Understanding Caching in Python
Chirag Shah (~avidLearnerInProgress) |
A cache can be easily understood as a saved answer to a question. Caching can speed up an application if a computationally complex question is asked frequently. Instead of the computing the answer over and over, we can use the previously cached answer.
Caching is an important component while scaling applications which are to be used by many users. It solves various problems related to cost and latency. Usually it takes more time to retrieve data from DB rather than cache. Using a cache to avoid recomputing data or accessing a slow database provides us with a great performance boost.
I will describe in depth the different methods of Caching, their pros and cons. This talk will help developers focus on their code before scaling their applications. It will provide immense performance improvements with this simple concept.
Outcomes: The novice audience will be able to understand basic Caching Mechanisms. They will be able to utiilize their knowledge which will serve pivotal while scaling applications
[HTML_REMOVED]Contents to be covered in talk:[HTML_REMOVED]
Local Caching: What is it, how to do it, example, built-in Python libraries: (using cachetools), advantages, dis-advantages
Memoization: What is it, pseudo-code algorithm, implementation using example, built-in Python libraries: (using lru_cache), advantages, dis-advantages
Distributed Caching: What is it, techniques: (using memcached, using pymemcache)
- Initial 10 minutes: Introduction to Caching and its various techniques.
- 10 - 20 minutes: Examples and code walk through for various techniques.
- 20 - 25 minutes: Comparative analysis of how caching is better than non-scaled applications.
- 25 - 30 minutes: Q&A session
- Basics of Python
Github repository links will be updated soon.
- I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology.
- Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time.
- I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github since a while.
- I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech and Investment Banking.