gowin2vcd 0.9.1

Convert Gowin GAO CSV captures to VCD waveform format.

gowin2vcd

Convert Gowin GAO CSV captures to VCD waveform format.

Features

• Single-pass streaming parser — opens the file exactly once, no matter how large
• Automatic GAO format detection — handles all known CSV variants
• Real GAO capture validated
• Hierarchical signal reconstruction — scope walker, no tree in memory
• Deterministic VCD output — same input always produces identical output
• Gzip-compressed output — use .vcd.gz to save space automatically
• Signal filtering — --include and --exclude options
• JSON output
• GTKWave save files — generates .gtkw files with groups and expanded scopes
• Signal aliases — preserves aliases from path/to/sig=alias_name CSV columns
• X/Z value propagation — handles unknown and high-impedance states
• Progress callback — for large captures
• Conversion statistics
• Zero runtime dependencies — pure Python 3.10+
• Golden regression tests

Supported outputs

• VCD
• JSON
• GTKWave save files

Installation

pip install gowin2vcd

Or from source:

git clone https://github.com/TSltd/gowin2vcd.git
cd gowin2vcd
pip install .

Usage

Command line

# Basic conversion
gowin2vcd capture.csv output.vcd

# Compressed output
gowin2vcd capture.csv output.vcd.gz

# Include only selected signals
gowin2vcd capture.csv output.vcd \
    --include top/clk top/rst

# Exclude selected signals
gowin2vcd capture.csv output.vcd \
    --exclude top/debug_state

# Override the VCD timescale
gowin2vcd capture.csv output.vcd \
    --timescale ns

# Omit the VCD date/version headers
gowin2vcd capture.csv output.vcd \
    --no-date --no-version

# Diagnostic mode
gowin2vcd capture.csv output.vcd \
    --verify

# Quiet mode
gowin2vcd capture.csv output.vcd \
    --quiet

# Verbose logging
gowin2vcd capture.csv output.vcd \
    --verbose

Python library

from gowin2vcd import GowinCSVParser
from gowin2vcd import VCDWriter

# Parse a capture
parser = GowinCSVParser("capture.csv")

# Access metadata
print(f"Time unit: {parser.metadata.time_unit}")
print(f"Signals: {[s.fullname for s in parser.signals]}")
print(f"Groups: {[g.name for g in parser.groups]}")

# Print stats
print(f"Signals: {stats.signals}")
print(f"Samples: {stats.samples}")
print(f"Changes: {stats.value_changes}")
print(f"Runtime: {stats.runtime:.2f}s")
print(f"Output:  {stats.output_path}")

# Convert to VCD
writer = VCDWriter("output.vcd")
stats = writer.write(parser)
print(f"Wrote {stats.num_samples} samples with {stats.num_changes} changes")

# Or iterate lazily
for sample in parser.iter_samples():
    print(f"t={sample.timestamp} clk={sample.values.get('top/clk')}")

JSON

from gowin2vcd import JSONWriter

writer = JSONWriter("capture.json")
writer.write(parser)

GTKWave save files

from gowin2vcd import GowinCSVParser
from gowin2vcd import GTKWSaveWriter

parser = GowinCSVParser("capture.csv")
capture = parser.parse()

writer = GTKWSaveWriter("output.gtkw")
writer.write(capture)

Architecture

See docs/architecture.md for details.

CSV
 │
 ▼             ┌──────────► VCD
Scanner ─► Parser ─┬──────► JSON
                   ├──────► GTKWave
                   └──────► FST (planned)

File Format

See docs/file_format.md for the GAO CSV format specification.

Status

The project is feature-complete for VCD conversion and has been validated against real Gowin GAO captures.

Current outputs:

• VCD
• JSON
• GTKWave save files

Python 3.10+ Zero runtime dependencies

Roadmap

Planned for v1.0:

• VCD reader
• Round-trip verification
• Fuzz testing
• Performance benchmarks

License

MIT