Aspose.Cells FOSS
Python
Use Cases for Aspose.Cells FOSS for Python

Use Cases for Aspose.Cells FOSS for Python

Aspose.Cells FOSS for Python is a pure Python library for creating, reading, and converting spreadsheet files without Microsoft Office. The following use cases illustrate where the library fits into real-world Python applications.

Data Export Pipeline

Convert XLSX workbooks to CSV, Markdown, or JSON for downstream processing:

from aspose.cells_foss import Workbook, SaveFormat

wb = Workbook("data.xlsx")
wb.save("data.csv", SaveFormat.CSV)
wb.save("data.md", SaveFormat.MARKDOWN)
wb.save("data.json", SaveFormat.JSON)

This pattern works for any supported output format. Use it to feed data into documentation pipelines, static site generators, or API responses.

See: How to Save Spreadsheets in Python

Report Generation

Build XLSX reports from application data and serve them to users:

from aspose.cells_foss import Workbook, SaveFormat

wb = Workbook()
ws = wb.add_worksheet("Report")
cells = ws.cells

cells.cell(0, 0).put_value("Month")
cells.cell(0, 1).put_value("Revenue")

rows = [("Jan", 12400), ("Feb", 15200), ("Mar", 11800)]
for i, (month, rev) in enumerate(rows, start=1):
    cells.cell(i, 0).put_value(month)
    cells.cell(i, 1).put_value(rev)

wb.save("monthly_report.xlsx", SaveFormat.XLSX)

See: How to Get Started with Aspose.Cells FOSS for Python

Batch Spreadsheet Processing

Process a directory of workbooks in a single script:

from pathlib import Path
from aspose.cells_foss import Workbook, SaveFormat

for src in Path("incoming/").glob("*.xlsx"):
    wb = Workbook(str(src))
    wb.save(str(src.with_suffix(".csv")), SaveFormat.CSV)

Reading and Transforming Data

Load a workbook, read cell values, and write the transformed result:

from aspose.cells_foss import Workbook, SaveFormat

wb = Workbook("sales.xlsx")
ws = wb.get_worksheet(0)
cells = ws.cells

# Read all rows and filter
out_wb = Workbook()
out_ws = out_wb.add_worksheet("Filtered")
out_row = 0

for row in ws.cells.iter_rows(0, None, 0, None, values_only=True):
    if row and row[1] is not None and row[1] > 10000:
        out_ws.cells.cell(out_row, 0).put_value(row[0])
        out_ws.cells.cell(out_row, 1).put_value(row[1])
        out_row += 1

out_wb.save("high_value.xlsx", SaveFormat.XLSX)

See: How to Load a Spreadsheet in Python

Chart Automation

Build charts programmatically from spreadsheet data:

from aspose.cells_foss import Workbook, SaveFormat

wb = Workbook()
ws = wb.add_worksheet("Sales")
cells = ws.cells

cells.cell(0, 0).put_value("Q1")
cells.cell(0, 1).put_value(4200)
cells.cell(1, 0).put_value("Q2")
cells.cell(1, 1).put_value(5800)

chart = ws.charts.add_bar(0, 2, 20, 10)
chart.series.add("B1:B2", "A1:A2", "Revenue")
chart.title = "Quarterly Revenue"

wb.save("chart_report.xlsx", SaveFormat.XLSX)

See: How to Create Charts in Python

See Also