no clue where i was going. found something called dogwood trail so just followed the arrows and tried not to stress the hills.
#running
no clue where i was going. found something called dogwood trail so just followed the arrows and tried not to stress the hills.
#running
# type = bot and optionally # retention = N so that feeds like @tiktok work like they did before, and... Updated some internal metrics in yarnd to be IMO "better", with queue depth, queue time and last processing time for feeds.
#!/bin/sh
# Position the pointer at the center of the dot, then run this script.
sleep 1
start=$(xdotool getmouselocation --shell)
eval $start
r=400
steps=100
down=0
for step in $(seq $((steps + 1)) )
do
# pi = 4 * atan(1)
new_x=$(printf '%s + %s * c(%s / %s * 2 * (4 * a(1)))\n' $X $r $step $steps | bc -l)
new_y=$(printf '%s + %s * s(%s / %s * 2 * (4 * a(1)))\n' $Y $r $step $steps | bc -l)
xte "mousemove ${new_x%%.*} ${new_y%%.*}"
if ! (( down ))
then
xte 'mousedown 1'
down=1
fi
done
xte 'mouseup 1'
xte "mousemove $X $Y"
Interestingly, you can abuse the scoring system (not manually, only with a script). Since the mouse *jumps* to the locations along the circle, you can just use very few steps and still get a great score because every step you make is very accurate – but the result looks funny:
🥴
#!/bin/sh
# Position the pointer at the center of the dot, then run this script.
sleep 1
start=$(xdotool getmouselocation --shell)
eval $start
r=400
steps=100
down=0
for step in $(seq $((steps + 1)) )
do
# pi = 4 * atan(1)
new_x=$(printf '%s + %s * c(%s / %s * 2 * (4 * a(1)))\n' $X $r $step $steps | bc -l)
new_y=$(printf '%s + %s * s(%s / %s * 2 * (4 * a(1)))\n' $Y $r $step $steps | bc -l)
xte "mousemove ${new_x%%.*} ${new_y%%.*}"
if ! (( down ))
then
xte 'mousedown 1'
down=1
fi
done
xte 'mouseup 1'
xte "mousemove $X $Y"
Interestingly, you can abuse the scoring system (not manually, only with a script). Since the mouse *jumps* to the locations along the circle, you can just use very few steps and still get a great score because every step you make is very accurate – but the result looks funny:
🥴
As I recover from yesterday's viral episode (ugh!) I'm getting some distraction playing the wonderful (and often hard for me) #lichess puzzles: https://lichess.org/training
$ bat https://twtxt.net/twt/edgwjcq | jq '.subject'
"(#yarnd)"
hahahahaha 🤣 Does your client allow you to do this or what? 🤔
#LetsMakeChartsFakeAgain
#LetsMakeChartsFakeAgain
#LetsMakeChartsFakeAgain
jenny, tt or any other client where fetches are driven by user interactions of invoking the app. What do we call this type of client? Hmmm 🤔 Then I can tell who uses yarnd because they are "seen" more frequently 🤣
I'll think about doing this too, but I have to do it carefully so as not to cost too much in terms of resources or performance...
> Note: "You should check https://marginalia-search.com/ I bet you'll love it."
- Drift into Failure: From Hunting Broken Components to Understanding Complex Systems by Sidney Dekker (2011)
- Engineering a Safer World by Nancy Leveson (2011)
The former I haven't read. The later I haven't finished reading 😅
The following flags no longer exist:
--max-cache-items
--max-cache-ttl
Instead use
--max-age-days, which controls how much of the cache is pulled back for Timeline, Discover and Mentions views.
- asynchronous evolution
- drift into failure
moved this to today since tomorrow we have to wake up early and drive to TN. half a pizza and two pints sloshing around still felt okay. the pepperoni definitely gave me some additional heartburn though!
#running
moved this to today since tomorrow we have to wake up early and drive to TN. half a pizza and two pints sloshing around still felt okay. the pepperoni definitely gave me some additional heartburn though!
#running