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Python package for symbolic propagation of uncertainties with latex interface
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Python package for symbolic propagation of uncertainties with Latex binding.

This project was archived a while ago. This might be an attempt to revive it. Maabara package currently still is not under active development. You can continue using it on your own risk. If you are interested in continuing the development, feel free to use the source code and documentation provided in this repository. For further information please visit (original creator's website, for the documentation look at

Maabara extends uncertainties package and allows you to calculate and document error propagation in one step. Type your equation once, get the result and its uncertainty including calculation specification - ready in Latex markup. It's easy to create Latex tables from the results. Moreover the data module provides functions for estimation of uncertainty, fitting with error bars, comparison with literature values and more.


  • Symbolic error propagation in Latex markup
  • Easy creation of Latex tables
  • Weighted average, deviation from statistical data, fitting with deviation etc.


The package uses uncertainties, sympy and numpy.


Maabara follows Sematic Versioning.

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