A wrapper library to read, manipulate and write data in xlsx and xlsm format using openpyxl
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README.rst

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

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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.

Known constraints

Fonts, colors and charts are not supported.

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

Support the project

If your company has embedded pyexcel and its components into a revenue generating product, please support me on 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.

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.

Note

As to rnd_requirements.txt, usually, it is created when a dependent library is not released. Once the dependecy is installed (will be released), the future version of the dependency in the requirements.txt will be valid.

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

How to update test environment and update documentation

Additional steps are required:

  1. pip install moban
  2. git clone https://github.com/moremoban/setupmobans.git # generic setup
  3. git clone https://github.com/pyexcel/pyexcel-commons.git commons
  4. make your changes in .moban.d directory, then issue command moban

What is pyexcel-commons

Many information that are shared across pyexcel projects, such as: this developer guide, license info, etc. are stored in pyexcel-commons project.

What is .moban.d

.moban.d stores the specific meta data for the library.

Acceptance criteria

  1. Has Test cases written
  2. Has all code lines tested
  3. Passes all Travis CI builds
  4. Has fair amount of documentation if your change is complex
  5. Please update CHANGELOG.rst
  6. Please add yourself to CONTRIBUTORS.rst
  7. Agree on NEW BSD License for your contribution
.. testcode::
   :hide:

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