Datasets:
Tasks:
Tabular Classification
Formats:
parquet
Languages:
English
Size:
< 1K
Tags:
economics
quantitative-finance
causal-inference
macroeconomics
housing-economics
market-microstructure
License:
| from __future__ import annotations | |
| from pathlib import Path | |
| import pyarrow.parquet as pq | |
| import pytest | |
| from microstructure.data.schemas import get_schema | |
| from microstructure.data.storage import ( | |
| StorageError, | |
| write_partitioned_parquet, | |
| write_source_manifest, | |
| ) | |
| from microstructure.data.synthetic import generate_synthetic_market | |
| from microstructure.provenance import read_json, sha256_file | |
| def test_partitioned_parquet_is_streamed_content_addressed_and_manifested( | |
| tmp_path: Path, | |
| ) -> None: | |
| start_ns = 1_704_153_600_000_000_000 | |
| data = generate_synthetic_market( | |
| symbols=("BTCUSDT", "ETHUSDT"), | |
| events_per_symbol=7, | |
| start_ts_ns=start_ns, | |
| seed=11, | |
| ) | |
| result = write_partitioned_parquet( | |
| data.trades.to_batches(max_chunksize=4), | |
| root=tmp_path, | |
| dataset="trades", | |
| schema_name="trades", | |
| source="synthetic_v1", | |
| requested_start_ns=start_ns, | |
| requested_end_ns=start_ns + 1_000_000_000, | |
| max_rows_per_file=3, | |
| downloaded_at_utc="2026-08-07T12:00:00Z", | |
| ) | |
| assert result.rows == 14 | |
| assert result.artifacts | |
| assert result.manifest_path.is_file() | |
| assert result.manifest_sha256 == sha256_file(result.manifest_path) | |
| assert {item.symbol for item in result.artifacts} == {"BTCUSDT", "ETHUSDT"} | |
| for artifact in result.artifacts: | |
| assert artifact.data_path.is_file() | |
| assert artifact.rows <= 3 | |
| assert "symbol-" + artifact.symbol in str(artifact.data_path) | |
| assert artifact.data_sha256 == sha256_file(artifact.data_path) | |
| assert pq.read_schema(artifact.data_path).equals(get_schema("trades"), check_metadata=True) | |
| manifest = read_json(artifact.manifest_path) | |
| assert manifest["source"] == "synthetic_v1" | |
| assert manifest["downloaded_at_utc"] == "2026-08-07T12:00:00Z" | |
| assert manifest["schema_version"] == "1.0.0" | |
| assert manifest["checksum"]["value"] == artifact.data_sha256 | |
| assert manifest["requested_range_ns"]["start"] == start_ns | |
| assert manifest["write_ordinal"] == artifact.write_ordinal | |
| assert manifest["observed_range_ns"] == { | |
| "start": artifact.observed_start_ns, | |
| "end_inclusive": artifact.observed_end_inclusive_ns, | |
| } | |
| dataset_manifest = read_json(result.manifest_path) | |
| assert [item["write_ordinal"] for item in dataset_manifest["artifacts"]] == list( | |
| range(len(result.artifacts)) | |
| ) | |
| def test_same_normalized_content_reuses_immutable_parquet(tmp_path: Path) -> None: | |
| data = generate_synthetic_market( | |
| symbols=("BTCUSDT",), | |
| events_per_symbol=3, | |
| start_ts_ns=1_704_153_600_000_000_000, | |
| seed=99, | |
| ) | |
| kwargs = { | |
| "root": tmp_path, | |
| "dataset": "trades", | |
| "schema_name": "trades", | |
| "source": "synthetic_v1", | |
| "downloaded_at_utc": "2026-08-07T12:00:00Z", | |
| } | |
| first = write_partitioned_parquet([data.trades], **kwargs) | |
| second = write_partitioned_parquet([data.trades], **kwargs) | |
| assert [item.data_path for item in first.artifacts] == [ | |
| item.data_path for item in second.artifacts | |
| ] | |
| assert first.manifest_path == second.manifest_path | |
| assert len(list(tmp_path.rglob("*.parquet"))) == 1 | |
| assert not list(tmp_path.rglob("*.tmp")) | |
| def test_raw_source_manifest_contains_required_lineage_and_checksum(tmp_path: Path) -> None: | |
| raw = tmp_path / "page.json" | |
| raw.write_bytes(b'[{"a":1}]') | |
| manifest_path, manifest_sha = write_source_manifest( | |
| raw, | |
| source="binance_spot_public_api", | |
| source_uri="https://data-api.binance.vision/api/v3/aggTrades?symbol=BTCUSDT", | |
| downloaded_at_utc="2026-08-07T12:00:00Z", | |
| requested_start_ns=100, | |
| requested_end_ns=200, | |
| response_headers={"ETag": "abc", "X-MBX-USED-WEIGHT-1M": "4"}, | |
| ) | |
| manifest = read_json(manifest_path) | |
| assert manifest_sha == sha256_file(manifest_path) | |
| assert manifest["artifact_kind"] == "raw_source" | |
| assert manifest["checksum"]["value"] == sha256_file(raw) | |
| assert manifest["requested_range_ns"] == {"start": 100, "end_exclusive": 200} | |
| assert manifest["response_headers"]["ETag"] == "abc" | |
| def test_partition_writer_rejects_oversized_input_before_materializing_it( | |
| tmp_path: Path, | |
| ) -> None: | |
| data = generate_synthetic_market( | |
| symbols=("BTCUSDT",), | |
| events_per_symbol=3, | |
| start_ts_ns=1_704_153_600_000_000_000, | |
| seed=101, | |
| ) | |
| with pytest.raises(StorageError, match="above the bounded-memory limit 2"): | |
| write_partitioned_parquet( | |
| iter((data.trades,)), | |
| root=tmp_path, | |
| dataset="trades", | |
| schema_name="trades", | |
| source="synthetic_v1", | |
| max_input_batch_rows=2, | |
| ) | |
| assert not list(tmp_path.rglob("*.parquet")) | |
| assert not list(tmp_path.rglob("*.manifest-*.json")) | |