Update the FOMC events dataset
Browse files- PIPELINE.md +23 -9
- data/auction_announcements/part-00000.parquet +2 -2
- data/auction_calendar/part-00000.parquet +2 -2
- data/auction_results/part-00000.parquet +2 -2
- data/bill_rates/part-00000.parquet +2 -2
- data/curve_features/part-00000.parquet +1 -1
- data/nominal_yield_curve/part-00000.parquet +2 -2
- data/pit/part-00000.parquet +2 -2
- data/pit/us_treasury_events.delta/_delta_log/00000000000000000000.json +3 -3
- data/pit/us_treasury_events.delta/{part-00000-2bb0a7ee-ab33-41bf-9c32-fe0953ae83dd-c000.snappy.parquet → part-00000-b2b0b029-9fa3-4076-932c-17ffc313e68b-c000.snappy.parquet} +2 -2
- data/real_yield_curve/part-00000.parquet +2 -2
- manifest.json +2 -2
- metadata/build.parquet +2 -2
- metadata/coverage.parquet +2 -2
- metadata/field_coverage.parquet +1 -1
- metadata/yield_curve_methodology.parquet +2 -2
- quality_report.json +1 -1
- recipe/pipeline.py +57 -10
- tests/test_auctions.py +49 -8
- tests/test_curves.py +17 -8
PIPELINE.md
CHANGED
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@@ -221,15 +221,29 @@ change, so a run that already holds the row does not ask TreasuryDirect for it
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again: the first build reads 6 229 artifacts in about thirty-five minutes, and
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every run after it reuses them and finishes in **four seconds**.
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## Scheduling
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again: the first build reads 6 229 artifacts in about thirty-five minutes, and
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every run after it reuses them and finishes in **four seconds**.
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+
What decides reuse for an auction is `raw_sha256`, not the precision of its
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instant. A row carrying a digest is one whose artifact was fetched and read,
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and that is settled whether or not the artifact turned out to state a release
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time -- **1 357 of them do not**, and reusing only the `minute` rows meant
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refetching every one of those on every run, forever, looking for a line that
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was never going to appear. A row with no digest is one whose artifact was never
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found, and that one is worth looking for again.
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For the rate feeds, **every** past year is settled, not only the ones that
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produced rows. The real curve begins in 2003 and the years before it return a
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file with nothing but a header; holding only the years with data meant fetching
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thirteen empty years on every run to be told again that they are empty.
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Five auctions of 11 114 state a noncompetitive closing time in the artifact
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that the query leaves empty, so those two fields are carried forward from the
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held announcement rather than rebuilt from the query. Without that the
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incremental build would quietly drop a field the dataset already had.
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Between them the reuse paths take a run that fetched 12 832 documents down to
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**seven requests** and about **two and a half seconds**, and the tables it
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produces are identical to the full build's in all eight configs.
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`--rebuild` ignores held rows entirely, which is what a parser change needs.
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## Scheduling
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data/auction_announcements/part-00000.parquet
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@@ -1,3 +1,3 @@
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data/auction_calendar/part-00000.parquet
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data/auction_results/part-00000.parquet
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data/bill_rates/part-00000.parquet
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data/curve_features/part-00000.parquet
CHANGED
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 189724
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data/nominal_yield_curve/part-00000.parquet
CHANGED
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@@ -1,3 +1,3 @@
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data/pit/part-00000.parquet
CHANGED
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@@ -1,3 +1,3 @@
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size 2724267
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data/pit/us_treasury_events.delta/_delta_log/00000000000000000000.json
CHANGED
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@@ -1,4 +1,4 @@
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-
{"commitInfo":{"timestamp":
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{"protocol":{"minReaderVersion":1,"minWriterVersion":2}}
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{"metaData":{"id":"
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{"add":{"path":"part-00000-
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{"commitInfo":{"timestamp":1789281131033,"operation":"WRITE","operationParameters":{"mode":"Overwrite"},"engineInfo":"delta-rs:py-1.6.2","operationMetrics":{"execution_time_ms":178,"num_added_files":1,"num_added_rows":268960,"num_partitions":0,"num_removed_files":0},"clientVersion":"delta-rs.py-1.6.2"}}
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{"protocol":{"minReaderVersion":1,"minWriterVersion":2}}
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{"add":{"path":"part-00000-b2b0b029-9fa3-4076-932c-17ffc313e68b-c000.snappy.parquet","partitionValues":{},"size":4422313,"modificationTime":1789281131031,"dataChange":true,"stats":"{\"numRecords\":268960,\"minValues\":{\"unit\":\"percent\",\"subset\":\"auction_results\",\"event_date\":\"1979-10-31\",\"knowledge_date\":\"1979-11-01T04:59:59Z\",\"change\":-98.69,\"value_method\":\"derived\",\"record_id\":\"UST_1979-10-31_912827KC5_RES\",\"source_url\":\"https://home.treasury.gov/resource-center/data-chart-center/inte\",\"knowledge_time_precision\":\"date\",\"actual\":-1.91,\"parser_version\":\"1.0.0\",\"ingested_at\":\"2026-09-13T06:32:10.260494Z\",\"previous\":-1.91,\"entity_id\":\"UST_AUCTION_101D_CMB_ALLOTMENT_AT_HIGH_PCT\"},\"maxValues\":{\"unit\":\"ratio\",\"parser_version\":\"1.0.0\",\"entity_id\":\"UST_REAL_LT_REAL_AVERAGE\",\"subset\":\"real_yield_curve\",\"record_id\":\"real_2026-09-11_7Y\",\"previous\":100.0,\"knowledge_time_precision\":\"modeled_conservative\",\"knowledge_date\":\"2026-09-11T22:00:00Z\",\"value_method\":\"reported\",\"actual\":100.0,\"change\":98.15,\"ingested_at\":\"2026-09-13T06:32:10.260494Z\",\"source_url\":\"https://www.treasurydirect.gov/xml/R_20260910_3.xml\",\"event_date\":\"2026-09-11\"},\"nullCount\":{\"entity_id\":0,\"knowledge_date\":0,\"value_method\":0,\"unit\":0,\"ingested_at\":0,\"previous\":1287,\"forecast\":268960,\"parser_version\":0,\"event_date\":0,\"subset\":0,\"actual\":0,\"change\":1287,\"knowledge_time_precision\":0,\"record_id\":0,\"source_url\":0}}","tags":null,"baseRowId":null,"defaultRowCommitVersion":null,"clusteringProvider":null}}
|
data/pit/us_treasury_events.delta/{part-00000-2bb0a7ee-ab33-41bf-9c32-fe0953ae83dd-c000.snappy.parquet → part-00000-b2b0b029-9fa3-4076-932c-17ffc313e68b-c000.snappy.parquet}
RENAMED
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@@ -1,3 +1,3 @@
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data/real_yield_curve/part-00000.parquet
CHANGED
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 405997
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manifest.json
CHANGED
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@@ -278,7 +278,7 @@
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"event_date": "event_date",
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"event_date_type": "date",
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"frequency_seconds": null,
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-
"generated_at": "2026-09-13T06:32:
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"knowledge_date": "knowledge_date",
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"knowledge_date_policy": {
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"auction_results": "the release minute stated in the Treasury's own result artifact, from March 2008; the end of the auction day before that",
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@@ -325,6 +325,6 @@
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"build_version": "1.0.0",
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"package_version": "1.0.0",
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"parser_version": "1.0.0",
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-
"recipe_hash": "sha256:
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}
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}
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"event_date": "event_date",
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"event_date_type": "date",
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"frequency_seconds": null,
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+
"generated_at": "2026-09-13T06:32:11.129328+00:00",
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"knowledge_date": "knowledge_date",
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"knowledge_date_policy": {
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"auction_results": "the release minute stated in the Treasury's own result artifact, from March 2008; the end of the auction day before that",
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"build_version": "1.0.0",
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| 326 |
"package_version": "1.0.0",
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| 327 |
"parser_version": "1.0.0",
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| 328 |
+
"recipe_hash": "sha256:2807f605f7c9b8a56e579329be5a28fc38539806641e82030a079a47db686251"
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}
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}
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metadata/build.parquet
CHANGED
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 5400
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metadata/coverage.parquet
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 5293
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metadata/field_coverage.parquet
CHANGED
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 3288
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version https://git-lfs.github.com/spec/v1
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oid sha256:fcdd257538b3ab9b7b50e10926538138ba3d43e8389b0ecb86abf83b2754486f
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size 3288
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metadata/yield_curve_methodology.parquet
CHANGED
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 7308
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quality_report.json
CHANGED
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@@ -1,6 +1,6 @@
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{
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"ok": true,
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-
"checked_at": "2026-09-13T06:32:
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"counts": {
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"auction_calendar": 11114,
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"auction_announcements": 11114,
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{
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"ok": true,
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+
"checked_at": "2026-09-13T06:32:11.067792+00:00",
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"counts": {
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"auction_calendar": 11114,
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"auction_announcements": 11114,
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recipe/pipeline.py
CHANGED
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@@ -30,7 +30,7 @@ from pathlib import Path
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import polars as pl
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-
from .config import COUNTRY, Settings, validate_user_agent
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from .coverage import write_build_record, write_coverage
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from .http import Artifact, Fetcher
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from .methodology import methodology_for, write_registry
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@@ -332,7 +332,32 @@ def result_row(auction: Auction, *, artifact: Artifact | None, times: dict) -> d
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CURVE_CONCURRENCY = 6
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def
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"""Which years of which feed a previous run already published.
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A year of rates that is over cannot change, and each of these files is
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@@ -345,7 +370,7 @@ def held_curve_years(data_dir: Path) -> dict[str, set[int]]:
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this_year = datetime.now(UTC).year
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held: dict[str, set[int]] = {}
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for feed, (table, curve_type,
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try:
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rows = read_table(data_dir, table).collect()
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except (FileNotFoundError, pl.exceptions.ComputeError):
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continue
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if curve_type is not None:
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rows = rows.filter(pl.col("curve_type") == curve_type)
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-
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-
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return held
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@@ -531,9 +562,14 @@ def held_results(data_dir: Path) -> dict[str, dict]:
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every scheduled run would refetch six thousand artifacts -- forty minutes
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of somebody else's bandwidth to rediscover numbers that cannot move.
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"""
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try:
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@@ -545,7 +581,7 @@ def held_results(data_dir: Path) -> dict[str, dict]:
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return {
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row["auction_id"]: row
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for row in rows.iter_rows(named=True)
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-
if row["
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}
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@@ -572,6 +608,7 @@ async def build(
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if limit:
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auctions = auctions[-limit:]
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held = held_results(Path(settings.data_dir)) if reuse and not refresh else {}
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LOGGER.info(
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"%d auctions in the query, %d results already held", len(auctions), len(held)
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)
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@@ -589,6 +626,11 @@ async def build(
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calendar.append(calendar_row(auction, artifact=query, times=times))
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announcement = announcement_row(auction, artifact=query, times=times)
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if announcement is not None:
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announcements.append(announcement)
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results.append(known)
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reused += 1
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@@ -609,7 +651,11 @@ async def build(
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LOGGER.info("%d/%d auctions read", index, len(auctions))
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LOGGER.info("%d results reused, %d read from source", reused, len(results) - reused)
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-
held_years =
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curves = await fetch_curves(
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fetcher, first_year=settings.first_curve_year, skip=held_years
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)
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@@ -722,6 +768,7 @@ __all__ = [
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"calendar_row",
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"curve_features",
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"curve_rows",
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"held_curve_rows",
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"held_curve_years",
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"held_results",
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import polars as pl
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+
from .config import COUNTRY, FIRST_CURVE_YEAR, Settings, validate_user_agent
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from .coverage import write_build_record, write_coverage
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from .http import Artifact, Fetcher
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from .methodology import methodology_for, write_registry
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CURVE_CONCURRENCY = 6
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+
def held_closing_times(data_dir: Path) -> dict[str, dict]:
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"""The closing times a previous run read out of an artifact.
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Almost every auction has its closing times in the query as well, but five
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of 11 114 do not: the artifact states a noncompetitive close that the query
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leaves empty. Rebuilding those announcements from the query alone would
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quietly drop a field that the dataset already had, and the incremental
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build would stop matching the full one.
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"""
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try:
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rows = read_table(data_dir, "auction_announcements").collect()
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except (FileNotFoundError, pl.exceptions.ComputeError):
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return {}
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if rows.is_empty():
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return {}
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return {
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row["auction_id"]: {
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"competitive_close_at": row["competitive_close_at"],
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"noncompetitive_close_at": row["noncompetitive_close_at"],
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}
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for row in rows.iter_rows(named=True)
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}
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def held_curve_years(data_dir: Path, *, first_year: int = FIRST_CURVE_YEAR) -> dict[str, set[int]]:
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"""Which years of which feed a previous run already published.
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A year of rates that is over cannot change, and each of these files is
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this_year = datetime.now(UTC).year
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held: dict[str, set[int]] = {}
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+
for feed, (table, curve_type, _column) in FEED_TABLES.items():
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try:
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rows = read_table(data_dir, table).collect()
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except (FileNotFoundError, pl.exceptions.ComputeError):
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continue
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if curve_type is not None:
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rows = rows.filter(pl.col("curve_type") == curve_type)
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if rows.is_empty():
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continue
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# Every past year is settled, not only the ones that produced rows.
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# The real curve starts in 2003 and the years before it return a file
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# with nothing but a header; treating those as unread meant fetching
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# thirteen empty years on every run, forever, to be told again that
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# they are empty.
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held[feed] = set(range(first_year, this_year))
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return held
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every scheduled run would refetch six thousand artifacts -- forty minutes
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of somebody else's bandwidth to rediscover numbers that cannot move.
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What decides reuse is `raw_sha256`, not the precision. A row carrying a
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digest is one whose artifact was fetched and read, and that is settled
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whether or not the artifact turned out to state a release time -- 1 357 of
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them do not, and an earlier version of this function kept refetching every
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one of them forever, looking for a line that was never going to appear.
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A row with no digest is one whose artifact was never found. Those are
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looked for again, in case the Treasury has since published one.
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"""
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try:
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return {
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row["auction_id"]: row
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for row in rows.iter_rows(named=True)
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if row["raw_sha256"]
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}
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if limit:
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auctions = auctions[-limit:]
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held = held_results(Path(settings.data_dir)) if reuse and not refresh else {}
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+
held_times = held_closing_times(Path(settings.data_dir)) if held else {}
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LOGGER.info(
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"%d auctions in the query, %d results already held", len(auctions), len(held)
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)
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calendar.append(calendar_row(auction, artifact=query, times=times))
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announcement = announcement_row(auction, artifact=query, times=times)
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if announcement is not None:
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# Carry forward the two fields that came from the artifact
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# and are not in the query.
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for field, value in (held_times.get(auction.auction_id) or {}).items():
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if announcement.get(field) is None:
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announcement[field] = value
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announcements.append(announcement)
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results.append(known)
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reused += 1
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LOGGER.info("%d/%d auctions read", index, len(auctions))
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LOGGER.info("%d results reused, %d read from source", reused, len(results) - reused)
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+
held_years = (
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held_curve_years(Path(settings.data_dir), first_year=settings.first_curve_year)
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if reuse and not refresh
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else {}
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)
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curves = await fetch_curves(
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fetcher, first_year=settings.first_curve_year, skip=held_years
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)
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"calendar_row",
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"curve_features",
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"curve_rows",
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+
"held_closing_times",
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"held_curve_rows",
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"held_curve_years",
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"held_results",
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tests/test_auctions.py
CHANGED
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@@ -162,11 +162,14 @@ def test_an_auction_with_no_date_is_not_an_auction():
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assert isinstance(Auction(auction_id="x", row={}), Auction)
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def
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"""
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-
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"""
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import polars as pl
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@@ -176,17 +179,55 @@ def test_only_results_dated_from_an_artifact_are_reused(tmp_path):
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from recipe.store import write_table
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rows = [
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-
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{"result_id": "
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]
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data_dir = tmp_path / "data"
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write_table(data_dir, "auction_results",
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align(pl.DataFrame(rows, infer_schema_length=None), RESULT_SCHEMA))
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held = held_results(data_dir)
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-
assert set(held) == {"UST_2020-01-02_X"}
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def test_nothing_is_held_when_there_is_no_published_tree(tmp_path):
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from recipe.pipeline import held_results
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assert held_results(tmp_path / "nothing") == {}
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assert isinstance(Auction(auction_id="x", row={}), Auction)
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+
def test_a_row_is_reused_when_its_artifact_was_read(tmp_path):
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"""The digest decides, not the precision.
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1 357 artifacts exist and state no release time. Their rows are dated to
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the end of the auction day, and an earlier version of this rule refetched
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every one of them on every run, looking for a line that was never going to
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appear. A row with no digest is one whose artifact was never found, and
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that one is worth looking for again.
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"""
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import polars as pl
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from recipe.store import write_table
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rows = [
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# Artifact read, stated a release minute.
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{"result_id": "A", "auction_id": "UST_2020-01-02_X",
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"knowledge_time_precision": "minute", "raw_sha256": "aaa"},
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# Artifact read, stated no release time. Settled all the same.
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{"result_id": "B", "auction_id": "UST_2009-03-05_Y",
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"knowledge_time_precision": "date", "raw_sha256": "bbb"},
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# No artifact was ever found. Look again.
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{"result_id": "C", "auction_id": "UST_1998-07-27_Z",
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"knowledge_time_precision": "date", "raw_sha256": None},
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]
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data_dir = tmp_path / "data"
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write_table(data_dir, "auction_results",
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align(pl.DataFrame(rows, infer_schema_length=None), RESULT_SCHEMA))
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held = held_results(data_dir)
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assert set(held) == {"UST_2020-01-02_X", "UST_2009-03-05_Y"}
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def test_nothing_is_held_when_there_is_no_published_tree(tmp_path):
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from recipe.pipeline import held_results
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assert held_results(tmp_path / "nothing") == {}
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+
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+
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+
def test_closing_times_that_only_the_artifact_had_survive_a_reuse(tmp_path):
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"""Five auctions of 11 114 state a noncompetitive close only in the artifact.
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Rebuilding their announcement from the query alone would silently drop a
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field the dataset already had, and the incremental build would stop
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matching the full one.
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"""
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import polars as pl
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from recipe.pipeline import held_closing_times
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from recipe.schema import ANNOUNCEMENT_SCHEMA, align
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from recipe.store import write_table
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rows = [
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{
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"announcement_id": "UST_2020-07-13_X_ANN",
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"auction_id": "UST_2020-07-13_X",
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"competitive_close_at": datetime(2020, 7, 13, 15, 30, tzinfo=UTC),
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"noncompetitive_close_at": datetime(2020, 7, 10, 15, 0, tzinfo=UTC),
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}
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]
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data_dir = tmp_path / "data"
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write_table(data_dir, "auction_announcements",
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align(pl.DataFrame(rows, infer_schema_length=None), ANNOUNCEMENT_SCHEMA))
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held = held_closing_times(data_dir)
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assert held["UST_2020-07-13_X"]["noncompetitive_close_at"] == datetime(
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2020, 7, 10, 15, 0, tzinfo=UTC
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)
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tests/test_curves.py
CHANGED
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@@ -112,8 +112,14 @@ def test_the_methodology_changed_on_the_date_the_treasury_states():
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assert all(len(text) > 100 for text in table["description"])
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-
def
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"""A year
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from datetime import UTC, datetime
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@@ -127,13 +133,13 @@ def test_only_finished_years_of_a_feed_are_reused(tmp_path):
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rows = [
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{"curve_id": f"nominal_{year}-06-01_10Y", "curve_date": date(year, 6, 1),
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"curve_type": "nominal", "maturity": "10Y", "yield_pct": 4.0}
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for year in (this_year - 2, this_year
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]
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data_dir = tmp_path / "data"
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write_table(data_dir, "nominal_yield_curve",
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align(pl.DataFrame(rows, infer_schema_length=None), CURVE_SCHEMA))
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held = held_curve_years(data_dir)
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assert held["nominal"] ==
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assert this_year not in held["nominal"]
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@@ -155,9 +161,12 @@ def test_two_feeds_sharing_a_table_are_tracked_apart(tmp_path):
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data_dir = tmp_path / "data"
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write_table(data_dir, "nominal_yield_curve",
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align(pl.DataFrame(rows, infer_schema_length=None), CURVE_SCHEMA))
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-
held = held_curve_years(data_dir)
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-
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assert held["
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def test_nothing_is_held_without_a_published_tree(tmp_path):
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assert all(len(text) > 100 for text in table["description"])
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+
def test_every_past_year_is_settled_including_the_empty_ones(tmp_path):
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"""A past year with no rows is a year the Treasury published nothing for.
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+
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The real curve begins in 2003 and the years before it return a file with
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nothing but a header. Holding only the years that produced rows meant
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refetching those empty years on every run, forever, to be told again that
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they are empty. The current year is never held: it gains a row a day.
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+
"""
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from datetime import UTC, datetime
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rows = [
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{"curve_id": f"nominal_{year}-06-01_10Y", "curve_date": date(year, 6, 1),
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"curve_type": "nominal", "maturity": "10Y", "yield_pct": 4.0}
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+
for year in (this_year - 2, this_year)
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]
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data_dir = tmp_path / "data"
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write_table(data_dir, "nominal_yield_curve",
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align(pl.DataFrame(rows, infer_schema_length=None), CURVE_SCHEMA))
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+
held = held_curve_years(data_dir, first_year=this_year - 5)
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+
assert held["nominal"] == set(range(this_year - 5, this_year))
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assert this_year not in held["nominal"]
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data_dir = tmp_path / "data"
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write_table(data_dir, "nominal_yield_curve",
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align(pl.DataFrame(rows, infer_schema_length=None), CURVE_SCHEMA))
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+
held = held_curve_years(data_dir, first_year=2010)
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# Both feeds have published rows, so both hold every past year.
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assert 2010 in held["nominal"]
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assert 2011 in held["long_term_composite"]
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# A feed with no rows at all holds nothing.
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assert "real" not in held
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def test_nothing_is_held_without_a_published_tree(tmp_path):
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