xlfunctions 0.2.2

Supported Functions

• ABS

• AVERAGE

• CHOOSE

• CONCAT

• COUNT

• COUNTA

• DATE

• IRR

• LN

  • Python Math.log() differs from Excel LN. Currently returning Math.log()

• MAX

• MID

• MIN

• MOD

• NPV

• PMT

• POWER

• RIGHT

• ROUND

• ROUNDDOWN

• ROUNDUP

• SLN

• SQRT

• SUM

• SUMPRODUCT

• TODAY

• VLOOKUP

  • Exact match only

• XNPV

• YEARFRAC

  • Basis 1, Actual/actual, is only within 3 decimal places

Run Tests

Setup your environment:

virtualenv -p 3.7 ve
ve/bin/pip install -e .[test]

From the root xlfunctions directory:

ve/bin/python -m unittest discover -p "test_*.py"

Or simply run tox:

tox

Adding/Registering Excel Functions

Excel functions can be added by any code using the the xlfunctions.xl.register() decorator. Here is a simple example:

from xlfunctions import xl

@xl.register()
@xl.validate_args
def ADDONE(num: xl.Number):
    return num + 1

The v@xl.alidate_args decorator will ensure that the annotated arguments are converted and validated. For example, even if you pass in a string, it is converted to a number (in typical Excel fashion):

>>> ADDONE(1):
2
>>> ADDONE('1'):
2

If you would like to contribute functions, please create a pull request. All new functions should be accompanied by sufficient tests to cover the functionality.

Excel number precision

Excel number precision is a complex discussion.

It has been discussed in a Wikipedia page.

The fundamentals come down to floating point numbers and a contention between how they are represented in memory Vs how they are stored on disk Vs how they are presented on screen. A Microsoft article explains the contention.

This project is attempting to take care while reading numbers from the Excel file to try and remove a variety of representation errors.

Further work will be required to keep numbers in-line with Excel throughout different transformations.

From what I can determine this requires a low-level implementation of a numeric datatype (C or C++, Cython??) to replicate its behaviour. Python built-in numeric types don’t replicate appropriate behaviours.

0.2.2 (2020-05-28)

• Implement a few more operators for the Excel Number type.

0.2.1 (2020-05-28)

• Fix an error message to refer to the righ type.

• Added a test to ensure SUM() works with arrays containing Excel data types.

0.2.0 (2020-05-28)

• Support for delayed argument execution by introducing expressions that can be evaluated when needed. This is required to support efficient logical operator implementations. For example, when an “if”-condition is true, the false value does not need to be computed.

• Implemented all Excel types.

  • Better control of logic differences between Python and Excel. (Compare with None and blank handling, for example.)

  • Tight control of type casting with very situation-specific edge case handling. (For example, when a string representing a boolean will evaluate as a boolean and when not. For example, int(bool(‘False’)) == 0 in Excel but AND(‘False’, True) == True.

  • Make date/time its own type.

• Moved errors back into their own module.

• Moved criteria parsing into its own module.

• Made function signature validation and conversion much more consistent allowing a lot less error handling and data conversion in the function body.

0.1.0 (2020-05-25)

• Complete rewrite of library.

  • Introduced a function registry that can be used to extend the function library in third party software.

  • Removed excessive use of static methods and converted all Excel functions to simple Python functions (with some decorators).

  • Organized functions into categories based on Microsoft documentation.

  • Proper argument validation and conversion where supported.

  • Many functions are now much more flexible with their types and more correctly mimic Excel behavior.

  • Use of dateutil and yearfrac libraries to do complicated date calculations instead of implementing it from scratch.

  • Achieved 100% test coverage.

0.0.3b (2020-05-11)

• Initial release.