|
DATA = json.loads((ROOT / 'content/research/ai-companies.seed.json').read_text())
|
|
AUDIT = json.loads((ROOT / 'content/research/ai-companies.coverage.json').read_text())
|
|
TARGET = ROOT / '.artifacts/reports/02-coverage-and-gaps.md'
|
|
SOURCE_SLUG = 'ai-company-research/02-coverage-and-gaps'
|
|
BASE = '/docs/other-research/ai-company-research/overview'
|
|
|
|
|
|
def render():
|
|
cov = DATA['coverage']
|
|
companies = DATA['companies']
|
|
depth = sum(bool(c.get('profileOnly')) for c in companies)
|
|
origin = sum(bool(c.get('profileOnly')) or c.get('directoryOrigin') == 'yc-2025-2026' for c in companies)
|
|
promoted = origin - depth
|
|
reviewed = sum(bool(c.get('profileOnly')) and '人工复核' in c.get('classificationBasis', '') for c in companies)
|
|
years = Counter(c['year'] for c in companies)
|
|
income = Counter(c['revenueStatus'] for c in companies)
|
|
technical = Counter(c.get('technicalReview', {}).get('level', 'unreviewed') for c in companies)
|
|
assert cov['profilesRead'] + cov['failedProfiles'] == cov['candidateRecords']
|
|
assert cov['matchingProfiles'] == cov['existingProfiles'] + cov['newProfiles']
|
|
assert cov['matchingProfiles'] + cov['otherOrMissingYear'] + cov['unclearAI'] + cov['dateConflicts'] == cov['profilesRead']
|
|
assert origin == cov['newProfiles']
|
|
assert AUDIT['accessedAt'] == cov['accessedAt']
|
|
assert AUDIT['counts'] == cov
|
|
assert len(AUDIT['records']) == cov['profilesRead']
|
|
assert Counter(x['status'] for x in AUDIT['records']) == {
|
|
'imported': cov['newProfiles'], 'existing': cov['existingProfiles'],
|
|
'year-outside-or-missing': cov['otherOrMissingYear'],
|
|
'ai-unclear': cov['unclearAI'], 'date-conflict': cov['dateConflicts']}
|
|
assert len({x['ycId'] for x in AUDIT['records']}) == len(AUDIT['records'])
|
|
lines = ['# AI 公司资料覆盖与缺项', '',
|
|
f"截至 {DATA['asOf']}，研究表含{len(companies):,}条公司或产品记录。YC候选池有逐条读取审计；其他来源为定向补充。清单尚不能作为全球AI公司普查，也不能将收入未知解释为零。", '',
|
|
'验收范围已于2026-10-30确认为：以确认的公开来源清单为边界，逐条核对并标明缺项。下方区分已逐条审计的候选池与定向补充来源；已使用某来源不代表该来源已被完整覆盖。', '',
|
|
f"[分类和数据工作台]({BASE})链接原始证据，[收入样本快照](/docs/other-research/ai-company-research/income-snapshot)展示当前可计算的MRR样本。", '',
|
|
'## 候选池与公司表的关系', '',
|
|
'| 环节 | 记录数 | 含义 |', '| --- | --- | --- |',
|
|
f"| YC批次候选 | {cov['candidateRecords']:,} | 从公开镜像发现，随后读取YC官方页面 |",
|
|
f"| 官方页面读取 | {cov['profilesRead']:,} | 此候选池读取失败{cov['failedProfiles']}条 |",
|
|
f"| 初筛匹配 | {cov['matchingProfiles']:,} | 成立年及AI相关描述通过初筛，尚非逐家商业验证 |",
|
|
f"| 与原表重合 | {cov['existingProfiles']} | URL匹配，未再次新增 |",
|
|
f"| 新增目录记录 | {cov['newProfiles']:,} | 原始入表来源，后续深化不改变发现计数 |",
|
|
f"| 年份不符或缺失 | {cov['otherOrMissingYear']} | 此轮不作为成立年匹配项 |",
|
|
f"| AI业务待确认 | {cov['unclearAI']} | 不强行把背景关键词当主营 |",
|
|
f"| 成立年与批次冲突 | {cov['dateConflicts']} | 另保留核查记录 |", '',
|
|
f"全表由{depth}条目录基础项和{len(companies)-depth}条个案或平台记录组成。候选池已匹配项之外另有{len(companies)-cov['matchingProfiles']}条记录，包含其他来源及发布/转型对照；其中已有{promoted}条原目录记录深化为个案，仍保留目录来源。两种统计边界不同。候选池数字只是该镜像快照的覆盖，Bud等后续定向补充不回填为原候选池已覆盖。", '',
|
|
'## 成立年与证据深度', '',
|
|
'| 维度 | 当前记录 | 解读 |', '| --- | --- | --- |',
|
|
f"| 记录为2025年成立 | {years[2025]} | 成立来源和精度见公司明细 |",
|
|
f"| 记录为2026年成立 | {years[2026]} | 不将产品发布日期代替成立日 |",
|
|
f"| 成立年未知或范围外 | {sum(v for k,v in years.items() if k not in (2025,2026))} | 发布/转型对照单列，不进入两年成立分组 |",
|
|
f"| 目录业务分类人工复核 | {reviewed} | 仅复核主营分类，不代表技术或财务审计 |",
|
|
f"| 其他目录基础项 | {depth-reviewed} | 规则初分或资料不足，继续待复核 |",
|
|
f"| 有团队数字 | {sum(c['team'] is not None for c in companies)} | 多为自报Team Size或Employees，时点与口径不统一 |",
|
|
f"| 专项技术证据记录 | {len(companies)-technical['unreviewed']} | 其中{technical['description']}条自述、{technical['public-artifact']}条公开材料、{technical['independent-test']}条第三方评测 |",
|
|
f"| 公司披露收入线索 | {income['self']} | 含历史、下界、币种不明及产品业务声明，不等于可比ARR |",
|
|
f"| 仅平台收入线索 | {income['platform']} | 同时有公司披露者计入上一行，不重复计数 |",
|
|
f"| 仅第三方估算 | {income['estimate']} | 不与直接披露混合 |",
|
|
f"| 暂无可用收入数字 | {income['unknown']} | 包含尚未逐家搜索的目录项，不代表没有收入 |", '',
|
|
'## 业务分类与数据入口', '',
|
|
'| 业务类别 | 记录数 |', '| --- | --- |',
|
|
]
|
|
counts = Counter(c['cat'] for c in companies)
|
|
for category in DATA['categories']:
|
|
lines.append(f"| [{category['name']}]({BASE}?category={category['id']}) | {counts[category['id']]} |")
|
|
lines += ['', '## 已使用来源的分布', '',
|
|
f"{len(DATA['evidence']):,}条证据记录对应{len({e['url'] for e in DATA['evidence']}):,}个不同URL。不同URL不自动构成独立验证；同一声明可能由公司、投资方和媒体重复转述。", '',
|
|
'| 来源 | 证据记录 | 不同URL | 用途及限制 |', '| --- | --- | --- | --- |',
|
|
]
|
|
families = [('YC官方目录', 'www.ycombinator.com', '公司自述的成立、团队与业务；英文及加速器样本偏多'),
|
|
('TrustMRR', 'trustmrr.com', '支付平台重建指标及方法；公开者存在选择偏差，非财务审计'),
|
|
('a16z Speedrun', 'speedrun.a16z.com', '投资机构中的公司介绍及收入声明；存在利益关系'),
|
|
('TechCrunch', 'techcrunch.com', '原始采访或报道；转述公司数字不等于查账'),
|
|
('Sacra', 'sacra.com', '第三方估算；与直接披露分开')]
|
|
included = set()
|
|
for name, host, note in families:
|
|
entries = [e for e in DATA['evidence'] if urlsplit(e['url']).netloc == host]
|
|
included.add(host)
|
|
lines.append(f"| {name} | {len(entries)} | {len({e['url'] for e in entries})} | {note} |")
|
|
others = [e for e in DATA['evidence'] if urlsplit(e['url']).netloc not in included]
|
|
lines.append(f"| 其他官网、评测及公开资料 | {len(others)} | {len({e['url'] for e in others})} | 按每条来源限制理解，不能统一当作独立证据 |")
|
|
lines += ['', '## 尚未满足的研究条件', '',
|
|
'行业ARR比较仍缺统一业务截止日、币种、经常性定义和业务边界。现有平台MRR可描述已采集产品，不足以代表全部新公司。技术评测只覆盖所列版本与任务，不宜跨领域汇总为统一强弱分数。', '',
|
|
'下一轮优先补收入线索的日期及合同定义、非YC和非英文来源、规则初分的人工复核，以及停止服务或被收购案例。这样能减少“只见赢家”和“只见融资公司”的偏差。公开来源池之外的未披露公司仍无法证明已被穷尽。', '',
|
|
]
|
|
return '\n'.join(lines)
|
|
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser(description=__doc__)
|
|
parser.add_argument('--check', action='store_true')
|
|
parser.add_argument('--document-export', type=Path, default=ROOT / '.artifacts/documents-migration.json')
|
|
args = parser.parse_args()
|
|
content = render()
|
|
if args.check:
|
|
bundle = json.loads(args.document_export.read_text())
|
|
stored = next((d['content'] for d in bundle['documents'] if d['sourceSlug'] == SOURCE_SLUG), None)
|
|
if stored != content:
|
|
sys.exit('Research coverage report differs; review and regenerate')
|
|
print('Research coverage accounting and report are consistent')
|
|
else:
|
|
TARGET.parent.mkdir(parents=True, exist_ok=True)
|
|
TARGET.write_text(content)
|
|
print(TARGET.relative_to(ROOT))
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|