mf4-rs 1.5.2

Python bindings for mf4-rs - A minimal library for working with ASAM MDF 4 measurement files

mf4-rs

mf4-rs is a minimal Rust library for working with ASAM MDF 4 (Measurement Data Format) files. It supports parsing existing files as well as writing new ones through a safe API, implementing a subset of the MDF 4.1 specification sufficient for simple data logging and inspection tasks.

Architecture

High-Level Structure

The codebase is organized into distinct layers:

1. API Layer (src/api/)

• High-level user-facing API for working with MDF files
• MDF - Main entry point for parsing files from disk
• ChannelGroup - Wrapper providing ergonomic access to channel group metadata
• Channel - High-level channel representation with value decoding

2. Writer Module (src/writer/)

• MdfWriter - Core writer for creating MDF 4.1-compliant files
• Guarantees little-endian encoding, 8-byte alignment, and zero-padding
• Handles block linking and manages open data blocks during writing
• Supports both single record writing (write_record) and batch operations (write_records)

3. Block Layer (src/blocks/)

• Low-level MDF block implementations matching the specification
• Each block type (HeaderBlock, ChannelBlock, ChannelGroupBlock, etc.) has parsing and serialization
• Conversion system supporting various data transformations (linear, formula, lookup tables)
• Common utilities for block headers and data type handling

4. Parsing Layer (src/parsing/)

• File parsing and memory management using memory-mapped files
• Raw block parsers that maintain references to memory-mapped data
• Channel value decoder supporting multiple data types
• Lazy evaluation - channels and values are decoded on demand

5. Utilities (src/)

• cut.rs - Time-based file cutting functionality
• merge.rs - File merging utilities
• error.rs - Centralized error handling
• index.rs - MDF file indexing system for fast metadata-based access

Key Design Patterns

Memory-Mapped File Access: The parser uses memmap2 to avoid loading entire files into memory, enabling efficient handling of large measurement files.

Lazy Evaluation: Channel groups, channels, and values are created as lightweight wrappers that decode data only when accessed.

Builder Pattern: The writer uses closure-based configuration for channels and channel groups, allowing flexible setup while maintaining type safety.

Block Linking: The MDF format uses address-based linking between blocks. The writer maintains a position map to update links after blocks are written.

Usage

Building and Testing

# Build the project
cargo build

# Run all tests
cargo test

# Run specific test file
cargo test --test api

Examples

The project includes simplified examples in the examples/ directory:

• write_file.rs - Comprehensive example of writing MDF files with multiple channels
• read_file.rs - Demonstrates parsing and inspecting MDF files
• index_operations.rs - Shows advanced indexing, byte-range reading, and conversion resolution
• merge_files.rs - Merging multiple MF4 files
• cut_file.rs - Time-based file cutting
• python_equivalent.rs - Comparison with Python functionality

Run them with:

cargo run --example write_file
cargo run --example read_file
cargo run --example index_operations

Working with MDF Files

Basic File Creation Pattern:

use mf4_rs::writer::MdfWriter;
use mf4_rs::blocks::common::DataType;
use mf4_rs::parsing::decoder::DecodedValue;

let mut writer = MdfWriter::new("output.mf4")?;
writer.init_mdf_file()?;
let cg = writer.add_channel_group(None, |_| {})?;

// Create master channel (usually time)
let time_ch_id = writer.add_channel(&cg, None, |ch| {
    ch.data_type = DataType::FloatLE;
    ch.name = Some("Time".to_string());
    ch.bit_count = 64;
})?;
writer.set_time_channel(&time_ch_id)?; // Mark as master channel

// Add data channels with master as parent
writer.add_channel(&cg, Some(&time_ch_id), |ch| {
    ch.data_type = DataType::UnsignedIntegerLE;
    ch.name = Some("DataChannel".to_string());
    ch.bit_count = 32;
})?;

writer.start_data_block_for_cg(&cg, 0)?;
writer.write_record(&cg, &[
    DecodedValue::Float(1.0),              // Time
    DecodedValue::UnsignedInteger(42),     // Data
])?;
writer.finish_data_block(&cg)?;
writer.finalize()?;

Basic File Parsing Pattern:

use mf4_rs::api::mdf::MDF;

let mdf = MDF::from_file("input.mf4")?;
for group in mdf.channel_groups() {
    println!("channels: {}", group.channels().len());
    for channel in group.channels() {
        let values = channel.values()?;
        // Process values...
    }
}

MDF Indexing System

The library includes a powerful indexing system that allows you to:

1. Create lightweight JSON indexes of MDF files containing all metadata needed for data access
2. Read channel data without full file parsing using only the index and targeted file I/O
3. Serialize/deserialize indexes for persistent storage and sharing
4. Support multiple data sources through the ByteRangeReader trait (local files, HTTP, S3, etc.)

Basic Indexing Workflow:

// Create an index from an MDF file
let index = MdfIndex::from_file("data.mf4")?;

// Save index to JSON for later use
index.save_to_file("data_index.json")?;

// Later: load index and read specific channel data
let loaded_index = MdfIndex::load_from_file("data_index.json")?;

// Option 1: Use built-in file reader
let mut file_reader = FileRangeReader::new("data.mf4")?;
let channel_values = loaded_index.read_channel_values(0, 1, &mut file_reader)?;

// Option 2: Use HTTP range reader (production)
let mut http_reader = HttpRangeReader::new("https://cdn.example.com/data.mf4".to_string());
let channel_values = loaded_index.read_channel_values(0, 1, &mut http_reader)?;

Python Bindings

mf4-rs includes high-performance Python bindings generated using pyo3. This allows you to use the library's features directly from Python with minimal overhead.

Installation

You can install the package directly using pip or uv (requires a Rust compiler):

pip install .
# or
uv pip install .

For development, you can use maturin:

# Install maturin
pip install maturin

# Build and install in current environment
maturin develop --release

Python Examples

Check the python_examples/ directory for complete scripts:

• write_file.py - Creating MDF files
• read_file.py - Reading and inspecting files
• index_operations.py - Using the indexing system

Basic Usage

import mf4_rs

# Writing a file
writer = mf4_rs.PyMdfWriter("output.mf4")
writer.init_mdf_file()
group = writer.add_channel_group("MyGroup")

# Add channels
time_ch = writer.add_time_channel(group, "Time")
data_ch = writer.add_float_channel(group, "Data")

# Write data
writer.start_data_block(group)
writer.write_record(group, [
    mf4_rs.create_float_value(0.1),  # Time
    mf4_rs.create_float_value(42.0)  # Data
])
writer.finish_data_block(group)
writer.finalize()

# Reading a file
mdf = mf4_rs.PyMDF("output.mf4")
for group in mdf.channel_groups():
    print(f"Group: {group.name}, Channels: {group.channel_count}")

Performance

mf4-rs is designed for high performance:

• Use write_records for batch operations instead of multiple write_record calls
• Data blocks automatically split when they exceed 4MB to maintain performance
• Memory-mapped file access minimizes memory usage for large files
• Channel values are decoded lazily only when accessed
• Use indexing for repeated access to the same files to avoid re-parsing overhead

Note: Previous benchmarks have been removed as they are being updated.

Dependencies

• nom - Binary parsing combinators
• byteorder - Endianness handling
• memmap2 - Memory-mapped file I/O
• meval - Mathematical expression evaluation for formula conversions
• thiserror - Error handling derive macros

Releases

Releases are fully automated. Every merge to main runs .github/workflows/release.yml, which:

1. Reads commit messages since the last v* tag.
2. Computes a SemVer bump from Conventional Commits prefixes (feat: → minor, fix:/perf: → patch, feat!: / BREAKING CHANGE: → major; other types do not produce a release).
3. Updates Cargo.toml, pyproject.toml, Cargo.lock, and CHANGELOG.md, then tags vX.Y.Z.
4. Builds wheels for Linux (x86_64, aarch64), macOS (x86_64, aarch64), and Windows (x64), plus an sdist, and publishes them to PyPI via OIDC trusted publishing.
5. Publishes the Rust crate to crates.io.

PR titles are linted against the convention by .github/workflows/pr-title.yml. Because PRs are squash-merged, the PR title is the source of truth for both the changelog and the version bump. See CHANGELOG.md for release history.

How PR titles map to version bumps

PR title prefix (or footer)	Bump	Example
feat!: / <type>!: / body contains BREAKING CHANGE:	major	feat!: drop Python 3.8 support
feat:	minor	feat: add ##DZ block decompression for index reads
fix: / perf:	patch	fix: handle empty CHANGELOG.md on first release
chore: / docs: / refactor: / test: / ci: / build: / style:	no release	docs: clarify VLSD record format

If multiple commits land between releases, the highest bump wins. Runs with no qualifying commits are a clean no-op — no tag is created and no artifacts are published, which is why the chore(release): vX.Y.Z commit pushed back by the workflow does not trigger another release.

What gets published

Each successful release run publishes, in parallel, after the tag is pushed:

• PyPI: mf4-rs wheels for Linux (x86_64, aarch64), macOS (x86_64 on 13, aarch64 on 14), and Windows (x64), plus an sdist. Authentication uses PyPI Trusted Publishing (OIDC) — no long-lived API token is stored. The pypi GitHub Actions environment gates this job.
• crates.io: the mf4-rs Rust crate, gated by a cargo publish --dry-run step. Authentication uses the CARGO_REGISTRY_TOKEN repository secret.
• GitHub Releases: a release named vX.Y.Z whose body is the same changelog section appended to CHANGELOG.md.

Manual triggers and recovery

• Re-run a release: the Release workflow accepts workflow_dispatch, so a maintainer can re-run it from the Actions tab. If the tag already exists, bump-and-tag will fail; in that case re-run only the publish-pypi / publish-crates jobs from the original run.
• Skip a release intentionally: use a non-releasing prefix (chore:, docs:, refactor:, test:, ci:, build:, style:) for the PR title. The workflow will run, compute bump=none, and exit cleanly without creating a tag.
• First-time setup (already complete for this repo): a PyPI Trusted Publisher entry for mf4-rs pointing at dmagyar-0/mf4-rs workflow release.yml, environment pypi; a CARGO_REGISTRY_TOKEN secret; and — if branch protection blocks GITHUB_TOKEN pushes to main — a RELEASE_PAT secret with contents:write.