Command Line Conversion (Supplementary)

[ewancook]

Description

Given the enormous amount of work to refactor this repository following #3, the following command-line conversion tool may be useful while v0.1.6 is still under development.

The tool will convert a single float file, provided that a tag file and an output file destination are supplied. Options for row averaging and for altering the precision (decimal places) are available. All tags are present in the converted file.

The tool should be added to the root of the transcriber directory (i.e. where run.py is located) or downloaded as a binary.

Edit: It's worth noting that, due to the version (v.01.5), issue #3 still applies: this tool can only be relied upon when the tags do not change in the middle of the float file.

Download

Platform	File	Build OS	Python Version
Linux	transcribe_utility_v0.1_linux.tar.gz	Ubuntu 18.04.5 LTS	3.6.3
Windows	transcribe_utility_v0.1_windows.zip	Windows 10 (19041)	3.8.2

Example Usage

Python:
./transcribe.py -f "2020 12 14 0000 (Float).DAT" -t  "2020 12 14 0000 (Tagname).DAT" -o converted.csv
./transcribe.py --float-file "2020 12 14 0000 (Float).DAT" --tag-file "2020 12 14 0000 (Tagname).DAT" --output-file converted.csv --precision 5 --average-rows 3

Windows:
.\transcribe.exe -f "2020 12 14 0000 (Float).DAT" -t  "2020 12 14 0000 (Tagname).DAT" -o converted.csv
.\transcribe.exe --float-file "2020 12 14 0000 (Float).DAT" --tag-file "2020 12 14 0000 (Tagname).DAT" --output-file converted.csv --precision 5 --average-rows 3

Linux:
./transcribe -f "2020 12 14 0000 (Float).DAT" -t  "2020 12 14 0000 (Tagname).DAT" -o converted.csv
./transcribe --float-file "2020 12 14 0000 (Float).DAT" --tag-file "2020 12 14 0000 (Tagname).DAT" --output-file converted.csv --precision 5 --average-rows 3

Help

usage: transcribe.py [-h] -f FLOAT_FILE -t TAG_FILE -o OUTPUT_FILE
                     [-p PRECISION] [-a AVERAGE_ROWS]

Convert FactoryTalk DAT Files

optional arguments:
  -h, --help            show this help message and exit
  -f FLOAT_FILE, --float-file FLOAT_FILE
                        Float File [(Float).DAT]
  -t TAG_FILE, --tag-file TAG_FILE
                        Tag File [(Tagname).DAT]
  -o OUTPUT_FILE, --output-file OUTPUT_FILE
                        Output File
  -p PRECISION, --precision PRECISION
                        Precision
  -a AVERAGE_ROWS, --average-rows AVERAGE_ROWS
                        Rows to Average

Source

Please see the code below. It is also linked above (gist.github.com).

#!/usr/bin/env python3
import argparse
from multiprocessing import freeze_support

from transcriber.converter.dbfworker import utils
from transcriber.converter.dbfworker.worker import DBFWorker
from transcriber.dbf.parser import Parser

TAG_LABEL = "Tagname"


def retrieve_tags(tag_file):
    parser = Parser(required_fields=[TAG_LABEL])
    return [r[TAG_LABEL].decode().strip() for r in parser.parse_all(tag_file)]


def run(float_file, tag_file, precision, average_rows):
    try:
        tags = retrieve_tags(tag_file)
        worker = DBFWorker(
            tag_lookup=tags,
            tags=set(tags),
            decimal_places=precision,
            filename=float_file,
            rows_to_average=average_rows,
        )
        print(f"Successfully converted {worker.work()}")
    except Exception as e:
        print(f"Conversion failed ({e})")


if __name__ == "__main__":
    freeze_support()
    parser = argparse.ArgumentParser(
        description="Convert FactoryTalk DAT Files"
    )
    parser.add_argument(
        "-f", "--float-file", required=True, help="Float File [(Float).DAT]"
    )
    parser.add_argument(
        "-t", "--tag-file", required=True, help="Tag File [(Tagname).DAT]"
    )
    parser.add_argument(
        "-o", "--output-file", required=True, help="Output File"
    )
    parser.add_argument(
        "-p", "--precision", help="Precision", default=8, type=int
    )
    parser.add_argument(
        "-a", "--average-rows", help="Rows to Average", default=1, type=int
    )
    args = parser.parse_args()

    utils.transcribed_filename = lambda x: args.output_file
    average_rows = None if args.average_rows < 2 else args.average_rows
    run(args.float_file, args.tag_file, args.precision, average_rows)