WolfXL

Edit existing Excel files from Python without losing formatting, 3.0-17.3x faster than openpyxl on the committed read/write benchmark (small-file gains vary), with an openpyxl-compatible API. MIT licensed.

WolfXL Community reads, writes, and edits Excel .xlsx and .xlsm workbooks through the openpyxl API, with parsing, serialization, and cell storage implemented in Rust. Modify mode saves the cells you change and keeps the rest of the file, and calculate() covers common Excel functions in Python. Most openpyxl code runs after a one-line import change.

python -m pip install wolfxl

Edit a workbook · Compared with openpyxl · Switch from openpyxl · Quick start · Benchmarks · Fidelity · Community vs Commercial · wolfxl.com

Edit an existing workbook

from wolfxl import load_workbook

wb = load_workbook("report.xlsx", modify=True)  # edit the existing file
wb["Summary"]["B2"] = 1500
print(wb.calculate()["Summary!B4"])  # 2450.0 from =SUM(B2:B3)
wb.save("report-updated.xlsx")  # cells you did not touch keep their formatting
wb.close()

Modify mode saves the cells you change and preserves unchanged styles, charts, and package parts within the documented boundaries; add keep_vba=True for .xlsm macros. calculate() returns the computed values and leaves the cached results in the saved file unchanged. Edit Excel in Python without losing formatting.

The following free recalculation-on-open recipe requires Community 2.0.9 or newer; earlier versions do not persist changes to this flag. Keep the workbook open in modify mode as above, then:

wb["Summary"]["B2"] = 1500
wb.calculation.fullCalcOnLoad = True
wb.save("report-updated.xlsx")

Excel recalculates when it opens the saved workbook. This flag does not calculate formulas in Python: cached values remain stale until Excel or another calculation engine recalculates. Close the workbook after saving.

Compared with openpyxl

• Same API for the covered surface. Change one import (Switch from openpyxl). openpyxl implements more of its own API, so check the compatibility matrix and the known limitations before switching a production path.
• Existing templates. openpyxl warns that it will remove data validations, conditional formats, and sparklines it does not support, and its documentation says shapes are lost. On a sheet with an extension data validation and a sparkline, one cell edit saved by openpyxl 3.1.5 lost both; load_workbook(path, modify=True) in WolfXL 2.0.2 kept both.
• Formulas. openpyxl stores formula text and never computes it; with data_only=True it returns the value Excel last cached, or None for a file Excel never opened. WolfXL Community calculate() covers common functions only, in Python. Need results that match Excel? Commercial includes a native engine verified on 704 Excel-calculated cases (pricing).
• Large files. In the current benchmark's 200,000-row plain workload, a full read with WolfXL took 0.305 s against 4.380 s for openpyxl 3.1.5. The edit-two-cells-and-save phase took 0.159 s against 9.202 s; the full edit benchmark, including verification with openpyxl, took 5.458 s against 14.509 s. See the current receipts.
• Other alternatives. python-calamine and fastexcel specialize in reading; XlsxWriter and PyExcelerate specialize in writing. WolfXL reads, writes, and edits through an openpyxl-compatible API. The current speed claims compare only WolfXL and openpyxl, not these specialists.
• Where openpyxl fits. openpyxl is pure Python and installs anywhere Python runs. WolfXL needs a published wheel for your platform or a Rust toolchain to build from source.

Community does not include native formula recalculation, PDF or image rendering, format conversion, or VBA and Power Query operations. Those ship in WolfXL Commercial:

• Recalculate formulas openpyxl leaves stale
• Render sheets and charts to PDF or PNG without LibreOffice
• Coming from Aspose.Cells for Python

See Community and Commercial.

Median read and write speedups over openpyxl 3.1.5 range from 3.0x on styled reads to 17.3x on multi-sheet bulk writes (WolfXL 2.0.8 PyPI wheel, Apple M5 Pro, Python 3.13.9, median of 5 rounds). Bulk writes use a different API shape from openpyxl's per-row or per-cell calls; workload details and all samples are in the current results. This is a measured range on this machine, not a guarantee for every workbook. Small-file gains vary: the separate officelibs small-feature benchmark reports about 1.7x for reads and 2.4x for writes, outside this range.

Switch from openpyxl

Most openpyxl-shaped code needs only an import change:

- from openpyxl import Workbook, load_workbook
+ from wolfxl import Workbook, load_workbook

The rest of the code stays the same:

from wolfxl import Workbook, load_workbook

workbook = Workbook()
sheet = workbook.active
sheet.append(["region", "revenue"])
for row in [("North", 1200), ("South", 950)]:
    sheet.append(row)
workbook.save("sales.xlsx")

workbook = load_workbook("sales.xlsx", read_only=True)
for row in workbook.active.iter_rows(min_row=2, values_only=True):
    print(row)
workbook.close()

For applications that cannot change every import, install the runtime alias once at process startup:

import wolfxl

wolfxl.install_as_openpyxl()

import openpyxl

Step-by-step guide: openpyxl migration.

Quick start

Install the current Community release:

python -m pip install wolfxl==2.0.9

WolfXL Community supports Python 3.9 and newer CPython versions for which a wheel is published.

from wolfxl import Alignment, Font, PatternFill, Workbook, load_workbook

workbook = Workbook()
sheet = workbook.active
sheet.title = "Summary"
sheet["A1"] = "Revenue"
sheet["A1"].font = Font(bold=True, color="FFFFFF")
sheet["A1"].fill = PatternFill(fill_type="solid", fgColor="336699")
sheet["B1"] = 125000
sheet["B1"].alignment = Alignment(horizontal="right")
workbook.save("report.xlsx")

loaded = load_workbook("report.xlsx")
print(loaded["Summary"]["B1"].value)
loaded.close()

For AI coding agents

skills/wolfxl-xlsx is an agent skill for editing existing workbooks without losing the parts the edit did not touch. It tells the agent to edit in modify mode, recalculate with WolfXL instead of a LibreOffice round trip, and run verify to confirm that every package part and sheet feature from the source is still present. Copy the directory into your agent's skills folder, for example ~/.claude/skills/wolfxl-xlsx.

Performance

The current comparison uses the published WolfXL 2.0.8 and openpyxl 3.1.5 packages on Apple M5 Pro, macOS 26.5.1, Python 3.13.9. Every timed case, including the large workloads, reports the median of five measured rounds.

Workload	openpyxl seconds	WolfXL seconds	Speedup
Styled cell read	0.051807	0.017246	3.0x
Multi-sheet bulk write	0.083623	0.004842	17.3x
Large plain full read	4.380110	0.304859	14.4x
Large plain bulk write	3.399683	0.228258	14.9x
Large two-cell edit, including verification	14.509416	5.458442	2.7x

Read and write ratios span 3.0-17.3x. End-to-end edit ratios span 2.4-2.7x and include openpyxl verification; edit-only phases are reported separately, not folded into the headline range. The large plain case is configured for 200,000 rows and eight columns, but the committed harness generates only five populated columns (one million cells). See the result notes rather than interpreting its nominal units-per-second as populated cell throughput.

The results and reproduction notes include raw samples, machine and package identities, warmup policy, and memory measurements. Earlier runs remain under benchmarks/results/ as historical evidence, not current headline claims.

Fidelity

The round-trip fidelity harness compares workbook packages before and after a no-edit save. Run it on your own files, inspect the typed part and relationship differences, and add another engine through the documented adapter protocol.

Community and Commercial

	WolfXL Community	WolfXL Commercial
License	MIT	Commercial
Release line	Maintained 2.0 generation	Current 2.1+ generation
Workbook I/O	Included	Included
Existing 2.0 modify and pivot APIs	Included	Current implementations and fixes
Native recalculation	Not included	Included
Render, PDF, and image output	Not included	Included
Format conversion	Not included	Included
VBA and Power Query operations	Not included	Included
Production operations SDK	Not included	Included
Direct support	Community issues	Included with paid plans

Community receives critical correctness and security fixes. New engines, expanded compatibility work, production operations, and direct support ship in WolfXL Commercial.

This split keeps the useful Excel I/O layer open while funding the compatibility, fidelity, and support work required by production workbook pipelines.

Use wolfxl.com for the current Commercial package, evaluation access, pricing, compatibility information, and support. Commercial source and releases are maintained separately and are not part of this repository.

Development

Prerequisites: a supported CPython, Rust, and maturin.

python -m pip install maturin pytest defusedxml openpyxl Pillow
maturin develop
pytest tests/test_community_distribution.py -q

The distribution-boundary test verifies the Community version, compiled backends, and absence of Commercial-only Python modules.

See CONTRIBUTING.md for contribution guidelines and SECURITY.md for how to report a vulnerability.

License

WolfXL Community is available under the MIT License.