orfipy VS reCOGnizer

You can probably use or adapt https://github.com/urmi-21/orfipy. I've never used this but it looks fantastic.

You don't need any specific hardware to run most bioinformatics programs. There is a web application of ORF finder and if you want to run large amounts of analyses you probably want to run them in a Linux environment. Look at Windows Subsystem for Linux if you are a Windows user. You may also be interested in new ORF finders like this one: https://github.com/urmi-21/orfipy

reCOGnizer (https://github.com/iquasere/reCOGnizer) will do that for you. It also outputs the COG categories in a krona plot

What tool are you using for analyzing them? Using something like reCOGnizer (https://github.com/iquasere/reCOGnizer) gives you the bitscores and evalues in a TSV table, next to the matches

Finally, a huge help on developing is having a Continuous Integration/Deployment on the tool. CD refers to the conda suggestion above, as your tool would be readily available in a controlled environment. CI could use the GitHub Actions functionality provided by GitHub. You can see an example here

You may run MOSCA (https://github.com/iquasere/MOSCA), it performs all major steps of metagenomics analysis. It includes that functional classification you are looking for, since with UPIMAPI (https://github.com/iquasere/UPIMAPI) it annotates with UniProt DB as reference, and obtains information including taxonomy, EC numbers, and even those GOs, and reCOGnizer (https://github.com/iquasere/reCOGnizer), which annotates with CDD DB as reference, and obtains orthologous groups information (COG, Pfam, etc).

Prediction of coding sequences takes as input the contigs you obtained, and gives you the translated genes. Besides annotating with the KEGG database, you may also want to annotate with more general purpose databases (e.g. UniProt), as these provide more taxonomies and functional information. MOSCA includes UPIMAPI (https://github.com/iquasere/UPIMAPI) and reCOGnizer (https://github.com/iquasere/reCOGnizer), which annotate genes with reference to UniProt and CDD databases using two different methods, providing complementary information. This is the same methodology used by widely popular tools such as eggNOG-mapper and Prokka, but these use other databases.

Install with mamba instead of conda, no more problems. Or use UPIMAPI (https://github.com/iquasere/UPIMAPI) together with reCOGnizer (https://github.com/iquasere/reCOGnizer), since these tools obtain better results when annotating proteins

I think reCOGnizer is a nice name

reCOGnizer (https://github.com/iquasere/reCOGnizer) can annotate with COGs, and the other databases available at CDD. It obtains all information concerning COGs description and categories, and outputs krona plots and TSV tables in formats easy to analyze. There is also mantis (https://github.com/PedroMTQ/mantis), prokka (https://github.com/tseemann/prokka) and DFAST (https://github.com/nigyta/dfast_core), the latter two work on contigs and the first two are for proteins