Coding, Python, software

Python: Some Performance Scores

I just finished reading Sebastian Raschka’s analytic discussion of Pyhton tweaks where the author tested with Python version: 3.3.3

Now, as I am a huge “fan” of Pythonic 1-liners, I made a summary of the article containing 1-liner-analysis-result.

Adding elements to dictionaries
Adding keys “By exploiting thrown KeyError exceptions via an try-except loop” is slightly(~1.2x) faster than “(first,) checking if a key already exists in the Python dictionary using if-else loop”

Filtering lists via (simple) conditional statements
List comprehension is ~1.5x faster than typical if-else loop, and ~1.8x faster than “list(filter(lambda…” combination.

Creating lists using function calls
Using built-in map() method is ~3.4x faster than the for-loop, and ~ 1.5x faster than list comprehension approach.

“So the bottom line of this analysis is that list comprehensions are ideal to create lists using simple evaluations via if-statements, and the in-built map() is the way to go for creating lists via function calls.”

Concatenating strings

“The .join() method is ~ 23x faster than the usage of the + operator to concatenate strings!”

Assembling strings
Using the + operator to format(& concate) strings performs similar as ‘%’ string formatting operator.

However, the format() function is, relatively, extremely slower (~10x).

Thanks for reading. For further digging, you can also find all the details from the author in this Github repository:


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