Using Python to analyze and filter adif log files

I’m a Software Engineer by trade. When facing issues with radio log data or software I can write a script or patch to address it.

Jump directly to Python code

Example adif-io Python code

While writing my 2024 retrospective post I wrote some Python code to summarize my QSOs by operating mode (SSB [voice], CW [Morse Code], or digital [FT8]).

I recently set a goal to earn my Straight Key Century Club (SCKCC) Centurion award by logging QSOs with 100 other SKCC members. To apply for the award I need to track and submit my SKCC contacts in a separate digital ledger.

I described my logging workflows in a previous post

I use QRZ’s logger and this poses some issues:

Not every QSO I have is with an SKCC member
No way to filter by comment text in QRZ’s basic logging app

Manually selecting SKCC QSOs for export then import into the SKCC logger is a pain. However, when logging SKCC QSOs I write SKCC# [their ID number] in the comment field. Could I filter by comments containing the text ‘SKCC’ and avoid manually selecting SKCC QSO records?

SKCC specific logging via a custom Python script

My solution was to update my QSO analysis script. I added a new command (./process-adif.py skcc) to check each QSO record for a comment field containing SKCC and write those to a new adi file.

Now, I can log my radio contacts as usual and have the script filter for SKCC QSOs to submit to the club.

You can find my Python adif filtering and analysis scripts at github.com/chrisfarnham/ham-radio-utils. If you want to use my utility script as written or fork it for your own needs, please do so.

I had an itch that Python could scratch

The image below shows my SKCC logging flow.

Example adif-io Python code

Reading and writing ADIF files is easy with the adif-io Python library written by DJ3EI.

Here are some basic examples of adif-io Python code so you can write your own scripts.

Installing the adif-io library

You should be using Python 3. I recommend you create a virtual environment (e.g., with pyenv) to write and manage your scripts and dependencies.

pip install adif-io

Reading an ADIF file with Python

import adif_io

adif = 'qso_logs.adi'
with open(adif, 'r', encoding="ISO-8859-1") as rf:
    content = ''.join(rf.readlines())
    qsos, header = adif_io.read_from_string(content)

Writing an ADIF file with Python

import adif_io

qsos = filter_skcc(qsos_list)
headers = {
    "generated_by": "Source code found at https://github.com/chrisfarnham/ham-radio-utils",
    "description": "Only QSOs with SKCC in comments",
}
headers = adif_io.headers_from_dict(headers)
with open('upated_qso_logs.adi'), 'w',  encoding="ISO-8859-1") as wf:
    wf.writelines(adif_io.headers_to_adif(headers))
    wf.writelines((adif_io.qso_to_adif(q) for q in qsos))

From adif file to dataframe

Dataframes are used like Excel tables in programs to sort, filter and analyze data. Here’s how to turn adif-io records into a polars dataframe for analysis.

pip install polars

import adif_io
import polars as pl

# qsos iterable created earlier, probably by reading in adi file (see above)
qsos = ...
dataframe = pl.DataFrame([{k: v for k, v in q.items()} for q in qsos])

# analyze QSO data using Polars data analysis tools
# Example, count and sort unique call signs to see your top 10 contacts
call_counts = dataframe['CALL'].value_counts().sort('count', descending=True)
top_10_calls = call_counts.head(10)
print("Top 10 CALL entries:")
print(top_10_calls)

Here’s what the dataframe data looks like when printed to the console.

I’d love to learn about your logging utilities and scripts. A good way to respond is through Mastodon, a federated social network. Right now, with the help of my Python scripts, QRZ logging works well enough.

I intend to use something more sophisticated at some point, maybe (WaveLog).