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from trafilatura import fetch_url, extract, extract_metadata
from datasets import load_dataset, Features, Value, Sequence
from typing import Dict, List, Any
from trafilatura.settings import DEFAULT_CONFIG
from copy import deepcopy
my_config = deepcopy(DEFAULT_CONFIG)
my_config["DEFAULT"]["DOWNLOAD_TIMEOUT"] = "3"
my_config["DEFAULT"]["SLEEP_TIME"] = "0"
def is_target(batch: Dict[str, List]) -> List[bool]:
result = []
for tpe, dead, deleted, url in zip(
batch["type"], batch["dead"], batch["deleted"], batch["url"]
):
if (
tpe == "story"
and dead is None
and deleted is None
and url is not None
and len(url) > 0
):
result.append(True)
else:
result.append(False)
return result
def fetch_one(doc: Dict[str, Any]) -> Dict[str, Any]:
downloaded = fetch_url(doc["url"], config=my_config)
result = {
"id": doc["id"],
"title": None,
"author": None,
"markdown": None,
"downloaded": False,
"meta_extracted": False,
"parsed": False,
"description": None,
"filedate": None,
"date": None,
"image": None,
"pagetype": None,
"hostname": None,
"sitename": None,
"categories": None,
"tags": None,
}
if downloaded:
result["downloaded"] = True
try:
raw_meta = extract_metadata(downloaded)
if raw_meta:
result["meta_extracted"] = True
meta = raw_meta.as_dict()
result["title"] = meta.get("title", None)
result["author"] = meta.get("author", None)
result["description"] = meta.get("description", None)
result["filedate"] = meta.get("filedate", None)
result["date"] = meta.get("date", None)
result["image"] = meta.get("image", None)
result["pagetype"] = meta.get("pagetype", None)
result["hostname"] = meta.get("hostname", None)
result["sitename"] = meta.get("sitename", None)
md = extract(downloaded, output_format="markdown", with_metadata=False)
if md:
result["parsed"] = True
result["markdown"] = md
except Exception:
print("failed to extract metadata")
return result
if __name__ == "__main__":
ds = load_dataset("nixiesearch/hackernews-comments", split="train", num_proc=16)
ds = ds.filter(is_target, num_proc=32, batched=True, desc="selecting stories")
ds = ds.select_columns(["id", "url"]).shuffle()
schema = Features(
{
"id": Value("int64"),
"url": Value("string"),
"title": Value("string"),
"author": Value("string"),
"markdown": Value("string"),
"downloaded": Value("bool"),
"meta_extracted": Value("bool"),
"parsed": Value("bool"),
"description": Value("string"),
"filedate": Value("string"),
"date": Value("string"),
"image": Value("string"),
"pagetype": Value("string"),
"hostname": Value("string"),
"sitename": Value("string"),
"categories": Sequence(Value("string")),
"tags": Sequence(Value("string")),
}
)
ds = ds.map(fetch_one, num_proc=128, desc="downloading", features=schema)
ds.save_to_disk("/tmp/hnstories")
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