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Big O analysis tip Big O notation describes the rate of increase of an algorithm. It could be possible for O(N) code to be faster than 0(1) code for *some inputs*. O(N^2) sorting algorithms are generally good for small inputs.
If you don't have a job, get something to pay the bills. And design a plan to transition to a better job. Ex: use the tools you need for the next job to build something at your current job. You'll develop skills while being paid and help your team
GCP has machine families with predefined amounts of RAM and CPU - General. Best price/perf for many tasks - Memory-optimized. For memory-intensive tasks - Compute-optimized. Highest perf/core - Shared-core. Cost-effective for small apps You can create custom machines too
Interview question. Write a function to check if a string s is a palindrome Python be like: return s == s[::-1]
Do not code if you are tired You'll end up redoing what you did Double waste of time
If you don't get comments in a pull request, your code is very good Or very bad
Writing code to make your colleagues think how brilliant you are is the stupidest mistake a programmer can make.
