Update french translations

[Dropries]

I added the missing french translations for each CSV file with a local_language_id (i.e. *_names.csv and *_prose.csv), except for files related with Conquest.
The name translations come from the section "In_other_languages" of bulbapedia.

I also fixed a few errors I noticed during the translation.

[Naramsim]

Thanks a lot for all the translations!

[Naramsim]

Did you use a script to gather all the data? Can it be run on other languages as well?

[Naramsim]

It appears that in the file pokemon_species_prose.csv there's a value longer than 1000 chars.

django.db.utils.DataError: value too long for type character varying(1000)

We either need to cut it or lenghten the field

[Naramsim]

Yep, this is 1078 chars.

[pokeapi-machine-user]

A PokeAPI/api-data refresh has started. In ~45 minutes the staging branch of PokeAPI/api-data will be pushed with the new generated data.

The staging branch will be deployed in our staging environment and the entire API will be ready to review.

A Pull Request (master<-staging) will be also created at PokeAPI/api-data and assigned to the PokeAPI Core team to be reviewed. If approved and merged new data will soon be available worldwide at pokeapi.co.

[pokeapi-machine-user]

The updater script has finished its job and has now opened a Pull Request towards PokeAPI/api-data with the updated data.

The Pull Request can be seen deployed in our staging environment when CircleCI deploy will be finished (check the start time of the last build).

[Dropries]

Did you use a script to gather all the data? Can it be run on other languages as well?

Yes, I used a R script (perhaps not optimal with the workflow?) to extract the names of all the .csv files in data/v2/csv with a local_language_id column.
Then, for each of them, I exported a temporary file with all combinations of id and local_language_id (adding the one we are interested in) and translated the missing fields.

Here is my code with an example :

library(dplyr)
library(tidyr)
library(purrr)

files_to_edit <- function(id_language){
  
  # check every .csv in "data/v2/csv 
  map_dfr(list.files("data/v2/csv", pattern = ".csv$", full.names = T), ~{
    file <- .x
    csv <- read.csv(file)
    
    # check if "local_language_id" is in the .csv
    if(!"local_language_id" %in% names(csv)) return(NULL)
    
    # get all combinations of id and id_language 
    full_csv <- crossing(csv %>% select(1),
                           local_language_id = c(unique(csv$local_language_id), id_language)) %>%
      left_join(csv) %>%
      filter(local_language_id == id_language | if_all(3:ncol(.), ~ !is.na(.x))) %>%
      mutate_all(~ifelse(is.na(.), "", .))
    
    # is there new lines (= missing translations) ?
    if(nrow(full_csv) == nrow(csv)) return(NULL)
    
    tibble(diff_rows = nrow(full_csv) - nrow(csv),
           file = sprintf("- [ ] %s (%.0f missing translations)", file, diff_rows))
    
  }) %>%
    # print result sorted by number of missing translations
    arrange(desc(diff_rows)) %>%
    pull(file) %>%
    paste(collapse = "\n") %>%
    cat
}

files_to_edit(2)

file_to_complete <- function(filename, language_id){
  csv <- read.csv(filename, sep = ",")
  
  crossing(csv %>% select(1),
           local_language_id = c(unique(csv$local_language_id), language_id)) %>%
    left_join(csv) %>%
    filter(local_language_id == language_id | if_all(3:ncol(.), ~ !is.na(.x))) %>%
    mutate_all(~ifelse(is.na(.), "", .))
}

file_to_complete("data/v2/csv/pokemon_species_names.csv", 2)

Does this answer your question ?