[ 
https://issues.apache.org/jira/browse/ARROW-14575?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Dragoș Moldovan-Grünfeld updated ARROW-14575:
---------------------------------------------
    Description: 
{*}Proposed approach{*}:
 * add functionality to allow binding registration with the {{pkg::fun()}} name;
 ** Modify register_binding() to register 2 identical copies for each pkg::fun 
binding, fun and pkg::fun.
 ** Add a binding for the :: operator, which helps with retrieving bindings 
from the function registry.
 ** Add generic unit tests for the pkg::fun functionality.
 * register {{nse_funcs}} requiring indirect mapping
** register each binding with and without the pkg:: prefix
** add / update unit tests for the nse_funcs bindings to include at least one 
pkg::fun() call for each binding
 * register {{use_funcs}} requiring direct mapping (unary and binary bindings)
** register each binding with and without the pkg:: prefix
** add / update unit tests for the nse_funcs bindings to include at least one 
pkg::fun() call for each binding
 * document changes in the _Writing bindings_ documentation
** going forward we should be using pkg::fun when defining a binding, which 
will register 2 copies of the same binding.

{*}Description{*}:
Currently we implement a number of functions from packages like {{lubridate}} 
which work well when called without namespacing (e.g. {{{}year(){}}}), however 
if someone calls {{lubridate::year()}} we get a not-implemented method (e.g. 
{{{}Warning: Expression lubridate::year(time_hour) not supported in Arrow{}}}). 
Is it possible for us to look and see if we have an arrow function that matches 
the function itself.
{code:r}
library(arrow, warn.conflicts = FALSE)
library(dplyr, warn.conflicts = FALSE)

ds <- InMemoryDataset$create(nycflights13::flights)

ds %>% 
  mutate(year = lubridate::year(time_hour)) %>%
  collect()
#> Warning: Expression lubridate::year(time_hour) not supported in Arrow; 
pulling
#> data into R
#> # A tibble: 336,776 × 19
#>     year month   day dep_time sched_dep_time dep_delay arr_time 
sched_arr_time
#>    <dbl> <int> <int>    <int>          <int>     <dbl>    <int>          
<int>
#>  1  2013     1     1      517            515         2      830            
819
#>  2  2013     1     1      533            529         4      850            
830
#>  3  2013     1     1      542            540         2      923            
850
#>  4  2013     1     1      544            545        -1     1004           
1022
#>  5  2013     1     1      554            600        -6      812            
837
#>  6  2013     1     1      554            558        -4      740            
728
#>  7  2013     1     1      555            600        -5      913            
854
#>  8  2013     1     1      557            600        -3      709            
723
#>  9  2013     1     1      557            600        -3      838            
846
#> 10  2013     1     1      558            600        -2      753            
745
#> # … with 336,766 more rows, and 11 more variables: arr_delay <dbl>,
#> #   carrier <chr>, flight <int>, tailnum <chr>, origin <chr>, dest <chr>,
#> #   air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour 
<dttm>

ds %>% 
  mutate(year = year(time_hour)) %>%
  collect()
#> # A tibble: 336,776 × 19
#>     year month   day dep_time sched_dep_time dep_delay arr_time 
sched_arr_time
#>    <int> <int> <int>    <int>          <int>     <dbl>    <int>          
<int>
#>  1  2013     1     1      517            515         2      830            
819
#>  2  2013     1     1      533            529         4      850            
830
#>  3  2013     1     1      542            540         2      923            
850
#>  4  2013     1     1      544            545        -1     1004           
1022
#>  5  2013     1     1      554            600        -6      812            
837
#>  6  2013     1     1      554            558        -4      740            
728
#>  7  2013     1     1      555            600        -5      913            
854
#>  8  2013     1     1      557            600        -3      709            
723
#>  9  2013     1     1      557            600        -3      838            
846
#> 10  2013     1     1      558            600        -2      753            
745
#> # … with 336,766 more rows, and 11 more variables: arr_delay <dbl>,
#> #   carrier <chr>, flight <int>, tailnum <chr>, origin <chr>, dest <chr>,
#> #   air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour 
<dttm>
{code}

  was:
{*}Proposed approach{*}:
 * add functionality to allow binding registration with the {{pkg::fun()}} name;
 ** Modify register_binding() to register 2 identical copies for each pkg::fun 
binding, fun and pkg::fun.
 ** Add a binding for the :: operator, which helps with retrieving bindings 
from the function registry.
 ** Add generic unit tests for the pkg::fun functionality.
 * register {{nse_funcs}} requiring indirect mapping
** register each binding with and without the pkg:: prefix
** add / update unit tests for the nse_funcs bindings to include at least one 
pkg::fun() call for each binding
 * register {{use_funcs}} requiring direct mapping (unary and binary bindings)
** register each binding with and without the pkg:: prefix
** add / update unit tests for the nse_funcs bindings to include at least one 
pkg::fun() call for each binding
 * document changes in the _Writing bindings_ documentation

{*}Description{*}:
Currently we implement a number of functions from packages like {{lubridate}} 
which work well when called without namespacing (e.g. {{{}year(){}}}), however 
if someone calls {{lubridate::year()}} we get a not-implemented method (e.g. 
{{{}Warning: Expression lubridate::year(time_hour) not supported in Arrow{}}}). 
Is it possible for us to look and see if we have an arrow function that matches 
the function itself.
{code:r}
library(arrow, warn.conflicts = FALSE)
library(dplyr, warn.conflicts = FALSE)

ds <- InMemoryDataset$create(nycflights13::flights)

ds %>% 
  mutate(year = lubridate::year(time_hour)) %>%
  collect()
#> Warning: Expression lubridate::year(time_hour) not supported in Arrow; 
pulling
#> data into R
#> # A tibble: 336,776 × 19
#>     year month   day dep_time sched_dep_time dep_delay arr_time 
sched_arr_time
#>    <dbl> <int> <int>    <int>          <int>     <dbl>    <int>          
<int>
#>  1  2013     1     1      517            515         2      830            
819
#>  2  2013     1     1      533            529         4      850            
830
#>  3  2013     1     1      542            540         2      923            
850
#>  4  2013     1     1      544            545        -1     1004           
1022
#>  5  2013     1     1      554            600        -6      812            
837
#>  6  2013     1     1      554            558        -4      740            
728
#>  7  2013     1     1      555            600        -5      913            
854
#>  8  2013     1     1      557            600        -3      709            
723
#>  9  2013     1     1      557            600        -3      838            
846
#> 10  2013     1     1      558            600        -2      753            
745
#> # … with 336,766 more rows, and 11 more variables: arr_delay <dbl>,
#> #   carrier <chr>, flight <int>, tailnum <chr>, origin <chr>, dest <chr>,
#> #   air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour 
<dttm>

ds %>% 
  mutate(year = year(time_hour)) %>%
  collect()
#> # A tibble: 336,776 × 19
#>     year month   day dep_time sched_dep_time dep_delay arr_time 
sched_arr_time
#>    <int> <int> <int>    <int>          <int>     <dbl>    <int>          
<int>
#>  1  2013     1     1      517            515         2      830            
819
#>  2  2013     1     1      533            529         4      850            
830
#>  3  2013     1     1      542            540         2      923            
850
#>  4  2013     1     1      544            545        -1     1004           
1022
#>  5  2013     1     1      554            600        -6      812            
837
#>  6  2013     1     1      554            558        -4      740            
728
#>  7  2013     1     1      555            600        -5      913            
854
#>  8  2013     1     1      557            600        -3      709            
723
#>  9  2013     1     1      557            600        -3      838            
846
#> 10  2013     1     1      558            600        -2      753            
745
#> # … with 336,766 more rows, and 11 more variables: arr_delay <dbl>,
#> #   carrier <chr>, flight <int>, tailnum <chr>, origin <chr>, dest <chr>,
#> #   air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour 
<dttm>
{code}


> [R] Allow functions with {{pkg::}} prefixes
> -------------------------------------------
>
>                 Key: ARROW-14575
>                 URL: https://issues.apache.org/jira/browse/ARROW-14575
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: R
>            Reporter: Jonathan Keane
>            Assignee: Dragoș Moldovan-Grünfeld
>            Priority: Major
>              Labels: pull-request-available
>          Time Spent: 5h 40m
>  Remaining Estimate: 0h
>
> {*}Proposed approach{*}:
>  * add functionality to allow binding registration with the {{pkg::fun()}} 
> name;
>  ** Modify register_binding() to register 2 identical copies for each 
> pkg::fun binding, fun and pkg::fun.
>  ** Add a binding for the :: operator, which helps with retrieving bindings 
> from the function registry.
>  ** Add generic unit tests for the pkg::fun functionality.
>  * register {{nse_funcs}} requiring indirect mapping
> ** register each binding with and without the pkg:: prefix
> ** add / update unit tests for the nse_funcs bindings to include at least one 
> pkg::fun() call for each binding
>  * register {{use_funcs}} requiring direct mapping (unary and binary bindings)
> ** register each binding with and without the pkg:: prefix
> ** add / update unit tests for the nse_funcs bindings to include at least one 
> pkg::fun() call for each binding
>  * document changes in the _Writing bindings_ documentation
> ** going forward we should be using pkg::fun when defining a binding, which 
> will register 2 copies of the same binding.
> {*}Description{*}:
> Currently we implement a number of functions from packages like {{lubridate}} 
> which work well when called without namespacing (e.g. {{{}year(){}}}), 
> however if someone calls {{lubridate::year()}} we get a not-implemented 
> method (e.g. {{{}Warning: Expression lubridate::year(time_hour) not supported 
> in Arrow{}}}). Is it possible for us to look and see if we have an arrow 
> function that matches the function itself.
> {code:r}
> library(arrow, warn.conflicts = FALSE)
> library(dplyr, warn.conflicts = FALSE)
> ds <- InMemoryDataset$create(nycflights13::flights)
> ds %>% 
>   mutate(year = lubridate::year(time_hour)) %>%
>   collect()
> #> Warning: Expression lubridate::year(time_hour) not supported in Arrow; 
> pulling
> #> data into R
> #> # A tibble: 336,776 × 19
> #>     year month   day dep_time sched_dep_time dep_delay arr_time 
> sched_arr_time
> #>    <dbl> <int> <int>    <int>          <int>     <dbl>    <int>          
> <int>
> #>  1  2013     1     1      517            515         2      830            
> 819
> #>  2  2013     1     1      533            529         4      850            
> 830
> #>  3  2013     1     1      542            540         2      923            
> 850
> #>  4  2013     1     1      544            545        -1     1004           
> 1022
> #>  5  2013     1     1      554            600        -6      812            
> 837
> #>  6  2013     1     1      554            558        -4      740            
> 728
> #>  7  2013     1     1      555            600        -5      913            
> 854
> #>  8  2013     1     1      557            600        -3      709            
> 723
> #>  9  2013     1     1      557            600        -3      838            
> 846
> #> 10  2013     1     1      558            600        -2      753            
> 745
> #> # … with 336,766 more rows, and 11 more variables: arr_delay <dbl>,
> #> #   carrier <chr>, flight <int>, tailnum <chr>, origin <chr>, dest <chr>,
> #> #   air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour 
> <dttm>
> ds %>% 
>   mutate(year = year(time_hour)) %>%
>   collect()
> #> # A tibble: 336,776 × 19
> #>     year month   day dep_time sched_dep_time dep_delay arr_time 
> sched_arr_time
> #>    <int> <int> <int>    <int>          <int>     <dbl>    <int>          
> <int>
> #>  1  2013     1     1      517            515         2      830            
> 819
> #>  2  2013     1     1      533            529         4      850            
> 830
> #>  3  2013     1     1      542            540         2      923            
> 850
> #>  4  2013     1     1      544            545        -1     1004           
> 1022
> #>  5  2013     1     1      554            600        -6      812            
> 837
> #>  6  2013     1     1      554            558        -4      740            
> 728
> #>  7  2013     1     1      555            600        -5      913            
> 854
> #>  8  2013     1     1      557            600        -3      709            
> 723
> #>  9  2013     1     1      557            600        -3      838            
> 846
> #> 10  2013     1     1      558            600        -2      753            
> 745
> #> # … with 336,766 more rows, and 11 more variables: arr_delay <dbl>,
> #> #   carrier <chr>, flight <int>, tailnum <chr>, origin <chr>, dest <chr>,
> #> #   air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour 
> <dttm>
> {code}



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