Uwe’s Blog

My writing about data engineering, opensource development, general programming and thoughts about engineering culture.

  • Data Science I/O - A baseline benchmark for 2019

    Data Science and Machine Learning are tasks that have their own requirements on I/O. As many other tasks, they start out on tabular data in most cases. In contrast to a typical reporting task, they don’t work on aggregates but require the data on the most granular level. Some machine learning algorithms are able to directly work on aggregates but...

  • PyFlame: profiling running Python processes

    Identifying performance bottlenecks in long-running processes often involves careful instrumentation ahead or guessing where the root of the problem may be. A very welcome set of tools are the ones that help you diagnose problems of live systems without modifying them. One important tool I recently came across is the pyflame profiler.

  • Use Numba to work with Apache Arrow in pure Python

    Apache Arrow is an in-memory memory format for columnar data. In more “plain” English, it is a standard on how to store DataFrames/tables in memory, independent of the programming language. One of its most prominent uses is for the @pandas_udf decorator in Apache Spark to move data quickly between Scala and Python/pandas.

  • AHL Python Hackathon April 2018

    Three weeks ago MAN AHL organised an opensource hackathon at their London office. As part of the Hackathon people should contribute to one of the PyData artifacts they regularly use. To support them in making their first contribution, AHL also coordinated that several core committers of opensource projects were present at the event. I joined in as the representative...