Speaker
Description
The term «architecture» in software has numerous definitions. Ultimately it defines whether your analysis code will be extensible and maintainable. We propose an architecture based on the functional style and separation of data, logic and presentation. It is implemented in a free software framework Lena.
Lena is a general data analysis framework in Python, named after a great Siberian river. It allows usage of any Python constructs and functions, but structures the analysis into reusable sequences and elements. It natively supports metadata (which is important for modern data analysis). It employs lazy evaluation, which makes it suitable for processing data which would not fit into memory, in particular, for big data analysis.
The talk will be of primary interest to those who write large programs and face architectural challenges and who need to automatically create many similar plots. The audience will get a powerful tool, which would make their code structured and beautiful, or understand strengths and weaknesses of an alternative approach to data analysis in Python.
