final codebase with all the fixes and cran compliances

DESCRIPTION

@@ -1,10 +1,17 @@
 Type: Package
 Package: regcensus
-Title: Accessing Data from the RegCensusAPI
+Title: Accessing Data from the 'RegCensusAPI'
 Version: 1.0.0
-Author: QuantGov
-Maintainer: QuantGov <info@quantgov.org>
-Description: Allowing users to access data from the RegCensusAPI. The RegCensusAPI is an API client that connects to the RegData regulatory restrictions data by the Mercatus Center at George Mason University. RegData uses machine learning algorithms to quantify the number of regulatory restrictions in a jurisdiction. You can find out more about RegData from 'QuantGov website' <https://www.quantgov.org>.
+Authors@R: c(
+    person("Jonathan", "Nelson", , "jnelson@mercatus.gmu.edu", 
+            role = c("aut", "cre")),
+    person("Thurston", "Powers", , "tpowers@mercatus.gmu.edu", 
+            role = c("aut")),
+    person("Aayush", "Gadia", , "agadia@mercatus.gmu.edu", 
+            role = c("aut")),
+    person("Mercatus Center", email = "info@quantgov.org",
+            role = c("cph", "fnd")))
+Description: Allowing users to access data from the 'RegCensusAPI'. The 'RegCensusAPI' is an API client that connects to the 'RegData' regulatory restrictions data by the 'Mercatus Center' at 'George Mason University'. 'RegData' uses machine learning algorithms to quantify the number of regulatory restrictions in a jurisdiction. You can find out more about 'RegData' from 'QuantGov website' <https://www.quantgov.org>.
 License: MIT+ file LICENSE
 URL: https://github.com/QuantGov/regcensus-api-client-R
 BugReports: https://github.com/QuantGov/regcensus-api-client-R/issues

R/agency_url.R

@@ -5,7 +5,7 @@
 #' @param keyword search for keyword in agency name
 #' @return url as a string
 #' @examples
-#' agency_url(jurisdiction_id = 38, keyword = "test_word")
+#' \dontrun{agency_url(jurisdiction_id = 38, keyword = "test_word")}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -20,7 +20,7 @@ agency_url <- function(jurisdiction_id, keyword) {
   } else if (!is.null(jurisdiction_id)) {
     url_call <- paste0(url, "/agencies?", "jurisdiction=", jurisdiction_id)
   } else {
-    print("Must include either 'jurisdiction_id' or 'keyword.'")
+    message("Must include either 'jurisdiction_id' or 'keyword.'")
     return()
   }
   return(url_call)

R/get_agencies.R

@@ -6,7 +6,7 @@
 #' @param verbose prints out the url of the API call, default value of 0
 #' @return Returns pandas dataframe with the metadata
 #' @examples
-#' get_agencies(jurisdiction_id = 38, keyword = "test")
+#' \dontrun{get_agencies(jurisdiction_id = 38, keyword = "test")}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -17,7 +17,7 @@
 get_agencies <- function(jurisdiction_id = NULL, keyword = NULL, verbose = 0) {
   url_call <- agency_url(jurisdiction_id, keyword)
   if (verbose) {
-    print(paste0("API call: ", url_call))
+    message(paste0("API call: ", url_call))
   }
   output <- clean_columns(fromJSON(content(GET(url_call), as = "parsed")))
   return(output)

R/get_datafinder.R

@@ -6,7 +6,7 @@
 #' @return Returns dataframe with the series and years available,
 #'          along with the endpoints to access the data
 #' @examples
-#' get_datafinder(jurisdiction = 38)
+#' \dontrun{get_datafinder(jurisdiction = 1)}
 #' @import httr
 #' @import jsonlite
 #' @import stats

R/get_document_values.R

@@ -35,10 +35,10 @@
 #'                default value is 0
 #' @return Returns pandas dataframe with the metadata
 #' @examples
-#' get_document_values(
+#' \dontrun{get_document_values(
 #'   series = 33, jurisdiction = 38,
 #'   year = 2018, label = "111"
-#' )
+#' )}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/get_documentation.R

@@ -5,7 +5,7 @@
 #'          documentation, the source name, source citation,
 #'          source url and documentation.
 #' @examples
-#' get_documentation()
+#' \dontrun{get_documentation()}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/get_documents.R

@@ -9,7 +9,7 @@
 #' @param verbose prints out the url of the API call, default value of 0
 #' @return Returns pandas dataframe with the metadata
 #' @examples
-#' get_documents(jurisdiction_id = 38, date = 2018)
+#' \dontrun{get_documents(jurisdiction_id = 38, date = 2022)}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -20,18 +20,18 @@
 get_documents <- function(document_id = NULL, jurisdiction_id = NULL,
                           date = NULL, document_type = 1, verbose = 0) {
   if (!is.null(document_id)) {
-    message <- paste0("document_id is no longer accessible as of version 1.0.",
-              " Use previous version of API or use jurisdiction_id",
-              " and date combination")
-    print(message)
+    text <- paste0("document_id is no longer accessible as of version 1.0.",
+                      " Use previous version of API or use jurisdiction_id",
+                      " and date combination")
+    message(text)
     return()
   } else if (!is.null(jurisdiction_id) && !is.null(date)) {
     return(get_values(series = 1, jurisdiction = jurisdiction_id,
                       year = date,
                       document_type = document_type,
                       summary = FALSE))
   } else {
-    print("Must include jurisdiction_id and date")
+    message("Must include jurisdiction_id and date")
     return()
   }
 }

R/get_endpoint.R

@@ -11,10 +11,10 @@
 #' @return Returns the endpoint, e.g. '/state-summary' for summary-level state
 #'         data
 #' @examples
-#' get_endpoint(
+#' \dontrun{get_endpoint(
 #'   series = c(28, 33, 36), jurisdiction = 38,
 #'   year = c(1970, 2003, 2004, 2018), document_type = 1
-#' )
+#' )}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/get_industries.R

@@ -7,7 +7,7 @@
 #' @param verbose prints out the url of the API call, default value of 0
 #' @return Returns pandas dataframe with the metadata
 #' @examples
-#' get_industries()
+#' \dontrun{get_industries()}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -19,7 +19,7 @@ get_industries <- function(keyword = NULL, label_level = 3,
                            label_source = NULL, verbose = 0) {
   url_call <- industries_url(keyword, label_level, label_source)
   if (verbose) {
-    print(paste0("API call: ", url_call))
+    message(paste0("API call: ", url_call))
   }
   output <- clean_columns(fromJSON(content(GET(url_call), as = "parsed")))
   return(output)

R/get_jurisdictions.R

@@ -4,7 +4,7 @@
 #' @param verbose prints out the url of the API call, default value of 0
 #' @return Returns pandas dataframe with the metadata
 #' @examples
-#' get_jurisdictions()
+#' \dontrun{get_jurisdictions()}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -15,7 +15,7 @@
 get_jurisdictions <- function(verbose = 0) {
   url_call <- jurisdictions_url()
   if (verbose) {
-    print(paste0("API call: ", url_call))
+    message(paste0("API call: ", url_call))
   }
   output <- clean_columns(fromJSON(content(GET(url_call), as = "parsed")))
   return(output)

R/get_reading_time.R

@@ -36,10 +36,10 @@
 #'                default value is 0
 #' @return Returns pandas dataframe with the metadata
 #' @examples
-#' get_reading_time(
-#'   jurisdiction = 38,
-#'   year = array(c(1970, 2003, 2004, 2018, 2020))
-#' )
+#' \dontrun{get_reading_time(
+#'   jurisdiction = 45,
+#'   year = array(c(2022, 2023))
+#' )}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -55,6 +55,10 @@ get_reading_time <- function(series = 2, jurisdiction, year, document_type = 1,
                              label_source = "NAICS", version = NULL,
                              download = FALSE, page = NULL, date = NULL,
                              verbose = 0) {
+  #for demo example
+  if (jurisdiction == 0) {
+    return(NULL)
+  }
   results <- get_values(
     series, jurisdiction, year, document_type, summary, date_is_range,
     country, agency, cluster, label, industry, filtered, label_level,

R/get_series.R

@@ -4,7 +4,7 @@
 #' @param verbose prints out the url of the API call, default value of 0
 #' @return Returns pandas dataframe with the metadata
 #' @examples
-#' get_series()
+#' \dontrun{get_series()}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -15,7 +15,7 @@
 get_series <- function(verbose = 0) {
   url_call <- series_url()
   if (verbose) {
-    print(paste0("API call: ", url_call))
+    message(paste0("API call: ", url_call))
   }
   output <- clean_columns(fromJSON(content(GET(url_call), as = "parsed")))
   return(output)

R/get_values.R

@@ -36,10 +36,10 @@
 #' @return Returns pandas dataframe with the values and various metadata,
 #'          and returns empty if required parameters are not given
 #' @examples
-#' get_values(
+#' \dontrun{get_values(
 #'   series = array(c(1, 28, 33, 36)), jurisdiction = 38,
 #'   year = array(c(1970, 2003, 2004, 2018, 2020)), country = TRUE
-#' )
+#' )}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -79,7 +79,7 @@ get_values <- function(series, jurisdiction, year, document_type = 1,
     error = function() {
       paste0("No data was found for these parameters.",
              " For this jurisdiction, consider the following: \n")
-      print(as.data.frame(get_datafinder(jurisdiction, document_type)))
+      message(as.data.frame(get_datafinder(jurisdiction, document_type)))
       return()
     }
   )
@@ -100,7 +100,7 @@ get_values <- function(series, jurisdiction, year, document_type = 1,
     # list of available series, and function returns empty.
   } else {
     warning("Valid series ID required. Select from the following list:")
-    print(pretty(list_series()))
+    message(pretty(list_series()))
     return()
   }
 
@@ -115,7 +115,7 @@ get_values <- function(series, jurisdiction, year, document_type = 1,
     # If no appropriate jurisdiction is given, prints warning message
     # jurisdictions, and function returns empty.
     warning("Valid jurisdiction ID required. Select from the following list:")
-    print(pretty(list_jurisdictions()))
+    message(pretty(list_jurisdictions()))
     return()
   }
 
@@ -180,9 +180,9 @@ get_values <- function(series, jurisdiction, year, document_type = 1,
     # list of available dates for the given jurisdiction(s),
     # and function returns empty.
   } else {
-    print("Valid date is required. Select from the following list:")
+    message("Valid date is required. Select from the following list:")
     dates <- list_dates(jurisdiction)
-    print(dates)
+    message(dates)
     return()
   }
 
@@ -223,7 +223,7 @@ get_values <- function(series, jurisdiction, year, document_type = 1,
 
   # Prints the url call if verbosity is flagged
   if (verbose) {
-    cat(paste0("API call: ", gsub(" ", "%20", url_call)))
+    message(paste0("API call: ", gsub(" ", "%20", url_call)))
   }
 
   # Allows user to manually select a page of the output

R/industries_url.R

@@ -6,7 +6,7 @@
 #' @param label_source classification standard (NAICS, BEA, SOC)
 #' @return url as a string
 #' @examples
-#' industries_url("test", 323, "NAICS")
+#' \dontrun{industries_url("test", 323, "NAICS")}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/jurisdictions_url.R

@@ -3,7 +3,7 @@
 #' Gets url call for jurisdictions endpoint.
 #' @return url as a string
 #' @examples
-#' jurisdictions_url()
+#' \dontrun{jurisdictions_url()}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/list_agencies.R

@@ -6,7 +6,7 @@
 #' @param reverse reverses the key-value mapping, default value of FALSE
 #' @return Returns dictionary containing names of agencies and associated IDs
 #' @examples
-#' list_agencies(jurisdiction_id = 38, reverse = TRUE)
+#' \dontrun{list_agencies(jurisdiction_id = 38)}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/list_clusters.R

@@ -4,7 +4,7 @@
 #' @param reverse reverses the key-value mapping, default value of FALSE
 #' @return Returns dictionary containing names of clusters & associated IDs
 #' @examples
-#' list_clusters(reverse = TRUE)
+#' \dontrun{list_clusters()}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/list_dates.R

@@ -5,7 +5,7 @@
 #' @param document_type ID for type of document
 #' @return Returns list of dates available for the jurisdiction
 #' @examples
-#' list_dates(jurisdiction_id = 38)
+#' \dontrun{list_dates(jurisdiction_id = 38)}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/list_document_types.R

@@ -6,7 +6,8 @@
 #' @param verbose prints out the url of the API call
 #' @return Returns dictionary containing names of documenttypes & associated IDs
 #' @examples
-#' list_document_types(jurisdiction_id = 38, reverse = FALSE, verbose = 0)
+#' \dontrun{list_document_types(jurisdiction_id = 65,
+#'          reverse = FALSE, verbose = 0)}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -23,20 +24,20 @@
     url_call <- paste0(url, "/documenttypes")
   }
   if (verbose) {
-    print(paste0("API call: ", url_call))
+    message(paste0("API call: ", url_call))
   }
   response <- fromJSON(content(GET(url_call), as = "parsed"))
   document_types <- response[!is.na(response$document_type), ]
   if (reverse) {
     document_types <- document_types[order(document_types$document_type_id), ]
     document_types <- document_types[
                       !duplicated(document_types$document_type_id), ]
     return(as.list(setNames(document_types$document_type,
                             document_types$document_type_id)))
   } else {
     document_types <- document_types[order(document_types$document_type), ]
     document_types <- document_types[!duplicated(document_types$document_type,
                                        document_types$document_type_id), ]
     return(as.list(setNames(document_types$document_type_id,
                             document_types$document_type)))
   }

R/list_industries.R

@@ -10,7 +10,7 @@
 #' @param reverse reverses the key-value mapping, default value of FALSE
 #' @return Returns dictionary containing names of industries and associated IDs
 #' @examples
-#' list_industries(only_id = TRUE, reverse = FALSE)
+#' \dontrun{list_industries(only_id = TRUE, reverse = FALSE)}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/list_jurisdictions.R

@@ -4,7 +4,7 @@
 #' @param reverse reverses the key-value mapping, default value of FALSE
 #' @return Returns dictionary containing names of jurisdictions & associated IDs
 #' @examples
-#' list_jurisdictions(reverse = TRUE)
+#' \dontrun{list_jurisdictions(reverse = TRUE)}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/list_series.R

@@ -4,7 +4,7 @@
 #' @param reverse reverses the key-value mapping, default value of FALSE
 #' @return Returns dictionary containing names of series and associated IDs
 #' @examples
-#' list_series(reverse = FALSE)
+#' \dontrun{list_series(reverse = FALSE)}
 #' @import jsonlite
 #' @import stringr
 #' @import httr

R/print_error.R

@@ -4,7 +4,7 @@
 #' @param output key-value mapping of the output
 #' @return None
 #' @examples
-#' print_error(list(message = "test"))
+#' \dontrun{print_error(list(message = "test"))}
 #' @import jsonlite
 #' @import stringr
 #' @import httr
@@ -15,10 +15,10 @@
 print_error <- function(output) {
   tryCatch(
     {
-      print(paste0("ERROR: ", output$message))
+      message(paste0("ERROR: ", output$message))
     },
     error = function() {
-      print(paste0("ERROR: ", output$errorMessage))
+      message(paste0("ERROR: ", output$errorMessage))
     }
   )
   return()

R/reading_time.R

@@ -10,7 +10,8 @@
 #' how many words the document has. The function assumes an 8 hour work-day,
 #' a 5 day work-week, and a 50 week work-year.
 #' @examples
-#' reading_time(1200000, workday = 8, workweek = 5, workyear = 50)
+#' \dontrun{reading_time(1200000, workday = 8,
+#'          workweek = 5, workyear = 50)}
 #' @import jsonlite
 #' @import stringr
 #' @import httr