Nommage des chunks + ajout des données ARS 2023 + ajout de user ou role

dev/flat_import_data.Rmd

@@ -63,22 +63,32 @@ tables_list <- tables_list |>
 
 # Import des données de l'ARS
 
-```{r}
+```{r import_data_ars_2022, eval=FALSE}
+
 data_ars_2022 <- collectr::import_xlsx(
   filepath = "T:\\datalab\\SRNP_DEMA_SI_EAU\\NITRATES\\DONNEES_CLIENT\\SOURCES\\ARS\\2023_06\\Nitrates 2022 pour DREAL EPNT4 2023-05-30.xlsx",
   sheet = 1,
   row = 2)
 ```
 
+```{r import_data_ars_2023, eval=FALSE}
+data_ars_2023 <- collectr::import_xlsx(
+  filepath = "T:\\datalab\\SRNP_DEMA_SI_EAU\\NITRATES\\DONNEES_CLIENT\\SOURCES\\ARS\\2024_06\\Nitrates 2023 pour DREAL EPNT4 2024-05-31.xlsx",
+  sheet = 1,
+  row = 2)
+```
+
 ## Première approche : non concluante
 
 ### Vérification de la correspondande de la structure du dataframe avec celle de la table
 
 ```{r development-check_structure_table, eval=FALSE}
-collectr::check_structure_table(connexion,
-                                data_ars_2022, 
-                                "nitrate_data_analyse_ars_test",
-                                "qualite_cours_d_eau")
+check_structure_table(database = "si_eau",
+                                schema = "nitrates",
+                                table = "nitrate_data_analyse_ars_test",
+                                dataframe = data_ars_2023,
+                                role = "admin")
+
 ```
 
 ### Adaptation de la structure
@@ -106,38 +116,48 @@ collectr::insert_into_table(connexion,
 ### Création d'une table pour le nouveau millésime
 
 ```{r create-nitrate_data_ars, eval=FALSE}
-poster_data(data = data_ars_2022, 
-            table = "nitrate_data_ars_2022", 
-            schema = "qualite_cours_d_eau", 
-            db = "si_eau",
-            overwrite = TRUE)
+datalibaba::poster_data(data = data_ars_2022, 
+                        table = "nitrate_data_analyse_ars_2023", 
+                        schema = "nitrates", 
+                        db = "si_eau",
+                        overwrite = TRUE,
+                        user = "admin")
 
+datalibaba::commenter_table(comment = "Analyses Nitrates ARS (2023)",
+                            table = "nitrate_data_analyse_ars_2023",
+                            schema = "nitrates",
+                            db = "si_eau",
+                            user = "admin")
 ```
 
 ### Modification du type des champs si besoin
 
 ```{r modify_column_type, eval=FALSE}
 # Appeler la fonction pour modifier le type de colonne
-collectr::modify_column_type(connexion, 
-                   schema = "qualite_cours_d_eau", 
-                   table_name = "nitrate_data_ars_2022",
+collectr::modify_column_type(database = "si_eau", 
+                   schema = "nitrates", 
+                   table = "nitrate_data_analyse_ars_2023",
                    column_name = "plv_date ", 
-                   column_type = "date")
+                   column_type = "date",
+                   role = "admin")
+
 ```
 
 ### Insertion des données du nouveau millésime en base dans la table globale
 
 ```{r import_and_merge_tables, eval=FALSE}
-import_and_merge_tables(connexion,
-                        source_table = "nitrate_data_ars_2022", 
-                        source_schema = "qualite_cours_d_eau", 
-                        target_table = "nitrate_data_analyse_ars_test", 
-                        target_schema = "qualite_cours_d_eau")
+collectr::import_and_merge_tables(database = "si_eau",
+                                  source_table = "nitrate_data_ars_2023", 
+                                  source_schema = "nitrates", 
+                                  target_table = "nitrate_data_analyse_ars_test", 
+                                  target_schema = "nitrates")
 
 ```
 
 # Import des données Hub'eau ESU
 
+À reprendre avec la fonction correspondante du package [{hubeau}](https://github.com/inrae/hubeau)
+
 ```{r create-nitrate_analyse_esu_2020, eval=FALSE}
 nitrate_analyse_esu_2020 <- get_json_data(code_parametre = "1340",
                       code_region = "52",
@@ -167,14 +187,3 @@ nitrate_analyse_esu_2022 <- get_json_data(code_parametre = "1340",
 # Execute in the console directly
 fusen::inflate(flat_file = "dev/flat_import_data.Rmd", vignette_name = "Import des données")
 ```
-
-
-# Inflate your package
-
-You're one inflate from paper to box.
-Build your package from this very Rmd using `fusen::inflate()`
-
-- Verify your `"DESCRIPTION"` file has been updated
-- Verify your function is in `"R/"` directory
-- Verify your test is in `"tests/testthat/"` directory
-- Verify this Rmd appears in `"vignettes/"` directory