Excel reports. Python simplicity.
Turn Python data into Excel workbooks — from everyday reports to large exports.
Read and write XLSB and XLSX, bring your pandas or polars DataFrames, and refresh existing XLSM templates while preserving their macros. Style the result with charts, tables, formatting, and cell notes — all from Python.
Get started · Usage guide · Examples · Benchmarks
Built for speed
2.5 million cells in under a second, as XLSB.
| 50,000 × 50 cells, Windows | xlspy XLSB | xlspy XLSX | xlsxwriter | openpyxl |
|---|---|---|---|---|
| Write | 0.81 s | 1.27 s | 10.17 s | 17.06 s |
| Read | 0.14 s | 0.73 s | — | 10.75 s |
The native (Rust) module writes 2.5–3.7× and reads XLSB 46× faster than
xlspy's pure-Python fallback. Medians of three runs on an AMD Ryzen 7 7840HS
with Python 3.14 (2026-11-02); xlspy with inline strings, xlsxwriter with
constant_memory, openpyxl with write_only and read_only.
See the full comparisons, hardware, and methodology →
Made for the work behind the workbook
| Your workflow | What xlspy brings |
|---|---|
| Export large datasets | XLSB and XLSX output from a generator or database cursor, with bounded memory via use_shared_strings=False, and native (Rust) acceleration for supported read and write paths. A failed export publishes no partial workbook (failure handling). |
| Deliver polished reports | Cell styles, number formats, formulas, dropdown validation, hyperlinks, images, print setup, charts (column, bar, line, area, pie, doughnut, scatter, stacked), tables, and conditional formatting. Both XLSX and XLSB support them; see the feature support table. |
| Work with DataFrames | Export pandas or polars data directly to either format. |
| Refresh a familiar template | Replace data in XLSB, XLSX, or XLSM while keeping workbook structure, styles, and unrelated sheets. |
| Connect a data pipeline | Read rows as a generator and stream updates from a database cursor. |
The core library has no required Python package dependencies. Add pandas or polars support when you need it. Microsoft Excel is not required for the core read and write APIs.
Quick start
Requires Python 3.11 or newer (tested on 3.11–3.15).
pip install xlspy
Wheels include the native (Rust) extension. Installing from the source
distribution builds it, which needs Rust 1.88 or newer
(rustup). Set XLSPY_ACCEL=python to run the pure-Python
code instead.
Create a report with a styled header and formatted values:
from xlspy import F, Style, XlsxWriter
with XlsxWriter("sales.xlsx") as workbook:
workbook.add_sheet("Sales")
workbook.write_sheet(
[
["Product", "Revenue"],
["Coffee", (12500, F.THOUSANDS_SEP)],
["Tea", (8400, F.THOUSANDS_SEP)],
],
header_style=Style(bold=True, fill="#183C52", font_color="#FFFFFF"),
)
For binary Excel output, use XlsbWriter and a .xlsb filename with the same
API. Explore formatting, charts, and tables
when your report needs more detail.
Bring your data. Keep your workflow.
Already using pandas or polars? Export with to_xlsx(df, "report.xlsx")
or to_xlsb(df, "report.xlsb").
See DataFrame examples →
Have an Excel template? Refresh its data with XlsxUpdater, XlsbUpdater,
or XlsmUpdater. XLSM updates preserve the existing VBA project.
Update a workbook →
Need to read the results? Use ExcelReader for XLSB and XLSX, with the same
API for both formats. It streams values without styles and is the fastest way in.
For random access, formatting and edits, load_workbook() loads either format
into an openpyxl-like model; styles are resolved only when you read them, so
there is no flag to set.
Choose a read mode →
Explore further
| Resource | What you will find |
|---|---|
| Usage guide | Detailed examples, API options, and format support limits. |
| API reference | Every public class and function, generated from the docstrings. |
| Runnable examples | Scripts for reports, DataFrames, and workbook updates. |
| Benchmarks | Read and write comparisons, dataset details, and reproduction commands. |
| Validation | Windows and WSL2 test results, compatibility checks, and known limitations. |
| Test suite | How to run tests and measure coverage. |
| Contributing | Development setup, building the Rust module, checks and commit style. |
| Architecture | Which module does what, the layers, and the native module. |
| Changelog | Releases, improvements, and fixes. |
1 maintainer
Metadata
1 maintainer
Release files for xlspy 0.12.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| xlspy-0.12.0.tar.gz | 764.8 kB | With provenance | Details for xlspy-0.12.0.tar.gz |
Built distributions (wheels)
Total release size: 46.9 MB
Release files / xlspy-0.12.0.tar.gz
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| Tags | Source |
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| Download URL | xlspy-0.12.0-cp311-cp311-manylinux_2_28_aarch64.whl |
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| Size | 1.2 MB |
| Tags | CPython 3.11 Linux glibc 2.28+ ARM64 |
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Transparency logRelease files / xlspy-0.12.0-cp311-cp311-macosx_11_0_arm64.whl
| Download URL | xlspy-0.12.0-cp311-cp311-macosx_11_0_arm64.whl |
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| Size | 1.1 MB |
| Tags | CPython 3.11 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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| Size | 1.2 MB |
| Tags | CPython 3.11 macOS 10.12+ x86-64 |
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SHA-256 checksum How to use checksums |
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