Files
CANveyor/stats/utils/extractor.py
T

64 lines
1.8 KiB
Python

# File: extractor.py
# Copyright (C) 2026 Erick Ahmed
# SPDX-License-Identifier: AGPL-3.0-or-later
import json
from pathlib import Path
import numpy as np
import pandas as pd
import polars as pl
def to_int(x):
if isinstance(x, (int, np.integer)):
return int(x)
if isinstance(x, str):
try:
return int(x, 16)
except ValueError:
return np.nan
return np.nan
def extract_id(row: pd.Series) -> str:
meta = row.get('j1939_metadata')
if pd.isna(meta):
return f"ID: {row['ID']}"
if isinstance(meta, str):
try:
meta = json.loads(meta)
except json.JSONDecodeError:
return f"ID: {row['ID']}"
if isinstance(meta, dict) and 'PGN' in meta:
return f"PGN: {meta['PGN']}"
return f"ID: {row['ID']}"
def load_data(file_path: Path) -> pd.DataFrame:
lf = pl.scan_parquet(file_path)
schema = lf.collect_schema()
names = schema.names()
byte_cols = [f"b{i}" for i in range(8) if f"b{i}" in names]
if byte_cols:
lf = lf.with_columns([
pl.col(c).str.to_integer(base=16, strict=False).cast(pl.Int16).alias(c)
for c in byte_cols
])
id_col = 'ID' if 'ID' in names else 'Identifier'
id_expr = pl.col(id_col).cast(pl.Utf8)
if 'j1939_metadata' in names:
try:
lf = lf.with_columns(
pl.when(pl.col('j1939_metadata').is_not_null())
.then(pl.lit('PGN: ') + pl.col('j1939_metadata').struct.field('PGN').cast(pl.Utf8))
.otherwise(pl.lit('ID: ') + id_expr)
.alias('Identifier')
)
except Exception:
lf = lf.with_columns((pl.lit('ID: ') + id_expr).alias('Identifier'))
else:
lf = lf.with_columns((pl.lit('ID: ') + id_expr).alias('Identifier'))
return lf.collect().to_pandas()