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pyexcel-ods3 is a tiny wrapper library to read, manipulate and write data in ods
format. You are likely to use pyexcel <https://github.com/pyexcel/pyexcel>__ together
with this library. pyexcel-ods <https://github.com/pyexcel/pyexcel-ods>__ is a sister
library that depends on GPL licensed odfpy.
pyexcel-odsr <https://github.com/pyexcel/pyexcel-odsr>_ is the other sister library
that has no external dependency but do ods reading only
If your company has embedded pyexcel and its components into a revenue generating
product, please support me on github, patreon <https://www.patreon.com/bePatron?u=5537627>_
or bounty source <https://salt.bountysource.com/teams/chfw-pyexcel>_ 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 <https://www.patreon.com/pyexcel/posts>_.
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.
Fonts, colors and charts are not supported.
Nor to read password protected xls, xlsx and ods files.
You can install pyexcel-ods3 via pip:
.. code-block:: bash
$ pip install pyexcel-ods3
or clone it and install it:
.. code-block:: bash
$ git clone https://github.com/pyexcel/pyexcel-ods3.git
$ cd pyexcel-ods3
$ python setup.py install
Write to an ods file
Here's the sample code to write a dictionary to an ods file:
.. code-block:: python
>>> from pyexcel_ods3 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:
.. code-block:: python
>>> from pyexcel_ods3 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"]]}
Write an ods to memory
Here's the sample code to write a dictionary to an ods file:
.. code-block:: python
>>> from pyexcel_ods3 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 ods from memory
Continue from previous example:
.. code-block:: python
>>> # 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
Special notice 30/01/2017: due to the constraints of the underlying 3rd party library, it will read the whole file before returning the paginated data. So at the end of day, the only benefit is less data returned from the reading function. No major performance improvement will be seen.
With that said, please install pyexcel-odsr <https://github.com/pyexcel/pyexcel-odsr>_
and it gives better performance in pagination.
Let's assume the following file is a huge ods file:
.. code-block:: python
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:
.. code-block:: python
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:
.. code-block:: python
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:
.. code-block:: python
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]]}
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:
.. code-block:: python
>>> 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 |
+-------+-------+-------+
Writing to an ods file
Here is the sample code:
.. code-block:: python
>>> sheet.save_as("another_file.ods")
Reading from a IO instance
You got to wrap the binary content with stream to get ods working:
.. code-block:: python
>>> # 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 |
+-------+-------+-------+
Writing to a StringIO instance
You need to pass a StringIO instance to Writer:
.. code-block:: python
>>> data = [
... [1, 2, 3],
... [4, 5, 6]
... ]
>>> io = StringIO()
>>> sheet = pe.Sheet(data)
>>> io = sheet.save_to_memory("ods", io)
>>> # then do something with io
>>> # In reality, you might give it to your http response
>>> # object for downloading
New BSD License
Development steps for code changes
#. git clone https://github.com/pyexcel/pyexcel-ods3.git #. cd pyexcel-ods3
Upgrade your setup tools and pip. They are needed for development and testing only:
#. pip install --upgrade setuptools pip
Then install relevant development requirements:
#. pip install -r rnd_requirements.txt # if such a file exists #. pip install -r requirements.txt #. pip install -r tests/requirements.txt
Once you have finished your changes, please provide test case(s), relevant documentation and update changelog.yml
.. 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.
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, please issue this command::
> test.bat
Please run::
$ make format
so as to beautify your code otherwise your build may fail your unit test.
The installation of lxml will be tricky on Windows platform. It is recommended that you download a lxml's own windows installer instead of using pip.
In alphabetical order:
Benedikt Waldvogel <https://github.com/bwaldvogel>_Mateusz Konieczny <https://github.com/matkoniecz>_Michael K. <https://github.com/michael-k>_Stephen J. Fuhry <https://github.com/fuhrysteve>_Vincent Raspal <https://github.com/vinraspa>_added
#. #28 <https://github.com/pyexcel/pyexcel-ods3/issues/28>_: support datetime
added
#. new style reader and writer plugins. works with pyexcel-io v0.6.2
added
#. pyexcel#57 <https://github.com/pyexcel/pyexcel/issues/57>_, long type will
not be written in ods. please use string type. And if the integer is equal or
greater than 10 to the power of 16, it will not be written either in ods. In
both situation, IntegerPrecisionLossError will be raised.
updated
#. pyexcel pyexcel#105 <https://github.com/pyexcel/pyexcel/issues/105>_,
remove gease from setup_requires, introduced by 0.5.1.
#. remove python2.6 test support
#. update its dependecy on pyexcel-io to 0.5.3
added
#. pyexcel#103 <https://github.com/pyexcel/pyexcel/issues/103>_, include
LICENSE file in MANIFEST.in, meaning LICENSE file will appear in the released
tar ball.
Updated
#. put dependency on pyexcel-io 0.5.0, which uses cStringIO instead of StringIO. Hence, there will be performance boost in handling files in memory.
Relocated
#. All ods type conversion code lives in pyexcel_io.service module
Updated
#. update dependency to use pyexcel-ezodf v0.3.3 as ezodf 0.3.2 has the bug <https://github.com/pyexcel/pyexcel-ezodf/issues/1>_, cannot handle file
alike objects and has not been updated for 2 years.
Updated
#. pyexcel#14 <https://github.com/pyexcel/pyexcel/issues/14>, close file
handle
#. pyexcel-io plugin interface now updated to use lml <https://github.com/chfw/lml>.
Updated
#. issue pyexcel#8 <https://github.com/pyexcel/pyexcel/issues/8>_,
PT288H00M00S is valid duration
Added
#. Recognize currency type
Updated
#. Code refactoring with pyexcel-io v 0.3.0
Updated
#. pyexcel#11 <https://github.com/pyexcel/pyexcel/issues/11>_, be able to
consume a generator of two dimensional arrays.
Added
#. support pagination. two pairs: start_row, row_limit and start_column, column_limit help you deal with large files.
Added
#. By default, float will be converted to int where fits. auto_detect_int,
a flag to switch off the autoatic conversion from float to int.
#. 'library=pyexcel-ods3' was added so as to inform pyexcel to use it instead of
other libraries, in the situation where multiple plugins for the same file
type are installed
Updated
#. support the auto-import feature of pyexcel-io 0.2.0 #. compatibility with pyexcel-io 0.1.0
Updated
#. support the auto-import feature of pyexcel-io 0.2.0 #. compatibility with pyexcel-io 0.1.0
FAQs
A wrapper library to read, manipulate and write data in ods format
We found that pyexcel-ods3 demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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