pyexcel-xlsx - Let you focus on data, instead of xlsx format

pyexcel-xlsx is a tiny wrapper library to read, manipulate and write data in xlsx and xlsm format using read_only mode reader, write_only mode writer from openpyxl. You are likely to use it with pyexcel.

Please note:

1. auto_detect_int flag will not take effect because openpyxl detect integer in python 3 by default.
2. skip_hidden_row_and_column will get a penalty where read_only mode cannot be used.

Support the project

If your company has embedded pyexcel and its components into a revenue generating product, please support me on github, patreon or bounty source to maintain the project and develop it further.

If you are an individual, you are welcome to support me too and for however long you feel like. As my backer, you will receive early access to pyexcel related contents.

And your issues will get prioritized if you would like to become my patreon as pyexcel pro user.

With your financial support, I will be able to invest a little bit more time in coding, documentation and writing interesting posts.

Known constraints

Fonts, colors and charts are not supported.

Nor to read password protected xls, xlsx and ods files.

Installation

You can install pyexcel-xlsx via pip:

$ pip install pyexcel-xlsx

or clone it and install it:

$ git clone https://github.com/pyexcel/pyexcel-xlsx.git
$ cd pyexcel-xlsx
$ python setup.py install

Usage

As a standalone library

.. testcode::
   :hide:

    >>> import os
    >>> import sys
    >>> if sys.version_info[0] < 3:
    ...     from StringIO import StringIO
    ... else:
    ...     from io import BytesIO as StringIO
    >>> PY2 = sys.version_info[0] == 2
    >>> if PY2 and sys.version_info[1] < 7:
    ...      from ordereddict import OrderedDict
    ... else:
    ...     from collections import OrderedDict

Write to an xlsx file

Here's the sample code to write a dictionary to an xlsx file:

>>> from pyexcel_xlsx import save_data
>>> data = OrderedDict() # from collections import OrderedDict
>>> data.update({"Sheet 1": [[1, 2, 3], [4, 5, 6]]})
>>> data.update({"Sheet 2": [["row 1", "row 2", "row 3"]]})
>>> save_data("your_file.xlsx", data)

Read from an xlsx file

Here's the sample code:

>>> from pyexcel_xlsx import get_data
>>> data = get_data("your_file.xlsx")
>>> import json
>>> print(json.dumps(data))
{"Sheet 1": [[1, 2, 3], [4, 5, 6]], "Sheet 2": [["row 1", "row 2", "row 3"]]}

Write an xlsx to memory

Here's the sample code to write a dictionary to an xlsx file:

>>> from pyexcel_xlsx import save_data
>>> data = OrderedDict()
>>> data.update({"Sheet 1": [[1, 2, 3], [4, 5, 6]]})
>>> data.update({"Sheet 2": [[7, 8, 9], [10, 11, 12]]})
>>> io = StringIO()
>>> save_data(io, data)
>>> # do something with the io
>>> # In reality, you might give it to your http response
>>> # object for downloading

Read from an xlsx from memory

Continue from previous example:

>>> # This is just an illustration
>>> # In reality, you might deal with xlsx file upload
>>> # where you will read from requests.FILES['YOUR_XLSX_FILE']
>>> data = get_data(io)
>>> print(json.dumps(data))
{"Sheet 1": [[1, 2, 3], [4, 5, 6]], "Sheet 2": [[7, 8, 9], [10, 11, 12]]}

Pagination feature

Let's assume the following file is a huge xlsx file:

>>> huge_data = [
...     [1, 21, 31],
...     [2, 22, 32],
...     [3, 23, 33],
...     [4, 24, 34],
...     [5, 25, 35],
...     [6, 26, 36]
... ]
>>> sheetx = {
...     "huge": huge_data
... }
>>> save_data("huge_file.xlsx", sheetx)

And let's pretend to read partial data:

>>> partial_data = get_data("huge_file.xlsx", start_row=2, row_limit=3)
>>> print(json.dumps(partial_data))
{"huge": [[3, 23, 33], [4, 24, 34], [5, 25, 35]]}

And you could as well do the same for columns:

>>> partial_data = get_data("huge_file.xlsx", start_column=1, column_limit=2)
>>> print(json.dumps(partial_data))
{"huge": [[21, 31], [22, 32], [23, 33], [24, 34], [25, 35], [26, 36]]}

Obvious, you could do both at the same time:

>>> partial_data = get_data("huge_file.xlsx",
...     start_row=2, row_limit=3,
...     start_column=1, column_limit=2)
>>> print(json.dumps(partial_data))
{"huge": [[23, 33], [24, 34], [25, 35]]}

.. testcode::
   :hide:

   >>> os.unlink("huge_file.xlsx")

As a pyexcel plugin

No longer, explicit import is needed since pyexcel version 0.2.2. Instead, this library is auto-loaded. So if you want to read data in xlsx format, installing it is enough.

Reading from an xlsx file

Here is the sample code:

>>> import pyexcel as pe
>>> sheet = pe.get_book(file_name="your_file.xlsx")
>>> sheet
Sheet 1:
+---+---+---+
| 1 | 2 | 3 |
+---+---+---+
| 4 | 5 | 6 |
+---+---+---+
Sheet 2:
+-------+-------+-------+
| row 1 | row 2 | row 3 |
+-------+-------+-------+

Writing to an xlsx file

Here is the sample code:

>>> sheet.save_as("another_file.xlsx")

Reading from a IO instance

You got to wrap the binary content with stream to get xlsx working:

>>> # This is just an illustration
>>> # In reality, you might deal with xlsx file upload
>>> # where you will read from requests.FILES['YOUR_XLSX_FILE']
>>> xlsxfile = "another_file.xlsx"
>>> with open(xlsxfile, "rb") as f:
...     content = f.read()
...     r = pe.get_book(file_type="xlsx", file_content=content)
...     print(r)
...
Sheet 1:
+---+---+---+
| 1 | 2 | 3 |
+---+---+---+
| 4 | 5 | 6 |
+---+---+---+
Sheet 2:
+-------+-------+-------+
| row 1 | row 2 | row 3 |
+-------+-------+-------+

Writing to a StringIO instance

You need to pass a StringIO instance to Writer:

>>> data = [
...     [1, 2, 3],
...     [4, 5, 6]
... ]
>>> io = StringIO()
>>> sheet = pe.Sheet(data)
>>> io = sheet.save_to_memory("xlsx", io)
>>> # then do something with io
>>> # In reality, you might give it to your http response
>>> # object for downloading

License

New BSD License

Developer guide

Development steps for code changes

1. git clone https://github.com/pyexcel/pyexcel-xlsx.git
2. cd pyexcel-xlsx

Upgrade your setup tools and pip. They are needed for development and testing only:

1. pip install --upgrade setuptools pip

Then install relevant development requirements:

1. pip install -r rnd_requirements.txt # if such a file exists
2. pip install -r requirements.txt
3. pip install -r tests/requirements.txt

Once you have finished your changes, please provide test case(s), relevant documentation and update CHANGELOG.rst.

How to test your contribution

Although nose and doctest are both used in code testing, it is adviable that unit tests are put in tests. doctest is incorporated only to make sure the code examples in documentation remain valid across different development releases.

On Linux/Unix systems, please launch your tests like this:

$ make

On Windows systems, please issue this command:

> test.bat

Before you commit

Please run:

$ make format

so as to beautify your code otherwise travis-ci may fail your unit test.

.. testcode::
   :hide:

   >>> import os
   >>> os.unlink("your_file.xlsx")
   >>> os.unlink("another_file.xlsx")