interrupted promise warning from reframe(broom:tidy)

Hi, thanks again for the excellent package!

Do you know why I get this warning message with feols(), but not with lm() ?

library(dplyr, warn.conflicts = FALSE)
library(fixest)

trade %>% 
  nest_by(Year) %>% 
  mutate(model = list(feols(Euros ~ dist_km | Origin, data = data))) %>% 
  reframe(broom::tidy(model))
#> Warning: There were 9 warnings in `reframe()`.
#> The first warning was:
#> ℹ In argument: `broom::tidy(model)`.
#> ℹ In row 2.
#> Caused by warning:
#> ! restarting interrupted promise evaluation
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 8 remaining warnings.
#> # A tibble: 10 × 6
#>     Year term    estimate std.error statistic  p.value
#>    <dbl> <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#>  1  2007 dist_km  -42260.    10081.     -4.19 0.000904
#>  2  2008 dist_km  -46187.    11033.     -4.19 0.000915
#>  3  2009 dist_km  -43362.    10223.     -4.24 0.000821
#>  4  2010 dist_km  -46795.    11035.     -4.24 0.000823
#>  5  2011 dist_km  -52298.    12220.     -4.28 0.000763
#>  6  2012 dist_km  -53253.    12667.     -4.20 0.000883
#>  7  2013 dist_km  -55766.    13397.     -4.16 0.000958
#>  8  2014 dist_km  -55920.    13551.     -4.13 0.00103 
#>  9  2015 dist_km  -57723.    13970.     -4.13 0.00102 
#> 10  2016 dist_km  -58494.    14546.     -4.02 0.00126

trade %>% 
  nest_by(Year) %>% 
  mutate(model = list(lm(Euros ~ dist_km + as.factor(Origin), data = data))) %>% 
  reframe(broom::tidy(model))
#> # A tibble: 160 × 6
#>     Year term                 estimate std.error statistic  p.value
#>    <dbl> <chr>                   <dbl>     <dbl>     <dbl>    <dbl>
#>  1  2007 (Intercept)         61449779.  7855309.      7.82 6.66e-15
#>  2  2007 dist_km               -42260.     3022.    -14.0  2.37e-43
#>  3  2007 as.factor(Origin)BE 37714454.  9763559.      3.86 1.14e- 4
#>  4  2007 as.factor(Origin)DE 73967731.  9755537.      7.58 4.25e-14
#>  5  2007 as.factor(Origin)DK 17392750.  9790353.      1.78 7.57e- 2
#>  6  2007 as.factor(Origin)ES 72818361.  9934761.      7.33 2.81e-13
#>  7  2007 as.factor(Origin)FI 28691575. 10798670.      2.66 7.92e- 3
#>  8  2007 as.factor(Origin)FR 71717039.  9748046.      7.36 2.29e-13
#>  9  2007 as.factor(Origin)GB 18898109.  9774637.      1.93 5.33e- 2
#> 10  2007 as.factor(Origin)GR 32502186. 10670611.      3.05 2.34e- 3
#> # … with 150 more rows

^{Created on 2023-02-24 with reprex v2.0.2}

I think what's causing the error is how reframe is being called under the hood and how that interacts with how feols objects are being transformed in broom::tidy(). There's no error in broom::tidy, so it must be something else going on (perhaps parallelism in C++ code).

library(dplyr, warn.conflicts = FALSE)
library(fixest)

ests = trade |>
  nest_by(Year) |>
  mutate(model = list(feols(Euros ~ dist_km | Origin, data = data)))

broom::tidy(ests$model[[1]])
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -42260.    10081.     -4.19 0.000904

purrr::map(ests$model, broom::tidy)
#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation

#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation

#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation

#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation

#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation

#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation

#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation

#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation

#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation

#> Warning in eval(x$call$data, x$call_env): restarting interrupted promise
#> evaluation
#> [[1]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -42260.    10081.     -4.19 0.000904
#> 
#> [[2]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -46187.    11033.     -4.19 0.000915
#> 
#> [[3]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -43362.    10223.     -4.24 0.000821
#> 
#> [[4]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -46795.    11035.     -4.24 0.000823
#> 
#> [[5]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -52298.    12220.     -4.28 0.000763
#> 
#> [[6]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -53253.    12667.     -4.20 0.000883
#> 
#> [[7]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -55766.    13397.     -4.16 0.000958
#> 
#> [[8]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic p.value
#>   <chr>      <dbl>     <dbl>     <dbl>   <dbl>
#> 1 dist_km  -55920.    13551.     -4.13 0.00103
#> 
#> [[9]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic p.value
#>   <chr>      <dbl>     <dbl>     <dbl>   <dbl>
#> 1 dist_km  -57723.    13970.     -4.13 0.00102
#> 
#> [[10]]
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic p.value
#>   <chr>      <dbl>     <dbl>     <dbl>   <dbl>
#> 1 dist_km  -58494.    14546.     -4.02 0.00126

I'm not sure exactly what you're doing, but it's probably easier to use the split argument in feols:

ests = feols(Euros ~ dist_km | Origin, data = trade, split = ~ Year)
purrr::map(ests, broom::tidy)
#> $`sample.var: Year; sample: 2007`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -42260.    10081.     -4.19 0.000904
#> 
#> $`sample.var: Year; sample: 2008`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -46187.    11033.     -4.19 0.000915
#> 
#> $`sample.var: Year; sample: 2009`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -43362.    10223.     -4.24 0.000821
#> 
#> $`sample.var: Year; sample: 2010`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -46795.    11035.     -4.24 0.000823
#> 
#> $`sample.var: Year; sample: 2011`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -52298.    12220.     -4.28 0.000763
#> 
#> $`sample.var: Year; sample: 2012`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -53253.    12667.     -4.20 0.000883
#> 
#> $`sample.var: Year; sample: 2013`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic  p.value
#>   <chr>      <dbl>     <dbl>     <dbl>    <dbl>
#> 1 dist_km  -55766.    13397.     -4.16 0.000958
#> 
#> $`sample.var: Year; sample: 2014`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic p.value
#>   <chr>      <dbl>     <dbl>     <dbl>   <dbl>
#> 1 dist_km  -55920.    13551.     -4.13 0.00103
#> 
#> $`sample.var: Year; sample: 2015`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic p.value
#>   <chr>      <dbl>     <dbl>     <dbl>   <dbl>
#> 1 dist_km  -57723.    13970.     -4.13 0.00102
#> 
#> $`sample.var: Year; sample: 2016`
#> # A tibble: 1 × 5
#>   term    estimate std.error statistic p.value
#>   <chr>      <dbl>     <dbl>     <dbl>   <dbl>
#> 1 dist_km  -58494.    14546.     -4.02 0.00126

^{Created on 2023-05-05 with reprex v2.0.2}

lrberge / fixest

interrupted promise warning from reframe(broom:tidy) #392