Python development Services: How to make python code run faster?

Python Development Services - Laitkor

It is really difficult to answer this without more relevant information regarding the coding. You can try using a profiler to find out which code is using the most time. Then you can use % timeit and perceive if you can elevate that code. If it is still unfortunate, consider looking at the data. Can you make optimizations based on particular characteristics of the data?

Making Python code run faster

You must consider some of the questions to answer along with the following points:

1.    As the data set grows, does your performance increase linearly? If so, you can try to evaluate what you can do to each piece of data and whether you are able to lessen the computation or storage requisite for each of the iterations.

2.    As the data set grows, can you find geometrically increase in the performance? If so, you may be using a hash that doesn’t work well for the size of your data. You may be able to process it in subsets and combine the results.

3.    Check if you have completely used all the memory space. Also check if the process is essentially using swap. If so, increase memory or split your datasets into smaller chunks.

4.    Some algorithms in scikit-learn support multiprocessing, try turn number of jobs up, closer to your number of cores. If your favorite algorithms do not support multiprocessing, then you can split your data sets, train models with similar datasets and average the results.

5.    You must change to faster algorithms. If your disk IO is intensive, use SSD. Use more efficient libraries because it is not possible for algorithm authors to publish only python code. There is usually C or Java implementations available.

6.    Do the operations on series / arrays, or even list comprehension, rather than for loops. You can use built in Python methods, e.g. collections, as they use C which is much faster. Depending on what you work, choose your tool.

The entire step important for coding in python is discussed above, that would help to code faster. Algorithms have their own importance, so you have to necessarily consider it during process. Also, keep the idea of storage and memory, and free the storage to keep it clean. Perform your operation in series and you can expect changes in your coding very soon.


Do contact us in case of any concerns on Python development services through live chat.

Share: