[Python] pandas or python equivalent of tidyr complete

I have data that looks like this:

library("tidyverse")

df <- tibble(user = c(1, 1, 2, 3, 3, 3), x = c("a", "b", "a", "a", "c", "d"), y = 1)
df

# user x y
# 1 1 a 1
# 2 1 b 1
# 3 2 a 1
# 4 3 a 1
# 5 3 c 1
# 6 3 d 1


Python format:

import pandas as pd
df = pd.DataFrame({'user':[1, 1, 2, 3, 3, 3], 'x':['a', 'b', 'a', 'a', 'c', 'd'], 'y':1})


I'd like to "complete" the data frame so that every user has a record for every possible x with the default y fill set to 0.

This is somewhat trivial in R (tidyverse/tidyr):

df %>%
complete(nesting(user), x = c("a", "b", "c", "d"), fill = list(y = 0))

# user x y
# 1 1 a 1
# 2 1 b 1
# 3 1 c 0
# 4 1 d 0
# 5 2 a 1
# 6 2 b 0
# 7 2 c 0
# 8 2 d 0
# 9 3 a 1
# 10 3 b 0
# 11 3 c 1
# 12 3 d 1


Is there a complete equivalent in pandas / python that will yield the same result?

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