pyexcel-odsr

a plugin to pyexcel and provides the capbility to read data in odsformats using tailored messytables.


Keywords
python, excel, ods, fods
License
BSD-3-Clause
Install
pip install pyexcel-odsr==0.6.0

Documentation

pyexcel-odsr - Let you focus on data, instead of ods format

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pyexcel-odsr is a specialized ods reader based on tailored ods reader from messytables. You are likely to use it with pyexcel. Differring from pyexcel-ods and pyexcel-ods3 in handling ods file, this library could read partial content from a huge ods file.

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.

Installation

You can install pyexcel-odsr via pip:

$ pip install pyexcel-odsr

or clone it and install it:

$ git clone https://github.com/pyexcel/pyexcel-odsr.git
$ cd pyexcel-odsr
$ 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


.. testcode::
   :hide:

    >>> from pyexcel_ods 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.ods", data)


Read from an ods file

Here's the sample code:

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

    >>> 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)
    >>> unused = io.seek(0)
    >>> # do something with the io
    >>> # In reality, you might give it to your http response
    >>> # object for downloading




Read from an ods from memory

Continue from previous example:

>>> # This is just an illustration
>>> # In reality, you might deal with ods file upload
>>> # where you will read from requests.FILES['YOUR_ODS_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 ods 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.ods", sheetx)

And let's pretend to read partial data:

>>> partial_data = get_data("huge_file.ods", 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.ods", 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.ods",
...     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.ods")


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 ods format, installing it is enough.

Reading from an ods file

Here is the sample code:

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

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



Reading from a IO instance

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

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

License

New BSD License

Developer guide

Development steps for code changes

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

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

Before you commit

Please run:

$ make format

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

Credits

This library is based on the ods of messytables, Open Knowledge Foundation Ltd.

.. testcode::
   :hide:

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