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pj-bridge

Bridge a delimiter-framed TCP binary stream into JSON over WebSocket for PlotJuggler or stdout (if file).

Mode: PlotJuggler runs the WebSocket Server. The bridge connects as a WebSocket client and pushes JSON messages.

What’s in this repo

  • derive_struct.py — Parse a C header (typedef struct { ... } Name;) and derive the Python struct format and expanded field labels.
  • stream_parser.py — Connect to the device (or read a .bin file), parse [DE AD BE EF][COUNT][MSG_ID][PAYLOAD] × COUNT batches into NDJSON (one JSON per line), or into CSV with --csv.
  • socket_client.py — Read NDJSON (stdin or file) and forward to PlotJuggler’s WebSocket Server.
  • bridge.py — One-process solution: connect to device, parse, and forward to PlotJuggler (no shell pipes needed) or stdout (if file, as NDJSON or CSV with --csv).
  • streamer.py — Library API (PlotJugglerStreamer) to run the parse-and-forward pipeline in-process from any byte source (e.g. a serial port), no subprocess or shell pipes.

Requirements

  • Python 3.12+

  • Device emits batches framed like:

    [ 0xDE 0xAD 0xBE 0xEF ][ COUNT:1 byte ][MSG_ID:2 bytes][ PAYLOAD ] * COUNT
    
  • The payload is a packed C struct defined in a header file.

  • PlotJuggler with the WebSocket Server plugin enabled (Protocol: JSON).

Install

python3.12 -m venv .venv
source .venv/bin/activate
pip install -e .

Start PlotJuggler’s WebSocket Server

  • In PlotJuggler: Streaming → WebSocket Server
  • Protocol: JSON
  • Port: for example 9871
  • Click Start

Start Bridge

Connect to device, parse batches, forward to PJ. Default TCP port is 5000; default WS URL is ws://127.0.0.1:9871. Timestamps are in milliseconds by default (--ts-scale 1e-3).

python3 bridge.py \
  --host 192.168.1.91 \
  --struct-header /path/to/telemetry.h \
  --struct-name MyStruct \
  --name-prefix "device_a."

Notes:

  • Add --controller-out-size if using a struct with HiddenHighLevelControllerOutputData_s to specify size (ex: 109) (this is CONTROLLER_OUTPUT_DATA_SIZE value in high_level_controller_common.h)
  • Add --ignore-errors only applies to file conversions, streaming always ignores errors regardless of this flag
  • Add --csv with --file to write CSV instead of NDJSON (see Parsing log files). File conversions only — passing it with --host is an error, since TCP mode forwards JSON to PlotJuggler.
  • Add --ws-url ws://<pj_host>:9871 if PlotJuggler runs elsewhere.
  • If needed, guard against corrupted batches with --max-frames-per-batch N.
  • To fall back to single [DELIM][PAYLOAD] (no COUNT), pass --no-counted-batch.

Two-process pipeline (for debugging)

  1. Derive the struct (optional sanity check). Prints JSON describing the derived struct_fmt, fields, and record_size.
python3 derive_struct.py \
  --header /path/to/telemetry.h \
  --struct-name MyStruct \
  1. Parse from device to NDJSON:
python3 stream_parser.py \
 --host 192.168.1.91 \
 --struct-header /path/to/telemetry.h \
 --struct-name MyStruct \
 --name-prefix "device_a."
  1. Forward NDJSON to PlotJuggler:
python3 stream_parser.py --host 192.168.1.91 --struct-header /path/to/telemetry.h --struct-name MyStruct | python3 socket_client.py --ws-url ws://127.0.0.1:9871

Use as a library

The same pipeline is importable, so a host application can supply its own byte source instead of TCP or a file. PlotJugglerStreamer takes a blocking read_fn() -> bytes (return b"" when idle), derives the struct from a header, parses 0xDEADBEEF batches, and forwards JSON to PlotJuggler's WebSocket Server on a background thread.

from pj_bridge import PlotJugglerStreamer

streamer = PlotJugglerStreamer(
    read_fn=lambda: ser.read(max(1, ser.in_waiting)),  # e.g. a pyserial port
    struct_header="/path/to/telemetry.h",
    struct_name="MyStruct",
    ts_field="timestamp",
    ws_url="ws://127.0.0.1:9871",
)
streamer.start()
# ...
streamer.stop()

stop() ends the reader and the WebSocket sender even if PlotJuggler's server was never up. Pass on_connect / on_disconnect callbacks to be notified when the WebSocket link to PlotJuggler is established or drops (they run on the event loop, so keep them cheap and marshal any UI work to your own thread):

PlotJugglerStreamer(
    ...,
    on_connect=lambda: print("connected to PlotJuggler"),
    on_disconnect=lambda: print("PlotJuggler link dropped"),
)

Other public names: derive_struct, DelimitedRecordParser, ws_sender, source_reader_to_queue.

Field naming

  • All non-timestamp fields are emitted with the optional prefix:

    --name-prefix "device_a."
    

    Example JSON:

    {"t": 1727370023.415, "device_a.ax": 0.02, "device_a.ay": -0.01, "device_a.az": 9.81}
    
  • Arrays like float gyro[3]; become device_a.gyro[0], device_a.gyro[1], device_a.gyro[2].

Timestamp (t)

  • If --ts-field ts_ms is provided, t = ts_ms * --ts-scale (default 1e-3, ms → seconds).
  • If no --ts-field is set, arrival time is used (time.time() in seconds).
  • If your device time is relative (since boot) and you want wall-clock, you can add an epoch offset in code; ask if you want a ready-made flag for that.

Parsing log files

stream-parser reads either source and writes to stdout:

  1. Live over TCP, using --host
  2. Offline from stored binary log files, using --file

By default it emits NDJSON (one JSON object per line). Add --csv to get CSV directly, ready for Excel, Pandas, or visualization tools.

Straight to CSV (recommended)

# offline log file
stream-parser --file capture.bin --struct-header telemetry.h --struct-name MyStruct --csv > logs.csv

# live TCP stream
stream-parser --host 192.168.1.91 --struct-header telemetry.h --struct-name MyStruct --csv > live.csv

pj-bridge accepts the same flags for its --file mode, so either entry point works:

pj-bridge --file capture.bin --struct-header telemetry.h --struct-name MyStruct --csv > logs.csv

With --host, pj-bridge forwards JSON to PlotJuggler instead, so --csv is rejected there rather than silently ignored.

Options:

  • --csv-delimiter ';' to change the column separator (default ,).
  • --no-header to omit the header row.

Column order follows the parser's field order, and the header is taken from the first record — the same layout json-to-csv produces, so existing CSVs stay comparable.

Via NDJSON and json-to-csv

json-to-csv converts NDJSON on stdin into CSV on stdout. All JSON lines must contain the same fields (the parsers ensure this).

stream-parser --file capture.bin ... | json-to-csv > logs.csv

This produces byte-identical output to --csv, but every record is serialized to JSON, written to a pipe, and parsed back again. Prefer --csv unless you actually want the NDJSON, for example to feed socket-client or to inspect individual records.

Uninstall

  • Deactivate the venv and remove the project directory, or run pip uninstall pj-bridge inside the venv (if installed as a package).

License

MIT

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