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Excel table reader library.

Project description

About xlref

xlref is an useful library to capture by a simple reference (e.g., A1(RD):..:RD) a table with non-empty cells from Excel-sheets when its exact position is not known beforehand.

This code was inspired by the xleash module of the pandalone library. The reason of developing a similar tool was to have a smaller library to install and improve the performances of reading .xlsx files.

Installation

To install it use (with root privileges):

$ pip install xlref

Or download the last git version and use (with root privileges):

$ python setup.py install

Tutorial

A typical example is capturing a table with a “header” row and convert into a dictionary. The code below shows how to do it:

>>> import xlref as xl
>>> _ref = 'excel.xlsx#ref!A1(RD):RD[%s]'
>>> ref = xl.Ref(_ref % '"dict"')
>>> ref.range  # Captured range.
B2:C24
>>> values = ref.values; values  # Captured values.
{...}
>>> values['st-cell-move']
'#D5(RU):H1(DL)'

You can notice from the code above that all the values of the dictionary are references. To parse it recursively, there are two options:

  1. add the “recursive” filter before the “dict”:

    >>> values = xl.Ref(_ref % '"recursive", "dict"').values
    >>> values['st-cell-move'].tolist()
    [[1.0, 2.0, 3.0],
     [4.0, 5.0, 6.0],
     [7.0, 8.0, 9.0]]
    
  2. apply a filter onto dictionary’ values using the extra

    functionality of the “dict” filter:

    >>> values = xl.Ref(_ref % '{"fun": "dict", "value":"ref"}').values
    >>> values['st-cell-move'].tolist()
    [[1.0, 2.0, 3.0],
     [4.0, 5.0, 6.0],
     [7.0, 8.0, 9.0]]
    

You have also the possibility to define and use your custom filters as follows:

>>> import numpy as np
>>> xl.FILTERS['my-filter'] = lambda parent, x: np.sum(x)
>>> xl.Ref('#D5(RU):H1(DL)["my-filter"]', ref).values
45.0

An alternative way is to use directly the methods of the filtered results as follows:

>>> xl.Ref('#D5(RU):H1(DL)["sum"]', ref).values
45.0

Project details


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