feat(convert): add task 05 sqlite converter with variant B keys" -m "- convert: convert_sqlite.py builds tribo.db (composite PKs, enforced FKs, Q1-Q7 indexes, track_summary)
- tools: common/track_summary.py fixes the cross-engine steady-state algorithm - rules: db-sql-schema records the FK enforcement decision and track_summary definition - specs: 05 aligned with data-naming-units, simtra_profiles added - docs: FK key-schema study added under docs/research/, README updated - replace manual CSV reading with CorpusReader for better data handling - streamline argument parsing and dependency checks using common pipeline functions - enhance marker writing for task completion tracking - remove unused regex and validation error classes for cleaner code
This commit is contained in:
73
common/corpus.py
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73
common/corpus.py
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"""Reading the CSV corpus with MANIFEST validation (converters, tasks 04-07).
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Every file consumed from ./out/csv/ is verified against MANIFEST.csv (byte
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size, sha256, row count) before its content is trusted - a mismatch aborts
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the converter (docs/rules/test-pipeline-validation.md section 2).
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"""
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from __future__ import annotations
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import hashlib
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import logging
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import re
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from pathlib import Path
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logger = logging.getLogger(__name__)
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MANIFEST_HEADER = "path,rows,bytes,sha256"
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INT_RE = re.compile(r"^-?[0-9]+$")
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FLOAT_RE = re.compile(r"^-?([0-9]+\.[0-9]*|\.[0-9]+|[0-9]+)([eE][+-]?[0-9]+)?$")
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class ValidationError(RuntimeError):
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pass
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def coerce(s: str) -> int | float | str:
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if INT_RE.match(s):
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return int(s)
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if FLOAT_RE.match(s):
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return float(s)
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return s
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class CorpusReader:
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def __init__(self, csv_root: Path) -> None:
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self.csv_root = csv_root
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self.manifest = self._load_manifest()
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def _load_manifest(self) -> dict[str, tuple[int, int, str]]:
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manifest: dict[str, tuple[int, int, str]] = {}
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with open(self.csv_root / "MANIFEST.csv", encoding="ascii") as fh:
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header = fh.readline().strip()
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if header != MANIFEST_HEADER:
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raise ValidationError(f"MANIFEST.csv: unexpected header {header!r}")
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for line in fh:
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path, rows, nbytes, sha = line.strip().split(",")
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manifest[path] = (int(rows), int(nbytes), sha)
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logger.info("manifest loaded: %d entries", len(manifest))
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return manifest
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def read(self, relpath: str) -> tuple[list[str], list[list[str]]]:
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"""Return (header, raw string rows), verified against MANIFEST."""
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data = (self.csv_root / relpath).read_bytes()
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exp_rows, exp_bytes, exp_sha = self.manifest[relpath]
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if len(data) != exp_bytes or hashlib.sha256(data).hexdigest() != exp_sha:
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raise ValidationError(f"{relpath}: bytes/sha256 mismatch vs MANIFEST")
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lines = data.decode("ascii").split("\n")
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header = lines[0].split(",")
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rows = [ln.split(",") for ln in lines[1:] if ln]
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if len(rows) != exp_rows:
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raise ValidationError(f"{relpath}: {len(rows)} rows != manifest {exp_rows}")
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return header, rows
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def dicts(self, relpath: str) -> list[dict]:
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"""Rows as dicts: lowercased CSV headers as keys, numerics coerced,
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empty cells omitted (docs/rules/data-naming-units.md section 4)."""
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header, rows = self.read(relpath)
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keys = [h.lower() for h in header]
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return [
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{k: coerce(v) for k, v in zip(keys, row) if v != ""}
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for row in rows
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]
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59
common/pipeline.py
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59
common/pipeline.py
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"""Task-orchestration helpers: CLI shape, dependency markers, completion
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markers, lab config loading (docs/rules/build-pipeline-tasks.md,
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docs/rules/code-python-style.md section 3).
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"""
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from __future__ import annotations
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import argparse
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import logging
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import sys
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from pathlib import Path
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import yaml
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logger = logging.getLogger(__name__)
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REPO_ROOT = Path(__file__).resolve().parent.parent
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def parse_task_args(description: str) -> argparse.Namespace:
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parser = argparse.ArgumentParser(description=description)
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parser.add_argument("--log-level", default="INFO", choices=["DEBUG", "INFO", "WARNING", "ERROR"])
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parser.add_argument("--out-root", type=Path, default=REPO_ROOT / "out", help="artifact tree root (default: ./out)")
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args = parser.parse_args()
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logging.basicConfig(
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level=args.log_level,
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stream=sys.stderr,
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format="%(asctime)s %(levelname)-7s %(name)s: %(message)s",
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)
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return args
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def check_dependencies(out_root: Path, deps: list[str]) -> None:
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for dep in deps:
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marker = out_root / ".done" / f"{dep}.ok"
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if not marker.exists():
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raise FileNotFoundError(f"dependency marker missing: {marker} - run task {dep} first")
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def remove_stale_marker(out_root: Path, task_id: str) -> Path:
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marker = out_root / ".done" / f"{task_id}.ok"
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if marker.exists():
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logger.info("re-run: removing stale marker %s", marker)
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marker.unlink()
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return marker
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def write_marker(out_root: Path, task_id: str, entries: dict) -> Path:
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marker = out_root / ".done" / f"{task_id}.ok"
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lines = [f"task: '{task_id}'", "status: ok"] + [f"{k}: {v}" for k, v in entries.items()]
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marker.parent.mkdir(parents=True, exist_ok=True)
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with open(marker, "w", encoding="utf-8", newline="\n") as fh:
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fh.write("\n".join(lines) + "\n")
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return marker
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def load_lab_config(out_root: Path) -> dict:
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with open(out_root / "config" / "lab_config.yaml", encoding="utf-8") as fh:
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return yaml.safe_load(fh)
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48
common/track_summary.py
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48
common/track_summary.py
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"""Per-track steady-state summary (docs/rules/db-sql-schema.md section 5).
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Both engines must produce identical values: SQLite calls this function
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during load (task 05); the PostgreSQL materialized view (task 06)
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implements the same three steps in SQL. Plain sequential float arithmetic
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keeps results within the 1e-9 checksum tolerance across implementations.
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"""
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from __future__ import annotations
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import math
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TAIL_START_CYCLE = 501 # steady-state proxy window: cycles 501..N
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def summarize_track(cofs: list[float]) -> tuple[float, float, int]:
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"""Return (cof_ss_mean, cof_ss_std, run_in_cycles) for cofs[i] = cof at cycle i+1."""
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n = len(cofs)
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tail = cofs[TAIL_START_CYCLE - 1:]
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m = _mean(tail)
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s = _stddev_pop(tail, m)
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run_in = TAIL_START_CYCLE - 1 # fallback when no cycle enters the 2-sigma band
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band = 2.0 * s
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for c in range(1, n + 1):
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if abs(cofs[c - 1] - m) < band:
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run_in = c
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break
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ss = cofs[run_in:] # cycles strictly greater than run_in
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ss_mean = _mean(ss)
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ss_std = _stddev_pop(ss, ss_mean)
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return ss_mean, ss_std, run_in
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def _mean(values: list[float]) -> float:
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total = 0.0
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for v in values:
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total += v
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return total / len(values)
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def _stddev_pop(values: list[float], mean: float) -> float:
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acc = 0.0
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for v in values:
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d = v - mean
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acc += d * d
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return math.sqrt(acc / len(values))
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