Abstract: Processing of large quantitities of data from bioinformatics domain pose significant challenge for contemporary computing systems. For that reason, it is important to employ all hardware ...

This project includes simple scripts to show how to write and read data from a PostgreSQL database using Python and pandas. The database is assumed to run in a local container (e.g., Docker).

Parallelization is a powerful technique to speed up computations by distributing tasks across multiple CPU cores or threads. This project evaluates the performance of four popular Python ...

Python is convenient because it is easy to program and has a rich library, but its only weak point is that execution is very slow outside of compiled libraries like Numpy. So, I will measure the ...

The larger our dataset, the longer it takes to process. While we can wait for the whole process to end, sometimes it takes too much time and needs to meet the business standards. That’s why there are ...