PyExcelerate
Accelerated Excel XLSX writing library for Python
PyExcelerate is a Python for writing Excel-compatible XLSX spreadsheet files, with an emphasis on speed.
Benchmarks
Benchmark code located in pyexcelerate/tests/benchmark.py
Ubuntu 12.04 LTS, Core i5-3450, 8GB DDR3, Python 2.7.3
| TEST_NAME | NUM_ROWS | NUM_COLS | TIME_IN_SECONDS |
|-----------------------------|----------|----------|-----------------|
| pyexcelerate value fastest | 1000 | 100 | 0.47 |
| pyexcelerate value faster | 1000 | 100 | 0.51 |
| pyexcelerate value fast | 1000 | 100 | 1.53 |
| xlsxwriter value | 1000 | 100 | 0.84 |
| openpyxl | 1000 | 100 | 2.74 |
| pyexcelerate style cheating | 1000 | 100 | 1.23 |
| pyexcelerate style fastest | 1000 | 100 | 2.40 |
| pyexcelerate style faster | 1000 | 100 | 2.75 |
| pyexcelerate style fast | 1000 | 100 | 6.15 |
| xlsxwriter style cheating | 1000 | 100 | 1.21 |
| xlsxwriter style | 1000 | 100 | 4.85 |
| openpyxl | 1000 | 100 | 6.32 |
* cheating refers to pregeneration of styles
Installation
PyExcelerate is supported on Python 2.7, 3.4, 3.5, 3.6, 3.7, and 3.8.
pip install pyexcelerate
Usage
Writing bulk data
Fastest
from pyexcelerate import Workbook
data = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # data is a 2D array
wb = Workbook()
wb.new_sheet("sheet name", data=data)
wb.save("output.xlsx")
Writing bulk data to a range
PyExcelerate also permits you to write data to ranges directly, which is faster than writing cell-by-cell. If writing a Pandas DataFrame, see the note on compatibility.
Fastest
from pyexcelerate import Workbook
wb = Workbook()
ws = wb.new_sheet("test", data=[[1, 2], [3, 4]])
wb.save("output.xlsx")
Fast
from pyexcelerate import Workbook
wb = Workbook()
ws = wb.new_sheet("test")
ws.range("B2", "C3").value = [[1, 2], [3, 4]]
wb.save("output.xlsx")
Writing cell data
Faster
from datetime import datetime
from pyexcelerate import Workbook
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws.set_cell_value(1, 1, 15) # a number
ws.set_cell_value(1, 2, 20)
ws.set_cell_value(1, 3, "=SUM(A1,B1)") # a formula
ws.set_cell_value(1, 4, datetime.now()) # a date
wb.save("output.xlsx")
Fast
from datetime import datetime
from pyexcelerate import Workbook
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws[1][1].value = 15 # a number
ws[1][2].value = 20
ws[1][3].value = "=SUM(A1,B1)" # a formula
ws[1][4].value = datetime.now() # a date
wb.save("output.xlsx")
Selecting cells by name
from pyexcelerate import Workbook
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws.cell("A1").value = 12
wb.save("output.xlsx")
Merging cells
from pyexcelerate import Workbook
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws[1][1].value = 15
ws.range("A1", "B1").merge()
wb.save("output.xlsx")
Styling cells
Styling cells causes non-negligible overhead. It will increase your execution time (up to 10x longer if done improperly!). Only style cells if absolutely necessary.
Fastest
from pyexcelerate import Workbook, Color, Style, Font, Fill, Format
from datetime import datetime
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws.set_cell_value(1, 1, 1)
ws.set_cell_style(1, 1, Style(font=Font(bold=True)))
ws.set_cell_style(1, 1, Style(font=Font(italic=True)))
ws.set_cell_style(1, 1, Style(font=Font(underline=True)))
ws.set_cell_style(1, 1, Style(font=Font(strikethrough=True)))
ws.set_cell_style(1, 1, Style(fill=Fill(background=Color(255,0,0,0))))
ws.set_cell_value(1, 2, datetime.now())
ws.set_cell_style(1, 1, Style(format=Format('mm/dd/yy')))
wb.save("output.xlsx")
Note that in this example, subsequent calls to set_cell_style() override the previous styles and they are not merged in. To have a combined style, create a single Style object with multiple properties, for example
ws.set_cell_style(1, 1, Style(font=Font(bold=True), format=Format('mm/dd/yy')))
Faster
from pyexcelerate import Workbook, Color
from datetime import datetime
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws.set_cell_value(1, 1, 1)
ws.get_cell_style(1, 1).font.bold = True
ws.get_cell_style(1, 1).font.italic = True
ws.get_cell_style(1, 1).font.underline = True
ws.get_cell_style(1, 1).font.strikethrough = True
ws.get_cell_style(1, 1).fill.background = Color(0, 255, 0, 0)
ws.set_cell_value(1, 2, datetime.now())
ws.get_cell_style(1, 1).format.format = 'mm/dd/yy'
wb.save("output.xlsx")
Fast
from pyexcelerate import Workbook, Color
from datetime import datetime
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws[1][1].value = 1
ws[1][1].style.font.bold = True
ws[1][1].style.font.italic = True
ws[1][1].style.font.underline = True
ws[1][1].style.font.strikethrough = True
ws[1][1].style.fill.background = Color(0, 255, 0, 0)
ws[1][2].value = datetime.now()
ws[1][2].style.format.format = 'mm/dd/yy'
wb.save("output.xlsx")
Note that .style.format.format's repetition is due to planned support for conditional formatting and other related features. The formatting syntax may be improved in the future.
Styling ranges
from pyexcelerate import Workbook, Color
from datetime import datetime
wb = Workbook()
ws = wb.new_sheet("test")
ws.range("A1","C3").value = 1
ws.range("A1","C1").style.font.bold = True
ws.range("A2","C3").style.font.italic = True
ws.range("A3","C3").style.fill.background = Color(255, 0, 0, 0)
ws.range("C1","C3").style.font.strikethrough = True
Styling rows
A simpler (and faster) way to style an entire row.
Fastest
from pyexcelerate import Workbook, Color, Style, Fill
from datetime import datetime
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws.set_row_style(1, Style(fill=Fill(background=Color(255,0,0,0))))
wb.save("output.xlsx")
Faster
from pyexcelerate import Workbook, Color
from datetime import datetime
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws.get_row_style(1).fill.background = Color(255, 0, 0)
wb.save("output.xlsx")
Fast
from pyexcelerate import Workbook, Color
from datetime import datetime
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws[1].style.fill.background = Color(255, 0, 0)
wb.save("output.xlsx")
Styling columns
Fastest
from pyexcelerate import Workbook, Color, Style, Fill
from datetime import datetime
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws.set_col_style(1, Style(fill=Fill(background=Color(255,0,0,0))))
wb.save("output.xlsx")
Available style attributes
Consistent with the implementation patterns above, the following style parameters are available:
ws[1][1].style.font.bold = True
ws[1][1].style.font.italic = True
ws[1][1].style.font.underline = True
ws[1][1].style.font.strikethrough = True
ws[1][1].style.font.color = Color(255, 0, 255)
ws[1][1].style.fill.background = Color(0, 255, 0)
ws[1][1].style.alignment.vertical = 'top'
ws[1][1].style.alignment.horizontal = 'right'
ws[1][1].style.alignment.rotation = 90
ws[1][1].style.alignment.wrap_text = True
ws[1][1].style.borders.top.color = Color(255, 0, 0)
ws[1][1].style.borders.right.style = '-.'
Each attribute also has constructors for implementing via set_cell_style().
The following border styles are available: .-, ..-, --, .., =, ., medium -., medium -.., medium --, /-., _
Setting row heights and column widths
Row heights and column widths are set using the size attribute in Style. Appropriate values are:
-1for auto-fit0for hidden- Any other value for the appropriate size.
For example, to hide column B:
from pyexcelerate import Workbook, Color, Style, Fill
from datetime import datetime
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws.set_col_style(2, Style(size=0))
wb.save("output.xlsx")
Linked styles
PyExcelerate supports using style objects instead manually setting each attribute as well. This permits you to modify the style at a later time.
from pyexcelerate import Workbook, Font
wb = Workbook()
ws = wb.new_sheet("sheet name")
ws[1][1].value = 1
font = Font(bold=True, italic=True, underline=True, strikethrough=True)
ws[1][1].style.font = font
wb.save("output.xlsx")
Pandas DataFrames
PyExcelerate does not support directly passing a Pandas DataFrame as the data argument to a new worksheet. If the sheet does not require having the headers rendered, the most efficient solution is:
ws = wb.new_sheet("sheet name", data=df.values.tolist())
Note that the conversion .tolist() is faster as PyExcelerate has some optimizations surrounding data that's provided in lists. If the sheet needs to have headers rendered, consider asking the Pandas maintainers to integrate PyExcelerate, use a transformation function, or convert your DataFrame to a list with the headers included.
Packaging with PyInstaller
PyInstaller is the only packager officially supported by PyExcelerate. Copy hook-pyexcelerate.Writer.py to your PyInstaller hooks directory.
- Authors: Kevin Wang and Kevin Zhang
- Copyright 2015 Kevin Wang, Kevin Zhang. Portions copyright Google, Inc.
- License: Simplified BSD License
- Source repository
- PyPI page
