Using openpyxl to Operate Excel Files in Python

Python offers several libraries for Excel manipulation, and openpyxl is a popular choice due to its balance of functionality and performance. The following sections demonstrate common tasks such as creating a new workbook, opening existing files, and configuring read‑only or write‑only modes for large datasets.

Creating a workbook

<code>from openpyxl import Workbook
wb = Workbook()
</code>

Opening an existing workbook

<code>from openpyxl import load_workbook
wb2 = load_workbook('test.xlsx')
</code>

For large files, you can reduce memory usage by using read_only=True or write_only=True when loading or creating a workbook.

<code>wb = load_workbook(filename='large_file.xlsx', read_only=True)
wb = Workbook(write_only=True)
</code>

Worksheet handling

Access the active sheet with ws = wb.active or create new sheets at specific positions:

<code>ws1 = wb.create_sheet('Mysheet')               # append at end (default)
ws2 = wb.create_sheet('Mysheet', 0)            # insert at first position
ws3 = wb.create_sheet('Mysheet', -1)           # insert before last sheet
</code>

Retrieve a sheet by name ( ws = wb['SheetName'] ) and list all sheet names with wb.sheetnames .

<code>print(wb.sheetnames)
# ['Sheet2', 'New Title', 'Sheet1']
</code>

Saving workbooks

You can save to a temporary stream for network transmission or directly to a file:

<code>from tempfile import NamedTemporaryFile
wb = Workbook()
with NamedTemporaryFile() as tmp:
    wb.save(tmp.name)
    tmp.seek(0)
    stream = tmp.read()
wb.save('balances.xlsx')
</code>

To save as a template, set wb.template = True before saving with an .xltx extension.

<code>wb = load_workbook('document.xlsx')
wb.template = True
wb.save('document_template.xltx')
</code>

Cell operations

Read and write cell values using the A1 notation:

<code>c = ws['A4']
ws['A4'] = 4
c.value = 'hello, world'
</code>

Access ranges with slicing, set number formats, and add formulas:

<code>cell_range = ws['A1':'C2']
ws['A1'] = datetime.datetime(2010, 7, 21)
print(ws['A1'].number_format)  # 'yyyy-mm-dd h:mm:ss'
ws['A1'] = '=SUM(1, 1)'
</code>

Merge and unmerge cells either by range string or by specifying start/end rows and columns:

<code>ws.merge_cells('A2:D2')
ws.unmerge_cells('A2:D2')
ws.merge_cells(start_row=2, start_column=1, end_row=4, end_column=4)
ws.unmerge_cells(start_row=2, start_column=1, end_row=4, end_column=4)
</code>

Row and column manipulation

Retrieve entire rows or columns, iterate over them, or insert/delete rows and columns:

<code>colC = ws['C']
col_range = ws['C:D']
row10 = ws[10]
row_range = ws[5:10]
for row in ws.iter_rows(min_row=1, max_col=3, max_row=2):
    for cell in row:
        print(cell)
for col in ws.iter_cols(min_row=1, max_col=3, max_row=2):
    for cell in col:
        print(cell)
ws.insert_rows(7)
ws.insert_cols(3)
ws.delete_rows(5, 2)
ws.delete_cols(2, 1)
</code>

Reading values only

Use ws.values or set values_only=True in iter_rows / iter_cols to retrieve just the cell contents:

<code>for row in ws.values:
    for value in row:
        print(value)
for row in ws.iter_rows(min_row=1, max_col=3, max_row=2, values_only=True):
    print(row)
</code>