Route predict output to UUID-named parquet with YAML reference sidecar
When no --out is given, predictions are written to a UUID-named parquet (/ceph central store for ceph inputs, sibling directory otherwise) and a YAML reference file is created next to the checkpoint recording the output path, dataset, checkpoint, and timestamp. Adds pyyaml as a core dependency and unit tests for the two new helper functions. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
+48
-6
@@ -1,9 +1,12 @@
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from collections import Counter
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from datetime import datetime, timezone
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from enum import Enum
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from pathlib import Path
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from typing import Optional
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import uuid as uuid_mod
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import numpy as np
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import yaml
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import torch
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import typer
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from typing_extensions import Annotated
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@@ -39,6 +42,46 @@ from giant.sample import sample_flow
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app = typer.Typer(no_args_is_help=True)
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_CEPH_PREDICTIONS = Path("/ceph/lbogner/geant_steps/predictions")
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def _resolve_prediction_output(
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data: Path, out: Path | None
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) -> tuple[Path, Path, str]:
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"""Return (out_path, resolved_dataset_path, pred_uuid).
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When *out* is None the output path is derived from *data*:
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- under /ceph/ → fixed central store with a UUID filename
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- elsewhere → sibling of *data* with a UUID filename
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"""
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dataset_path = data.resolve()
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pred_uuid = str(uuid_mod.uuid4())
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if out is None:
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if str(dataset_path).startswith("/ceph/"):
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out = _CEPH_PREDICTIONS / f"{pred_uuid}.parquet"
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else:
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out = data.parent / f"{pred_uuid}.parquet"
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return out, dataset_path, pred_uuid
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def _write_prediction_ref(
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checkpoint: Path,
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pred_uuid: str,
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out: Path,
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dataset_path: Path,
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) -> Path:
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"""Write a YAML sidecar in the checkpoint directory and return its path."""
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ref = {
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"prediction_id": pred_uuid,
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"output": str(out),
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"dataset": str(dataset_path),
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"checkpoint": str(checkpoint.resolve()),
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"timestamp": datetime.now(timezone.utc).isoformat(),
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}
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ref_path = checkpoint.parent / f"{pred_uuid}.yaml"
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ref_path.write_text(yaml.dump(ref, default_flow_style=False, sort_keys=False))
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return ref_path
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@app.callback()
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def _main() -> None:
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@@ -331,12 +374,8 @@ def predict(
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gconfig.warn_if_checkpoint_config_mismatch(checkpoint)
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# --- Output path ---
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if out is None:
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stem = data.stem if data.is_file() else data.name
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suffix = (
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"_predicted_local.parquet" if coord == Coord.local else "_predicted.parquet"
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)
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out = data.parent / f"{stem}{suffix}"
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out, dataset_path, pred_uuid = _resolve_prediction_output(data, out)
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out.parent.mkdir(parents=True, exist_ok=True)
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typer.echo(f"output: {out}")
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# --- Stream input, generate predictions, write output ---
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@@ -494,6 +533,9 @@ def predict(
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if writer is not None:
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writer.close()
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ref_path = _write_prediction_ref(checkpoint, pred_uuid, out, dataset_path)
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typer.echo(f"reference: {ref_path}")
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if skipped:
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codes = ", ".join(
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f"{pdg} ({count})" for pdg, count in sorted(unknown_pdg_counts.items())
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@@ -10,6 +10,7 @@ dependencies = [
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"pyarrow>=16,<25",
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"tqdm>=4.60,<5",
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"typer>=0.12,<1",
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"pyyaml>=6,<7",
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]
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[project.optional-dependencies]
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@@ -0,0 +1,131 @@
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import uuid
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import yaml
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from giant.cli import _CEPH_PREDICTIONS, _resolve_prediction_output, _write_prediction_ref
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# ---------------------------------------------------------------------------
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# _resolve_prediction_output
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# ---------------------------------------------------------------------------
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def test_non_ceph_path_goes_to_data_parent(tmp_path):
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data = tmp_path / "pools" / "pbwo4" / "full.manifest"
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out, dataset_path, pred_uuid = _resolve_prediction_output(data, None)
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assert out.parent == data.parent
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assert out.name == f"{pred_uuid}.parquet"
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assert dataset_path == data.resolve()
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def test_ceph_path_goes_to_central_store(tmp_path, monkeypatch):
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# Patch resolve() so /ceph/... exists on any machine running the tests.
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ceph_data = _CEPH_PREDICTIONS.parent / "pools" / "pbwo4" / "full.manifest"
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monkeypatch.setattr(
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"giant.cli.Path.resolve",
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lambda self: ceph_data if self == ceph_data else self.absolute(),
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)
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out, _, pred_uuid = _resolve_prediction_output(ceph_data, None)
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assert out.parent == _CEPH_PREDICTIONS
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assert out.name == f"{pred_uuid}.parquet"
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def test_explicit_out_is_used_as_is(tmp_path):
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data = tmp_path / "data.parquet"
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explicit = tmp_path / "my_output.parquet"
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out, _, _ = _resolve_prediction_output(data, explicit)
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assert out == explicit
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def test_uuid_is_valid(tmp_path):
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data = tmp_path / "data.parquet"
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_, _, pred_uuid = _resolve_prediction_output(data, None)
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parsed = uuid.UUID(pred_uuid)
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assert parsed.version == 4
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def test_each_call_produces_a_distinct_uuid(tmp_path):
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data = tmp_path / "data.parquet"
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_, _, uuid1 = _resolve_prediction_output(data, None)
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_, _, uuid2 = _resolve_prediction_output(data, None)
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assert uuid1 != uuid2
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def test_dataset_path_is_resolved(tmp_path):
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data = tmp_path / "data.parquet"
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_, dataset_path, _ = _resolve_prediction_output(data, None)
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assert dataset_path.is_absolute()
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# ---------------------------------------------------------------------------
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# _write_prediction_ref
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# ---------------------------------------------------------------------------
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def test_ref_file_created_in_checkpoint_dir(tmp_path):
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ckpt_dir = tmp_path / "checkpoints" / "run1"
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ckpt_dir.mkdir(parents=True)
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checkpoint = ckpt_dir / "best.pt"
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checkpoint.touch()
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out = tmp_path / "predictions" / "abc.parquet"
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dataset = tmp_path / "pools" / "pbwo4" / "full.manifest"
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pred_uuid = str(uuid.uuid4())
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ref_path = _write_prediction_ref(checkpoint, pred_uuid, out, dataset)
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assert ref_path == ckpt_dir / f"{pred_uuid}.yaml"
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assert ref_path.exists()
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def test_ref_yaml_contains_expected_fields(tmp_path):
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ckpt_dir = tmp_path / "checkpoints"
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ckpt_dir.mkdir()
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checkpoint = ckpt_dir / "best.pt"
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checkpoint.touch()
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out = tmp_path / "pred.parquet"
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dataset = tmp_path / "full.manifest"
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pred_uuid = str(uuid.uuid4())
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ref_path = _write_prediction_ref(checkpoint, pred_uuid, out, dataset)
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data = yaml.safe_load(ref_path.read_text())
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assert data["prediction_id"] == pred_uuid
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assert data["output"] == str(out)
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assert data["dataset"] == str(dataset)
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assert data["checkpoint"] == str(checkpoint.resolve())
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assert "timestamp" in data
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def test_ref_timestamp_is_iso_format(tmp_path):
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from datetime import datetime
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ckpt_dir = tmp_path / "checkpoints"
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ckpt_dir.mkdir()
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checkpoint = ckpt_dir / "best.pt"
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checkpoint.touch()
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pred_uuid = str(uuid.uuid4())
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ref_path = _write_prediction_ref(checkpoint, pred_uuid, tmp_path / "p.parquet", tmp_path / "d")
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data = yaml.safe_load(ref_path.read_text())
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# Must parse without error and be timezone-aware (UTC).
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ts = datetime.fromisoformat(data["timestamp"])
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assert ts.tzinfo is not None
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def test_ref_checkpoint_path_is_absolute(tmp_path):
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ckpt_dir = tmp_path / "checkpoints"
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ckpt_dir.mkdir()
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checkpoint = ckpt_dir / "best.pt"
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checkpoint.touch()
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pred_uuid = str(uuid.uuid4())
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ref_path = _write_prediction_ref(checkpoint, pred_uuid, tmp_path / "p.parquet", tmp_path / "d")
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data = yaml.safe_load(ref_path.read_text())
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assert data["checkpoint"].startswith("/")
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@@ -440,6 +440,7 @@ dependencies = [
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{ name = "numpy" },
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{ name = "pandas" },
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{ name = "pyarrow" },
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{ name = "pyyaml" },
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{ name = "tqdm" },
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{ name = "typer" },
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]
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@@ -479,6 +480,7 @@ requires-dist = [
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{ name = "polars", marker = "extra == 'convert'", specifier = ">=1.0,<2" },
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{ name = "pyarrow", specifier = ">=16,<25" },
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{ name = "pytest", marker = "extra == 'dev'", specifier = ">=8,<10" },
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{ name = "pyyaml", specifier = ">=6,<7" },
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{ name = "ruff", marker = "extra == 'dev'", specifier = ">=0.15,<1" },
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{ name = "torch", marker = "extra == 'cpu'", specifier = ">=2.3,<2.4", index = "https://download.pytorch.org/whl/cpu", conflict = { package = "giant", extra = "cpu" } },
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{ name = "torch", marker = "extra == 'cuda'", specifier = ">=2.3,<2.4", index = "https://download.pytorch.org/whl/cu118", conflict = { package = "giant", extra = "cuda" } },
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@@ -1436,6 +1438,52 @@ wheels = [
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]
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[[package]]
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name = "pyyaml"
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version = "6.0.3"
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source = { registry = "https://pypi.org/simple" }
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[[package]]
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name = "pyzmq"
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version = "27.1.0"
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Reference in New Issue
Block a user