Optimizing Memory Usage of Python Applications

• DAWG

  1 294 0.0 C++

  DAFSA-based dictionary-like read-only objects for Python. Based on `dawgdic` C++ library. (by pytries)

  

Optimizing applications is difficult problem in general. It also heavily depends on the task at hand as well as the type of data itself. In this article we looked at common ways to find memory usage issues and some options for fixing them. There are however many other approaches to reducing memory footprint of an application. This includes trading accuracy for storage space by using probabilistic data structures such as bloom filters or HyperLogLog. Another option is using tree-like data structures like DAWG or Marissa trie which are very efficient at storing string data.

• marisa-trie

  1 1,013 5.9 Cython

  Static memory-efficient Trie-like structures for Python based on marisa-trie C++ library.

  

Optimizing applications is difficult problem in general. It also heavily depends on the task at hand as well as the type of data itself. In this article we looked at common ways to find memory usage issues and some options for fixing them. There are however many other approaches to reducing memory footprint of an application. This includes trading accuracy for storage space by using probabilistic data structures such as bloom filters or HyperLogLog. Another option is using tree-like data structures like DAWG or Marissa trie which are very efficient at storing string data.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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