Oscar Peña/

Writing Efficient Python Code


Writing Efficient Python Code

Run the hidden code cell below to import the data used in this course.

Take Notes

Add notes about the concepts you've learned and code cells with code you want to keep.

Add your notes here

# measuring time of one line code

#can be used -r (for the number of runs), and -n (the number of loops)
%timeit -r 5 -n 10 [*range(1, 51, 2)]

# double percentage sign is used to measure multiline code like functions

# Add your code snippets here
%load_ext line_profiler
%lprun -f <function_name> <function_name(arg, arg1)>

# to use the memory profiler the file needs to be in the same directory
from <file_name> import <function_name>
%load_ext memory_profiler
%mprun -f <function_name> <function_name(arg, arg1)>
  • AI Chat
  • Code