kadubon's picture
Stage paper TeX corpus v1 (batch 1)
9aa0c5c verified
Raw
History Blame Contribute Delete
15.3 kB
from __future__ import annotations
import hashlib
import json
import mimetypes
import re
import unicodedata
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Iterable
DOI_RE = re.compile(r"10\.\d{4,9}/[-._;()/:A-Z0-9]+", re.IGNORECASE)
HEADING_RE = re.compile(
r"\\(?P<kind>part|chapter|section|subsection|subsubsection)\*?\s*\{",
re.IGNORECASE,
)
ENV_TOKEN_RE = re.compile(r"\\(?P<op>begin|end)\s*\{(?P<env>[^{}]+)\}")
PROTECTED_ENVS = {
"equation",
"equation*",
"align",
"align*",
"alignat",
"alignat*",
"gather",
"gather*",
"multline",
"multline*",
"displaymath",
"math",
"theorem",
"lemma",
"proposition",
"corollary",
"definition",
"assumption",
"remark",
"example",
"proof",
"axiom",
"verbatim",
"lstlisting",
}
HEADING_LEVELS = {
"part": 0,
"chapter": 0,
"section": 1,
"subsection": 2,
"subsubsection": 3,
}
SECRET_PATTERNS = {
"openai_key": re.compile(r"(?<![A-Za-z0-9])sk-[A-Za-z0-9_-]{20,}"),
"huggingface_token": re.compile(r"(?<![A-Za-z0-9])hf_[A-Za-z0-9]{20,}"),
"github_token": re.compile(r"(?<![A-Za-z0-9])gh[pousr]_[A-Za-z0-9]{20,}"),
"private_key": re.compile(
r"-----BEGIN (?:RSA |OPENSSH |EC )?PRIVATE KEY-----"
),
}
def sha256_bytes(data: bytes) -> str:
return hashlib.sha256(data).hexdigest()
def sha256_file(path: Path, chunk_size: int = 1024 * 1024) -> str:
digest = hashlib.sha256()
with path.open("rb") as stream:
while chunk := stream.read(chunk_size):
digest.update(chunk)
return digest.hexdigest()
def canonical_json(data: Any) -> str:
return json.dumps(
data,
ensure_ascii=False,
indent=2,
sort_keys=True,
separators=(",", ": "),
) + "\n"
def write_text_lf(path: Path, text: str) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(text.replace("\r\n", "\n"), encoding="utf-8", newline="\n")
def strip_tex_comments(text: str) -> str:
output: list[str] = []
for line in text.splitlines(keepends=True):
cut = None
for index, char in enumerate(line):
if char != "%":
continue
backslashes = 0
cursor = index - 1
while cursor >= 0 and line[cursor] == "\\":
backslashes += 1
cursor -= 1
if backslashes % 2 == 0:
cut = index
break
if cut is None:
output.append(line)
else:
newline = "\n" if line.endswith("\n") else ""
output.append(line[:cut] + newline)
return "".join(output)
def extract_braced_command(text: str, command: str) -> str:
match = re.search(rf"\\{re.escape(command)}\s*\{{", text)
if not match:
return ""
start = match.end()
cursor = start
depth = 1
while cursor < len(text) and depth:
char = text[cursor]
escaped = cursor > 0 and text[cursor - 1] == "\\"
if char == "{" and not escaped:
depth += 1
elif char == "}" and not escaped:
depth -= 1
cursor += 1
if depth:
return ""
return text[start : cursor - 1]
def clean_tex_label(text: str) -> str:
cleaned = strip_tex_comments(text)
cleaned = re.sub(r"\\\\(?:\[[^\]]*\])?", " ", cleaned)
cleaned = re.sub(r"\\(?:href)\s*\{[^{}]*\}\s*\{([^{}]*)\}", r"\1", cleaned)
cleaned = re.sub(r"\\(?:url)\s*\{([^{}]*)\}", r"\1", cleaned)
cleaned = re.sub(r"\\[A-Za-z@]+\*?(?:\[[^\]]*\])?", " ", cleaned)
cleaned = cleaned.replace("{", " ").replace("}", " ").replace("~", " ")
cleaned = re.sub(r"\s+", " ", cleaned)
return cleaned.strip()
def normalize_title(text: str) -> str:
normalized = unicodedata.normalize("NFKD", clean_tex_label(text)).lower()
normalized = normalized.replace("–", "-").replace("—", "-")
normalized = re.sub(r"[^a-z0-9]+", " ", normalized)
return " ".join(normalized.split())
def archive_stem_title(name: str) -> str:
stem = Path(name).stem
stem = re.sub(r"\s+\(\d+\)$", "", stem)
return stem.replace("__", " ").replace("_", " ").strip()
def extract_document_body(text: str) -> str:
begin = re.search(r"\\begin\s*\{document\}", text)
end_matches = list(re.finditer(r"\\end\s*\{document\}", text))
if not begin:
return strip_tex_comments(text).strip()
end = end_matches[-1].start() if end_matches else len(text)
return strip_tex_comments(text[begin.end() : end]).strip()
def brace_balance(text: str) -> int:
balance = 0
stripped = strip_tex_comments(text)
for index, char in enumerate(stripped):
if char not in "{}":
continue
backslashes = 0
cursor = index - 1
while cursor >= 0 and stripped[cursor] == "\\":
backslashes += 1
cursor -= 1
if backslashes % 2:
continue
balance += 1 if char == "{" else -1
return balance
def mime_type_for(name: str) -> str:
extension = Path(name).suffix.lower()
overrides = {
".tex": "application/x-tex",
".bib": "application/x-bibtex",
".json": "application/json",
".py": "text/x-python",
".zip": "application/zip",
}
return overrides.get(extension) or mimetypes.guess_type(name)[0] or "application/octet-stream"
def find_secret_patterns(text: str) -> list[str]:
return sorted(name for name, pattern in SECRET_PATTERNS.items() if pattern.search(text))
def find_unsafe_tex_references(text: str) -> list[str]:
unsafe: list[str] = []
pattern = re.compile(
r"\\(?:input|include|includegraphics|lstinputlisting)\s*"
r"(?:\[[^\]]*\])?\s*\{([^}]+)\}"
)
for match in pattern.finditer(text):
candidate = match.group(1)
if (
re.match(r"^[A-Za-z]:", candidate)
or candidate.startswith(("/", "\\\\"))
or ".." in Path(candidate).parts
):
unsafe.append(candidate)
return sorted(set(unsafe))
def readable_tex(text: str) -> tuple[str, list[str]]:
flags: list[str] = []
try:
from pylatexenc.latex2text import LatexNodes2Text
converter = LatexNodes2Text(
math_mode="verbatim",
keep_comments=False,
strict_latex_spaces=False,
)
rendered = converter.latex_to_text(text)
except Exception:
flags.append("latex_to_text_fallback")
rendered = clean_tex_label(text)
rendered = re.sub(r"[ \t]+\n", "\n", rendered)
rendered = re.sub(r"\n{3,}", "\n\n", rendered)
return rendered.strip(), flags
@dataclass(slots=True)
class TexEntry:
path: str
size: int
compressed_size: int
crc32: str
sha256: str
text: str
title_raw: str
title_clean: str
author_raw: str
author_clean: str
date_raw: str
doi_candidates: list[str]
content_status: str
quality_flags: list[str] = field(default_factory=list)
@dataclass(slots=True)
class Archive:
filename: str
source_path: Path
raw_path: str
size: int
sha256: str
entries: list[dict[str, Any]]
tex_entries: list[TexEntry]
primary_tex_index: int | None
mapped_dois: list[str] = field(default_factory=list)
mapping_method: str = "unresolved"
mapping_score: float = 0.0
mapping_status: str = "archive_only"
candidate_dois: list[str] = field(default_factory=list)
duplicate_of_archive: str = ""
quality_flags: list[str] = field(default_factory=list)
@property
def primary_tex(self) -> TexEntry | None:
if self.primary_tex_index is None:
return None
return self.tex_entries[self.primary_tex_index]
@property
def content_status(self) -> str:
primary = self.primary_tex
if primary is None:
return "invalid_source"
if self.duplicate_of_archive:
return "exact_duplicate"
return primary.content_status
@dataclass(slots=True)
class Block:
start: int
end: int
text: str
section_path: tuple[str, ...]
kind: str
def _protected_spans(text: str) -> list[tuple[int, int]]:
spans: list[tuple[int, int]] = []
stack: list[tuple[str, int]] = []
for match in ENV_TOKEN_RE.finditer(text):
env = match.group("env").strip().lower()
if env not in PROTECTED_ENVS:
continue
if match.group("op") == "begin":
stack.append((env, match.start()))
continue
for index in range(len(stack) - 1, -1, -1):
open_env, open_start = stack[index]
if open_env != env:
continue
is_outer = index == 0
del stack[index:]
if is_outer:
spans.append((open_start, match.end()))
break
return sorted(spans)
def _heading_title(block_text: str) -> tuple[int | None, str]:
match = HEADING_RE.search(block_text)
if not match:
return None, ""
command = match.group("kind").lower()
start = match.end()
cursor = start
depth = 1
while cursor < len(block_text) and depth:
char = block_text[cursor]
escaped = cursor > 0 and block_text[cursor - 1] == "\\"
if char == "{" and not escaped:
depth += 1
elif char == "}" and not escaped:
depth -= 1
cursor += 1
raw = block_text[start : cursor - 1] if depth == 0 else ""
return HEADING_LEVELS[command], clean_tex_label(raw)
def latex_blocks(body: str) -> list[Block]:
spans = _protected_spans(body)
raw_parts: list[tuple[int, int, str]] = []
cursor = 0
for start, end in spans:
if start > cursor:
raw_parts.append((cursor, start, "text"))
raw_parts.append((start, end, "environment"))
cursor = end
if cursor < len(body):
raw_parts.append((cursor, len(body), "text"))
pieces: list[tuple[int, int, str]] = []
for start, end, kind in raw_parts:
if kind == "environment":
pieces.append((start, end, kind))
continue
segment = body[start:end]
paragraph_starts = [0]
for match in re.finditer(r"\n\s*\n", segment):
paragraph_starts.append(match.end())
paragraph_starts.append(len(segment))
for left, right in zip(paragraph_starts, paragraph_starts[1:]):
absolute_left = start + left
absolute_right = start + right
content = body[absolute_left:absolute_right]
if not content.strip():
continue
heading_positions = [m.start() for m in HEADING_RE.finditer(content)]
if not heading_positions:
pieces.append((absolute_left, absolute_right, "text"))
continue
split_points = sorted(set([0, *heading_positions, len(content)]))
for local_left, local_right in zip(split_points, split_points[1:]):
if local_right <= local_left:
continue
piece_start = absolute_left + local_left
piece_end = absolute_left + local_right
if body[piece_start:piece_end].strip():
pieces.append((piece_start, piece_end, "heading_or_text"))
section_stack: list[str] = []
blocks: list[Block] = []
for start, end, kind in sorted(pieces):
text = body[start:end]
level, title = _heading_title(text)
block_kind = kind
if level is not None:
section_stack = section_stack[:level]
while len(section_stack) < level:
section_stack.append("")
if level == 0:
section_stack = [title]
else:
section_stack.append(title)
block_kind = "heading"
blocks.append(
Block(
start=start,
end=end,
text=text,
section_path=tuple(item for item in section_stack if item),
kind=block_kind,
)
)
return blocks
def make_chunks(
body: str,
target_chars: int = 4000,
max_chars: int = 6000,
overlap_chars: int = 400,
min_chars: int = 1500,
) -> list[dict[str, Any]]:
blocks = latex_blocks(body)
if not blocks and body.strip():
blocks = [Block(0, len(body), body, tuple(), "text")]
chunks: list[dict[str, Any]] = []
current: list[Block] = []
def emit(selected: list[Block]) -> None:
if not selected:
return
start = selected[0].start
end = selected[-1].end
tex = body[start:end].strip()
if not tex:
return
flags: list[str] = []
if len(tex) > max_chars:
flags.append("oversize_block")
plain, render_flags = readable_tex(tex)
flags.extend(render_flags)
path = selected[0].section_path
chunks.append(
{
"char_start": start,
"char_end": end,
"chunk_tex": tex,
"chunk_text": plain,
"section_path": list(path),
"section_title": path[-1] if path else "",
"quality_flags": sorted(set(flags)),
}
)
for block in blocks:
block_length = block.end - block.start
if block_length > max_chars:
emit(current)
current = []
emit([block])
continue
current_length = current[-1].end - current[0].start if current else 0
starts_new_section = block.kind == "heading" and bool(current)
would_exceed = current and block.end - current[0].start > max_chars
target_reached = current_length >= min_chars and (
starts_new_section or current_length >= target_chars
)
if current and (would_exceed or target_reached):
previous = list(current)
emit(previous)
overlap: list[Block] = []
overlap_size = 0
for candidate in reversed(previous):
candidate_size = candidate.end - candidate.start
if overlap and overlap_size + candidate_size > overlap_chars:
break
if candidate.kind == "heading" and overlap:
break
overlap.insert(0, candidate)
overlap_size += candidate_size
if overlap_size >= overlap_chars:
break
current = [] if starts_new_section else overlap
current.append(block)
emit(current)
return chunks
def content_size_category(count: int) -> str:
if count < 1000:
return "n<1K"
if count < 10_000:
return "1K<n<10K"
if count < 100_000:
return "10K<n<100K"
if count < 1_000_000:
return "100K<n<1M"
return "n>1M"
def batched(items: Iterable[Any], size: int) -> Iterable[list[Any]]:
batch: list[Any] = []
for item in items:
batch.append(item)
if len(batch) == size:
yield batch
batch = []
if batch:
yield batch