# ⌨️ [Dygma Defy](https://dygma.com/pages/defy) w/ [Kailh speed copper switches]([https://www.kailh.net/products/kailh-speed-switch-set?variant=43775890555122](https://dygma.com/products/switches?variant=43658510270702)) and [dashed keys](https://dygma.com/products/keycaps?variant=43658946314478) The [reasoning behind my choice of keyboard](https://snarky.ca/the-many-shapes-and-sizes-of-keyboards/). # Layout - I'm using [Colemak Mod-DH](https://colemakmods.github.io/mod-dh/) for alpha keys - Motivation is ergonomics - Choice based on perceived popularity (alt keyboard layouts are all so much better than QWERTY that the benefits between them is miniscule; [validated for myself](https://github.com/brettcannon/defy-layout-scorer)) # Alternatives - Traditional - [Raise 2](https://dygma.com/pages/dygma-raise-2) - Columnar - [Moonlander](https://www.zsa.io/moonlander) - Concave - [Advantage 360 Pro](https://kinesis-ergo.com/shop/adv360pro/) # Symbol frequency | Python | Rust | Gleam | | ------ | ---- | ----- | | _ | _ | / | | . | / | ) | | ( | : | ( | | ) | ( | , | | , | ) | " | | ' | , | . | | " | . | _ | | = | " | `` | | : | = | = | | - | { | > | | # | } | - | | \ | ; | : | | [ | ? | [ | | ] | - | { | | > | ` | } | | * | [ | ] | | / | ] | # | | { | # | < | | } | < | \| | | + | ! | \ | | 2x | 1.5x | 1.0x | | ----- | ---- | ----- | | ( | ( | ==)== | | ) | ) | ==(== | | _ | _ | _ | | , | , | , | | . | . | . | | " | " | " | | : | : | : | | = | = | = | | ' | ' | ==`== | | - | - | ==>== | | > | > | =='== | | ` | ` | ==-== | | ==#== | { | { | | ==[== | } | } | | ==]== | [ | [ | | =={== | ] | ] | | ==}== | # | # | | ; | ; | ; | | ==\== | < | < | | < | \ | \ | 1. ( 2. ) 3. \_/- 4. : 5. =/+ 6. \[/{ 7. ]/} 8. # 9. \` 10. \ ### 2x multiplier ``` Symbol Importance Ranking (Python multiplier: 2.0) ================================================================================ 1. '(' - Total: 6.7370 2. ')' - Total: 6.7360 3. '_' - Total: 6.6910 4. ',' - Total: 5.9660 5. '.' - Total: 5.6040 6. '"' - Total: 3.8880 7. ':' - Total: 3.3460 8. '=' - Total: 2.9150 9. ''' - Total: 2.5420 10. '0' - Total: 2.0410 11. '1' - Total: 1.8620 12. '-' - Total: 1.7170 13. '>' - Total: 1.5290 14. '`' - Total: 1.4270 15. '2' - Total: 1.3920 16. '#' - Total: 1.2460 17. '[' - Total: 1.2230 18. ']' - Total: 1.2180 19. '{' - Total: 1.1800 20. '}' - Total: 1.1800 21. '3' - Total: 0.8040 22. '4' - Total: 0.6480 23. ';' - Total: 0.5960 24. '\\' - Total: 0.5850 25. '<' - Total: 0.5580 26. '5' - Total: 0.5320 27. '6' - Total: 0.5230 28. '8' - Total: 0.4530 29. '/' - Total: 0.4320 30. '*' - Total: 0.3530 31. '|' - Total: 0.3030 32. '9' - Total: 0.2860 33. '!' - Total: 0.2800 34. '7' - Total: 0.2680 35. '&' - Total: 0.2540 36. '+' - Total: 0.2110 37. '@' - Total: 0.1810 38. '%' - Total: 0.1210 39. '?' - Total: 0.0910 40. '^' - Total: 0.0650 41. ' - Total: 0.0600 42. '~' - Total: 0.0580 ``` ### 1.5x multiplier ``` Symbol Importance Ranking (Python multiplier: 1.5) ================================================================================ 1. '(' - Total: 5.9570 2. ')' - Total: 5.9565 3. '_' - Total: 5.8435 4. ',' - Total: 5.2955 5. '.' - Total: 4.8090 6. '"' - Total: 3.4860 7. ':' - Total: 2.9925 8. '=' - Total: 2.5490 9. ''' - Total: 1.9625 10. '0' - Total: 1.7455 11. '1' - Total: 1.6725 12. '-' - Total: 1.5370 13. '>' - Total: 1.4570 14. '`' - Total: 1.4180 15. '2' - Total: 1.2545 16. '{' - Total: 1.1430 17. '}' - Total: 1.1430 18. '[' - Total: 1.1210 19. ']' - Total: 1.1165 20. '#' - Total: 0.9345 21. '3' - Total: 0.7300 22. '4' - Total: 0.5855 23. ';' - Total: 0.5815 24. '<' - Total: 0.5345 25. '\\' - Total: 0.4805 26. '6' - Total: 0.4790 27. '5' - Total: 0.4770 28. '8' - Total: 0.4080 29. '|' - Total: 0.2915 30. '*' - Total: 0.2885 31. '!' - Total: 0.2700 32. '&' - Total: 0.2500 33. '9' - Total: 0.2470 34. '/' - Total: 0.2430 35. '7' - Total: 0.2365 36. '+' - Total: 0.1755 37. '@' - Total: 0.1650 38. '%' - Total: 0.0955 39. '?' - Total: 0.0810 40. '^' - Total: 0.0610 41. ' - Total: 0.0575 42. '~' - Total: 0.0550 ``` ### 1.0x multiplier ``` Symbol Importance Ranking (Python multiplier: 1.0) ================================================================================ 1. ')' - Total: 5.1770 2. '(' - Total: 5.1770 3. '_' - Total: 4.9960 4. ',' - Total: 4.6250 5. '.' - Total: 4.0140 6. '"' - Total: 3.0840 7. ':' - Total: 2.6390 8. '=' - Total: 2.1830 9. '1' - Total: 1.4830 10. '0' - Total: 1.4500 11. '`' - Total: 1.4090 12. '>' - Total: 1.3850 13. ''' - Total: 1.3830 14. '-' - Total: 1.3570 15. '2' - Total: 1.1170 16. '{' - Total: 1.1060 17. '}' - Total: 1.1060 18. '[' - Total: 1.0190 19. ']' - Total: 1.0150 20. '3' - Total: 0.6560 21. '#' - Total: 0.6230 22. ';' - Total: 0.5670 23. '4' - Total: 0.5230 24. '<' - Total: 0.5110 25. '6' - Total: 0.4350 26. '5' - Total: 0.4220 27. '\\' - Total: 0.3760 28. '8' - Total: 0.3630 29. '|' - Total: 0.2800 30. '!' - Total: 0.2600 31. '&' - Total: 0.2460 32. '*' - Total: 0.2240 33. '9' - Total: 0.2080 34. '7' - Total: 0.2050 35. '@' - Total: 0.1490 36. '+' - Total: 0.1400 37. '/' - Total: 0.1080 38. '?' - Total: 0.0710 39. '%' - Total: 0.0700 40. '^' - Total: 0.0570 41. ' - Total: 0.0550 42. '~' - Total: 0.0520 ```