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profile_sector_upstream.Rmd

Source: vignettes/articles/profile_sector_upstream.Rmd
profile_sector_upstream.Rmd

This workflow runs in chunks of the *companies data and caches intermediate results. This saves memory, completes faster, and allows you to resume after interruptions.

Setup 

library(dplyr, warn.conflicts = FALSE)
library(readr, warn.conflicts = FALSE)
library(rappdirs)
library(future)
library(fs)

# Masking `tiltIndicatorAfter::profile*()` to use `chunks`
library(tiltWorkflows)
#> Loading required package: tiltIndicatorAfter
#> Loading required package: tiltToyData
#> 
#> Attaching package: 'tiltWorkflows'
#> The following objects are masked from 'package:tiltIndicatorAfter':
#> 
#>     profile_emissions, profile_emissions_upstream, profile_sector,
#>     profile_sector_upstream

If the parameter chunks is NULL (default) your *companies dataset is automatically chunked to distribute its companies across available cores. This uses your computer resources efficiently but may not be enough. Consider adjusting the chunks parameter manually. Aim to balance memory-usage and speed. A small number of chunks makes each chunk bigger and may overwhelm your memory. A large number of chunks may take longer because of the overhead of caching each chunk.

Parameters 
params
#> $chunks
#> [1] ""
#> 
#> $order
#> [1] "sample"
#> 
#> $cache_dir
#> [1] ""
#> 
#> $input
#> [1] "input"
#> 
#> $output
#> [1] "output"
#> 
#> $europages_companies
#> [1] "europages_companies.csv"
#> 
#> $ecoinvent_activities
#> [1] "ecoinvent_activities.csv"
#> 
#> $ecoinvent_europages
#> [1] "ecoinvent_europages.csv"
#> 
#> $isic
#> [1] "isic.csv"
#> 
#> $sector_profile_upstream_companies
#> [1] "sector_profile_upstream_companies.csv"
#> 
#> $sector_profile_any_scenarios
#> [1] "sector_profile_any_scenarios.csv"
#> 
#> $sector_profile_upstream_products
#> [1] "sector_profile_upstream_products.csv"
#> 
#> $ecoinvent_inputs
#> [1] "ecoinvent_inputs.csv"
options(
  # Determines the number of chunks
  tiltWorkflows.chunks = params$chunks,
  # Determines the order in which the chunks run
  tiltWorkflows.order = params$order,
  # Determines where to store the cache
  tiltWorkflows.cache_dir = params$cache_dir,
  # Read data quietly
  readr.show_col_types = FALSE,
  # Make printed output wider
  width = 500
)

# Enable computing over multiple workers in parallel
plan(multisession)

# Ensure input/ and output/ directories
if (!dir_exists(params$input)) use_toy_input()
if (!dir_exists(params$output)) dir_create(params$output)
Session information 
getwd()
#> [1] "/home/runner/work/tiltWorkflows/tiltWorkflows/vignettes/articles"

availableCores()
#> system 
#>      4

dir_tree(params$input)
#> input
#> ├── ecoinvent_activities.csv
#> ├── ecoinvent_europages.csv
#> ├── ecoinvent_inputs.csv
#> ├── emissions_profile_any_companies.csv
#> ├── emissions_profile_products.csv
#> ├── emissions_profile_upstream_products.csv
#> ├── europages_companies.csv
#> ├── isic.csv
#> ├── sector_profile_any_scenarios.csv
#> ├── sector_profile_companies.csv
#> ├── sector_profile_upstream_companies.csv
#> └── sector_profile_upstream_products.csv

dir_tree(params$output)
#> output
#> ├── emissions_profile_at_company_level.csv
#> ├── emissions_profile_at_product_level.csv
#> ├── emissions_profile_upstream_at_company_level.csv
#> └── emissions_profile_upstream_at_product_level.csv

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.4.1 (2024-06-14)
#>  os       Ubuntu 22.04.4 LTS
#>  system   x86_64, linux-gnu
#>  ui       X11
#>  language en
#>  collate  C.UTF-8
#>  ctype    C.UTF-8
#>  tz       UTC
#>  date     2024-08-30
#>  pandoc   3.1.11 @ /opt/hostedtoolcache/pandoc/3.1.11/x64/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#>  package            * version    date (UTC) lib source
#>  bslib                0.8.0      2024-07-29 [1] RSPM
#>  cachem               1.1.0      2024-05-16 [1] RSPM
#>  cli                  3.6.3      2024-06-21 [1] RSPM
#>  codetools            0.2-20     2024-03-31 [3] CRAN (R 4.4.1)
#>  crayon               1.5.3      2024-06-20 [1] RSPM
#>  dchunkr              0.0.0.9001 2024-08-30 [1] Github (maurolepore/dchunkr@9748350)
#>  desc                 1.4.3      2023-12-10 [1] RSPM
#>  digest               0.6.37     2024-08-19 [1] RSPM
#>  dplyr              * 1.1.4      2023-11-17 [1] RSPM
#>  evaluate             0.24.0     2024-06-10 [1] RSPM
#>  fansi                1.0.6      2023-12-08 [1] RSPM
#>  fastmap              1.2.0      2024-05-15 [1] RSPM
#>  fs                 * 1.6.4      2024-04-25 [1] RSPM
#>  furrr                0.3.1      2022-08-15 [1] RSPM
#>  future             * 1.34.0     2024-07-29 [1] RSPM
#>  generics             0.1.3      2022-07-05 [1] RSPM
#>  globals              0.16.3     2024-03-08 [1] RSPM
#>  glue                 1.7.0      2024-01-09 [1] RSPM
#>  hms                  1.1.3      2023-03-21 [1] RSPM
#>  htmltools            0.5.8.1    2024-04-04 [1] RSPM
#>  htmlwidgets          1.6.4      2023-12-06 [1] RSPM
#>  httpuv               1.6.15     2024-03-26 [1] RSPM
#>  jquerylib            0.1.4      2021-04-26 [1] RSPM
#>  jsonlite             1.8.8      2023-12-04 [1] RSPM
#>  knitr                1.48       2024-07-07 [1] RSPM
#>  later                1.3.2      2023-12-06 [1] RSPM
#>  lifecycle            1.0.4      2023-11-07 [1] RSPM
#>  listenv              0.9.1      2024-01-29 [1] RSPM
#>  magrittr             2.0.3      2022-03-30 [1] RSPM
#>  memoise              2.0.1      2021-11-26 [1] RSPM
#>  mime                 0.12       2021-09-28 [1] RSPM
#>  parallelly           1.38.0     2024-07-27 [1] RSPM
#>  pillar               1.9.0      2023-03-22 [1] RSPM
#>  pkgconfig            2.0.3      2019-09-22 [1] RSPM
#>  pkgdown              2.1.0      2024-07-06 [1] RSPM
#>  promises             1.3.0      2024-04-05 [1] RSPM
#>  purrr                1.0.2      2023-08-10 [1] RSPM
#>  R6                   2.5.1      2021-08-19 [1] RSPM
#>  ragg                 1.3.2      2024-05-15 [1] RSPM
#>  rappdirs           * 0.3.3      2021-01-31 [1] RSPM
#>  Rcpp                 1.0.13     2024-07-17 [1] RSPM
#>  readr              * 2.1.5      2024-01-10 [1] RSPM
#>  rlang                1.1.4      2024-06-04 [1] RSPM
#>  rmarkdown            2.28       2024-08-17 [1] RSPM
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#>  sessioninfo          1.2.2      2021-12-06 [1] RSPM
#>  shiny                1.9.1      2024-08-01 [1] RSPM
#>  stringi              1.8.4      2024-05-06 [1] RSPM
#>  stringr              1.5.1      2023-11-14 [1] RSPM
#>  systemfonts          1.1.0      2024-05-15 [1] RSPM
#>  textshaping          0.4.0      2024-05-24 [1] RSPM
#>  tibble               3.2.1      2023-03-20 [1] RSPM
#>  tidyr                1.3.1      2024-01-24 [1] RSPM
#>  tidyselect           1.2.1      2024-03-11 [1] RSPM
#>  tiltAddCO2           0.0.0.9002 2024-08-30 [1] Github (2DegreesInvesting/tiltAddCO2@e1b399e)
#>  tiltIndicator        0.0.0.9228 2024-08-30 [1] Github (2DegreesInvesting/tiltIndicator@5ac79f8)
#>  tiltIndicatorAfter * 0.0.0.9057 2024-08-30 [1] Github (2DegreesInvesting/tiltIndicatorAfter@b6ee424)
#>  tiltPolish           0.0.0.9006 2024-08-30 [1] Github (2degreesinvesting/tiltPolish@f2811aa)
#>  tiltToyData        * 0.0.0.9204 2024-08-30 [1] Github (2DegreesInvesting/tiltToyData@472b803)
#>  tiltTransitionRisk   0.0.0.9003 2024-08-30 [1] Github (2degreesinvesting/tiltTransitionRisk@181b6c4)
#>  tiltWorkflows      * 0.0.0.9033 2024-08-30 [1] local
#>  tzdb                 0.4.0      2023-05-12 [1] RSPM
#>  utf8                 1.2.4      2023-10-22 [1] RSPM
#>  vctrs                0.6.5      2023-12-01 [1] RSPM
#>  withr                3.0.1      2024-07-31 [1] RSPM
#>  xfun                 0.47       2024-08-17 [1] RSPM
#>  xtable               1.8-4      2019-04-21 [1] RSPM
#>  yaml                 2.3.10     2024-07-26 [1] RSPM
#> 
#>  [1] /home/runner/work/_temp/Library
#>  [2] /opt/R/4.4.1/lib/R/site-library
#>  [3] /opt/R/4.4.1/lib/R/library
#> 
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────

Data

This example defaults to using toy datasets but you may use the parameters of this file to instead use your own data.

europages_companies <- read_csv(path(params$input, params$europages_companies))
ecoinvent_activities <- read_csv(path(params$input, params$ecoinvent_activities))
ecoinvent_europages <- read_csv(path(params$input, params$ecoinvent_europages))
isic <- read_csv(path(params$input, params$isic))

The “upstream” workflows also need this dataset.

ecoinvent_inputs <- read_csv(path(params$input, params$ecoinvent_inputs))

Data specific to this indicator.

sector_profile_upstream_companies <- read_csv(path(params$input, params$sector_profile_upstream_companies))
sector_profile_any_scenarios <- read_csv(path(params$input, params$sector_profile_any_scenarios))
sector_profile_upstream_products <- read_csv(path(params$input, params$sector_profile_upstream_products))

Sector profile upstream

For this TILT indicator, compute results both at product and company level.

sector_profile_upstream <- profile_sector_upstream(
  companies = sector_profile_upstream_companies,
  scenarios = sector_profile_any_scenarios,
  inputs = sector_profile_upstream_products,
  europages_companies = europages_companies,
  ecoinvent_activities = ecoinvent_activities,
  ecoinvent_inputs = ecoinvent_inputs,
  ecoinvent_europages = ecoinvent_europages,
  isic = isic
)
#> Warning: Splitting `companies` into 4 chunks.

Results

Overview and save results at each level.

sector_profile_upstream |>
  unnest_product() |>
  print() |>
  write_csv(path(params$output, "sector_profile_upstream_at_product_level.csv"))
#> # A tibble: 436 × 32
#>    companies_id             company_name     country sector_profile_upstr…¹ reduction_targets scenario  year ep_product matched_activity_name matched_reference_pr…² unit  tilt_sector multi_match matching_certainty matching_certainty_c…³ input_name input_unit input_tilt_sector input_tilt_subsector company_city postcode address main_activity activity_uuid_produc…⁴ input_isic_4digit sector_scenario subsector_scenario ei_input_geography min_headcount max_headcount input_isic_4digit_name ei_geography
#>    <chr>                    <chr>            <chr>   <chr>                              <dbl> <chr>    <dbl> <chr>      <chr>                 <chr>                  <chr> <chr>       <lgl>       <chr>              <chr>                  <chr>      <chr>      <chr>             <chr>                <chr>        <chr>    <chr>   <chr>         <chr>                  <chr>             <chr>           <chr>              <chr>                      <dbl>         <dbl> <chr>                  <chr>       
#>  1 leathery_acornwoodpecker leathery_acornw… germany medium                              0.18 1.5C RPS  2030 exhibitio… market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… düsseldorf   40468    ulmens… wholesaler    76269c17-78d6-420b-99… '4100'            buildings       NA                 tilt_land                      1            10 NA                     tilt_world  
#>  2 leathery_acornwoodpecker leathery_acornw… germany high                                0.98 1.5C RPS  2050 exhibitio… market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… düsseldorf   40468    ulmens… wholesaler    76269c17-78d6-420b-99… '4100'            buildings       NA                 tilt_land                      1            10 NA                     tilt_world  
#>  3 leathery_acornwoodpecker leathery_acornw… germany high                                0.4  NZ 2050   2030 exhibitio… market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… düsseldorf   40468    ulmens… wholesaler    76269c17-78d6-420b-99… '4100'            total           residential        tilt_land                      1            10 NA                     tilt_world  
#>  4 leathery_acornwoodpecker leathery_acornw… germany high                                0.97 NZ 2050   2050 exhibitio… market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… düsseldorf   40468    ulmens… wholesaler    76269c17-78d6-420b-99… '4100'            total           residential        tilt_land                      1            10 NA                     tilt_world  
#>  5 warriorlike_graysquirrel warriorlike_gra… germany medium                              0.18 1.5C RPS  2030 exhibitio… market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… grünwald     82031    bavari… wholesaler    76269c17-78d6-420b-99… '4100'            buildings       NA                 tilt_land                      1            10 NA                     tilt_world  
#>  6 warriorlike_graysquirrel warriorlike_gra… germany high                                0.98 1.5C RPS  2050 exhibitio… market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… grünwald     82031    bavari… wholesaler    76269c17-78d6-420b-99… '4100'            buildings       NA                 tilt_land                      1            10 NA                     tilt_world  
#>  7 warriorlike_graysquirrel warriorlike_gra… germany high                                0.4  NZ 2050   2030 exhibitio… market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… grünwald     82031    bavari… wholesaler    76269c17-78d6-420b-99… '4100'            total           residential        tilt_land                      1            10 NA                     tilt_world  
#>  8 warriorlike_graysquirrel warriorlike_gra… germany high                                0.97 NZ 2050   2050 exhibitio… market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… grünwald     82031    bavari… wholesaler    76269c17-78d6-420b-99… '4100'            total           residential        tilt_land                      1            10 NA                     tilt_world  
#>  9 antimonarchy_canine      NA               NA      medium                              0.18 1.5C RPS  2030 tent       market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… NA           NA       NA      NA            76269c17-78d6-420b-99… '4100'            buildings       NA                 tilt_land                     NA            NA NA                     tilt_world  
#> 10 antimonarchy_canine      NA               NA      high                                0.98 1.5C RPS  2050 tent       market for shed, lar… shed, large, wood, no… m2    constructi… NA          NA                 NA                     shed, lar… m2         construction      construction reside… NA           NA       NA      NA            76269c17-78d6-420b-99… '4100'            buildings       NA                 tilt_land                     NA            NA NA                     tilt_world  
#> # ℹ 426 more rows
#> # ℹ abbreviated names: ¹​sector_profile_upstream, ²​matched_reference_product, ³​matching_certainty_company_average, ⁴​activity_uuid_product_uuid

sector_profile_upstream |>
  unnest_company() |>
  print() |>
  write_csv(path(params$output, "sector_profile_upstream_at_company_level.csv"))
#> # A tibble: 1,152 × 13
#>    companies_id             company_name             country sector_profile_upstream_share sector_profile_upstream scenario  year matching_certainty_company_average company_city postcode address                             main_activity reduction_targets_avg
#>    <chr>                    <chr>                    <chr>                           <dbl> <chr>                   <chr>    <dbl> <chr>                              <chr>        <chr>    <chr>                               <chr>                         <dbl>
#>  1 leathery_acornwoodpecker leathery_acornwoodpecker germany                             0 high                    1.5C RPS  2030 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.18
#>  2 leathery_acornwoodpecker leathery_acornwoodpecker germany                             1 medium                  1.5C RPS  2030 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.18
#>  3 leathery_acornwoodpecker leathery_acornwoodpecker germany                             0 low                     1.5C RPS  2030 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.18
#>  4 leathery_acornwoodpecker leathery_acornwoodpecker germany                             0 NA                      1.5C RPS  2030 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.18
#>  5 leathery_acornwoodpecker leathery_acornwoodpecker germany                             1 high                    1.5C RPS  2050 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.98
#>  6 leathery_acornwoodpecker leathery_acornwoodpecker germany                             0 medium                  1.5C RPS  2050 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.98
#>  7 leathery_acornwoodpecker leathery_acornwoodpecker germany                             0 low                     1.5C RPS  2050 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.98
#>  8 leathery_acornwoodpecker leathery_acornwoodpecker germany                             0 NA                      1.5C RPS  2050 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.98
#>  9 leathery_acornwoodpecker leathery_acornwoodpecker germany                             1 high                    NZ 2050   2030 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.4 
#> 10 leathery_acornwoodpecker leathery_acornwoodpecker germany                             0 medium                  NZ 2050   2030 NA                                 düsseldorf   40468    ulmenstrasse 275 | 40468 düsseldorf wholesaler                     0.4 
#> # ℹ 1,142 more rows

The results at product and company level are now saved in the output/ directory.

# NOTE: If other workflows run before this one, this shows the results of all
params$output |> dir_tree()
#> output
#> ├── emissions_profile_at_company_level.csv
#> ├── emissions_profile_at_product_level.csv
#> ├── emissions_profile_upstream_at_company_level.csv
#> ├── emissions_profile_upstream_at_product_level.csv
#> ├── sector_profile_upstream_at_company_level.csv
#> └── sector_profile_upstream_at_product_level.csv

Cleanup

Here is the cache that allows you to resume after interruptions.

  • The number of files is determined by params$chunks.
# NOTE: If other workflows run before this one, this shows the cache of all
cache_info()
#> # A tibble: 16 × 18
#>    modification_time   path                                                               type         size permissions user   group  device_id hard_links special_device_id  inode block_size blocks flags generation access_time         change_time         birth_time         
#>    <dttm>              <fs::path>                                                         <fct> <fs::bytes> <fs::perms> <chr>  <chr>      <dbl>      <dbl>             <dbl>  <dbl>      <dbl>  <dbl> <int>      <dbl> <dttm>              <dttm>              <dttm>             
#>  1 2024-08-30 23:08:52 /home/runner/.cache/tiltWorkflows/profile_emissions/1.rds          file       186.1K rw-r--r--   runner docker      2065          1                 0 811732       4096    376     0          0 2024-08-30 23:08:53 2024-08-30 23:08:52 2024-08-30 23:08:52
#>  2 2024-08-30 23:08:52 /home/runner/.cache/tiltWorkflows/profile_emissions/2.rds          file       185.5K rw-r--r--   runner docker      2065          1                 0 811733       4096    376     0          0 2024-08-30 23:08:53 2024-08-30 23:08:52 2024-08-30 23:08:52
#>  3 2024-08-30 23:08:53 /home/runner/.cache/tiltWorkflows/profile_emissions/3.rds          file       190.7K rw-r--r--   runner docker      2065          1                 0 811734       4096    384     0          0 2024-08-30 23:08:53 2024-08-30 23:08:53 2024-08-30 23:08:53
#>  4 2024-08-30 23:08:53 /home/runner/.cache/tiltWorkflows/profile_emissions/4.rds          file         191K rw-r--r--   runner docker      2065          1                 0 811735       4096    384     0          0 2024-08-30 23:08:53 2024-08-30 23:08:53 2024-08-30 23:08:53
#>  5 2024-08-30 23:08:54 /home/runner/.cache/tiltWorkflows/profile_emissions_upstream/1.rds file       911.9K rw-r--r--   runner docker      2065          1                 0 811737       4096   1824     0          0 2024-08-30 23:08:55 2024-08-30 23:08:54 2024-08-30 23:08:54
#>  6 2024-08-30 23:08:54 /home/runner/.cache/tiltWorkflows/profile_emissions_upstream/2.rds file       190.9K rw-r--r--   runner docker      2065          1                 0 811738       4096    384     0          0 2024-08-30 23:08:55 2024-08-30 23:08:54 2024-08-30 23:08:54
#>  7 2024-08-30 23:08:55 /home/runner/.cache/tiltWorkflows/profile_emissions_upstream/3.rds file       922.8K rw-r--r--   runner docker      2065          1                 0 811739       4096   1848     0          0 2024-08-30 23:08:55 2024-08-30 23:08:55 2024-08-30 23:08:55
#>  8 2024-08-30 23:08:55 /home/runner/.cache/tiltWorkflows/profile_emissions_upstream/4.rds file       921.3K rw-r--r--   runner docker      2065          1                 0 811740       4096   1848     0          0 2024-08-30 23:08:55 2024-08-30 23:08:55 2024-08-30 23:08:55
#>  9 2024-08-30 23:08:58 /home/runner/.cache/tiltWorkflows/profile_sector/1.rds             file        91.6K rw-r--r--   runner docker      2065          1                 0 811744       4096    184     0          0 2024-08-30 23:08:58 2024-08-30 23:08:58 2024-08-30 23:08:58
#> 10 2024-08-30 23:08:58 /home/runner/.cache/tiltWorkflows/profile_sector/2.rds             file        88.4K rw-r--r--   runner docker      2065          1                 0 811745       4096    184     0          0 2024-08-30 23:08:58 2024-08-30 23:08:58 2024-08-30 23:08:58
#> 11 2024-08-30 23:08:58 /home/runner/.cache/tiltWorkflows/profile_sector/3.rds             file        89.8K rw-r--r--   runner docker      2065          1                 0 811746       4096    184     0          0 2024-08-30 23:08:58 2024-08-30 23:08:58 2024-08-30 23:08:58
#> 12 2024-08-30 23:08:58 /home/runner/.cache/tiltWorkflows/profile_sector/4.rds             file        87.9K rw-r--r--   runner docker      2065          1                 0 811747       4096    176     0          0 2024-08-30 23:08:58 2024-08-30 23:08:58 2024-08-30 23:08:58
#> 13 2024-08-30 23:08:59 /home/runner/.cache/tiltWorkflows/profile_sector_upstream/1.rds    file       100.5K rw-r--r--   runner docker      2065          1                 0 812029       4096    208     0          0 2024-08-30 23:08:59 2024-08-30 23:08:59 2024-08-30 23:08:59
#> 14 2024-08-30 23:08:59 /home/runner/.cache/tiltWorkflows/profile_sector_upstream/2.rds    file       119.8K rw-r--r--   runner docker      2065          1                 0 812030       4096    240     0          0 2024-08-30 23:08:59 2024-08-30 23:08:59 2024-08-30 23:08:59
#> 15 2024-08-30 23:08:59 /home/runner/.cache/tiltWorkflows/profile_sector_upstream/3.rds    file       101.2K rw-r--r--   runner docker      2065          1                 0 812031       4096    208     0          0 2024-08-30 23:08:59 2024-08-30 23:08:59 2024-08-30 23:08:59
#> 16 2024-08-30 23:08:59 /home/runner/.cache/tiltWorkflows/profile_sector_upstream/4.rds    file       135.9K rw-r--r--   runner docker      2065          1                 0 812032       4096    272     0          0 2024-08-30 23:08:59 2024-08-30 23:08:59 2024-08-30 23:08:59

If you want to recompute some result, you must first delete the relevant cache:

library(fs)
library(rappdirs)

dir_delete(user_cache_dir("tiltWorkflows/PROFILE-DIRECTORY-YOU-WANT-TO-DELETE"))

# DANGER: Or delete the entire default cache directory with
cache_delete()