Python in Excel Alternatives in 2026

A dated comparison of Microsoft Python in Excel, Boardflare, xlwings Lite, Anaconda Code, and external Python across runtime, integration, and sharing.

There are now several materially different ways to run Python with Excel. Comparing them only by “supports Python” hides the choices that actually determine whether a workflow will work: where Python executes, how it reaches workbook data, what packages it can load, whether it can create worksheet functions, and what another user receives when the workbook is shared. Those differences are real platform distinctions: Microsoft’s Python in Excel security documentation describes a managed cloud container, while Pyodide describes Python running in the browser through WebAssembly.

This review compares Microsoft Python in Excel, Boardflare Python for Excel, xlwings Lite, and Anaconda Code. It was originally published July 15, 2026 and reviewed against current product documentation on August 20, 2026. Because these products are changing quickly, treat it as a dated market snapshot and verify the linked official documentation before making a deployment decision.

For a much deeper maintained comparison of the first two—including row-major calculation, source storage/export, type conversion, data limits, reusable worksheet functions, packages, networking, and security boundaries—see Boardflare Python for Excel vs. Microsoft Python in Excel.

Start with the execution model

Python + Excel
│
├── Microsoft-managed cloud runtime
│   └── Microsoft Python in Excel
│
├── Browser / WebAssembly add-in runtime
│   ├── Boardflare Python for Excel
│   ├── xlwings Lite
│   └── Anaconda Code (Pyodide / WebR)
│
└── Local / external Python
    ├── xlwings desktop/server patterns
    ├── PyXLL
    └── pandas/openpyxl/COM/scripts

The execution model affects far more than performance. It determines the security boundary, package environment, access to local files and web APIs, workbook integration model, deployment requirements, and how much of the runtime the organization must manage. Microsoft’s Excel add-in platform overview and Office shared-runtime documentation explain the add-in side of that comparison.

At-a-glance comparison

Dimension	Microsoft Python in Excel	Boardflare Python for Excel	xlwings Lite	Anaconda Code
Primary runtime	Microsoft Cloud	Browser / Pyodide	Browser / Pyodide	Excel add-in / Pyodide or WebR (WASM)
Primary code surface	Worksheet PY cells	Reactive marimo notebook	Scripts, custom functions, notebooks	Excel code environment
Separate local Python install	No	No	No for Lite	No external desktop Python required for Code
Interactive notebook surface	Worksheet-focused	Reactive marimo notebook + optional App mode	Stateful .nb.py notebook + App Mode	Code-oriented Excel environment
Worksheet custom-function model	Native PY calculation, not user-published Python UDFs	BF.FUNCTION() plus focused Editor functions	Native custom functions	UDF support
Explicit application output registry	PY cell result	BF.OUTPUT()	Workflow-dependent workbook writes/UDFs	Workflow-dependent
Package/runtime model	Microsoft-managed package set	Pyodide/WebAssembly	Pyodide/WebAssembly	User-selectable Pyodide/WebR environment
Main design center	Python analysis in Excel grid	Reactive notebook connected to workbook data, outputs, and functions	xlwings-style automation, notebooks, scripts, and UDFs in browser	Python/R code cells and UDFs inside the Excel add-in

The table intentionally omits pricing and fine-grained licensing. Those change too quickly to freeze into an article without frequent maintenance.

Microsoft Python in Excel

Microsoft’s native Python feature uses the PY function and executes Python in a secure Microsoft Cloud runtime. Microsoft provides a managed set of libraries and integrates Python results directly into the Excel calculation surface.

Official documentation:

• Introduction to Python in Excel
• PY function
• Data security and Python in Excel
• Python in Excel availability
• Use Power Query to import data for Python in Excel

Strengths

• native Microsoft experience inside the grid;
• no separate Python environment for the user to maintain;
• strong fit for pandas/statistical analysis that starts from workbook data;
• managed security and package environment;
• Python results can feed the surrounding workbook.

Tradeoffs

The same managed environment that simplifies deployment also imposes boundaries. Python is not running as an unrestricted local desktop process. External data access follows Microsoft’s supported worksheet/Power Query model, and arbitrary local packages, folders, operating-system automation, and general desktop integration are outside the core product design.

Best fit

Start here when the artifact is fundamentally an Excel workbook containing bounded Python analysis and the Microsoft-managed runtime fits the organization’s platform, security, package, and licensing requirements.

Boardflare Python for Excel

Boardflare uses a stock marimo reactive notebook running through Pyodide in the Office add-in browser environment. Workbook data enters through explicit bf.inputs() declarations. The notebook can publish values/tables through BF.OUTPUT() and short callable Python functions through BF.FUNCTION().

Notebook source and startup preference are saved with the Excel workbook. The notebook is the primary authoring surface; optional Open as: App can present the same notebook more simply when an analysis becomes a repeatable tool.

Current product documentation: Python for Excel. For the detailed two-way Microsoft comparison, see Boardflare vs. Microsoft Python in Excel.

Strengths

• one coherent reactive notebook rather than Python logic distributed across worksheet cells;
• explicit workbook input and published-output contracts;
• interactive notebook UI through marimo;
• published worksheet functions;
• source travels with the workbook;
• no separate desktop Python installation for workbook users;
• the same notebook model can be demonstrated in the standalone Univer host.

Tradeoffs

Boardflare inherits browser/WebAssembly constraints. Some native Python packages and desktop/system integrations are not appropriate for Pyodide. User-authored web requests are also subject to browser security and CORS behavior.

Boardflare App mode is a presentation experience rather than a permissions or source-protection boundary, and recipients need the Boardflare add-in when the workbook depends on Boardflare notebook execution.

Best fit

Evaluate Boardflare when the Python work is substantial enough to benefit from a coherent notebook while Excel still matters to the workflow. App mode becomes relevant when that notebook also needs to serve as a simplified repeatable interface.

xlwings Lite

xlwings Lite has evolved substantially. Its current documentation covers custom functions, automation scripts, browser/Pyodide execution, .nb.py notebooks, package installation, web API access, testing, multiple workbook-stored source files, and an App Mode that can expose scripts to end users without showing the editor. Its August 2026 changelog also documents pinned dependency resolution for reproducible workbooks and continued notebook improvements.

Official documentation:

• xlwings Lite
• Notebooks
• Custom Functions
• App Mode
• Dependencies
• Changelog

Strengths

• familiar xlwings-style workbook programming model;
• browser runtime without requiring a normal desktop Python installation;
• custom functions and scripts;
• notebook workflow with regular .nb.py source files;
• App Mode for end-user operation;
• direct workbook-object-model style programming;
• workbook-stored source files, dependency management, and pytest-oriented testing support;
• current Lite builds also support workbook-managed file import/export and, on Windows desktop, mounted local-directory access through the add-in.

Tradeoffs

The most important difference from Boardflare is not a missing checkbox. It is the programming model. xlwings Lite is organized around xlwings workbook APIs, scripts, custom functions, and a stateful notebook in which cells are run individually or in groups. Boardflare uses marimo’s dependency-reactive graph and emphasizes an explicit workbook-input registry plus explicit live output/function publication.

Teams choosing between them should prototype the real application rather than compare slogans such as “browser Python” or “app mode.” Host-dependent features also matter: for example, current xlwings Lite releases expose local-directory mounting on Windows desktop even though Python itself runs through the add-in’s Pyodide environment.

Best fit

Evaluate xlwings Lite when you want xlwings-style automation and UDFs in a browser-based Excel add-in, particularly if the team already knows the xlwings API.

Anaconda Code

Anaconda Code runs Python or R locally within Excel’s add-in environment using Pyodide or WebR. Current Anaconda documentation describes code cells, configurable package/runtime versions, worksheet references, linked or isolated execution, and user-defined functions. Anaconda Toolbox for Excel is a generally available product, while the Anaconda Code feature is still labeled beta in the current documentation.

Official documentation:

• Anaconda Code
• Anaconda Toolbox for Excel

Strengths

• Python and R support;
• environment/package control within the Excel experience;
• worksheet references;
• user-defined functions;
• familiar Anaconda ecosystem positioning.

Tradeoffs

The product model is different from Boardflare’s notebook-centered workbook workflow and from Microsoft’s managed PY calculation model. Because Code is still documented as beta, organizations should verify current support, deployment, and sharing behavior before standardizing on it.

Best fit

Evaluate Anaconda Code when the priority is an Anaconda-oriented Python/R coding environment inside Excel with configurable packages and UDFs.

What about external or local Python?

The four products above are not substitutes for every Python/Excel workflow.

If the job needs:

• broad or unattended local folder traversal beyond an add-in’s supported host bridge;
• PDF/email processing;
• scheduled jobs;
• database pipelines;
• desktop application automation;
• unsupported native packages;
• large multi-workbook batch processing;

then an external Python environment may be the right answer. The workbook can remain the user-facing artifact without containing the whole runtime.

This distinction is visible in practitioner discussions: many successful “Python + Excel” automations use pandas, openpyxl, xlwings, COM, or scripts around Excel rather than Python executing in the workbook itself. The relevant external-runtime options have their own documentation: xlwings, openpyxl, and PyXLL.

How to choose

Ask these questions in order:

1. What is the artifact?

• A few Python calculations in a workbook?
• A reusable custom function?
• An interactive application another person operates?
• A batch process that produces workbooks?

The artifact is more important than the language.

2. Where must the code run?

If the workflow needs local system access, a browser or cloud sandbox may be the wrong runtime before package choice even enters the discussion.

3. Who maintains the code?

A workbook sent to non-programmers has a different deployment problem from an analyst’s personal notebook.

4. What package and network boundaries apply?

Browser/Pyodide environments support a large Python ecosystem, including many scientific packages, but not every native dependency. Microsoft’s environment is separately managed. Test the actual package set and external services early.

5. How does the second user open it?

This is the question product comparisons often skip. Test save/reopen behavior, required add-ins/licenses, startup, calculation, network access, and what the recipient sees when something goes wrong.

Bottom line

A useful shorthand is:

• Microsoft Python in Excel: Python analysis integrated directly into the Excel grid.
• Boardflare: a reactive Python notebook connected to workbook inputs, outputs, and functions, with optional App mode for a simplified interactive presentation.
• xlwings Lite: browser-based xlwings automation, scripts, notebooks, and custom functions.
• Anaconda Code: Python/R code and UDFs in an Anaconda-managed Excel add-in environment.
• External Python: the right answer when the workflow is really system automation or a data pipeline that happens to produce or consume Excel files.

The category will keep moving. The August 2026 xlwings changes alone show why feature checklists age quickly. That is why this article records a reviewed snapshot rather than pretending to be permanent product documentation.