No and it never will. You can e.g. assume normality, but it remains an assumption. There exists normality tests, but these are sensitive to number of observations and outliers.
Look at this e.g.:
That doesn't look normal - right?
Well, it is - I created it using this code:
library("tidyverse")
n <- 50
d <- tibble(
s = rnorm(n = n,
mean = 0,
sd = 1),
p = seq(from = 0.001,
to = 0.999,
length.out = n),
x = qnorm(p = p,
mean = 0,
sd = 1),
y = quantile(x = s, probs = p)
)
pl <- d %>%
ggplot(aes(x = x, y = y)) +
geom_point() +
geom_abline(slope = 1,
intercept = 0,
linetype = "dashed") +
theme_minimal()
print(pl)