docs: #84 readme update, revert type back

R/type.R

@@ -62,11 +62,8 @@ xportr_type <- function(.df,
 
   ## Pull out correct metadata
   metadata <- metadata %||%
-    attr(.df, "_xportr.df_metadata_")
-
-  if (is.null(metadata)) {
+    attr(.df, "_xportr.df_metadata_") %||%
     rlang::abort("Metadata must be set with `metadata` or `xportr_metadata()`")
-  }
 
   if (inherits(metadata, "Metacore")) {
     metadata <- metadata$var_spec

README.Rmd

@@ -82,7 +82,7 @@ data sets (≤ 200)
 - Coerces variables to only numeric or character types
 - Display format support for numeric float and date/time values
 - Variables names are ≤ 8 characters.
-- Variable labels are ≤ 200 characters. 
+- Variable labels are ≤ 40 characters. 
 - Data set labels are ≤ 40 characters.
 - Presence of non-ASCII characters in Variable Names, Labels or data set labels.
 
@@ -103,7 +103,7 @@ To do this we will need to do the following:
   - Apply a dataset label 
   - Write out a version 5 xpt file
 
-All of which can be done using a well-defined specification file and the `xportr` package! 
+All of which can be done using a well-defined specification file and the `{xportr}` package! 
 
 First we will start with our `ADSL` dataset created in R.  This example `ADSL` dataset is taken from the [`{admiral}`](https://pharmaverse.github.io/admiral/index.html) package. The script that generates this `ADSL` dataset can be created by using this command `admiral::use_ad_template("adsl")`.  This `ADSL` dataset has 306 observations and 48 variables.
 
@@ -125,20 +125,19 @@ var_spec <- readxl::read_xlsx(spec_path, sheet = "Variables") %>%
   rlang::set_names(tolower)
 ```
 
-Each `xportr_` function has been written in a way to take in a part of the specification file and apply that piece to the dataset. 
+Each `xportr_` function has been written in a way to take in a part of the specification file and apply that piece to the dataset. Setting `verbose = "warn"` will send appropriate warning message to the console. We have suppressed the warning for the sake of brevity.
 
-```{r, message=FALSE, eval=FALSE}
+```{r, warning = FALSE, message=FALSE, eval=TRUE}
 adsl %>%
-  xportr_metadata(var_spec, "ADSL") %>%
-  xportr_type() %>%
-  xportr_length() %>%
-  xportr_label() %>%
-  xportr_order() %>%
-  xportr_format() %>%
+  xportr_type(var_spec, "ADSL", verbose = "warn") %>%
+  xportr_length(var_spec, "ADSL", verbose = "warn") %>%
+  xportr_label(var_spec, "ADSL", verbose = "warn") %>%
+  xportr_order(var_spec, "ADSL", verbose = "warn") %>%
+  xportr_format(var_spec, "ADSL", verbose = "warn") %>%
   xportr_write("adsl.xpt", label = "Subject-Level Analysis Dataset")
 ```
 
-The `xportr_metadata()` function can reduce duplication by setting the variable specification and domain explicitly at the top of a pipeline.
+The `xportr_metadata()` function can reduce duplication by setting the variable specification and domain explicitly at the top of a pipeline. If you would like to use the `verbose` argument, you will need to set in each function call.
 
 ```{r, message=FALSE, eval=FALSE}
 adsl %>%

README.md

@@ -76,7 +76,7 @@ to any validators or data reviewers.
 - Coerces variables to only numeric or character types
 - Display format support for numeric float and date/time values
 - Variables names are ≤ 8 characters.
-- Variable labels are ≤ 200 characters.
+- Variable labels are ≤ 40 characters.
 - Data set labels are ≤ 40 characters.
 - Presence of non-ASCII characters in Variable Names, Labels or data set
   labels.
@@ -99,7 +99,7 @@ To do this we will need to do the following:
 - Write out a version 5 xpt file
 
 All of which can be done using a well-defined specification file and the
-`xportr` package!
+`{xportr}` package!
 
 First we will start with our `ADSL` dataset created in R. This example
 `ADSL` dataset is taken from the
@@ -131,7 +131,24 @@ var_spec <- readxl::read_xlsx(spec_path, sheet = "Variables") %>%
 ```
 
 Each `xportr_` function has been written in a way to take in a part of
-the specification file and apply that piece to the dataset.
+the specification file and apply that piece to the dataset. Setting
+`verbose = "warn"` will send appropriate warning message to the console.
+We have suppressed the warning for the sake of brevity.
+
+``` r
+adsl %>%
+  xportr_type(var_spec, "ADSL", verbose = "warn") %>%
+  xportr_length(var_spec, "ADSL", verbose = "warn") %>%
+  xportr_label(var_spec, "ADSL", verbose = "warn") %>%
+  xportr_order(var_spec, "ADSL", verbose = "warn") %>%
+  xportr_format(var_spec, "ADSL", verbose = "warn") %>%
+  xportr_write("adsl.xpt", label = "Subject-Level Analysis Dataset")
+```
+
+The `xportr_metadata()` function can reduce duplication by setting the
+variable specification and domain explicitly at the top of a pipeline.
+If you would like to use the `verbose` argument, you will need to set in
+each function call.
 
 ``` r
 adsl %>%