Readme
Accelerated Excel XLSX writing library for Python
master: |build-status-master| dev: |build-status-dev| test coverage: |coverage-status|
Kevin Wang <https://github.com/kevmo314>__ and Kevin Zhang <https://github.com/kz26>__Source repository <https://github.com/kz26/PyExcelerate>__PyPI page <https://pypi.python.org/pypi/PyExcelerate>__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 2.6, 2.7, 3.3, 3,4, and 3.5.
::
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.
Fastest
^^^^^^^
::
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")
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: * -1 for auto-fit * 0 for
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")
Hidden sheet
~~~~~~~~~~~~
PyExcelerate supports adding hidden sheets. Note that the first sheet cannot be hidden.
::
from pyexcelerate import Workbook
wb = Workbook()
ws = wb.new_sheet("visible sheet")
ws = wb.new_sheet("hidden sheet", hidden=True)
wb.save("output.xlsx")
Packaging with PyInstaller
--------------------------
PyInstaller is the only packager officially supported by PyExcelerate.
Copy hook-pyexcelerate.Writer.py to your PyInstaller hooks directory.
Support
-------
Please use the GitHub Issue Tracker and pull request system to report
bugs/issues and submit improvements/changes, respectively. **Pull
requests *must* be based against the dev branch - if not, we will reject the PR
and ask you to rebase against the correct branch.** All nontrivial
changes to code should be accompanied by a test when appropriate. We use
the Nose testing framework.
.. |build-status-master| image:: https://travis-ci.org/kz26/PyExcelerate.png?branch=master
:target: https://travis-ci.org/kz26/PyExcelerate
.. |build-status-dev| image:: https://travis-ci.org/kz26/PyExcelerate.png?branch=dev
:target: https://travis-ci.org/kz26/PyExcelerate
.. |coverage-status| image:: https://coveralls.io/repos/kz26/PyExcelerate/badge.png
:target: https://coveralls.io/r/kz26/PyExcelerate
FAQs
Accelerated Excel XLSX Writing Library for Python 2/3
We found that PyExcelerate demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Product
Socket now supports four distinct alert actions instead of the previous two, and alert triaging allows users to override the actions taken for all individual alerts.
Security News
Polyfill.io has been serving malware for months via its CDN, after the project's open source maintainer sold the service to a company based in China.
Security News
OpenSSF is warning open source maintainers to stay vigilant against reputation farming on GitHub, where users artificially inflate their status by manipulating interactions on closed issues and PRs.