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Basic input of ADIF radio amateur log files.

Project description

This is an ADIF parser in Python.

Actual usage

Main result of parsing: List of QSOs:

  • Each QSO is represented by one Python dict.
  • Keys in that dict are ADIF field names in upper case,
  • value for a key is whatever was found in the ADIF, as a string.

Order of QSOs in the list is same as in ADIF file.

Secondary result of parsing: The ADIF headers. This is returned as a Python dict.

Normally, you'd call adif_io.read_from_file(filename). But you can also provide a string with an ADI-file's content, as follows:

import adif_io

qsos, header =  adif_io.read_from_string(
    "A sample ADIF content for demonstration.\n"
    "<adif_ver:5>3.1.0<eoh>\n"
    
    "<QSO_DATE:8>20190714 <TIME_ON:4>1140<CALL:5>LY0HQ"
    "<MODE:2>CW<BAND:3>40M<RST_SENT:3>599<RST_RCVD:3>599"
    "<STX_STRING:2>28<SRX_STRING:4>LRMD<EOR>\n"

    "<QSO_DATE:8>20190714<TIME_ON:4>1130<CALL:5>SE9HQ<MODE:2>CW<FREQ:1>7"
    "<BAND:3>40M<RST_SENT:3>599<RST_RCVD:3>599"
    "<SRX_STRING:3>SSA<DXCC:3>284<EOR>")

print("QSOs: {}\nADIF Header: {}".format(qsos, header))

This will print out

QSOs: [{'RST_SENT': '599', 'CALL': 'LY0HQ', 'MODE': 'CW', 'RST_RCVD': '599', 'QSO_DATE': '20190714', 'TIME_ON': '1140', 'BAND': '40M', 'STX_STRING': '28', 'SRX_STRING': 'LRMD'}, {'DXCC': '284', 'RST_SENT': '599', 'CALL': 'SE9HQ', 'MODE': 'CW', 'RST_RCVD': '599', 'BAND': '40M', 'FREQ': '7', 'QSO_DATE': '20190714', 'TIME_ON': '1130', 'SRX_STRING': 'SSA'}]
ADIF Header: {'ADIF_VER': '3.1.0'}

Time on and time off

Given one qso dict, you can also have the QSO's start time calculated as a Python datetime.datetime value:

adif_io.time_on(qsos[0])

If your QSO data also includes TIME_OFF fields (and, ideally, though not required, QSO_DATE_OFF), this will also work:

adif_io.time_off(qsos[0])

Geographic coordinates - to some degree

ADIF uses a somewhat peculiar 11 character XDDD MM.MMM format to code geographic coordinates (fields LAT or LON). The more common format these days are simple floats that code degrees. You can convert from one to the other:

adif_io.degrees_from_location("N052 26.592") # Result: 52.4432
adif_io.location_from_degrees(52.4432, True) # Result: "N052 26.592"

The additional bool argument of location_from_degrees should be True for latitudes (N / S) and False for longitudes (E / W).

ADIF version

There is little ADIF-version-specific here. (Everything should work with ADI-files of ADIF version 3.1.3, if you want to nail it.)

Not supported: ADIF data types.

This parser knows nothing about ADIF data types or enumerations. Everything is a string. So in that sense, this parser is fairly simple.

But it does correcly handle things like:

<notes:66>In this QSO, we discussed ADIF and in particular the <eor> marker.

So, in that sense, this parser is somewhat sophisticated.

Only ADI.

This parser only handles ADI files. It knows nothing of the ADX file format.

For now: input only

There may be an ADIF output facility some time later.

Sample code

Here is some sample code:

import adif_io

qsos_raw, adif_header = adif_io.read_from_file("log.adi")

# The QSOs are probably sorted by QSO time already, but make sure:
for qso in qsos_raw:
    qso["t"] = adif_io.time_on(qso)
qsos_raw_sorted = sorted(qsos_raw, key = lambda qso: qso["t"])

Pandas / Jupyter users may want to add import pandas as pd up above and continue like this:

qsos = pd.DataFrame(qsos_raw_sorted)
qsos.info()

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