Remedies if code takes too long, never gives resuluts

My data relates if activities from people are completed or not and affected by sunshine - completion is the outcome variable and sunshine would be the explanatory variable; this is a simplified version.

 df <-  people = c(1,1,1,2,2,3,3,4,4,5,5),
        activity = c(1,1,1,2,2,3,4,5,5,6,6),
        completion = c(0,0,1,0,1,1,1,0,1,0,1),
        sunshine = c(1,2,3,4,5,4,6,2,4,8,4)

so far I've use this code for the cloglog:

model<- as.formula("completion ~  sunshine")
clog_full = glm(model,data=df,family = binomial(link = cloglog))
summary(clog_full)


> using package glmmML
 model_re<- as.formula("completion ~  sunshine")
    > clog_re = glmmML(model_re,cluster = people, data= df,family =
    > binomial(link = cloglog)) summary(clog_re)
> 
> using package lme4
> 
> model_re1<- as.formula("completion ~  (1|people) + sunshine") clog_re1
> = glmer(model_re1, data=df,family = binomial(link = cloglog)) summary(clog_re1) summ(clog_re1, exp = TRUE)