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.
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Fonts, colors and charts are not supported.
Nor to read password protected xls, xlsx and ods files.
You can install pyexcel-odsr via pip:
$ pip install pyexcel-odsror clone it and install it:
$ git clone https://github.com/pyexcel/pyexcel-odsr.git
$ cd pyexcel-odsr
$ python setup.py install.. testcode::
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>>> import os
>>> import sys
>>> from io import BytesIO as StringIO
>>> from collections import OrderedDict
.. testcode::
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>>> 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)
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::
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>>> 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
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]]}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::
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>>> os.unlink("huge_file.ods")
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.
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::
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>>> sheet.save_as("another_file.ods")
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 |
+-------+-------+-------+New BSD License
Development steps for code changes
- git clone https://github.com/pyexcel/pyexcel-odsr.git
- 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
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.
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
Please run:
$ make format
so as to beautify your code otherwise travis-ci may fail your unit test.
This library is based on the ods of messytables, Open Knowledge Foundation Ltd.
.. testcode::
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>>> import os
>>> os.unlink("your_file.ods")
>>> os.unlink("another_file.ods")