Should I Fully Convert My Python Code to C/C or Adopt a More Practical Approach?

Rethinking the Quest for Python-to-C/C Conversion: A Practical Approach

While the performance gap between Python and C/C can be significant, it's crucial to evaluate if the trade-off in development effort warrants a full-fledged conversion. Instead, consider the following approach:

1. Build a Python Foundation:
   Create a working implementation in Python, taking advantage of its rapid development capabilities. Use performance profiling to identify bottlenecks.
2. Fine-Tune Python:
   Optimize Python code by adjusting data structures, algorithms, and addressing performance issues found through profiling. This will yield significant performance improvements without the need for C/C .
3. Selective Translation:
   If performance remains inadequate, manually translate isolated portions of the Python code into C or C . By starting with a well-structured and tested Python codebase, the translation effort will be significantly reduced.

It's important to remember Thompson's Rule, which highlights the efficiency of iterating on existing code (in this case, Python) rather than starting from scratch with C/C . By following these steps, you can balance performance needs with the benefits of Python development, ultimately leading to faster and more effective results.

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