a plugin to pyexcel and provides the capbility to read data in ods formats using tailored messytables.
Project description
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.
Known constraints
Fonts, colors and charts are not supported.
Installation
You can install it 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
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
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"]]}
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]]}
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 |
+-------+-------+-------+
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
cd pyexcel-odsr
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
Credits
This library is based on the ods of messytables, Open Knowledge Foundation Ltd.
Change log
0.4.0 - 19.06.2017
Updated
Updated to use lml interface
0.3.2 - 07.05.2017
Updated
issue #2, not all texts in a multi-node cell were extracted.
0.3.1 - 13.04.2017
Updated
issue #1, PT288H00M00S is valid duration
0.3.0 - 02.02.2017
initial release. It has all functionalities of pyexcel-ods and pyexcel-ods3. Specially, it supports partial reading of the ods file. When dealing with big data file, this capability enables pagination feature to indeed read partial files.
Project details
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