[Python] python/pandas equivalent to dplyr 1.0.0 summarize(across())

In R, I find the following very useful when dealing with many variables:

library(dplyr)
dat <- group_by(mtcars, cyl)
summarize(dat, across(c('mpg','disp'), sum), across(c('drat','wt','qsec'), mean))
# A tibble: 3 x 5
cyl disp hp drat wt
<dbl> <dbl> <dbl> <dbl> <dbl>
1 4 1156. 909 4.07 2.29
2 6 1283. 856 3.59 3.12
3 8 4943. 2929 3.23 4.00


Or even better, selecting with pseudo-regex

summarize(dat, across(ends_with('p'), sum), across(ends_with('t'), mean))


In pandas, the equivalent seems to pass variables one-by-one into a dictionary, eg from this gist:

group_agg = df.groupby("group1").agg({
"var1" : ["mean"],
"var2" : ["sum"],
"var3" : ["mean"]
})


Is there a less verbose way to do this operation in pandas, or with some other package?

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