Inspect and strip fields from FIT activity files

fixfit.py

#!/usr/bin/env python3

# This tool operates on CSV files as created (and read) by the FitCSVTool.jar
# tool included in the FIT SDK. Input is always read from stdin, and output is
# written to stdout.
#
# Example usage:
# java -jar FitCSVTool.jar -b original_activity.fit original_activity.csv
# ./fixfit.py detect <original_activity.csv
# ./fixfit.py strip --field=accumulated_power --field=avg_power --field=functional_threshold_power --field=max_power --field=normalized_power --field=power --field=power_zone_high_boundary --field=threshold_power --field=time_in_power_zone <original_activity.csv >fixed_activity.csv
# java -jar FitCSVTool.jar -c fixed_activity.csv fixed_activity.fit
#
# This tool is intended to be fully information-preserving _except_ for the
# fields that are stripped. That means that output files should include _all_
# original metadata, etc. It is currently a blunt instrument because it does not
# attempt to limit stripping to a particular subset of data message _types_,
# just field names as they appear in their original definitions. The result is
# that, if multiple message type definitions happen to have fields of the same
# name, then both such message types will be impacted by this tool.

import argparse
import csv
import itertools
import sys


def main():
    parser = argparse.ArgumentParser("fixfit")
    subparsers = parser.add_subparsers(dest="command", required=True)
    detect_fields_parser = subparsers.add_parser(
        "detect", help="Detect data fields in a FIT file")
    strip_fields_parser = subparsers.add_parser(
        "strip",
        help=
        "Strip specified data fields from a FIT file. Does NOT remove or modify field definitions."
    )
    strip_fields_parser.add_argument(
        "--field",
        default=[],
        action="append",
        help="Remove this field from the output. May be set multiple times.")
    args = parser.parse_args()
    reader = csv.reader(sys.stdin)
    if args.command == "detect":
        detect_fields(reader)
    else:
        writer = csv.writer(sys.stdout)
        strip_fields(reader, writer, args.field)
        sys.stdout.flush()


def is_data_message(record):
    return record[0] == "Data"


def detect_fields(reader):
    fields = set()
    for record in filter(is_data_message, itertools.islice(reader, 1, None)):
        for field_idx in range(3, len(record), 3):
            field = record[field_idx]
            if len(field) > 0:
                fields.add(field)
    for field in sorted(fields):
        print(field)


def strip_fields(reader, writer, fields):

    def scrub_message(record):
        record = record[:]
        for idx in range(3, len(record), 3):
            field = record[idx]
            if len(field) > 0 and field in fields:
                record[idx] = ""
                record[idx + 1] = ""
                record[idx + 2] = ""
        return record

    for record in reader:
        if is_data_message(record):
            writer.writerow(scrub_message(record))
        else:
            writer.writerow(record)


if __name__ == "__main__":
    main()

~LICENSE

MIT License

Copyright (c) 2024 Benjamin Sidhom

Permission is hereby granted, free of charge, to any person obtaining a copy
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SOFTWARE.