pyexcel-xls - Let you focus on data, instead of xls format

pyexcel-xls is a tiny wrapper library to read, manipulate and write data in xls format and it can read xlsx and xlsm fromat. You are likely to use it with pyexcel.

New flag: detect_merged_cells allows you to spread the same value among all merged cells. But be aware that this may slow down its reading performance.

New flag: skip_hidden_row_and_column allows you to skip hidden rows and columns and is defaulted to True. It may slow down its reading performance. And it is only valid for 'xls' files. For 'xlsx' files, please use pyexcel-xlsx.

Warning

xls file cannot contain more than 65,000 rows. You are risking the reputation of yourself/your company/ your country if you keep using xls and are not aware of its row limit.

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-xls via pip:

$ pip install pyexcel-xls

or clone it and install it:

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

Usage

As a standalone library

.. testcode::
   :hide:

    >>> 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 xls file

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

>>> from pyexcel_xls 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.xls", data)

Read from an xls file

Here's the sample code:

>>> from pyexcel_xls import get_data
>>> data = get_data("your_file.xls")
>>> import json
>>> print(json.dumps(data))
{"Sheet 1": [[1, 2, 3], [4, 5, 6]], "Sheet 2": [["row 1", "row 2", "row 3"]]}

Write an xls to memory

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

>>> from pyexcel_xls 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 xls from memory

Continue from previous example:

>>> # This is just an illustration
>>> # In reality, you might deal with xls file upload
>>> # where you will read from requests.FILES['YOUR_XLS_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 xls 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.xls", sheetx)

And let's pretend to read partial data:

>>> partial_data = get_data("huge_file.xls", 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.xls", 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.xls",
...     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::
   :hide:

   >>> os.unlink("huge_file.xls")

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 xls format, installing it is enough.

Reading from an xls file

Here is the sample code:

>>> import pyexcel as pe
>>> sheet = pe.get_book(file_name="your_file.xls")
>>> sheet
Sheet 1:
+---+---+---+
| 1 | 2 | 3 |
+---+---+---+
| 4 | 5 | 6 |
+---+---+---+
Sheet 2:
+-------+-------+-------+
| row 1 | row 2 | row 3 |
+-------+-------+-------+

Writing to an xls file

Here is the sample code:

>>> sheet.save_as("another_file.xls")

Reading from a IO instance

You got to wrap the binary content with stream to get xls working:

>>> # This is just an illustration
>>> # In reality, you might deal with xls file upload
>>> # where you will read from requests.FILES['YOUR_XLS_FILE']
>>> xlsfile = "another_file.xls"
>>> with open(xlsfile, "rb") as f:
...     content = f.read()
...     r = pe.get_book(file_type="xls", 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("xls", 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

1. git clone https://github.com/pyexcel/pyexcel-xls.git
2. cd pyexcel-xls

Upgrade your setup tools and pip. They are needed for development and testing only:

1. pip install --upgrade setuptools pip

Then install relevant development requirements:

1. pip install -r rnd_requirements.txt # if such a file exists
2. pip install -r requirements.txt
3. 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.

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

Before you commit

Please run:

$ make format

so as to beautify your code otherwise travis-ci may fail your unit test.

Known Issues

• If a zero was typed in a DATE formatted field in xls, you will get "01/01/1900".
• If a zero was typed in a TIME formatted field in xls, you will get "00:00:00".

.. testcode::
   :hide:

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