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A pragmatic pipeline around trafilatura for JS-rendered pages and list discovery.

Project description

trafi-pipeline

基于 trafilatura 的“组合式”网页正文抽取管线:先抓取/渲染,再抽取;支持列表页发现详情页,再批量抽取。

特性

  • 自动渲染策略:auto | always | never,正文过短或抓取失败时可自动切换渲染
  • auto 模式还会根据页面“展开/更多/阅读全文”等标记触发渲染,避免只抓到摘要
  • 列表页爬取:按深度与页数限制发现详情页链接
  • 代理支持:抓取/渲染分别配置代理
  • 图片处理:保留图片、追加图片列表、或原位插入(Markdown)
  • 元数据:标题、来源站点、耗时等
  • SVG 文本抽取:对 PDF/SVG 转换页面可直接提取文字

安装

pip install trafi-pipeline

建议完整安装(抓取 + 渲染能力都具备):

pip install "trafi-pipeline[http,render]"
python -m playwright install chromium

分开安装(更细粒度控制):

pip install "trafi-pipeline[http]"      # 使用 httpx
pip install "trafi-pipeline[render]"    # 使用 Playwright 进行渲染

说明:

  • 默认配置 render.mode="auto",可能会触发渲染;若未安装 render 依赖或未安装浏览器,将导致结果为空或报错。
  • 如果不需要渲染,请显式设置 render.mode="never",避免依赖缺失导致失败。

快速开始

from trafipipe import Pipeline, PipelineConfig

pipeline = Pipeline(PipelineConfig())
result = pipeline.extract_url("https://example.com/article")
print(result.text)

返回字段(ExtractResult):

  • text:正文
  • title:标题
  • source:来源站点
  • images:图片 URL 列表
  • videos:视频 URL 列表
  • used_render:是否使用渲染
  • status_code:抓取到的 HTTP 状态码(抓取失败时可能为空)
  • elapsed_ms:耗时(毫秒)
  • fetch_ms:抓取耗时(毫秒)
  • render_ms:渲染耗时(毫秒)
  • extract_ms:正文抽取耗时(毫秒)
  • image_ms:图片收集耗时(毫秒)
  • video_ms:视频收集耗时(毫秒)
  • error:错误信息(如有)

说明:

  • 如遇到验证码/人机验证页面,会直接返回 error="captcha_detected",避免误判为正文。

常见配置

代理与渲染

from trafipipe import Pipeline, PipelineConfig, ProxyConfig

cfg = PipelineConfig()
cfg.fetch.proxy = ProxyConfig(http="http://user:pass@host:port", https="http://user:pass@host:port")
cfg.render.proxy = ProxyConfig(server="http://user:pass@host:port")
cfg.render.extra_headers = {
    "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
    "Referer": "https://mp.weixin.qq.com/",
}
cfg.render.wait_selector = "article, .article, .article-content"  # 支持多选择器
cfg.render.cookies = [
    {"name": "your_cookie", "value": "xxx", "domain": ".mp.weixin.qq.com", "path": "/"}
]
cfg.render.reuse_context = True  # 批量渲染时复用 context 以提速

pipeline = Pipeline(cfg)
result = pipeline.extract_url("https://example.com/article")

说明:

  • 未设置 wait_selector 时,会按域名与 HTML 结构自动挑选常见正文容器(多选择器)用于等待。

图片保留与输出格式

cfg = PipelineConfig()
cfg.extract.keep_images = True
cfg.extract.append_images = True   # 在正文末尾追加图片列表(HTML 模式下为 <ul><img>)
cfg.extract.inline_images = False  # 设为 True 时输出 Markdown 并原位插入图片(对所有站点生效)
cfg.extract.keep_videos = True
cfg.extract.append_videos = False  # 在正文末尾追加视频列表(HTML 模式下为 <ul><video>)
cfg.extract.inline_videos = False  # 设为 True 时会在正文中插入 [Video] url
cfg.extract.output_format = "txt"  # "txt" / "md" / "html"

说明:

  • inline_images=Trueoutput_format="txt" 时,会把 ![](url) 转为 [Image] url
  • output_format="html" 时,将保留 HTML 并输出 <img> 标签(会自动修正懒加载 src)。
  • HTML 输出会自动附带一份基础样式(居中排版、图片/视频自适应、表格样式等)。
  • inline_videos=True 时,会把 HTML 中的 <video>/<source> 转成 [Video] url;若 output_format="html" 则输出 <video> 标签。

微信文章图片(mp.weixin.qq.com)

from trafipipe import Pipeline, PipelineConfig

cfg = PipelineConfig()
cfg.extract.keep_images = True
cfg.extract.append_images = True
cfg.render.mode = "auto"  # 如图片仍缺失可改为 "always"
cfg.render.extra_headers = {"Referer": "https://mp.weixin.qq.com/"}
cfg.render.cookies = [
    {"name": "your_cookie", "value": "xxx", "domain": ".mp.weixin.qq.com", "path": "/"}
]

result = Pipeline(cfg).extract_url("https://mp.weixin.qq.com/s/xxxxxx")
print(result.images)

列表页发现链接并抽取

from trafipipe import Pipeline, PipelineConfig

cfg = PipelineConfig()
cfg.crawl.max_pages = 50
cfg.crawl.max_depth = 2
cfg.crawl.max_workers = 4  # 并发抓取列表页

pipeline = Pipeline(cfg)
urls = pipeline.crawl(["https://example.com/list"])
results = pipeline.crawl_and_extract(urls, max_workers=4)

CLI

trafipipe extract https://example.com/article
trafipipe crawl https://example.com/list --max-pages 50 --max-depth 2 --workers 4

开发

pip install -e ".[dev]"
pytest
ruff check .

性能基准

python doc/benchmark.py --file doc/urls.txt --render auto --repeat 1
python doc/benchmark.py --file doc/urls.txt --format csv --summary > report.csv
python doc/benchmark.py --file doc/urls.txt --format json --summary > report.json

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