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CCC Python Course

Python constant-factor engineering at scale

Stage
7
Module
M7.12
Lessons
1

In this module

  • Identify performance bottlenecks in Python programs that run on PyPy.
  • Use flat 1D lists and parallel lists instead of tuples and dictionaries.
  • Encode integers into single values to reduce memory and cache misses.
  • Read input in one call, join output, and measure on maximum-size test cases.
  • Know when further optimisation returns diminishing marks and when to stop.

Before this module

M2.9Complexity analysis and deriving the target from NM3.10Fast input and outputM5.7Iterative DFS and recursion elimination

Lessons

  1. 1Python constant-factor engineering at scale

Practice

Try these on the judge. Each link opens the problem on DMOJ.

  1. 2019 S4
    Tourism (opens on DMOJ in a new tab) DMOJ

    Find the minimum cost to process a stream of updates to a flat array.

    Why DMOJ: An older large-input problem, good for practicing fast I/O and tight loops.

  2. 2015 S5
    Greedy For Pies (opens on DMOJ in a new tab) DMOJ

    Compute the shortest meeting time for scheduled intervals.

    Why DMOJ: An older problem that builds timing-critical fast-I/O and loop skills.