canml Module

This is the top‐level package for canml.

canml.iter_blf_chunks(blf_path: str, db: Database, chunk_size: int = 10000, filter_ids: Set[int] | None = None) → Iterator[DataFrame]

Stream‐decode a BLF file in manageable pandas DataFrame chunks.

Parameters:

• blf_path – Path to the BLF log.

• db – cantools Database with message definitions (possibly prefixed).

• chunk_size – Rows per DataFrame chunk.

• filter_ids – If set, only decode messages with these arbitration IDs.

Yields:

DataFrame chunks with decoded signals + timestamp column.

Raises:

FileNotFoundError – If BLF file not found.

canml.load_blf(blf_path: str, db: Database | str | List[str], message_ids: Set[int] | None = None, expected_signals: List[str] | None = None, force_uniform_timing: bool = False, interval_seconds: float = 0.01) → DataFrame

Load an entire BLF file into a DataFrame, with optional filters and signal injection.

Parameters:

• blf_path – Path to the BLF log.

• db – Database instance or DBC path(s).

• message_ids – Set of arbitration IDs to include (default all).

• expected_signals – List of signal names to ensure exist (fill NaN if missing).

• force_uniform_timing – If True, override timestamps with uniform spacing.

• interval_seconds – Interval for uniform timing.

Returns:

A DataFrame with ‘timestamp’ + decoded signal columns.

Raises:

FileNotFoundError – If files missing.

canml.load_dbc_files(dbc_paths: str | List[str], prefix_signals: bool = False) → Database

Load and merge one or more DBC files into a single Database. Optionally prefix signal names with message names to avoid collisions.

Parameters:

• dbc_paths – Path or list of paths to DBC files.

• prefix_signals – If True, automatically rename signals to “<MessageName>_<SignalName>”.

Returns:

A cantools Database with all definitions loaded.

Raises:

• FileNotFoundError – If any DBC file is missing.

• ValueError – If loading fails.

canml.to_csv(df_or_iter: DataFrame | Iterator[DataFrame], output_path: str, mode: str = 'w', header: bool = True) → None

Write DataFrame or iterator of DataFrames to CSV incrementally.

Parameters:

• df_or_iter – DataFrame or iterator of DataFrames.

• output_path – Destination CSV file.

• mode – Write mode (‘w’ or ‘a’).

• header – Write header for first block.

Raises:

ValueError – If write fails.

canml.to_parquet(df: DataFrame, output_path: str, compression: str = 'snappy') → None

Write a DataFrame to Parquet.

Parameters:

• df – pandas DataFrame.

• output_path – ‘.parquet’ file path.

• compression – Parquet codec.

Raises:

ValueError – If write fails.