A wrapper library to read, manipulate and write data in ods format
Project description
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
Known constraints
Fonts, colors and charts are not supported.
Installation
You can install it 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
Support the project
If your company has embedded pyexcel and its components into a revenue generating product, please support me on patreon to maintain the project and develop it further.
If you are an individual, you are welcome to support me too on patreon and for however long you feel like to. As a patreon, you will receive early access to pyexcel related contents.
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
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
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]]}
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
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
In order to update test environment, and documentation, additional steps are required:
pip install moban
git clone https://github.com/pyexcel/pyexcel-commons.git commons
make your changes in .moban.d directory, then issue command moban
What is 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.
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.
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
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.
Change log
0.4.0 - 19.06.2017
Updated
0.3.2 - 13.04.2017
Updated
issue #8, PT288H00M00S is valid duration
0.3.1 - 02.02.2017
Added
Recognize currency type
0.3.0 - 22.12.2016
Updated
Code refactoring with pyexcel-io v 0.3.0
0.2.2 - 05.11.2016
Updated
#11, be able to consume a generator of two dimensional arrays.
0.2.1 - 31.08.2016
Added
support pagination. two pairs: start_row, row_limit and start_column, column_limit help you deal with large files.
0.2.0 - 01.06.2016
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
0.1.0 - 17.01.2016
compatibility with pyexcel-io 0.1.0
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