Sustainable Coding: Why Your "Hello World" Matters
summary
A tiny Python loop that pings a server every 500 ms and a for loop that reallocates a list each iteration are shown to multiply waste at scale, costing CPU cycles, electricity, cooling water and measurable CO2. CodeCarbon wraps processes, estimates energy from CPU/RAM/GPU and hardware specs and plugs into local runs and CI/CD to show before/after gains. Practical fixes include avoiding heavyweight libraries for simple stats, choosing the right data structures and measuring changes; alternatives mentioned are Pyool, CodeCarbon, Intel RAPL and powertop.
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chapters (9)
- 0:00Sustainable coding intro
- 2:30Sustainable coding principles
- 5:21Why sustainable coding matters
- 7:06Small code choices impact
- 9:54Measuring energy waste
- 10:58CodeCarbon for tracking
- 12:44Sustainable coding tips
- 14:32AI and sustainable code
- 15:38Q&A
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