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tab2xml tab2xml website

CRAN status R-CMD-check Codecov test coverage CRAN Downloads

The goal of tab2xml is to convert spreadsheet files (.xlsx or .ods) into structured XML documents using a predefined template. The package processes the spreadsheet data, replacing template tokens with corresponding values, and manages foreign key relationships automatically.

Installation

You can install the released version of tab2xml from CRAN with:

install.packages("tab2xml")

And the development version from GitHub with:

# install.packages("pak")
pak::pak("josesamos/tab2xml")

Example

This example demonstrates how to use tab2xml to convert an Excel or ODS file into an XML file, based on a schema example from the Mondrian Documentation.

library(tab2xml)

# Define file paths
source_xml <- system.file("extdata", "schema_template.xml", package = "tab2xml")
source_xlsx <- system.file("extdata", "schema.xlsx", package = "tab2xml")
temp_file <- tempfile(fileext = ".xml")

Show spreadsheet contents

sheet_names <- readxl::excel_sheets(source_xlsx)
for (sheet in sheet_names) {
  cat("\n#### Sheet:", sheet)
  data <- readxl::read_excel(source_xlsx, sheet = sheet)
  print(knitr::kable(data))
}

Sheet: Cube

cube_pk name table_fk
1 Sales 1

Sheet: Table

table_pk name
1 sales_fact_1997
2 customer
3 time_by_day

Sheet: Dimension

dimension_pk name foreignKey cube_fk
1 Gender customer_id 1
2 Time time_id 1

Sheet: Hierarchy

hierarchy_pk name hasAll allMemberName primaryKey dimension_fk table_fk
1 Gender true allMemberName=“All Genders” customer_id 1 2
2 Time false NA time_id 2 3

Sheet: Level

name column type uniqueMembers hierarchy_fk
Gender gender String true 1
Year the_year Numeric true 2
Quarter quarter Numeric false 2
Month month_of_year Numeric false 2

Sheet: Measure

name column aggregator formatString cube_fk
Unit Sales unit_sales sum #,### 1
Store Sales store_sales sum #,###.## 1
Store Cost store_cost sum #,###.00 1

Sheet: CalculatedMember

calculatedmember_pk name dimension formula cube_fk
1 Profit Measures [Measures].[Store Sales] - [Measures].[Store Cost] 1

Sheet: CalculatedMemberProperty

name value calculatedmember_fk
FORMAT_STRING $#,##0.00 1

Convert spreadsheet to XML

file <- sheet2xml(source_xlsx, source_xml, temp_file, optimize = TRUE)

Check output

library(xml2)
#> Warning: package 'xml2' was built under R version 4.4.3

xml_content <- readLines(file, warn = FALSE)

cat("```xml\n", paste(xml_content, collapse = "\n"), "\n```", sep = "")
<?xml version="1.0" encoding="UTF-8"?>
<Schema>
  <Cube name="Sales">
    <Table name="sales_fact_1997"/>
    <Dimension name="Gender" foreignKey="customer_id">
      <Hierarchy name="Gender" hasAll="true" allMemberName="All Genders" primaryKey="customer_id">
        <Table name="customer"/>
        <Level name="Gender" column="gender" type="String" uniqueMembers="true"/>
      </Hierarchy>
    </Dimension>
    <Dimension name="Time" foreignKey="time_id">
      <Hierarchy name="Time" hasAll="false" primaryKey="time_id">
        <Table name="time_by_day"/>
        <Level name="Year" column="the_year" type="Numeric" uniqueMembers="true"/>
        <Level name="Quarter" column="quarter" type="Numeric" uniqueMembers="false"/>
        <Level name="Month" column="month_of_year" type="Numeric" uniqueMembers="false"/>
      </Hierarchy>
    </Dimension>
    <Measure name="Unit Sales" column="unit_sales" aggregator="sum" formatString="#,###"/>
    <Measure name="Store Sales" column="store_sales" aggregator="sum" formatString="#,###.##"/>
    <Measure name="Store Cost" column="store_cost" aggregator="sum" formatString="#,###.00"/>
    <CalculatedMember name="Profit" dimension="Measures" formula="[Measures].[Store Sales] - [Measures].[Store Cost]">
      <CalculatedMemberProperty name="FORMAT_STRING" value="$#,##0.00"/>
    </CalculatedMember>
  </Cube>
</Schema>

In this way, we can organize and work with the data in tabular form and generate XML documents directly using the provided templates.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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