Ods

ODS creation, editing, and analysis

Overview

An .ods file is an OpenDocument ZIP package for spreadsheets. Important package files:

• mimetype - should be the first ZIP entry and stored uncompressed as application/vnd.oasis.opendocument.spreadsheet
• content.xml - sheets, rows, cells, formulas, charts, and most content
• styles.xml - cell, table, page, and number styles
• meta.xml - document metadata
• settings.xml - application settings
• META-INF/manifest.xml - package manifest

Quick Reference

Tool Checks

Before starting a real ODS task, check available tools:

python3 -c "import pandas, odf; print('pandas and odfpy available')"

Resolve the LibreOffice command as described in docs/soffice-resolver.md.

Use the bundled workspace Python when normal python3 lacks pandas or other spreadsheet libraries.

Reading Data

When pandas and odfpy are available:

import pandas as pd

sheets = pd.read_excel("input.ods", sheet_name=None, engine="odf")
for name, df in sheets.items():
    print(name, df.shape)

When the ODF engine is unavailable, prefer LibreOffice conversion:

# Resolve SOFFICE as shown in Tool Checks.
"$SOFFICE" --headless --convert-to xlsx input.ods --outdir converted

Then inspect the resulting XLSX with normal spreadsheet tooling.

For raw package inspection:

python -m zipfile -e input.ods unpacked_ods

Cells live in content.xml under table:table, table:table-row, and table:table-cell.

Bundled scripts for common inspection tasks:

python scripts/extract_sheets.py input.ods
python scripts/extract_sheets.py input.ods --json
python scripts/extract_formulas.py input.ods
python scripts/inspect_package.py input.ods

For the full script reference, see docs/script-reference.md.

content.xml Structure

An ODS workbook normally stores sheets in content.xml under:

office:document-content
  office:body
    office:spreadsheet
      table:table
        table:table-row
          table:table-cell
            text:p

Important spreadsheet elements and attributes:

• table:table - one sheet; table:name is the sheet name
• table:table-row - row; may use table:number-rows-repeated
• table:table-cell - cell; may use table:number-columns-repeated
• office:value-type - string, float, percentage, currency, date, time, boolean
• office:value, office:date-value, office:time-value, office:boolean-value - typed stored values
• table:formula - formula, commonly with an of:= prefix
• text:p - displayed text inside the cell
• table:covered-table-cell - merged-cell covered area
• table:named-expressions, table:named-range - named ranges when present

ODS often compresses empty or repeated cells/rows. Always expand table:number-columns-repeated and table:number-rows-repeated when mapping to A1 addresses, and preserve or intentionally rewrite them when saving.

Creating ODS Files

ODS is an XML package and can be generated directly. Do not default to XLSX as an intermediate when the deliverable is natively ODS.

Choose the creation path by risk:

Direct ODS XML Generation

Use this for straightforward sheet exports, data tables, and simple formulas:

python scripts/create_minimal_ods.py workbook.json output.ods

Keep the first generated version small: sheets, rows, typed cells, formulas, simple styles. Add charts, named ranges, print areas, and protection only when needed.

Template-First ODS

Use this for styled reports, financial models, or workbooks with formulas/formatting that users expect to keep.

1. Extract the template.
2. Inspect sheets, styles, formulas, named ranges, and repeated cells.
3. Edit targeted cells by sheet and A1 address.
4. Preserve formulas as formulas.
5. Repack and run recalc/data QA.

Conversion Fallback

Use pandas/LibreOffice conversion when the source already exists in another tabular format:

import pandas as pd

with pd.ExcelWriter("output.ods", engine="odf") as writer:
    df.to_excel(writer, sheet_name="Data", index=False)

For XLSX/CSV interoperability:

# Resolve SOFFICE as shown in Tool Checks.
"$SOFFICE" --headless --convert-to ods workbook.xlsx --outdir out

Treat conversion as lossy until QA proves otherwise. Verify formulas, date/number formats, charts, sheet names, and repeated/merged cells.

Themes

create_minimal_ods.py accepts --theme NAME — a curated colour palette and font pairing. For a workbook this is a light touch: the first row of each sheet gets a themed header cell style, and a table-cell default style applies the body font. Five themes:

python scripts/create_minimal_ods.py workbook.json out.ods --theme corporate-blue

Without --theme the workbook is unstyled, exactly as before. Themes name fonts as stacks with a Liberation fallback so a themed sheet renders even where the first-choice font is absent.

Bundled Scripts

For creation and editing scripts, see docs/script-reference.md. All scripts use the Python standard library and are invoked as:

python scripts/<script_name>.py [args]

Editing Existing ODS Files

For data-only updates, load sheets into DataFrames, modify, and write a new ODS. Warn the user if this will not preserve complex formatting, formulas, charts, or macros.

For template-preserving edits:

1. Extract the package.
2. Parse content.xml and styles.xml with an XML parser.
3. Preserve table names, repeated row/cell attributes, style names, and formula attributes.
4. Update META-INF/manifest.xml when adding or removing embedded objects.
5. Repack with mimetype first and uncompressed.

Repack pattern:

cd unpacked_ods
zip -0 -X ../output.ods mimetype
zip -r -X ../output.ods . -x mimetype

Named Ranges, Data Validation, and Charts

For workbook semantics beyond plain cells, v0.6+ provides direct ODF-native helpers:

# Named range (cell-range alias usable in formulas):
python scripts/add_named_range.py wb.ods --name Sales \
    --range 'Sheet1.B2:B100' -o wb-nr.ods

# Named expression (formula or constant alias):
python scripts/add_named_range.py wb.ods --name TaxRate \
    --expression '0.19' -o wb-nr.ods

# Dropdown list:
python scripts/add_data_validation.py wb.ods --name months --type list \
    --values 'Jan,Feb,Mar,Apr' --apply 'Sheet1.A2:A100' -o wb-val.ods

# Numeric constraint:
python scripts/add_data_validation.py wb.ods --name positive --type number \
    --condition 'value() > 0' --apply 'Sheet1.B2:B100' -o wb-val.ods

# Bar chart embedded into a cell:
python scripts/add_chart.py wb.ods --type bar \
    --data 'Sheet1.A1:B10' --title 'Q1 Sales' \
    --cell 'Sheet1.D1' -o wb-chart.ods

# Inspect:
python scripts/list_named_ranges.py wb.ods --json
python scripts/list_charts.py wb.ods --json

Chart types: bar, line, pie, scatter. Charts are embedded as LibreOffice-native Object N/ sub-packages with the application/vnd.oasis.opendocument.chart MIME type. LibreOffice renders them when the file is opened or converted to PDF.

The validator (validate_refs.py) catches dangling named-range sheet targets, dangling content-validation references, and missing chart object package targets.

Conditional Formatting and Pivot Tables

add_conditional_format.py highlights cells that meet a condition; add_pivot_table.py computes a pivot and writes both the result grid and a refreshable pivot definition.

# Conditional formatting — highlight cells by value or formula:
python scripts/add_conditional_format.py wb.ods --range 'Data.B2:B100' \
    --condition 'value > 100' --background '#C8E6C9' --text-color '#1B5E20' -o cf.ods
python scripts/add_conditional_format.py cf.ods --range 'Data.B2:B100' \
    --condition 'value < 50' --background '#FFCDD2' --bold -o cf.ods   # rules stack

# Pivot table — group, aggregate, and write the result grid:
python scripts/add_pivot_table.py wb.ods --source 'Data.A1:D100' \
    --rows Region,Product --columns Quarter --data Revenue \
    --function sum --target 'Pivot.A1' -o pv.ods
python scripts/list_pivot_tables.py pv.ods --json

Conditions: value > N, value < N, value >= N, value <= N, value = N, value != N, value between A B, value not-between A B, and formula:EXPR (any ODF formula). Formatting flags: --background, --text-color, --bold, --italic. Repeating the command on the same --range stacks another rule (first match wins).

Each conditional-formatting rule is written twice: as a calcext:conditional-format (the form LibreOffice renders) and as an ODF-core style:map (for other ODF consumers). The calcext namespace is a documented LibreOffice extension that ODF permits as foreign content; validate_refs.py --strict excludes it from the OASIS core-schema check and reports it as a warning rather than an error.

Pivot tables aggregate with sum, count, average, min, or max. --rows takes one or more comma-separated fields (nested grouping); --columns is an optional single field; --target names the top-left output cell and its sheet is created if missing. The pivot is computed in Python and the grid written into the target range, so LibreOffice shows it immediately; a matching ODF-core table:data-pilot-table is written too, so LibreOffice can refresh it.

validate_refs.py also catches dangling style:map style references and pivot tables whose source or target range names an unknown sheet.

Format Conversion (Excel: XLSX/XLS)

For one-shot conversion between ODS and Microsoft Excel formats, convert.py wraps soffice --headless --convert-to with an isolated temp profile:

# ODS → XLSX:
python scripts/convert.py book.ods --to xlsx --outdir qa

# XLSX → ODS (the bridge: edit an Excel file with our skills, then export back):
python scripts/convert.py source.xlsx --to ods --outdir qa
python scripts/replace_cells.py qa/source.ods --cell "Sheet1.A1=Updated" -o edited.ods
python scripts/convert.py edited.ods --to xlsx --outdir qa

# Legacy MS Excel 97-2003 (.xls):
python scripts/convert.py book.ods --to xls --outdir qa
python scripts/convert.py legacy.xls --to ods --outdir qa

Fidelity caveat: soffice handles cell values, basic formatting, and most formulas well. Macros (VBA), advanced pivot-table options, conditional- formatting graphical variants (data bars, icon sets), and some chart styles can be lost or rendered differently on round-trip. Always inspect the output before relying on it.

For text documents, use the odt skill's convert.py (ODT ↔ DOCX/DOC); for presentations, the odp skill's convert.py (ODP ↔ PPTX/PPT). The script enforces format families — cross-family conversions are rejected with a clear hint.

Formula and Data Rules

• Preserve formulas as formulas. Do not replace formulas with hardcoded calculated values unless the user explicitly asks.
• ODS formulas commonly appear in attributes such as table:formula, often with an of:= prefix.
• Keep value metadata aligned with displayed text: office:value-type, office:value, office:date-value, office:time-value, and percentage/currency attributes matter.
• Watch for compressed repeated cells/rows via table:number-columns-repeated and table:number-rows-repeated.
• After conversion from XLSX, verify formula compatibility because not every Excel formula maps cleanly to OpenFormula/LibreOffice Calc.

ODS Modeling Checklist

• Set explicit cell types; do not store all values as strings.
• Preserve formulas as formulas and keep displayed text/value metadata aligned.
• Expand repeated cells/rows before positional edits.
• Keep headers, assumptions, calculations, and outputs clearly separated for model workbooks.
• Use consistent number formats for currency, percentages, dates, and zeros.
• Treat blank cells, nulls, zero values, and error values deliberately.
• Verify merged cells and covered cells after XML edits.
• For formula-heavy workbooks, recalc with LibreOffice before delivery.
• For data exports, compare row/column counts against the source.

QA (Required)

For created or edited ODS files, run a data-first QA loop.

Content QA

python scripts/extract_sheets.py output.ods --json > qa/sheets.json
python scripts/extract_formulas.py output.ods > qa/formulas.json

Check sheet names, dimensions, row/column counts, typed values, formulas, dates, percentages, currency cells, and obvious error strings.

Package QA

python scripts/inspect_package.py output.ods > qa/package.json
python scripts/validate_refs.py output.ods

Check that mimetype is first, required XML files exist, media/chart targets exist, manifest entries are present, and style references are not broken.

Recalc and Export QA

Recalculate with LibreOffice when formulas are present:

python scripts/recalc.py output.ods --outdir qa

Export important sheets to CSV for data comparison:

python scripts/export_csv.py output.ods --sheet Data --output qa/data.csv

Visual Design Loop

For user-facing reports, rendering is a design step, not only a final check — render an early draft, look at how LibreOffice paginates it, and adjust column widths and print ranges before finishing:

python scripts/render.py output.ods --outdir qa                  # PDF
python scripts/render.py output.ods --outdir qa --contact-sheet  # all printed pages in one image

The contact sheet composes every printed page into a single labelled grid image — the quickest way to spot bad page breaks, clipped columns, and charts that span pages. Open it and actually look at it: check layout, charts, table widths, page breaks, headers, and footers.

Verification Loop

The final pass of a loop you should already be running while building the sheet:

1. Extract sheet data and formulas.
2. Validate package references.
3. Recalculate if formulas exist.
4. Export CSV, and render to PDF/contact sheet and look at it.
5. Fix data, formula, type, formatting, or package issues.
6. Re-run the relevant checks until no unresolved issues remain.

See also

Part of the open-document-skills suite:

• odt — OpenDocument Text / LibreOffice Writer
• odp — OpenDocument Presentation / LibreOffice Impress
• odg — OpenDocument Graphics / LibreOffice Draw