Datasets:
File size: 3,397 Bytes
7825400 | 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 | """JSON and JSONL I/O helpers."""
import json
import hashlib
import os
from pathlib import Path
import tempfile
from typing import TypeVar, Type
from pydantic import BaseModel
T = TypeVar("T", bound=BaseModel)
def sha256_file(path: Path) -> str:
"""Hash files in bounded memory, including transferable image payloads."""
digest = hashlib.sha256()
with Path(path).open("rb") as handle:
for block in iter(lambda: handle.read(1024 * 1024), b""):
digest.update(block)
return digest.hexdigest()
def append_jsonl(path: Path, item: BaseModel) -> None:
"""Append a single Pydantic model as one JSON line."""
with open(path, "a") as f:
f.write(item.model_dump_json() + "\n")
def write_jsonl(path: Path, items: list[BaseModel]) -> None:
"""Write multiple Pydantic models as JSONL (append mode)."""
with open(path, "a") as f:
for item in items:
f.write(item.model_dump_json() + "\n")
def write_jsonl_atomic(path: Path, items: list[BaseModel]) -> None:
"""Replace a JSONL artifact atomically rather than appending to it."""
path.parent.mkdir(parents=True, exist_ok=True)
fd, temporary = tempfile.mkstemp(prefix=f".{path.name}.", dir=path.parent)
temporary_path = Path(temporary)
try:
os.fchmod(fd, 0o644)
with os.fdopen(fd, "w") as f:
for item in items:
f.write(item.model_dump_json() + "\n")
f.flush()
os.fsync(f.fileno())
os.replace(temporary_path, path)
except BaseException:
temporary_path.unlink(missing_ok=True)
raise
def read_jsonl(path: Path, model_class: Type[T]) -> list[T]:
"""Read a JSONL file and validate each line as a Pydantic model."""
items: list[T] = []
with open(path) as f:
for line in f:
line = line.strip()
if line:
items.append(model_class.model_validate_json(line))
return items
def write_json(path: Path, data: dict | BaseModel) -> None:
"""Write a dict or Pydantic model to a JSON file."""
with open(path, "w") as f:
if isinstance(data, BaseModel):
f.write(data.model_dump_json(indent=2))
else:
json.dump(data, f, indent=2, default=str)
def write_json_atomic(path: Path, data: dict | BaseModel) -> None:
"""Write JSON via an adjacent temporary file, then atomically replace it."""
path.parent.mkdir(parents=True, exist_ok=True)
fd, temporary = tempfile.mkstemp(prefix=f".{path.name}.", dir=path.parent)
temporary_path = Path(temporary)
try:
# ``mkstemp`` deliberately starts at 0600. Result manifests are moved
# between a root-run Docker container and the unprivileged host user,
# so retain the normal JSON-file readability of ``open(..., "w")``.
os.fchmod(fd, 0o644)
with os.fdopen(fd, "w") as f:
if isinstance(data, BaseModel):
f.write(data.model_dump_json(indent=2))
else:
json.dump(data, f, indent=2, default=str)
f.flush()
os.fsync(f.fileno())
os.replace(temporary_path, path)
except BaseException:
temporary_path.unlink(missing_ok=True)
raise
def read_json(path: Path) -> dict:
"""Read a JSON file and return as dict."""
with open(path) as f:
return json.load(f)
|