pyexcel-ods3 - Let you focus on data, instead of ods format

pyexcel-ods3 is a tiny wrapper library to read, manipulate and write data in ods format. You are likely to use pyexcel together with this library. pyexcel-ods is a sister library that depends on GPL licensed odfpy. pyexcel-odsr is the other sister library that has no external dependency but do ods reading only

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-ods3 via pip:

$ pip install pyexcel-ods3

or clone it and install it:

$ git clone https://github.com/pyexcel/pyexcel-ods3.git
$ cd pyexcel-ods3
$ python setup.py install

Usage

As a standalone library

>>> 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 ods file

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

>>> 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:

>>> 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:

>>> 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

>>> notneeded=io.seek(0)

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

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 and it gives better performance in pagination.

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]]}

>>> 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 |
+-------+-------+-------+

Writing to an ods file

Here is the sample code:

>>> 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 |
+-------+-------+-------+

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("ods", 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

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.

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, please issue this command:

> test.bat

Before you commit

Please run:

$ make format

so as to beautify your code otherwise your build may fail your unit test.

Installation Note

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.

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

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