pyexcel-xls 0.4.0

A wrapper library to read, manipulate and write data in xls format. It reads xlsx and xlsm 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.

Known constraints

Fonts, colors and charts are not supported.

Installation

You can install it 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

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 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]]}

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

In order to update test environment, and documentation, additional steps are required:

1. pip install moban

2. git clone https://github.com/pyexcel/pyexcel-commons.git commons

3. 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

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”.

Change log

0.4.0 - 19.06.2017

Updated

1. #15, close file handle

2. pyexcel-io plugin interface now updated to use lml.

0.3.3 - 30/05/2017

Updated

1. #18, pass on encoding_override and others to xlrd.

0.3.2 - 18.05.2017

Updated

1. #16, allow mmap to be passed as file content

0.3.1 - 16.01.2017

Updated

1. #14, Python 3.6 - cannot use LOCALE flag with a str pattern

2. fix its dependency on pyexcel-io 0.3.0

0.3.0 - 22.12.2016

Updated

1. #13, alert on empyty file content

2. Support pyexcel-io v0.3.0

0.2.3 - 20.09.2016

Updated

1. #10, To support generator as member of the incoming two dimensional data

0.2.2 - 31.08.2016

Added

1. support pagination. two pairs: start_row, row_limit and start_column, column_limit help you deal with large files.

0.2.1 - 13.07.2016

Added

1. #9, skip_hidden_sheets is added. By default, hidden sheets are skipped when reading all sheets. Reading sheet by name or by index are not affected.

0.2.0 - 01.06.2016

Added

1. 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.

2. ‘library=pyexcel-xls’ was added so as to inform pyexcel to use it instead of other libraries, in the situation where there are more than one plugin for a file type, e.g. xlsm

Updated

1. support the auto-import feature of pyexcel-io 0.2.0

2. xlwt is now used for python 2 implementation while xlwt-future is used for python 3

0.1.0 - 17.01.2016

Added

1. Passing “streaming=True” to get_data, you will get the two dimensional array as a generator

2. Passing “data=your_generator” to save_data is acceptable too.