Use jsoup to parse the HTML, normalize every table into a rectangular row-and-column model, then serialize that model with Jackson (JSON), a standards-aware CSV writer, and Apache POI (XLSX). Normalizing once is the key: the same handling for headers, missing cells, rowspan, and colspan can feed all three formats.
What the conversion pipeline should do
A reliable converter has four stages:
- Load HTML from a string, file, or URL with jsoup.
- Select one or more
tableelements and traverse their logical rows inthead,tbody, andtfootorder. - Normalize spans and missing cells into a rectangular matrix with a defined column order.
- Serialize that matrix as JSON, CSV, or XLSX.
Do not write three independent parsers. A single intermediate model prevents differences such as JSON containing six columns while CSV contains five.
Dependencies and project setup
For Maven, add jsoup, Jackson, and Apache POI’s XLSX artifact:
<dependencies>
<dependency>
<groupId>org.jsoup</groupId>
<artifactId>jsoup</artifactId>
<version>1.23.2</version>
</dependency>
<dependency>
<groupId>com.fasterxml.jackson.core</groupId>
<artifactId>jackson-databind</artifactId>
<version>2.20.0</version>
</dependency>
<dependency>
<groupId>org.apache.poi</groupId>
<artifactId>poi-ooxml</artifactId>
<version>5.4.1</version>
</dependency>
</dependencies>The jsoup project currently shows 1.23.2 in its Maven and Gradle examples; check the project before pinning a version because dependencies change. Apache POI’s poi-ooxml component supplies XLSX support.
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A complete Java converter
The following Java 17 example reads a local HTML file, converts the first table (or a CSS-selected table), and writes JSON, CSV, and XLSX. It treats visible text as the cell value and collapses runs of whitespace.
import com.fasterxml.jackson.databind.ObjectMapper;
import org.apache.poi.ss.usermodel.*;
import org.apache.poi.xssf.usermodel.XSSFWorkbook;
import org.jsoup.Jsoup;
import org.jsoup.nodes.Document;
import org.jsoup.nodes.Element;
import org.jsoup.select.Elements;
import java.io.*;
import java.nio.charset.StandardCharsets;
import java.nio.file.*;
import java.util.*;
public class HtmlTableConverter {
record Grid(List<String> headers, List<List<String>> rows, boolean objectJson) {}
public static void main(String[] args) throws Exception {
if (args.length < 2) {
System.err.println("Usage: java HtmlTableConverter input.html output-prefix [css-selector]");
System.exit(2);
}
Document doc = Jsoup.parse(Files.readString(Path.of(args[0]), StandardCharsets.UTF_8));
String selector = args.length > 2 ? args[2] : "table";
Elements tables = doc.select(selector);
if (tables.isEmpty()) throw new IllegalArgumentException("No table matched: " + selector);
Grid grid = normalize(tables.first());
ObjectMapper mapper = new ObjectMapper();
List<Object> json = new ArrayList<>();
if (grid.objectJson()) {
for (List<String> row : grid.rows()) {
Map<String,String> item = new LinkedHashMap<>();
for (int i = 0; i < grid.headers().size(); i++)
item.put(grid.headers().get(i), i < row.size() ? row.get(i) : "");
json.add(item);
}
} else {
json.addAll(grid.rows());
}
mapper.writerWithDefaultPrettyPrinter().writeValue(Path.of(args[1] + ".json").toFile(), json);
writeCsv(grid, Path.of(args[1] + ".csv"));
writeXlsx(grid, Path.of(args[1] + ".xlsx"));
}
static Grid normalize(Element table) {
Elements rows = table.select("> thead > tr, > tbody > tr, > tfoot > tr");
if (rows.isEmpty()) rows = table.select("> tr");
List<List<String>> matrix = new ArrayList<>();
for (int r = 0; r < rows.size(); r++) {
while (matrix.size() <= r) matrix.add(new ArrayList<>());
int col = 0;
for (Element cell : rows.get(r).select("> th, > td")) {
while (col < matrix.get(r).size() && matrix.get(r).get(col) != null) col++;
int colspan = Math.max(1, parseSpan(cell.attr("colspan")));
int rowspan = Math.max(1, parseSpan(cell.attr("rowspan")));
String value = cell.text().replaceAll("\s+", " ").trim();
for (int rr = r; rr < r + rowspan; rr++) {
while (matrix.size() <= rr) matrix.add(new ArrayList<>());
while (matrix.get(rr).size() < col + colspan) matrix.get(rr).add(null);
for (int cc = col; cc < col + colspan; cc++)
if (matrix.get(rr).get(cc) == null) matrix.get(rr).set(cc, value);
}
col += colspan;
}
}
int width = matrix.stream().mapToInt(List::size).max().orElse(0);
for (List<String> row : matrix) while (row.size() < width) row.add("");
if (matrix.isEmpty()) return new Grid(List.of(), List.of(), false);
List<String> candidate = matrix.get(0).stream().map(v -> v == null ? "" : v).toList();
Set<String> unique = new LinkedHashSet<>(candidate);
boolean headersOk = candidate.stream().allMatch(s -> !s.isBlank()) && unique.size() == candidate.size();
if (headersOk) return new Grid(candidate, new ArrayList<>(matrix.subList(1, matrix.size())), true);
return new Grid(List.of(), matrix, false);
}
static int parseSpan(String s) { try { return Integer.parseInt(s); } catch (Exception e) { return 1; } }
static void writeCsv(Grid grid, Path file) throws IOException {
try (BufferedWriter out = Files.newBufferedWriter(file, StandardCharsets.UTF_8)) {
if (grid.objectJson()) writeCsvRow(out, grid.headers());
for (List<String> row : grid.rows()) writeCsvRow(out, row);
}
}
static void writeCsvRow(Writer out, List<String> row) throws IOException {
for (int i = 0; i < row.size(); i++) {
if (i > 0) out.write(',');
String v = row.get(i) == null ? "" : row.get(i);
if (v.indexOf(',') >= 0 || v.indexOf('"') >= 0 || v.indexOf('n') >= 0 || v.indexOf('r') >= 0)
out.write('"' + v.replace(""", """") + '"');
else out.write(v);
}
out.write(System.lineSeparator());
}
static void writeXlsx(Grid grid, Path file) throws IOException {
try (Workbook wb = new XSSFWorkbook(); OutputStream out = Files.newOutputStream(file)) {
Sheet sheet = wb.createSheet("Table");
int r = 0;
if (grid.objectJson()) writeSheetRow(sheet.createRow(r++), grid.headers());
for (List<String> row : grid.rows()) writeSheetRow(sheet.createRow(r++), row);
wb.write(out);
}
}
static void writeSheetRow(Row xrow, List<String> values) {
for (int c = 0; c < values.size(); c++) xrow.createCell(c, CellType.STRING).setCellValue(values.get(c) == null ? "" : values.get(c));
}
}Compile and run it with java HtmlTableConverter page.html export '#orders'. The selector is optional; without it, the first table is used. For a URL, replace Jsoup.parse(Files.readString(...)) with Jsoup.connect(url).get() and set an appropriate timeout.
How headers and JSON shape are decided
Object arrays when headers are trustworthy
If the first meaningful row has non-empty, unique labels, the converter emits an array of objects:
[{"name":"Ada","score":"10"}]Values remain strings. This preserves IDs, leading zeroes, and long numeric-looking values. Convert to numbers or dates only when your application has explicit, validated rules.
Array-of-arrays for ambiguous tables
When headers are absent, duplicated, or structurally ambiguous, emit rows as arrays and preserve source column order:
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[["Ada","10"],["Lin","09"]]That is safer than inventing keys that imply meaning the HTML does not establish. If your API requires object keys, generate stable names such as column_1 and document that policy.
CSV details that prevent broken exports
- Write UTF-8 deliberately, as the example does.
- Quote fields containing commas, quotes, or line breaks.
- Escape an embedded quote by doubling it.
- Decide whether your contract always emits a final line ending; the example does.
- If untrusted values will be opened in spreadsheet software, define a CSV-injection policy for values beginning with
=,+,-, or@(for example, prefixing an apostrophe).
For production pipelines, a standards-aware CSV library can replace the small writer while retaining the same normalized model.
XLSX output and large tables
XSSFWorkbook is straightforward for ordinary workbook sizes and writes modern XLSX files through poi-ooxml. The example creates text cells intentionally, so leading zeroes and identifiers are not silently changed. Add numeric or date cell types only after defining conversion and validation rules.
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For very large exports, use Apache POI’s SXSSFWorkbook, which streams rows with a bounded memory footprint. Dispose of its temporary files after writing, and set a row window appropriate to your workload. Do not assume that streaming removes all costs: styles, very wide tables, and shared strings still affect memory and file size.
Handling real-world HTML
Multiple tables
Expose a CSS selector such as #orders or table.data. You can call normalize for every match and write each result to a separate JSON/CSV file or a separate XLSX sheet. Do not silently merge unrelated tables.
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Row and column spans
The sample expands each rowspan and colspan into a rectangular grid by repeating the cell’s visible text. If your meaning requires blank cells instead, change that policy explicitly; either choice is preferable to accidental column shifts.
Sections, empty cells, and malformed markup
Rows are read from thead, then tbody, then tfoot. Missing cells are filled with empty strings. An empty table becomes an empty dataset. jsoup is designed to create a sensible parse tree even for invalid, tag-soup HTML, but you should still validate that the selected table is the one your contract expects.
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Element.text() returns visible text from links and lists and decodes HTML entities. If you need URLs, list structure, or a data attribute instead, extract that attribute deliberately rather than mixing presentation text and metadata.
Performance, reliability, and cost decisions
- Parse once: keep the normalized matrix in memory when producing several small outputs.
- Stream large XLSX: switch to
SXSSFWorkbookand clean up temporary files. - Bound network loads: set connection and read timeouts when using
Jsoup.connect; treat timeouts and non-success responses as explicit errors. - Measure your data: no universal accuracy or throughput benchmark applies to every table shape. Test representative pages, span patterns, encodings, and row counts in your environment.
- Make failures observable: record the selector, source URL or file, row count, column count, and output paths.
Troubleshooting
“No table matched”
The selector may target a generated class, an iframe, or a table different from the one you inspected. Print the document’s table count, test a broad table selector, and verify that the HTML you loaded actually contains the rows.
Columns shift after a merged cell
Inspect rowspan and colspan. A converter that ignores spans will shift subsequent values. Expand spans into the rectangular matrix, or document a flattening rule and test it with a fixture.
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The first row is not a valid header. Use array-of-arrays JSON, or provide an explicit header mapping rather than silently overwriting duplicate keys.
CSV opens as one column or shows garbled characters
Check the delimiter expected by the target program and confirm the file is UTF-8. Ensure fields containing delimiters, quotes, or newlines are quoted and embedded quotes doubled.
Excel changed an ID or removed leading zeroes
Write the value as a text cell, as the example does. Introduce numeric/date types only with explicit coercion rules.
Out-of-memory errors during XLSX creation
Use SXSSFWorkbook, reduce retained rows, avoid creating unnecessary styles, and process one table at a time.
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FAQ
Frequently Asked Questions
Should I preserve HTML attributes as well as visible text?
Only when your data contract needs them. Keep visible text as the default, then add an explicit attribute-extraction field for links, IDs, or data attributes so presentation and metadata remain distinguishable.
How can I guarantee stable output when a site changes its markup?
Select a stable table identifier, validate expected headers and column count, and fail the job when those checks do not pass instead of exporting a plausible but wrong table.
Can one normalized model support additional formats later?
Yes. Once rows and columns are rectangular and policies are explicit, you can add another writer without changing HTML traversal or span handling.
The Bottom Line
Parse with jsoup, normalize spans and headers once, then reuse that model for Jackson JSON, quoted UTF-8 CSV, and Apache POI XLSX. Explicit policies for ambiguous headers, types, encoding, and large files are what make the exports dependable.
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