xlsx-viewer-pro (Excel Viewer Pro)

A high-performance Python spreadsheet library, headless formula engine (129+ functions), native x64 SIMD SSE2 math engine, and modern Office Ribbon desktop application for .xlsx, .xlsm, .csv, and .tsv files.

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⚡ Key Highlights

• 🧮 Headless Excel Formula Engine: Evaluate Excel formulas in pure Python without launching any UI. Supports 129 functions across Math, Trigonometry, Statistics, Finance (PMT, PV, FV, NPV, IRR), Lookups (VLOOKUP, XLOOKUP, INDEX, MATCH), Text, Logic, and Date/Time.
• 🚀 Hardware SIMD SSE2 Acceleration: Built-in 64-bit native assembly engine (xlsx_math64.dll) delivering up to 7.4+ million double-precision operations per second with automatic pure-Python fallback on non-Windows/ARM platforms.
• 🛠️ Dual-Use Architecture: Use it as a lightweight Python library, a command-line tool (xlsx-viewer-pro / xlsx-viewer / xv), or a full-featured desktop spreadsheet application.
• 🎨 Modern Desktop GUI: Office Ribbon UI with dynamic real-time status bar statistics (SUM, AVERAGE, COUNT, MIN, MAX), 10+ chart types, conditional formatting, auto-filter, and goal seek.
• 🧩 Zero Heavy Spreadsheet Engine Dependencies: No LibreOffice, COM, or Excel installation required.

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📦 Installation

Install via pip:

pip install xlsx-viewer-pro

Or via uv:

uv pip install xlsx-viewer-pro

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🐍 Python Library Quickstart

1. Headless Formula Evaluation

Evaluate any Excel formula directly from Python:

from xlsx_viewer import evaluate_formula

# Basic arithmetic & math
result = evaluate_formula("=SUM(10, 20, 30) * 2")
print(result)  # 120.0

# Financial formulas
monthly_payment = evaluate_formula("=PMT(0.05 / 12, 360, -250000)")
print(f"Monthly Mortgage: ${monthly_payment:.2f}")  # $1342.05

# Statistical & Logic
val = evaluate_formula("=IF(AVERAGE(85, 90, 92) >= 90, 'Honors', 'Standard')")
print(val)  # 'Honors'

2. Evaluating Formulas with Cell Context

Pass cell coordinate mappings directly using standard Excel notation:

from xlsx_viewer import evaluate_formula

context = {
    "A1": 15000,
    "A2": 3200,
    "B1": 0.15,
    "B2": "Tier-1",
}

# Reference cells directly
net_profit = evaluate_formula("=(A1 - A2) * (1 - B1)", context=context)
print(f"Net Profit: ${net_profit:.2f}")  # $10030.00

# Text and conditional logic with context
status = evaluate_formula(
    '=IF(A1 > 10000, CONCAT(B2, " - High Volume"), "Normal")',
    context=context,
)
print(status)  # 'Tier-1 - High Volume'

3. Using the FormulaEngine Class

For dynamic resolution or integrating with custom data sources:

from xlsx_viewer import FormulaEngine

# Custom resolver: fn(row: int, col: int, sheet: str | None) -> value
matrix = [
    [10, 20, 30],
    [40, 50, 60],
]

def custom_resolver(row: int, col: int, sheet: str | None = None):
    try:
        return matrix[row][col]
    except IndexError:
        return 0

engine = FormulaEngine(resolver=custom_resolver)
result = engine.evaluate("=SUM(A1:C2) + MAX(A1:C2)")
print(result)  # 210 + 60 = 270.0

4. SIMD Hardware-Accelerated Vector Math

Leverage native 64-bit SSE2 assembly routines for high-throughput calculations:

from xlsx_viewer.asm import is_asm_available, simd_avg, simd_max, simd_min, simd_sum, simd_sumproduct

print("SIMD SSE2 Active:", is_asm_available())

data_a = [10.5, 20.25, 30.75, 40.0, 50.5, 60.0]
data_b = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0]

print("Sum:", simd_sum(data_a))
print("Average:", simd_avg(data_a))
print("Min / Max:", simd_min(data_a), simd_max(data_a))
print("Sumproduct:", simd_sumproduct(data_a, data_b))

5. In-Memory Workbook Data Models

Load, inspect, and manipulate Excel workbooks programmatically:

from xlsx_viewer import WorkbookData, load_workbook

# Load an existing workbook
wb = load_workbook("report.xlsx")
print(f"Sheets: {wb.sheet_names}")

sheet = wb.get_sheet("Sheet1")
print(f"Dimensions: {sheet.max_row} rows x {sheet.max_col} cols")

# Read cell values and formulas
cell = sheet.get_cell(row=0, col=0)  # A1
if cell:
    print(f"A1 Value: {cell.value}, Formula: {cell.formula}")

# Modify cells in-memory
sheet.set_cell(row=0, col=1, value=1250.50)

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💻 Command Line Interface (CLI)

xlsx-viewer comes with a CLI tool accessible as both xlsx-viewer and xv:

# Evaluate an Excel formula from the terminal
xv --calc "=SUM(10, 20, 30) * 2"
# 120.0

# Calculate financial loan payment
xv -c "=PMT(0.065 / 12, 360, -350000)"
# 2212.24

# List all 129 supported Excel formula functions
xv --list-formulas

# Inspect environment and hardware SIMD acceleration status
xv --info

# Open a workbook in the desktop GUI
xv sample_report.xlsx

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🖥️ Desktop Application Features

Launch the desktop spreadsheet GUI with:

xlsx-viewer
# or
python -m xlsx_viewer

📊 Office Ribbon Navigation

• Home Tab: Undo/Redo, Clipboard (Cut, Copy, Paste, Paste Special), Font styling, Cell fill & text colors, Cell borders, Alignment & Wrap Text, Number formats ($, €, ₽, %, decimals), Conditional Formatting.
• Insert Tab: Chart Wizard (10+ chart types), Shapes, and Comments.
• Data Tab: Multi-level Sorting, AutoFilter with column search checkboxes, Remove Duplicates, Text-to-Columns, and Goal Seek.
• Formulas Tab: Function Wizard (fx), Precedence auditing, and calculation options (F9).
• View Tab: Gridline toggling, Zoom levels (50% – 200%), and Theme switcher.

📈 Chart Wizard (10+ Types)

Interactive charts powered by Matplotlib:

• Column & Bar Charts
• Line & Area Charts
• Pie & Donut Charts
• XY Scatter Plots & Histograms
• Professional color palettes: Excel Classic, Modern Teal, Vibrant, Pastel, Monochrome.

⌨️ Keyboard Shortcuts

Shortcut	Action
Ctrl + N	New Workbook
Ctrl + O	Open File
Ctrl + S	Save File
Ctrl + Shift + S	Save As...
Ctrl + Z / Ctrl + Y	Undo / Redo
Ctrl + C / Ctrl + X / Ctrl + V	Copy / Cut / Paste
Ctrl + A	Select Entire Sheet
Ctrl + F / Ctrl + H	Find / Replace
Ctrl + G	Go to Cell
F2 / Double Click	In-place Cell Editor
F9	Recalculate All Formulas
Shift + Arrow Keys	Expand Cell Selection
Tab / Enter	Move Right / Down

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🧮 Supported Formula Functions (129 Total)

Click to expand full function list by category

📐 Math & Trigonometry (33)

SUM, SUMIF, SUMIFS, PRODUCT, ROUND, ROUNDUP, ROUNDDOWN, INT, TRUNC, ABS, MOD, POWER, SQRT, PI, RAND, RANDBETWEEN, CEILING, FLOOR, SIGN, SIN, COS, TAN, ASIN, ACOS, ATAN, DEGREES, RADIANS, EXP, LN, LOG, LOG10, FACT, SUMPRODUCT

📊 Statistical (20)

AVERAGE, AVERAGEA, AVERAGEIF, AVERAGEIFS, COUNT, COUNTA, COUNTBLANK, COUNTIF, COUNTIFS, MIN, MINIFS, MAX, MAXIFS, MEDIAN, MODE, STDEV, STDEVP, VAR, VARP, LARGE, SMALL, RANK

💰 Financial (9)

PMT, PV, FV, RATE, NPER, NPV, IRR, SLN, SYD

🔍 Lookup & Reference (11)

VLOOKUP, HLOOKUP, XLOOKUP, INDEX, MATCH, LOOKUP, CHOOSE, ROW, COLUMN, ROWS, COLUMNS

🔤 Text (23)

CONCAT, CONCATENATE, TEXTJOIN, LEFT, RIGHT, MID, LEN, TRIM, UPPER, LOWER, PROPER, EXACT, FIND, SEARCH, REPLACE, SUBSTITUTE, REPT, TEXT, VALUE, CHAR, CODE, CLEAN, T

⚖️ Logical (11)

IF, IFS, SWITCH, AND, OR, NOT, XOR, IFERROR, IFNA, TRUE, FALSE

📅 Date & Time (11)

TODAY, NOW, DATE, TIME, YEAR, MONTH, DAY, DAYS, EDATE, EOMONTH, WEEKDAY

ℹ️ Information (10)

ISBLANK, ISNUMBER, ISTEXT, ISNONTEXT, ISLOGICAL, ISERROR, ISERR, ISNA, TYPE, N

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🏛️ Architecture

xlsx-viewer/
├── xlsx_viewer/            # Core Library Package
│   ├── __init__.py         # Public API exports
│   ├── api.py              # evaluate_formula, load_workbook, launch_gui
│   ├── cli.py              # CLI entrypoint (xlsx-viewer / xv)
│   ├── formulas.py         # Headless formula evaluation engine (129 functions)
│   ├── models.py           # In-memory workbook, sheet, cell, and formatting models
│   ├── formatting.py       # Number, date, currency, and conditional formatting
│   ├── widgets.py          # Tkinter / ttkbootstrap UI widgets (Ribbon, Sheet, Grid)
│   ├── dialogs.py          # Wizards (Chart, Function, Filter, Goal Seek)
│   ├── config.py           # Styling, themes, and configuration
│   └── asm/                # Hardware acceleration
│       ├── xlsx_math64.dll # Native x64 SSE2 assembly DLL
│       └── asm_bridge.py   # ctypes bridge with fallback
├── tests/                  # Integration and Unit Test Suite (29 tests)
│   ├── test_app.py
│   └── test_library_api.py
├── pyproject.toml          # PEP 517 / 621 Build Specification
└── README.md

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🧪 Running Tests

Run the test suite with pytest:

uv run pytest -v

All 29 tests pass with 100% success rate on Python 3.10 through 3.14.

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📄 License

This project is licensed under the MIT License.

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👤 Author

Developed by eminsk (GitHub) • M_N_Nik@yahoo.com