Hamradio contest evaluator


To help Romanian hamradio comunity

Actual status

Work in progress

What it can do ?

For the time being will replica YODX HF contest rule set Will be the base core for a new YO international contest


September 2020 -first commit
September 2021 - second commit
2022 :No github push will be committed while a new YO contest will be based on, therefore code secret has to be keep !

Status update

Code review and changes

Core software is about 80% done. It can process about 8100 log files in just 30 minutes. All logs have been taken from CQ WW CW 2021 public website, and I did replicated their contest rules just to test the code.

Unfortunately, no check logs are published there so I miss some log files, but after my compute time, the result is the same as CQ WW within 5 % error margin. It could be a different approach for validate/ invalidate cross checks, could be the penalties within CQ WW which I did not introduce, bottom line is that for  a “not sweat at all” 3 days job, my code does great !

  • Parsing header elements : Done
  • Telegram bot chat added : Done
  • Web page upload validator : Done
  • Hacking protection added : Done
Willingly I started to build this software free of charge for anyone simply coz hamradio aint just me, hamradio is about all of us.Only together can produce more quality and more value for hamradio itself. So,  that being said I would love to see feedbacks for what is going to be universal contest evaluator, even though in this primary form is just a simple project.
After YODX HF 2021  I decided to resume the work even no one will give a shi..t about it 2022 update: this would be the core for new YO international contest
  • Log files can be uploaded via web page
  • Once uploaded, software will validate log file and auto respond with claimed score, computed score .
  • Once validated will get into real time score processor, real time meaning 0.09 seconds for an average 600 qso log file.
  • This average computing is based on single core CPU, will be split to all CPU cores/ threads to be much more faster.
It is pity that ARRL entity list is so garbled and a lot of compute power is wasted to parse that list which is prone to errors. What I am working now is  another code to reparse ARRL list into a more precise one , one that will be auto updated. So far I am testing against an older version of dxcc   embeded in call_to_dxcc

pip3 install cabrillo

So there is a module available into PIP ,  it has it’s own matching 2 QSO’s method

So far I am testing against an older version URI dxcc_uri = “http://www.arrl.org/files/file/DXCC/2019_Current_Deleted(3).txt” embeded in call_to_dxcc